SPTrans_Passengers.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'German_Germany.1252'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#------ Importing the libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import pandas as pd\n",
    "import calendar\n",
    "import urllib3\n",
    "from datetime import datetime\n",
    "import locale\n",
    "locale.setlocale(locale.LC_ALL, 'German')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Jan/01/2014 exists. Saving...\n",
      "url from Jan/02/2014 exists. Saving...\n",
      "url from Jan/03/2014 exists. Saving...\n",
      "url from Jan/04/2014 exists. Saving...\n",
      "url from Jan/05/2014 exists. Saving...\n",
      "url from Jan/06/2014 exists. Saving...\n",
      "url from Jan/07/2014 exists. Saving...\n",
      "url from Jan/08/2014 exists. Saving...\n",
      "url from Jan/09/2014 exists. Saving...\n",
      "url from Jan/10/2014 exists. Saving...\n",
      "url from Jan/11/2014 exists. Saving...\n",
      "url from Jan/12/2014 exists. Saving...\n",
      "url from Jan/13/2014 exists. Saving...\n",
      "url from Jan/14/2014 exists. Saving...\n",
      "url from Jan/15/2014 exists. Saving...\n",
      "url from Jan/16/2014 exists. Saving...\n",
      "url from Jan/17/2014 exists. Saving...\n",
      "url from Jan/18/2014 exists. Saving...\n",
      "url from Jan/19/2014 exists. Saving...\n",
      "url from Jan/20/2014 exists. Saving...\n",
      "url from Jan/21/2014 exists. Saving...\n",
      "url from Jan/22/2014 exists. Saving...\n",
      "url from Jan/23/2014 exists. Saving...\n",
      "url from Jan/24/2014 exists. Saving...\n",
      "url from Jan/25/2014 exists. Saving...\n",
      "url from Jan/26/2014 exists. Saving...\n",
      "url from Jan/27/2014 exists. Saving...\n",
      "url from Jan/28/2014 exists. Saving...\n",
      "url from Jan/29/2014 exists. Saving...\n",
      "url from Jan/30/2014 exists. Saving...\n",
      "url from Jan/31/2014 exists. Saving...\n",
      "url from Total Jan/2014 exists. Saving...\n",
      "url from Fev/01/2014 exists. Saving...\n",
      "url from Fev/02/2014 exists. Saving...\n",
      "url from Fev/03/2014 exists. Saving...\n",
      "url from Fev/04/2014 exists. Saving...\n",
      "url from Fev/05/2014 exists. Saving...\n",
      "url from Fev/06/2014 exists. Saving...\n",
      "url from Fev/07/2014 exists. Saving...\n",
      "url from Fev/08/2014 exists. Saving...\n",
      "url from Fev/09/2014 exists. Saving...\n",
      "url from Fev/10/2014 exists. Saving...\n",
      "url from Fev/11/2014 exists. Saving...\n",
      "url from Fev/12/2014 exists. Saving...\n",
      "url from Fev/13/2014 exists. Saving...\n",
      "url from Fev/14/2014 exists. Saving...\n",
      "url from Fev/15/2014 exists. Saving...\n",
      "url from Fev/16/2014 exists. Saving...\n",
      "url from Fev/17/2014 exists. Saving...\n",
      "url from Fev/18/2014 exists. Saving...\n",
      "url from Fev/19/2014 exists. Saving...\n",
      "url from Fev/20/2014 exists. Saving...\n",
      "url from Fev/21/2014 exists. Saving...\n",
      "url from Fev/22/2014 exists. Saving...\n",
      "url from Fev/23/2014 exists. Saving...\n",
      "url from Fev/24/2014 exists. Saving...\n",
      "url from Fev/25/2014 exists. Saving...\n",
      "url from Fev/26/2014 exists. Saving...\n",
      "url from Fev/27/2014 exists. Saving...\n",
      "url from Fev/28/2014 exists. Saving...\n",
      "url from Total Fev/2014 exists. Saving...\n",
      "url from Mar/01/2014 exists. Saving...\n",
      "url from Mar/02/2014 exists. Saving...\n",
      "url from Mar/03/2014 exists. Saving...\n",
      "url from Mar/04/2014 exists. Saving...\n",
      "url from Mar/05/2014 exists. Saving...\n",
      "url from Mar/06/2014 exists. Saving...\n",
      "url from Mar/07/2014 exists. Saving...\n",
      "url from Mar/08/2014 exists. Saving...\n",
      "url from Mar/09/2014 exists. Saving...\n",
      "url from Mar/10/2014 exists. Saving...\n",
      "url from Mar/11/2014 exists. Saving...\n",
      "url from Mar/12/2014 exists. Saving...\n",
      "url from Mar/13/2014 exists. Saving...\n",
      "url from Mar/14/2014 exists. Saving...\n",
      "url from Mar/15/2014 exists. Saving...\n",
      "url from Mar/16/2014 exists. Saving...\n",
      "url from Mar/17/2014 exists. Saving...\n",
      "url from Mar/18/2014 exists. Saving...\n",
      "url from Mar/19/2014 exists. Saving...\n",
      "url from Mar/20/2014 exists. Saving...\n",
      "url from Mar/21/2014 exists. Saving...\n",
      "url from Mar/22/2014 exists. Saving...\n",
      "url from Mar/23/2014 exists. Saving...\n",
      "url from Mar/24/2014 exists. Saving...\n",
      "url from Mar/25/2014 exists. Saving...\n",
      "url from Mar/26/2014 exists. Saving...\n",
      "url from Mar/27/2014 exists. Saving...\n",
      "url from Mar/28/2014 exists. Saving...\n",
      "url from Mar/29/2014 exists. Saving...\n",
      "url from Mar/30/2014 exists. Saving...\n",
      "url from Mar/31/2014 exists. Saving...\n",
      "url from Total Mar/2014 exists. Saving...\n",
      "url from Abr/01/2014 exists. Saving...\n",
      "url from Abr/02/2014 exists. Saving...\n",
      "url from Abr/03/2014 exists. Saving...\n",
      "url from Abr/04/2014 exists. Saving...\n",
      "url from Abr/05/2014 exists. Saving...\n",
      "url from Abr/06/2014 exists. Saving...\n",
      "url from Abr/07/2014 exists. Saving...\n",
      "url from Abr/08/2014 exists. Saving...\n",
      "url from Abr/09/2014 exists. Saving...\n",
      "url from Abr/10/2014 exists. Saving...\n",
      "url from Abr/11/2014 exists. Saving...\n",
      "url from Abr/12/2014 exists. Saving...\n",
      "url from Abr/13/2014 exists. Saving...\n",
      "url from Abr/14/2014 exists. Saving...\n",
      "url from Abr/15/2014 exists. Saving...\n",
      "url from Abr/16/2014 exists. Saving...\n",
      "url from Abr/17/2014 exists. Saving...\n",
      "url from Abr/18/2014 exists. Saving...\n",
      "url from Abr/19/2014 exists. Saving...\n",
      "url from Abr/20/2014 exists. Saving...\n",
      "url from Abr/21/2014 exists. Saving...\n",
      "url from Abr/22/2014 exists. Saving...\n",
      "url from Abr/23/2014 exists. Saving...\n",
      "url from Abr/24/2014 exists. Saving...\n",
      "url from Abr/25/2014 exists. Saving...\n",
      "url from Abr/26/2014 exists. Saving...\n",
      "url from Abr/27/2014 exists. Saving...\n",
      "url from Abr/28/2014 exists. Saving...\n",
      "url from Abr/29/2014 exists. Saving...\n",
      "url from Abr/30/2014 exists. Saving...\n",
      "url from Total Abr/2014 exists. Saving...\n",
      "url from Mai/01/2014 exists. Saving...\n",
      "url from Mai/02/2014 exists. Saving...\n",
      "url from Mai/03/2014 exists. Saving...\n",
      "url from Mai/04/2014 exists. Saving...\n",
      "url from Mai/05/2014 exists. Saving...\n",
      "url from Mai/06/2014 exists. Saving...\n",
      "url from Mai/07/2014 exists. Saving...\n",
      "url from Mai/08/2014 exists. Saving...\n",
      "url from Mai/09/2014 exists. Saving...\n",
      "url from Mai/10/2014 exists. Saving...\n",
      "url from Mai/11/2014 exists. Saving...\n",
      "url from Mai/12/2014 exists. Saving...\n",
      "url from Mai/13/2014 exists. Saving...\n",
      "url from Mai/14/2014 exists. Saving...\n",
      "url from Mai/15/2014 exists. Saving...\n",
      "url from Mai/16/2014 exists. Saving...\n",
      "url from Mai/17/2014 exists. Saving...\n",
      "url from Mai/18/2014 exists. Saving...\n",
      "url from Mai/19/2014 exists. Saving...\n",
      "url from Mai/20/2014 exists. Saving...\n",
      "url from Mai/21/2014 exists. Saving...\n",
      "url from Mai/22/2014 exists. Saving...\n",
      "url from Mai/23/2014 exists. Saving...\n",
      "url from Mai/24/2014 exists. Saving...\n",
      "url from Mai/25/2014 exists. Saving...\n",
      "url from Mai/26/2014 exists. Saving...\n",
      "url from Mai/27/2014 exists. Saving...\n",
      "url from Mai/28/2014 exists. Saving...\n",
      "url from Mai/29/2014 exists. Saving...\n",
      "url from Mai/30/2014 exists. Saving...\n",
      "url from Mai/31/2014 exists. Saving...\n",
      "url from Total Mai/2014 exists. Saving...\n",
      "url from Jun/01/2014 exists. Saving...\n",
      "url from Jun/02/2014 exists. Saving...\n",
      "url from Jun/03/2014 exists. Saving...\n",
      "url from Jun/04/2014 exists. Saving...\n",
      "url from Jun/05/2014 exists. Saving...\n",
      "url from Jun/06/2014 exists. Saving...\n",
      "url from Jun/07/2014 exists. Saving...\n",
      "url from Jun/08/2014 exists. Saving...\n",
      "url from Jun/09/2014 exists. Saving...\n",
      "url from Jun/10/2014 exists. Saving...\n",
      "url from Jun/11/2014 exists. Saving...\n",
      "url from Jun/12/2014 exists. Saving...\n",
      "url from Jun/13/2014 exists. Saving...\n",
      "url from Jun/14/2014 exists. Saving...\n",
      "url from Jun/15/2014 exists. Saving...\n",
      "url from Jun/16/2014 exists. Saving...\n",
      "url from Jun/17/2014 exists. Saving...\n",
      "url from Jun/18/2014 exists. Saving...\n",
      "url from Jun/19/2014 exists. Saving...\n",
      "url from Jun/20/2014 exists. Saving...\n",
      "url from Jun/21/2014 exists. Saving...\n",
      "url from Jun/22/2014 exists. Saving...\n",
      "url from Jun/23/2014 exists. Saving...\n",
      "url from Jun/24/2014 exists. Saving...\n",
      "url from Jun/25/2014 exists. Saving...\n",
      "url from Jun/26/2014 exists. Saving...\n",
      "url from Jun/27/2014 exists. Saving...\n",
      "url from Jun/28/2014 exists. Saving...\n",
      "url from Jun/29/2014 exists. Saving...\n",
      "url from Jun/30/2014 exists. Saving...\n",
      "url from Total Jun/2014 exists. Saving...\n",
      "url from Jul/01/2014 exists. Saving...\n",
      "url from Jul/02/2014 exists. Saving...\n",
      "url from Jul/03/2014 exists. Saving...\n",
      "url from Jul/04/2014 exists. Saving...\n",
      "url from Jul/05/2014 exists. Saving...\n",
      "url from Jul/06/2014 exists. Saving...\n",
      "url from Jul/07/2014 exists. Saving...\n",
      "url from Jul/08/2014 exists. Saving...\n",
      "url from Jul/09/2014 exists. Saving...\n",
      "url from Jul/10/2014 exists. Saving...\n",
      "url from Jul/11/2014 exists. Saving...\n",
      "url from Jul/12/2014 exists. Saving...\n",
      "url from Jul/13/2014 exists. Saving...\n",
      "url from Jul/14/2014 exists. Saving...\n",
      "url from Jul/15/2014 exists. Saving...\n",
      "url from Jul/16/2014 exists. Saving...\n",
      "url from Jul/17/2014 exists. Saving...\n",
      "url from Jul/18/2014 exists. Saving...\n",
      "url from Jul/19/2014 exists. Saving...\n",
      "url from Jul/20/2014 exists. Saving...\n",
      "url from Jul/21/2014 exists. Saving...\n",
      "url from Jul/22/2014 exists. Saving...\n",
      "url from Jul/23/2014 exists. Saving...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Jul/24/2014 exists. Saving...\n",
      "url from Jul/25/2014 exists. Saving...\n",
      "url from Jul/26/2014 exists. Saving...\n",
      "url from Jul/27/2014 exists. Saving...\n",
      "url from Jul/28/2014 exists. Saving...\n",
      "url from Jul/29/2014 exists. Saving...\n",
      "url from Jul/30/2014 exists. Saving...\n",
      "url from Jul/31/2014 exists. Saving...\n",
      "url from Total Jul/2014 exists. Saving...\n",
      "url from Ago/01/2014 exists. Saving...\n",
      "url from Ago/02/2014 exists. Saving...\n",
      "url from Ago/03/2014 exists. Saving...\n",
      "url from Ago/04/2014 exists. Saving...\n",
      "url from Ago/05/2014 exists. Saving...\n",
      "url from Ago/06/2014 exists. Saving...\n",
      "url from Ago/07/2014 exists. Saving...\n",
      "url from Ago/08/2014 exists. Saving...\n",
      "url from Ago/09/2014 exists. Saving...\n",
      "url from Ago/10/2014 exists. Saving...\n",
      "url from Ago/11/2014 exists. Saving...\n",
      "url from Ago/12/2014 exists. Saving...\n",
      "url from Ago/13/2014 exists. Saving...\n",
      "url from Ago/14/2014 exists. Saving...\n",
      "url from Ago/15/2014 exists. Saving...\n",
      "url from Ago/16/2014 exists. Saving...\n",
      "url from Ago/17/2014 exists. Saving...\n",
      "url from Ago/18/2014 exists. Saving...\n",
      "url from Ago/19/2014 exists. Saving...\n",
      "url from Ago/20/2014 exists. Saving...\n",
      "url from Ago/21/2014 exists. Saving...\n",
      "url from Ago/22/2014 exists. Saving...\n",
      "url from Ago/23/2014 exists. Saving...\n",
      "url from Ago/24/2014 exists. Saving...\n",
      "url from Ago/25/2014 exists. Saving...\n",
      "url from Ago/26/2014 exists. Saving...\n",
      "url from Ago/27/2014 exists. Saving...\n",
      "url from Ago/28/2014 exists. Saving...\n",
      "url from Ago/29/2014 exists. Saving...\n",
      "url from Ago/30/2014 exists. Saving...\n",
      "url from Ago/31/2014 exists. Saving...\n",
      "url from Total Ago/2014 exists. Saving...\n",
      "url from Set/01/2014 exists. Saving...\n",
      "url from Set/02/2014 exists. Saving...\n",
      "url from Set/03/2014 exists. Saving...\n",
      "url from Set/04/2014 exists. Saving...\n",
      "url from Set/05/2014 exists. Saving...\n",
      "url from Set/06/2014 exists. Saving...\n",
      "url from Set/07/2014 exists. Saving...\n",
      "url from Set/08/2014 exists. Saving...\n",
      "url from Set/09/2014 exists. Saving...\n",
      "url from Set/10/2014 exists. Saving...\n",
      "url from Set/11/2014 exists. Saving...\n",
      "url from Set/12/2014 exists. Saving...\n",
      "url from Set/13/2014 exists. Saving...\n",
      "url from Set/14/2014 exists. Saving...\n",
      "url from Set/15/2014 exists. Saving...\n",
      "url from Set/16/2014 exists. Saving...\n",
      "url from Set/17/2014 exists. Saving...\n",
      "url from Set/18/2014 exists. Saving...\n",
      "url from Set/19/2014 exists. Saving...\n",
      "url from Set/20/2014 exists. Saving...\n",
      "url from Set/21/2014 exists. Saving...\n",
      "url from Set/22/2014 exists. Saving...\n",
      "url from Set/23/2014 exists. Saving...\n",
      "url from Set/24/2014 exists. Saving...\n",
      "url from Set/25/2014 exists. Saving...\n",
      "url from Set/26/2014 exists. Saving...\n",
      "url from Set/27/2014 exists. Saving...\n",
      "url from Set/28/2014 exists. Saving...\n",
      "url from Set/29/2014 exists. Saving...\n",
      "url from Set/30/2014 exists. Saving...\n",
      "url from Total Set/2014 exists. Saving...\n",
      "url from Out/01/2014 exists. Saving...\n",
      "url from Out/02/2014 exists. Saving...\n",
      "url from Out/03/2014 exists. Saving...\n",
      "url from Out/04/2014 exists. Saving...\n",
      "url from Out/05/2014 exists. Saving...\n",
      "url from Out/06/2014 exists. Saving...\n",
      "url from Out/07/2014 exists. Saving...\n",
      "url from Out/08/2014 exists. Saving...\n",
      "url from Out/09/2014 exists. Saving...\n",
      "url from Out/10/2014 exists. Saving...\n",
      "url from Out/11/2014 exists. Saving...\n",
      "url from Out/12/2014 exists. Saving...\n",
      "url from Out/13/2014 exists. Saving...\n",
      "url from Out/14/2014 exists. Saving...\n",
      "url from Out/15/2014 exists. Saving...\n",
      "url from Out/16/2014 exists. Saving...\n",
      "url from Out/17/2014 exists. Saving...\n",
      "url from Out/18/2014 exists. Saving...\n",
      "url from Out/19/2014 exists. Saving...\n",
      "url from Out/20/2014 exists. Saving...\n",
      "url from Out/21/2014 exists. Saving...\n",
      "url from Out/22/2014 exists. Saving...\n",
      "url from Out/23/2014 exists. Saving...\n",
      "url from Out/24/2014 exists. Saving...\n",
      "url from Out/25/2014 exists. Saving...\n",
      "url from Out/26/2014 exists. Saving...\n",
      "url from Out/27/2014 exists. Saving...\n",
      "url from Out/28/2014 exists. Saving...\n",
      "url from Out/29/2014 exists. Saving...\n",
      "url from Out/30/2014 exists. Saving...\n",
      "url from Out/31/2014 exists. Saving...\n",
      "url from Total Out/2014 exists. Saving...\n",
      "url from Nov/01/2014 exists. Saving...\n",
      "url from Nov/02/2014 exists. Saving...\n",
      "url from Nov/03/2014 exists. Saving...\n",
      "url from Nov/04/2014 exists. Saving...\n",
      "url from Nov/05/2014 exists. Saving...\n",
      "url from Nov/06/2014 exists. Saving...\n",
      "url from Nov/07/2014 exists. Saving...\n",
      "url from Nov/08/2014 exists. Saving...\n",
      "url from Nov/09/2014 exists. Saving...\n",
      "url from Nov/10/2014 exists. Saving...\n",
      "url from Nov/11/2014 exists. Saving...\n",
      "url from Nov/12/2014 exists. Saving...\n",
      "url from Nov/13/2014 exists. Saving...\n",
      "url from Nov/14/2014 exists. Saving...\n",
      "url from Nov/15/2014 exists. Saving...\n",
      "url from Nov/16/2014 exists. Saving...\n",
      "url from Nov/17/2014 exists. Saving...\n",
      "url from Nov/18/2014 exists. Saving...\n",
      "url from Nov/19/2014 exists. Saving...\n",
      "url from Nov/20/2014 exists. Saving...\n",
      "url from Nov/21/2014 exists. Saving...\n",
      "url from Nov/22/2014 exists. Saving...\n",
      "url from Nov/23/2014 exists. Saving...\n",
      "url from Nov/24/2014 exists. Saving...\n",
      "url from Nov/25/2014 exists. Saving...\n",
      "url from Nov/26/2014 exists. Saving...\n",
      "url from Nov/27/2014 exists. Saving...\n",
      "url from Nov/28/2014 exists. Saving...\n",
      "url from Nov/29/2014 exists. Saving...\n",
      "url from Nov/30/2014 exists. Saving...\n",
      "url from Total Nov/2014 exists. Saving...\n",
      "url from Dez/01/2014 exists. Saving...\n",
      "url from Dez/02/2014 exists. Saving...\n",
      "url from Dez/03/2014 exists. Saving...\n",
      "url from Dez/04/2014 exists. Saving...\n",
      "url from Dez/05/2014 exists. Saving...\n",
      "url from Dez/06/2014 exists. Saving...\n",
      "url from Dez/07/2014 exists. Saving...\n",
      "url from Dez/08/2014 exists. Saving...\n",
      "url from Dez/09/2014 exists. Saving...\n",
      "url from Dez/10/2014 exists. Saving...\n",
      "url from Dez/11/2014 exists. Saving...\n",
      "url from Dez/12/2014 exists. Saving...\n",
      "url from Dez/13/2014 exists. Saving...\n",
      "url from Dez/14/2014 exists. Saving...\n",
      "url from Dez/15/2014 exists. Saving...\n",
      "url from Dez/16/2014 exists. Saving...\n",
      "url from Dez/17/2014 exists. Saving...\n",
      "url from Dez/18/2014 exists. Saving...\n",
      "url from Dez/19/2014 exists. Saving...\n",
      "url from Dez/20/2014 exists. Saving...\n",
      "url from Dez/21/2014 exists. Saving...\n",
      "url from Dez/22/2014 exists. Saving...\n",
      "url from Dez/23/2014 exists. Saving...\n",
      "url from Dez/24/2014 exists. Saving...\n",
      "url from Dez/25/2014 exists. Saving...\n",
      "url from Dez/26/2014 exists. Saving...\n",
      "url from Dez/27/2014 exists. Saving...\n",
      "url from Dez/28/2014 exists. Saving...\n",
      "url from Dez/29/2014 exists. Saving...\n",
      "url from Dez/30/2014 exists. Saving...\n",
      "url from Dez/31/2014 exists. Saving...\n",
      "url from Total Dez/2014 exists. Saving...\n",
      "url from Jan/01/2015 exists. Saving...\n",
      "url from Jan/02/2015 exists. Saving...\n",
      "url from Jan/03/2015 exists. Saving...\n",
      "url from Jan/04/2015 exists. Saving...\n",
      "url from Jan/05/2015 exists. Saving...\n",
      "url from Jan/06/2015 exists. Saving...\n",
      "url from Jan/07/2015 exists. Saving...\n",
      "url from Jan/08/2015 exists. Saving...\n",
      "url from Jan/09/2015 exists. Saving...\n",
      "url from Jan/10/2015 exists. Saving...\n",
      "url from Jan/11/2015 exists. Saving...\n",
      "url from Jan/12/2015 exists. Saving...\n",
      "url from Jan/13/2015 exists. Saving...\n",
      "url from Jan/14/2015 exists. Saving...\n",
      "url from Jan/15/2015 exists. Saving...\n",
      "url from Jan/16/2015 exists. Saving...\n",
      "url from Jan/17/2015 exists. Saving...\n",
      "url from Jan/18/2015 exists. Saving...\n",
      "url from Jan/19/2015 exists. Saving...\n",
      "url from Jan/20/2015 exists. Saving...\n",
      "url from Jan/21/2015 exists. Saving...\n",
      "url from Jan/22/2015 exists. Saving...\n",
      "url from Jan/23/2015 exists. Saving...\n",
      "url from Jan/24/2015 exists. Saving...\n",
      "url from Jan/25/2015 exists. Saving...\n",
      "url from Jan/26/2015 exists. Saving...\n",
      "url from Jan/27/2015 exists. Saving...\n",
      "url from Jan/28/2015 exists. Saving...\n",
      "url from Jan/29/2015 exists. Saving...\n",
      "url from Jan/30/2015 exists. Saving...\n",
      "url from Jan/31/2015 exists. Saving...\n",
      "url from Total Jan/2015 exists. Saving...\n",
      "url from Fev/01/2015 exists. Saving...\n",
      "url from Fev/02/2015 exists. Saving...\n",
      "url from Fev/03/2015 exists. Saving...\n",
      "url from Fev/04/2015 exists. Saving...\n",
      "url from Fev/05/2015 exists. Saving...\n",
      "url from Fev/06/2015 exists. Saving...\n",
      "url from Fev/07/2015 exists. Saving...\n",
      "url from Fev/08/2015 exists. Saving...\n",
      "url from Fev/09/2015 exists. Saving...\n",
      "url from Fev/10/2015 exists. Saving...\n",
      "url from Fev/11/2015 exists. Saving...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Fev/12/2015 exists. Saving...\n",
      "url from Fev/13/2015 exists. Saving...\n",
      "url from Fev/14/2015 exists. Saving...\n",
      "url from Fev/15/2015 exists. Saving...\n",
      "url from Fev/16/2015 exists. Saving...\n",
      "url from Fev/17/2015 exists. Saving...\n",
      "url from Fev/18/2015 exists. Saving...\n",
      "url from Fev/19/2015 exists. Saving...\n",
      "url from Fev/20/2015 exists. Saving...\n",
      "url from Fev/21/2015 exists. Saving...\n",
      "url from Fev/22/2015 exists. Saving...\n",
      "url from Fev/23/2015 exists. Saving...\n",
      "url from Fev/24/2015 exists. Saving...\n",
      "url from Fev/25/2015 exists. Saving...\n",
      "url from Fev/26/2015 exists. Saving...\n",
      "url from Fev/27/2015 exists. Saving...\n",
      "url from Fev/28/2015 exists. Saving...\n",
      "url from Total Fev/2015 exists. Saving...\n",
      "url from Mar/01/2015 exists. Saving...\n",
      "url from Mar/02/2015 exists. Saving...\n",
      "url from Mar/03/2015 exists. Saving...\n",
      "url from Mar/04/2015 exists. Saving...\n",
      "url from Mar/05/2015 exists. Saving...\n",
      "url from Mar/06/2015 exists. Saving...\n",
      "url from Mar/07/2015 exists. Saving...\n",
      "url from Mar/08/2015 exists. Saving...\n",
      "url from Mar/09/2015 exists. Saving...\n",
      "url from Mar/10/2015 exists. Saving...\n",
      "url from Mar/11/2015 exists. Saving...\n",
      "url from Mar/12/2015 exists. Saving...\n",
      "url from Mar/13/2015 exists. Saving...\n",
      "url from Mar/14/2015 exists. Saving...\n",
      "url from Mar/15/2015 exists. Saving...\n",
      "url from Mar/16/2015 exists. Saving...\n",
      "url from Mar/17/2015 exists. Saving...\n",
      "url from Mar/18/2015 exists. Saving...\n",
      "url from Mar/19/2015 exists. Saving...\n",
      "url from Mar/20/2015 exists. Saving...\n",
      "url from Mar/21/2015 exists. Saving...\n",
      "url from Mar/22/2015 exists. Saving...\n",
      "url from Mar/23/2015 exists. Saving...\n",
      "url from Mar/24/2015 exists. Saving...\n",
      "url from Mar/25/2015 exists. Saving...\n",
      "url from Mar/26/2015 exists. Saving...\n",
      "url from Mar/27/2015 exists. Saving...\n",
      "url from Mar/28/2015 exists. Saving...\n",
      "url from Mar/29/2015 exists. Saving...\n",
      "url from Mar/30/2015 exists. Saving...\n",
      "url from Mar/31/2015 exists. Saving...\n",
      "url from Total Mar/2015 exists. Saving...\n",
      "url from Abr/01/2015 exists. Saving...\n",
      "url from Abr/02/2015 exists. Saving...\n",
      "url from Abr/03/2015 exists. Saving...\n",
      "url from Abr/04/2015 exists. Saving...\n",
      "url from Abr/05/2015 exists. Saving...\n",
      "url from Abr/06/2015 exists. Saving...\n",
      "url from Abr/07/2015 exists. Saving...\n",
      "url from Abr/08/2015 exists. Saving...\n",
      "url from Abr/09/2015 exists. Saving...\n",
      "url from Abr/10/2015 exists. Saving...\n",
      "url from Abr/11/2015 exists. Saving...\n",
      "url from Abr/12/2015 exists. Saving...\n",
      "url from Abr/13/2015 exists. Saving...\n",
      "url from Abr/14/2015 exists. Saving...\n",
      "url from Abr/15/2015 exists. Saving...\n",
      "url from Abr/16/2015 exists. Saving...\n",
      "url from Abr/17/2015 exists. Saving...\n",
      "url from Abr/18/2015 exists. Saving...\n",
      "url from Abr/19/2015 exists. Saving...\n",
      "url from Abr/20/2015 exists. Saving...\n",
      "url from Abr/21/2015 exists. Saving...\n",
      "url from Abr/22/2015 exists. Saving...\n",
      "url from Abr/23/2015 exists. Saving...\n",
      "url from Abr/24/2015 exists. Saving...\n",
      "url from Abr/25/2015 exists. Saving...\n",
      "url from Abr/26/2015 exists. Saving...\n",
      "url from Abr/27/2015 exists. Saving...\n",
      "url from Abr/28/2015 exists. Saving...\n",
      "url from Abr/29/2015 exists. Saving...\n",
      "url from Abr/30/2015 exists. Saving...\n",
      "url from Total Abr/2015 exists. Saving...\n",
      "url from Mai/01/2015 exists. Saving...\n",
      "url from Mai/02/2015 exists. Saving...\n",
      "url from Mai/03/2015 exists. Saving...\n",
      "url from Mai/04/2015 exists. Saving...\n",
      "url from Mai/05/2015 exists. Saving...\n",
      "url from Mai/06/2015 exists. Saving...\n",
      "url from Mai/07/2015 exists. Saving...\n",
      "url from Mai/08/2015 exists. Saving...\n",
      "url from Mai/09/2015 exists. Saving...\n",
      "url from Mai/10/2015 exists. Saving...\n",
      "url from Mai/11/2015 exists. Saving...\n",
      "url from Mai/12/2015 exists. Saving...\n",
      "url from Mai/13/2015 exists. Saving...\n",
      "url from Mai/14/2015 exists. Saving...\n",
      "url from Mai/15/2015 exists. Saving...\n",
      "url from Mai/16/2015 exists. Saving...\n",
      "url from Mai/17/2015 exists. Saving...\n",
      "url from Mai/18/2015 exists. Saving...\n",
      "url from Mai/19/2015 exists. Saving...\n",
      "url from Mai/20/2015 exists. Saving...\n",
      "url from Mai/21/2015 exists. Saving...\n",
      "url from Mai/22/2015 exists. Saving...\n",
      "url from Mai/23/2015 exists. Saving...\n",
      "url from Mai/24/2015 exists. Saving...\n",
      "url from Mai/25/2015 exists. Saving...\n",
      "url from Mai/26/2015 exists. Saving...\n",
      "url from Mai/27/2015 exists. Saving...\n",
      "url from Mai/28/2015 exists. Saving...\n",
      "url from Mai/29/2015 exists. Saving...\n",
      "url from Mai/30/2015 exists. Saving...\n",
      "url from Mai/31/2015 exists. Saving...\n",
      "url from Total Mai/2015 exists. Saving...\n",
      "url from Jun/01/2015 exists. Saving...\n",
      "url from Jun/02/2015 exists. Saving...\n",
      "url from Jun/03/2015 exists. Saving...\n",
      "url from Jun/04/2015 exists. Saving...\n",
      "url from Jun/05/2015 exists. Saving...\n",
      "url from Jun/06/2015 exists. Saving...\n",
      "url from Jun/07/2015 exists. Saving...\n",
      "url from Jun/08/2015 exists. Saving...\n",
      "url from Jun/09/2015 exists. Saving...\n",
      "url from Jun/10/2015 exists. Saving...\n",
      "url from Jun/11/2015 exists. Saving...\n",
      "url from Jun/12/2015 exists. Saving...\n",
      "url from Jun/13/2015 exists. Saving...\n",
      "url from Jun/14/2015 exists. Saving...\n",
      "url from Jun/15/2015 exists. Saving...\n",
      "url from Jun/16/2015 exists. Saving...\n",
      "url from Jun/17/2015 exists. Saving...\n",
      "url from Jun/18/2015 exists. Saving...\n",
      "url from Jun/19/2015 exists. Saving...\n",
      "url from Jun/20/2015 exists. Saving...\n",
      "url from Jun/21/2015 exists. Saving...\n",
      "url from Jun/22/2015 exists. Saving...\n",
      "url from Jun/23/2015 exists. Saving...\n",
      "url from Jun/24/2015 exists. Saving...\n",
      "url from Jun/25/2015 exists. Saving...\n",
      "url from Jun/26/2015 exists. Saving...\n",
      "url from Jun/27/2015 exists. Saving...\n",
      "url from Jun/28/2015 exists. Saving...\n",
      "url from Jun/29/2015 exists. Saving...\n",
      "url from Jun/30/2015 exists. Saving...\n",
      "url from Total Jun/2015 exists. Saving...\n",
      "url from Jul/01/2015 exists. Saving...\n",
      "url from Jul/02/2015 exists. Saving...\n",
      "url from Jul/03/2015 exists. Saving...\n",
      "url from Jul/04/2015 exists. Saving...\n",
      "url from Jul/05/2015 exists. Saving...\n",
      "url from Jul/06/2015 exists. Saving...\n",
      "url from Jul/07/2015 exists. Saving...\n",
      "url from Jul/08/2015 exists. Saving...\n",
      "url from Jul/09/2015 exists. Saving...\n",
      "url from Jul/10/2015 exists. Saving...\n",
      "url from Jul/11/2015 exists. Saving...\n",
      "url from Jul/12/2015 exists. Saving...\n",
      "url from Jul/13/2015 exists. Saving...\n",
      "url from Jul/14/2015 exists. Saving...\n",
      "url from Jul/15/2015 exists. Saving...\n",
      "url from Jul/16/2015 exists. Saving...\n",
      "url from Jul/17/2015 exists. Saving...\n",
      "url from Jul/18/2015 exists. Saving...\n",
      "url from Jul/19/2015 exists. Saving...\n",
      "url from Jul/20/2015 exists. Saving...\n",
      "url from Jul/21/2015 exists. Saving...\n",
      "url from Jul/22/2015 exists. Saving...\n",
      "url from Jul/23/2015 exists. Saving...\n",
      "url from Jul/24/2015 exists. Saving...\n",
      "url from Jul/25/2015 exists. Saving...\n",
      "url from Jul/26/2015 exists. Saving...\n",
      "url from Jul/27/2015 exists. Saving...\n",
      "url from Jul/28/2015 exists. Saving...\n",
      "url from Jul/29/2015 exists. Saving...\n",
      "url from Jul/30/2015 exists. Saving...\n",
      "url from Jul/31/2015 exists. Saving...\n",
      "url from Total Jul/2015 exists. Saving...\n",
      "url from Ago/01/2015 exists. Saving...\n",
      "url from Ago/02/2015 exists. Saving...\n",
      "url from Ago/03/2015 exists. Saving...\n",
      "url from Ago/04/2015 exists. Saving...\n",
      "url from Ago/05/2015 exists. Saving...\n",
      "url from Ago/06/2015 exists. Saving...\n",
      "url from Ago/07/2015 exists. Saving...\n",
      "url from Ago/08/2015 exists. Saving...\n",
      "url from Ago/09/2015 exists. Saving...\n",
      "url from Ago/10/2015 exists. Saving...\n",
      "url from Ago/11/2015 exists. Saving...\n",
      "url from Ago/12/2015 exists. Saving...\n",
      "url from Ago/13/2015 exists. Saving...\n",
      "url from Ago/14/2015 exists. Saving...\n",
      "url from Ago/15/2015 exists. Saving...\n",
      "url from Ago/16/2015 exists. Saving...\n",
      "url from Ago/17/2015 exists. Saving...\n",
      "url from Ago/18/2015 exists. Saving...\n",
      "url from Ago/19/2015 exists. Saving...\n",
      "url from Ago/20/2015 exists. Saving...\n",
      "url from Ago/21/2015 exists. Saving...\n",
      "url from Ago/22/2015 exists. Saving...\n",
      "url from Ago/23/2015 exists. Saving...\n",
      "url from Ago/24/2015 exists. Saving...\n",
      "url from Ago/25/2015 exists. Saving...\n",
      "url from Ago/26/2015 exists. Saving...\n",
      "url from Ago/27/2015 exists. Saving...\n",
      "url from Ago/28/2015 exists. Saving...\n",
      "url from Ago/29/2015 exists. Saving...\n",
      "url from Ago/30/2015 exists. Saving...\n",
      "url from Ago/31/2015 exists. Saving...\n",
      "url from Total Ago/2015 exists. Saving...\n",
      "url from Set/01/2015 exists. Saving...\n",
      "url from Set/02/2015 exists. Saving...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Set/03/2015 exists. Saving...\n",
      "url from Set/04/2015 exists. Saving...\n",
      "url from Set/05/2015 exists. Saving...\n",
      "url from Set/06/2015 exists. Saving...\n",
      "url from Set/07/2015 exists. Saving...\n",
      "url from Set/08/2015 exists. Saving...\n",
      "url from Set/09/2015 exists. Saving...\n",
      "url from Set/10/2015 exists. Saving...\n",
      "url from Set/11/2015 exists. Saving...\n",
      "url from Set/12/2015 exists. Saving...\n",
      "url from Set/13/2015 exists. Saving...\n",
      "url from Set/14/2015 exists. Saving...\n",
      "url from Set/15/2015 exists. Saving...\n",
      "url from Set/16/2015 exists. Saving...\n",
      "url from Set/17/2015 exists. Saving...\n",
      "url from Set/18/2015 exists. Saving...\n",
      "url from Set/19/2015 exists. Saving...\n",
      "url from Set/20/2015 exists. Saving...\n",
      "url from Set/21/2015 exists. Saving...\n",
      "url from Set/22/2015 exists. Saving...\n",
      "url from Set/23/2015 exists. Saving...\n",
      "url from Set/24/2015 exists. Saving...\n",
      "url from Set/25/2015 exists. Saving...\n",
      "url from Set/26/2015 exists. Saving...\n",
      "url from Set/27/2015 exists. Saving...\n",
      "url from Set/28/2015 exists. Saving...\n",
      "url from Set/29/2015 exists. Saving...\n",
      "url from Set/30/2015 exists. Saving...\n",
      "url from Total Set/2015 exists. Saving...\n",
      "url from Out/01/2015 exists. Saving...\n",
      "url from Out/02/2015 exists. Saving...\n",
      "url from Out/03/2015 exists. Saving...\n",
      "url from Out/04/2015 exists. Saving...\n",
      "url from Out/05/2015 exists. Saving...\n",
      "url from Out/06/2015 exists. Saving...\n",
      "url from Out/07/2015 exists. Saving...\n",
      "url from Out/08/2015 exists. Saving...\n",
      "url from Out/09/2015 exists. Saving...\n",
      "url from Out/10/2015 exists. Saving...\n",
      "url from Out/11/2015 exists. Saving...\n",
      "url from Out/12/2015 exists. Saving...\n",
      "url from Out/13/2015 exists. Saving...\n",
      "url from Out/14/2015 exists. Saving...\n",
      "url from Out/15/2015 exists. Saving...\n",
      "url from Out/16/2015 exists. Saving...\n",
      "url from Out/17/2015 exists. Saving...\n",
      "url from Out/18/2015 exists. Saving...\n",
      "url from Out/19/2015 exists. Saving...\n",
      "url from Out/20/2015 exists. Saving...\n",
      "url from Out/21/2015 exists. Saving...\n",
      "url from Out/22/2015 exists. Saving...\n",
      "url from Out/23/2015 exists. Saving...\n",
      "url from Out/24/2015 exists. Saving...\n",
      "url from Out/25/2015 exists. Saving...\n",
      "url from Out/26/2015 exists. Saving...\n",
      "url from Out/27/2015 exists. Saving...\n",
      "url from Out/28/2015 exists. Saving...\n",
      "url from Out/29/2015 exists. Saving...\n",
      "url from Out/30/2015 exists. Saving...\n",
      "url from Out/31/2015 exists. Saving...\n",
      "url from Total Out/2015 exists. Saving...\n",
      "url from Nov/01/2015 exists. Saving...\n",
      "url from Nov/02/2015 exists. Saving...\n",
      "url from Nov/03/2015 exists. Saving...\n",
      "url from Nov/04/2015 exists. Saving...\n",
      "url from Nov/05/2015 exists. Saving...\n",
      "url from Nov/06/2015 exists. Saving...\n",
      "url from Nov/07/2015 exists. Saving...\n",
      "url from Nov/08/2015 exists. Saving...\n",
      "url from Nov/09/2015 exists. Saving...\n",
      "url from Nov/10/2015 exists. Saving...\n",
      "url from Nov/11/2015 exists. Saving...\n",
      "url from Nov/12/2015 exists. Saving...\n",
      "url from Nov/13/2015 exists. Saving...\n",
      "url from Nov/14/2015 exists. Saving...\n",
      "url from Nov/15/2015 exists. Saving...\n",
      "url from Nov/16/2015 exists. Saving...\n",
      "url from Nov/17/2015 exists. Saving...\n",
      "url from Nov/18/2015 exists. Saving...\n",
      "url from Nov/19/2015 exists. Saving...\n",
      "url from Nov/20/2015 exists. Saving...\n",
      "url from Nov/21/2015 exists. Saving...\n",
      "url from Nov/22/2015 exists. Saving...\n",
      "url from Nov/23/2015 exists. Saving...\n",
      "url from Nov/24/2015 exists. Saving...\n",
      "url from Nov/25/2015 exists. Saving...\n",
      "url from Nov/26/2015 exists. Saving...\n",
      "url from Nov/27/2015 exists. Saving...\n",
      "url from Nov/28/2015 exists. Saving...\n",
      "url from Nov/29/2015 exists. Saving...\n",
      "url from Nov/30/2015 exists. Saving...\n",
      "url from Total Nov/2015 exists. Saving...\n",
      "url from Dez/01/2015 exists. Saving...\n",
      "url from Dez/02/2015 exists. Saving...\n",
      "url from Dez/03/2015 exists. Saving...\n",
      "url from Dez/04/2015 exists. Saving...\n",
      "url from Dez/05/2015 exists. Saving...\n",
      "url from Dez/06/2015 exists. Saving...\n",
      "url from Dez/07/2015 exists. Saving...\n",
      "url from Dez/08/2015 exists. Saving...\n",
      "url from Dez/09/2015 exists. Saving...\n",
      "url from Dez/10/2015 exists. Saving...\n",
      "url from Dez/11/2015 exists. Saving...\n",
      "url from Dez/12/2015 exists. Saving...\n",
      "url from Dez/13/2015 exists. Saving...\n",
      "url from Dez/14/2015 exists. Saving...\n",
      "url from Dez/15/2015 exists. Saving...\n",
      "url from Dez/16/2015 exists. Saving...\n",
      "url from Dez/17/2015 exists. Saving...\n",
      "url from Dez/18/2015 exists. Saving...\n",
      "url from Dez/19/2015 exists. Saving...\n",
      "url from Dez/20/2015 exists. Saving...\n",
      "url from Dez/21/2015 exists. Saving...\n",
      "url from Dez/22/2015 exists. Saving...\n",
      "url from Dez/23/2015 exists. Saving...\n",
      "url from Dez/24/2015 exists. Saving...\n",
      "url from Dez/25/2015 exists. Saving...\n",
      "url from Dez/26/2015 exists. Saving...\n",
      "url from Dez/27/2015 exists. Saving...\n",
      "url from Dez/28/2015 exists. Saving...\n",
      "url from Dez/29/2015 exists. Saving...\n",
      "url from Dez/30/2015 exists. Saving...\n",
      "url from Dez/31/2015 exists. Saving...\n",
      "url from Total Dez/2015 exists. Saving...\n",
      "url from Jan/01/2016 exists. Saving...\n",
      "url from Jan/02/2016 exists. Saving...\n",
      "url from Jan/03/2016 exists. Saving...\n",
      "url from Jan/04/2016 exists. Saving...\n",
      "url from Jan/05/2016 exists. Saving...\n",
      "url from Jan/06/2016 exists. Saving...\n",
      "url from Jan/07/2016 exists. Saving...\n",
      "url from Jan/08/2016 exists. Saving...\n",
      "url from Jan/09/2016 exists. Saving...\n",
      "url from Jan/10/2016 exists. Saving...\n",
      "url from Jan/11/2016 exists. Saving...\n",
      "url from Jan/12/2016 exists. Saving...\n",
      "url from Jan/13/2016 exists. Saving...\n",
      "url from Jan/14/2016 exists. Saving...\n",
      "url from Jan/15/2016 exists. Saving...\n",
      "url from Jan/16/2016 exists. Saving...\n",
      "url from Jan/17/2016 exists. Saving...\n",
      "url from Jan/18/2016 exists. Saving...\n",
      "url from Jan/19/2016 exists. Saving...\n",
      "url from Jan/20/2016 exists. Saving...\n",
      "url from Jan/21/2016 exists. Saving...\n",
      "url from Jan/22/2016 exists. Saving...\n",
      "url from Jan/23/2016 exists. Saving...\n",
      "url from Jan/24/2016 exists. Saving...\n",
      "url from Jan/25/2016 exists. Saving...\n",
      "url from Jan/26/2016 exists. Saving...\n",
      "url from Jan/27/2016 exists. Saving...\n",
      "url from Jan/28/2016 exists. Saving...\n",
      "url from Jan/29/2016 exists. Saving...\n",
      "url from Jan/30/2016 exists. Saving...\n",
      "url from Jan/31/2016 exists. Saving...\n",
      "url from Total Jan/2016 exists. Saving...\n",
      "url from Fev/01/2016 exists. Saving...\n",
      "url from Fev/02/2016 exists. Saving...\n",
      "url from Fev/03/2016 exists. Saving...\n",
      "url from Fev/04/2016 exists. Saving...\n",
      "url from Fev/05/2016 exists. Saving...\n",
      "url from Fev/06/2016 exists. Saving...\n",
      "url from Fev/07/2016 exists. Saving...\n",
      "url from Fev/08/2016 exists. Saving...\n",
      "url from Fev/09/2016 exists. Saving...\n",
      "url from Fev/10/2016 exists. Saving...\n",
      "url from Fev/11/2016 exists. Saving...\n",
      "url from Fev/12/2016 exists. Saving...\n",
      "url from Fev/13/2016 exists. Saving...\n",
      "url from Fev/14/2016 exists. Saving...\n",
      "url from Fev/15/2016 exists. Saving...\n",
      "url from Fev/16/2016 exists. Saving...\n",
      "url from Fev/17/2016 exists. Saving...\n",
      "url from Fev/18/2016 exists. Saving...\n",
      "url from Fev/19/2016 exists. Saving...\n",
      "url from Fev/20/2016 exists. Saving...\n",
      "url from Fev/21/2016 exists. Saving...\n",
      "url from Fev/22/2016 exists. Saving...\n",
      "url from Fev/23/2016 exists. Saving...\n",
      "url from Fev/24/2016 exists. Saving...\n",
      "url from Fev/25/2016 exists. Saving...\n",
      "url from Fev/26/2016 exists. Saving...\n",
      "url from Fev/27/2016 exists. Saving...\n",
      "url from Fev/28/2016 exists. Saving...\n",
      "url from Fev/29/2016 exists. Saving...\n",
      "url from Total Fev/2016 exists. Saving...\n",
      "url from Mar/01/2016 exists. Saving...\n",
      "url from Mar/02/2016 exists. Saving...\n",
      "url from Mar/03/2016 exists. Saving...\n",
      "url from Mar/04/2016 exists. Saving...\n",
      "url from Mar/05/2016 exists. Saving...\n",
      "url from Mar/06/2016 exists. Saving...\n",
      "url from Mar/07/2016 exists. Saving...\n",
      "url from Mar/08/2016 exists. Saving...\n",
      "url from Mar/09/2016 exists. Saving...\n",
      "url from Mar/10/2016 exists. Saving...\n",
      "url from Mar/11/2016 exists. Saving...\n",
      "url from Mar/12/2016 exists. Saving...\n",
      "url from Mar/13/2016 exists. Saving...\n",
      "url from Mar/14/2016 exists. Saving...\n",
      "url from Mar/15/2016 exists. Saving...\n",
      "url from Mar/16/2016 exists. Saving...\n",
      "url from Mar/17/2016 exists. Saving...\n",
      "url from Mar/18/2016 exists. Saving...\n",
      "url from Mar/19/2016 exists. Saving...\n",
      "url from Mar/20/2016 exists. Saving...\n",
      "url from Mar/21/2016 exists. Saving...\n",
      "url from Mar/22/2016 exists. Saving...\n",
      "url from Mar/23/2016 exists. Saving...\n",
      "url from Mar/24/2016 exists. Saving...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Mar/25/2016 exists. Saving...\n",
      "url from Mar/26/2016 exists. Saving...\n",
      "url from Mar/27/2016 exists. Saving...\n",
      "url from Mar/28/2016 exists. Saving...\n",
      "url from Mar/29/2016 exists. Saving...\n",
      "url from Mar/30/2016 exists. Saving...\n",
      "url from Mar/31/2016 exists. Saving...\n",
      "url from Total Mar/2016 exists. Saving...\n",
      "url from Abr/01/2016 exists. Saving...\n",
      "url from Abr/02/2016 exists. Saving...\n",
      "url from Abr/03/2016 exists. Saving...\n",
      "url from Abr/04/2016 exists. Saving...\n",
      "url from Abr/05/2016 exists. Saving...\n",
      "url from Abr/06/2016 exists. Saving...\n",
      "url from Abr/07/2016 exists. Saving...\n",
      "url from Abr/08/2016 exists. Saving...\n",
      "url from Abr/09/2016 exists. Saving...\n",
      "url from Abr/10/2016 exists. Saving...\n",
      "url from Abr/11/2016 exists. Saving...\n",
      "url from Abr/12/2016 exists. Saving...\n",
      "url from Abr/13/2016 exists. Saving...\n",
      "url from Abr/14/2016 exists. Saving...\n",
      "url from Abr/15/2016 exists. Saving...\n",
      "url from Abr/16/2016 exists. Saving...\n",
      "url from Abr/17/2016 exists. Saving...\n",
      "url from Abr/18/2016 exists. Saving...\n",
      "url from Abr/19/2016 exists. Saving...\n",
      "url from Abr/20/2016 exists. Saving...\n",
      "url from Abr/21/2016 exists. Saving...\n",
      "url from Abr/22/2016 exists. Saving...\n",
      "url from Abr/23/2016 exists. Saving...\n",
      "url from Abr/24/2016 exists. Saving...\n",
      "url from Abr/25/2016 exists. Saving...\n",
      "url from Abr/26/2016 exists. Saving...\n",
      "url from Abr/27/2016 exists. Saving...\n",
      "url from Abr/28/2016 exists. Saving...\n",
      "url from Abr/29/2016 exists. Saving...\n",
      "url from Abr/30/2016 exists. Saving...\n",
      "url from Total Abr/2016 exists. Saving...\n",
      "url from Mai/01/2016 exists. Saving...\n",
      "url from Mai/02/2016 exists. Saving...\n",
      "url from Mai/03/2016 exists. Saving...\n",
      "url from Mai/04/2016 exists. Saving...\n",
      "url from Mai/05/2016 exists. Saving...\n",
      "url from Mai/06/2016 exists. Saving...\n",
      "url from Mai/07/2016 exists. Saving...\n",
      "url from Mai/08/2016 exists. Saving...\n",
      "url from Mai/09/2016 exists. Saving...\n",
      "url from Mai/10/2016 exists. Saving...\n",
      "url from Mai/11/2016 exists. Saving...\n",
      "url from Mai/12/2016 exists. Saving...\n",
      "url from Mai/13/2016 exists. Saving...\n",
      "url from Mai/14/2016 exists. Saving...\n",
      "url from Mai/15/2016 exists. Saving...\n",
      "url from Mai/16/2016 exists. Saving...\n",
      "url from Mai/17/2016 exists. Saving...\n",
      "url from Mai/18/2016 exists. Saving...\n",
      "url from Mai/19/2016 exists. Saving...\n",
      "url from Mai/20/2016 exists. Saving...\n",
      "url from Mai/21/2016 exists. Saving...\n",
      "url from Mai/22/2016 exists. Saving...\n",
      "url from Mai/23/2016 exists. Saving...\n",
      "url from Mai/24/2016 exists. Saving...\n",
      "url from Mai/25/2016 exists. Saving...\n",
      "url from Mai/26/2016 exists. Saving...\n",
      "url from Mai/27/2016 exists. Saving...\n",
      "url from Mai/28/2016 exists. Saving...\n",
      "url from Mai/29/2016 exists. Saving...\n",
      "url from Mai/30/2016 exists. Saving...\n",
      "url from Mai/31/2016 exists. Saving...\n",
      "url from Total Mai/2016 exists. Saving...\n",
      "url from Jun/01/2016 exists. Saving...\n",
      "url from Jun/02/2016 exists. Saving...\n",
      "url from Jun/03/2016 exists. Saving...\n",
      "url from Jun/04/2016 exists. Saving...\n",
      "url from Jun/05/2016 exists. Saving...\n",
      "url from Jun/06/2016 exists. Saving...\n",
      "url from Jun/07/2016 exists. Saving...\n",
      "url from Jun/08/2016 exists. Saving...\n",
      "url from Jun/09/2016 exists. Saving...\n",
      "url from Jun/10/2016 exists. Saving...\n",
      "url from Jun/11/2016 exists. Saving...\n",
      "url from Jun/12/2016 exists. Saving...\n",
      "url from Jun/13/2016 exists. Saving...\n",
      "url from Jun/14/2016 exists. Saving...\n",
      "url from Jun/15/2016 exists. Saving...\n",
      "url from Jun/16/2016 exists. Saving...\n",
      "url from Jun/17/2016 exists. Saving...\n",
      "url from Jun/18/2016 exists. Saving...\n",
      "url from Jun/19/2016 exists. Saving...\n",
      "url from Jun/20/2016 exists. Saving...\n",
      "url from Jun/21/2016 exists. Saving...\n",
      "url from Jun/22/2016 exists. Saving...\n",
      "url from Jun/23/2016 exists. Saving...\n",
      "url from Jun/24/2016 exists. Saving...\n",
      "url from Jun/25/2016 exists. Saving...\n",
      "url from Jun/26/2016 exists. Saving...\n",
      "url from Jun/27/2016 exists. Saving...\n",
      "url from Jun/28/2016 exists. Saving...\n",
      "url from Jun/29/2016 exists. Saving...\n",
      "url from Jun/30/2016 exists. Saving...\n",
      "url from Total Jun/2016 exists. Saving...\n",
      "url from Jul/01/2016 exists. Saving...\n",
      "url from Jul/02/2016 exists. Saving...\n",
      "url from Jul/03/2016 exists. Saving...\n",
      "url from Jul/04/2016 exists. Saving...\n",
      "url from Jul/05/2016 exists. Saving...\n",
      "url from Jul/06/2016 exists. Saving...\n",
      "url from Jul/07/2016 exists. Saving...\n",
      "url from Jul/08/2016 exists. Saving...\n",
      "url from Jul/09/2016 exists. Saving...\n",
      "url from Jul/10/2016 exists. Saving...\n",
      "url from Jul/11/2016 exists. Saving...\n",
      "url from Jul/12/2016 exists. Saving...\n",
      "url from Jul/13/2016 exists. Saving...\n",
      "url from Jul/14/2016 exists. Saving...\n",
      "url from Jul/15/2016 exists. Saving...\n",
      "url from Jul/16/2016 exists. Saving...\n",
      "url from Jul/17/2016 exists. Saving...\n",
      "url from Jul/18/2016 exists. Saving...\n",
      "url from Jul/19/2016 exists. Saving...\n",
      "url from Jul/20/2016 exists. Saving...\n",
      "url from Jul/21/2016 exists. Saving...\n",
      "url from Jul/22/2016 exists. Saving...\n",
      "url from Jul/23/2016 exists. Saving...\n",
      "url from Jul/24/2016 exists. Saving...\n",
      "url from Jul/25/2016 exists. Saving...\n",
      "url from Jul/26/2016 exists. Saving...\n",
      "url from Jul/27/2016 exists. Saving...\n",
      "url from Jul/28/2016 exists. Saving...\n",
      "url from Jul/29/2016 exists. Saving...\n",
      "url from Jul/30/2016 exists. Saving...\n",
      "url from Jul/31/2016 exists. Saving...\n",
      "url from Total Jul/2016 exists. Saving...\n",
      "url from Ago/01/2016 exists. Saving...\n",
      "url from Ago/02/2016 exists. Saving...\n",
      "url from Ago/03/2016 exists. Saving...\n",
      "url from Ago/04/2016 exists. Saving...\n",
      "url from Ago/05/2016 exists. Saving...\n",
      "url from Ago/06/2016 exists. Saving...\n",
      "url from Ago/07/2016 exists. Saving...\n",
      "url from Ago/08/2016 exists. Saving...\n",
      "url from Ago/09/2016 exists. Saving...\n",
      "url from Ago/10/2016 exists. Saving...\n",
      "url from Ago/11/2016 exists. Saving...\n",
      "url from Ago/12/2016 exists. Saving...\n",
      "url from Ago/13/2016 exists. Saving...\n",
      "url from Ago/14/2016 exists. Saving...\n",
      "url from Ago/15/2016 exists. Saving...\n",
      "url from Ago/16/2016 exists. Saving...\n",
      "url from Ago/17/2016 exists. Saving...\n",
      "url from Ago/18/2016 exists. Saving...\n",
      "url from Ago/19/2016 exists. Saving...\n",
      "url from Ago/20/2016 exists. Saving...\n",
      "url from Ago/21/2016 exists. Saving...\n",
      "url from Ago/22/2016 exists. Saving...\n",
      "url from Ago/23/2016 exists. Saving...\n",
      "url from Ago/24/2016 exists. Saving...\n",
      "url from Ago/25/2016 exists. Saving...\n",
      "url from Ago/26/2016 exists. Saving...\n",
      "url from Ago/27/2016 exists. Saving...\n",
      "url from Ago/28/2016 exists. Saving...\n",
      "url from Ago/29/2016 exists. Saving...\n",
      "url from Ago/30/2016 exists. Saving...\n",
      "url from Ago/31/2016 exists. Saving...\n",
      "url from Total Ago/2016 exists. Saving...\n",
      "url from Set/01/2016 exists. Saving...\n",
      "url from Set/02/2016 exists. Saving...\n",
      "url from Set/03/2016 exists. Saving...\n",
      "url from Set/04/2016 exists. Saving...\n",
      "url from Set/05/2016 exists. Saving...\n",
      "url from Set/06/2016 exists. Saving...\n",
      "url from Set/07/2016 exists. Saving...\n",
      "url from Set/08/2016 exists. Saving...\n",
      "url from Set/09/2016 exists. Saving...\n",
      "url from Set/10/2016 exists. Saving...\n",
      "url from Set/11/2016 exists. Saving...\n",
      "url from Set/12/2016 exists. Saving...\n",
      "url from Set/13/2016 exists. Saving...\n",
      "url from Set/14/2016 exists. Saving...\n",
      "url from Set/15/2016 exists. Saving...\n",
      "url from Set/16/2016 exists. Saving...\n",
      "url from Set/17/2016 exists. Saving...\n",
      "url from Set/18/2016 exists. Saving...\n",
      "url from Set/19/2016 exists. Saving...\n",
      "url from Set/20/2016 exists. Saving...\n",
      "url from Set/21/2016 exists. Saving...\n",
      "url from Set/22/2016 exists. Saving...\n",
      "url from Set/23/2016 exists. Saving...\n",
      "url from Set/24/2016 exists. Saving...\n",
      "url from Set/25/2016 exists. Saving...\n",
      "url from Set/26/2016 exists. Saving...\n",
      "url from Set/27/2016 exists. Saving...\n",
      "url from Set/28/2016 exists. Saving...\n",
      "url from Set/29/2016 exists. Saving...\n",
      "url from Set/30/2016 exists. Saving...\n",
      "url from Total Set/2016 exists. Saving...\n",
      "url from Out/01/2016 exists. Saving...\n",
      "url from Out/02/2016 exists. Saving...\n",
      "url from Out/03/2016 exists. Saving...\n",
      "url from Out/04/2016 exists. Saving...\n",
      "url from Out/05/2016 exists. Saving...\n",
      "url from Out/06/2016 exists. Saving...\n",
      "url from Out/07/2016 exists. Saving...\n",
      "url from Out/08/2016 exists. Saving...\n",
      "url from Out/09/2016 exists. Saving...\n",
      "url from Out/10/2016 exists. Saving...\n",
      "url from Out/11/2016 exists. Saving...\n",
      "url from Out/12/2016 exists. Saving...\n",
      "url from Out/13/2016 exists. Saving...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "url from Out/14/2016 exists. Saving...\n",
      "url from Out/15/2016 exists. Saving...\n",
      "url from Out/16/2016 exists. Saving...\n",
      "url from Out/17/2016 exists. Saving...\n",
      "url from Out/18/2016 exists. Saving...\n",
      "url from Out/19/2016 exists. Saving...\n",
      "url from Out/20/2016 exists. Saving...\n",
      "url from Out/21/2016 exists. Saving...\n",
      "url from Out/22/2016 exists. Saving...\n",
      "url from Out/23/2016 exists. Saving...\n",
      "url from Out/24/2016 exists. Saving...\n",
      "url from Out/25/2016 exists. Saving...\n",
      "url from Out/26/2016 exists. Saving...\n",
      "url from Out/27/2016 exists. Saving...\n",
      "url from Out/28/2016 exists. Saving...\n",
      "url from Out/29/2016 exists. Saving...\n",
      "url from Out/30/2016 exists. Saving...\n",
      "url from Out/31/2016 exists. Saving...\n",
      "url from Total Out/2016 exists. Saving...\n",
      "url from Nov/01/2016 exists. Saving...\n",
      "url from Nov/02/2016 exists. Saving...\n",
      "url from Nov/03/2016 exists. Saving...\n",
      "url from Nov/04/2016 exists. Saving...\n",
      "url from Nov/05/2016 exists. Saving...\n",
      "url from Nov/06/2016 exists. Saving...\n",
      "url from Nov/07/2016 exists. Saving...\n",
      "url from Nov/08/2016 exists. Saving...\n",
      "url from Nov/09/2016 exists. Saving...\n",
      "url from Nov/10/2016 exists. Saving...\n",
      "url from Nov/11/2016 exists. Saving...\n",
      "url from Nov/12/2016 exists. Saving...\n",
      "url from Nov/13/2016 exists. Saving...\n",
      "url from Nov/14/2016 exists. Saving...\n",
      "url from Nov/15/2016 exists. Saving...\n",
      "url from Nov/16/2016 exists. Saving...\n",
      "url from Nov/17/2016 exists. Saving...\n",
      "url from Nov/18/2016 exists. Saving...\n",
      "url from Nov/19/2016 exists. Saving...\n",
      "url from Nov/20/2016 exists. Saving...\n",
      "url from Nov/21/2016 exists. Saving...\n",
      "url from Nov/22/2016 exists. Saving...\n",
      "url from Nov/23/2016 exists. Saving...\n",
      "url from Nov/24/2016 exists. Saving...\n",
      "url from Nov/25/2016 exists. Saving...\n",
      "url from Nov/26/2016 exists. Saving...\n",
      "url from Nov/27/2016 exists. Saving...\n",
      "url from Nov/28/2016 exists. Saving...\n",
      "url from Nov/29/2016 exists. Saving...\n",
      "url from Nov/30/2016 exists. Saving...\n",
      "url from Total Nov/2016 exists. Saving...\n",
      "url from Dez/01/2016 exists. Saving...\n",
      "url from Dez/02/2016 exists. Saving...\n",
      "url from Dez/03/2016 exists. Saving...\n",
      "url from Dez/04/2016 exists. Saving...\n",
      "url from Dez/05/2016 exists. Saving...\n",
      "url from Dez/06/2016 exists. Saving...\n",
      "url from Dez/07/2016 exists. Saving...\n",
      "url from Dez/08/2016 exists. Saving...\n",
      "url from Dez/09/2016 exists. Saving...\n",
      "url from Dez/10/2016 exists. Saving...\n",
      "url from Dez/11/2016 exists. Saving...\n",
      "url from Dez/12/2016 exists. Saving...\n",
      "url from Dez/13/2016 exists. Saving...\n",
      "url from Dez/14/2016 exists. Saving...\n",
      "url from Dez/15/2016 exists. Saving...\n",
      "url from Dez/16/2016 exists. Saving...\n",
      "url from Dez/17/2016 exists. Saving...\n",
      "url from Dez/18/2016 exists. Saving...\n",
      "url from Dez/19/2016 exists. Saving...\n",
      "url from Dez/20/2016 exists. Saving...\n",
      "url from Dez/21/2016 exists. Saving...\n",
      "url from Dez/22/2016 exists. Saving...\n",
      "url from Dez/23/2016 exists. Saving...\n",
      "url from Dez/24/2016 exists. Saving...\n",
      "url from Dez/25/2016 exists. Saving...\n",
      "url from Dez/26/2016 exists. Saving...\n",
      "url from Dez/27/2016 exists. Saving...\n",
      "url from Dez/28/2016 exists. Saving...\n",
      "url from Dez/29/2016 exists. Saving...\n",
      "url from Dez/30/2016 exists. Saving...\n",
      "url from Dez/31/2016 exists. Saving...\n",
      "url from Total Dez/2016 exists. Saving...\n",
      "url from Jan/01/2017 exists. Saving...\n",
      "url from Jan/02/2017 exists. Saving...\n",
      "url from Jan/03/2017 exists. Saving...\n",
      "url from Jan/04/2017 exists. Saving...\n",
      "url from Jan/05/2017 exists. Saving...\n",
      "url from Jan/06/2017 exists. Saving...\n",
      "url from Jan/07/2017 exists. Saving...\n",
      "url from Jan/08/2017 exists. Saving...\n",
      "url from Jan/09/2017 exists. Saving...\n",
      "url from Jan/10/2017 exists. Saving...\n",
      "url from Jan/11/2017 exists. Saving...\n",
      "url from Jan/12/2017 exists. Saving...\n",
      "url from Jan/13/2017 exists. Saving...\n",
      "url from Jan/14/2017 exists. Saving...\n",
      "url from Jan/15/2017 exists. Saving...\n",
      "url from Jan/16/2017 exists. Saving...\n",
      "url from Jan/17/2017 exists. Saving...\n",
      "url from Jan/18/2017 exists. Saving...\n",
      "url from Jan/19/2017 exists. Saving...\n",
      "url from Jan/20/2017 exists. Saving...\n",
      "url from Jan/21/2017 exists. Saving...\n",
      "url from Jan/22/2017 exists. Saving...\n",
      "url from Jan/23/2017 exists. Saving...\n",
      "url from Jan/24/2017 exists. Saving...\n",
      "url from Jan/25/2017 exists. Saving...\n",
      "url from Jan/26/2017 exists. Saving...\n",
      "url from Jan/27/2017 exists. Saving...\n",
      "url from Jan/28/2017 exists. Saving...\n",
      "url from Jan/29/2017 exists. Saving...\n",
      "url from Jan/30/2017 exists. Saving...\n",
      "url from Jan/31/2017 exists. Saving...\n",
      "url from Total Jan/2017 exists. Saving...\n",
      "url from Fev/01/2017 exists. Saving...\n",
      "url from Fev/02/2017 exists. Saving...\n",
      "url from Fev/03/2017 exists. Saving...\n",
      "url from Fev/04/2017 exists. Saving...\n",
      "url from Fev/05/2017 exists. Saving...\n",
      "url from Fev/06/2017 exists. Saving...\n",
      "url from Fev/07/2017 exists. Saving...\n",
      "url from Fev/08/2017 exists. Saving...\n",
      "url from Fev/09/2017 exists. Saving...\n",
      "url from Fev/10/2017 exists. Saving...\n",
      "url from Fev/11/2017 exists. Saving...\n",
      "url from Fev/12/2017 exists. Saving...\n",
      "url from Fev/13/2017 exists. Saving...\n",
      "url from Fev/14/2017 exists. Saving...\n",
      "url from Fev/15/2017 exists. Saving...\n",
      "url from Fev/16/2017 exists. Saving...\n",
      "url from Fev/17/2017 exists. Saving...\n",
      "url from Fev/18/2017 exists. Saving...\n",
      "url from Fev/19/2017 exists. Saving...\n",
      "url from Fev/20/2017 exists. Saving...\n",
      "url from Fev/21/2017 exists. Saving...\n",
      "url from Fev/22/2017 exists. Saving...\n",
      "url from Fev/23/2017 exists. Saving...\n",
      "url from Fev/24/2017 exists. Saving...\n",
      "url from Fev/25/2017 exists. Saving...\n",
      "url from Fev/26/2017 exists. Saving...\n",
      "url from Fev/27/2017 exists. Saving...\n",
      "url from Fev/28/2017 exists. Saving...\n",
      "url from Total Fev/2017 exists. Saving...\n",
      "url from Mar/01/2017 exists. Saving...\n",
      "url from Mar/02/2017 exists. Saving...\n",
      "url from Mar/03/2017 exists. Saving...\n",
      "url from Mar/04/2017 exists. Saving...\n",
      "url from Mar/05/2017 exists. Saving...\n",
      "url from Mar/06/2017 exists. Saving...\n",
      "url from Mar/07/2017 exists. Saving...\n",
      "url from Mar/08/2017 exists. Saving...\n",
      "url from Mar/09/2017 exists. Saving...\n",
      "url from Mar/10/2017 exists. Saving...\n",
      "url from Mar/11/2017 exists. Saving...\n",
      "url from Mar/12/2017 exists. Saving...\n",
      "url from Mar/13/2017 exists. Saving...\n",
      "url from Mar/14/2017 exists. Saving...\n",
      "url from Mar/15/2017 exists. Saving...\n",
      "url from Mar/16/2017 exists. Saving...\n",
      "url from Mar/17/2017 exists. Saving...\n",
      "url from Mar/18/2017 exists. Saving...\n",
      "url from Mar/19/2017 exists. Saving...\n",
      "url from Mar/20/2017 exists. Saving...\n",
      "url from Mar/21/2017 exists. Saving...\n",
      "url from Mar/22/2017 exists. Saving...\n",
      "url from Mar/23/2017 exists. Saving...\n",
      "url from Mar/24/2017 exists. Saving...\n",
      "url from Mar/25/2017 exists. Saving...\n",
      "url from Mar/26/2017 exists. Saving...\n",
      "url from Mar/27/2017 exists. Saving...\n",
      "url from Mar/28/2017 exists. Saving...\n",
      "url from Mar/29/2017 exists. Saving...\n",
      "url from Mar/30/2017 exists. Saving...\n",
      "url from Mar/31/2017 exists. Saving...\n",
      "url from Total Mar/2017 exists. Saving...\n",
      "url from Abr/01/2017 exists. Saving...\n",
      "url from Abr/02/2017 exists. Saving...\n",
      "url from Abr/03/2017 exists. Saving...\n",
      "url from Abr/04/2017 exists. Saving...\n",
      "url from Abr/05/2017 exists. Saving...\n",
      "url from Abr/06/2017 exists. Saving...\n",
      "url from Abr/07/2017 exists. Saving...\n",
      "url from Abr/08/2017 exists. Saving...\n",
      "url from Abr/09/2017 exists. Saving...\n",
      "url from Abr/10/2017 exists. Saving...\n",
      "url from Abr/11/2017 exists. Saving...\n",
      "url from Abr/12/2017 exists. Saving...\n",
      "url from Abr/13/2017 exists. Saving...\n",
      "url from Abr/14/2017 exists. Saving...\n",
      "url from Abr/15/2017 exists. Saving...\n",
      "url from Abr/16/2017 exists. Saving...\n",
      "url from Abr/17/2017 exists. Saving...\n",
      "url from Abr/18/2017 exists. Saving...\n",
      "url from Abr/19/2017 exists. Saving...\n",
      "url from Abr/20/2017 exists. Saving...\n",
      "url from Abr/21/2017 exists. Saving...\n",
      "url from Abr/22/2017 exists. Saving...\n",
      "url from Abr/23/2017 exists. Saving...\n",
      "url from Abr/24/2017 exists. Saving...\n",
      "url from Abr/25/2017 exists. Saving...\n",
      "url from Abr/26/2017 exists. Saving...\n",
      "Dia Abr/27/2017 não encontrado\n",
      "http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/2017/abril/passageiros/Passag-20170427.xls\n",
      "Mês Total Abr/2017 não encontrado\n",
      "http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/2017/abril/passageiros/Pass_Transp_Abr17.xls\n"
     ]
    }
   ],
   "source": [
    "#------ Importing the datasets\n",
    "\n",
    "# Years 2014 ~ 2017\n",
    "dataset_d = {}\n",
    "dataset_m = {}\n",
    "month_list = [\"janeiro\", \"fevereiro\", \"marco\", \"abril\", \"maio\", \"junho\", \"julho\", \"agosto\", \"setembro\", \"outubro\", \"novembro\", \"dezembro\"]\n",
    "month_list_abr = [\"Jan\", \"Fev\", \"Mar\", \"Abr\", \"Mai\", \"Jun\", \"Jul\", \"Ago\", \"Set\", \"Out\", \"Nov\", \"Dez\"]\n",
    "errors = []\n",
    "\n",
    "current_year = 2017\n",
    "for year in range(2014, current_year + 1):\n",
    "    for month in range(1, 13):\n",
    "        for day in range(1, calendar.monthrange(year, month)[1] + 1):\n",
    "            year_str = str(year)\n",
    "            month_str = str(month)\n",
    "            day_str = str(day)\n",
    "            \n",
    "            month_str = month_str.zfill(2)\n",
    "            day_str = day_str.zfill(2)\n",
    "            date_str = year_str + month_str + day_str\n",
    "            \n",
    "            if year <= 2014 and month < 10: # Before this date, the links doesn't have /before acesso_a_informacao\n",
    "                url = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/{}/{}/passageiros/Passag-{}.xls\".format(year_str, month_list[month - 1], date_str))\n",
    "            else:\n",
    "                url = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/{}/{}/passageiros/Passag-{}.xls\".format(year_str, month_list[month - 1], date_str))\n",
    "            http = urllib3.PoolManager()\n",
    "            r = http.request('GET', url)\n",
    "            \n",
    "            if r.status < 400:\n",
    "                print (\"url from {} exists. Saving...\".format(month_list_abr[month - 1] + \"/\" + day_str + \"/\" + year_str))\n",
    "                dataset_d[date_str] = pd.read_excel(url)\n",
    "                last_day= day\n",
    "            else:\n",
    "                print (\"Dia {} não encontrado\".format(month_list_abr[month - 1] + \"/\" + day_str + \"/\" + year_str))\n",
    "                print (url)\n",
    "                errors.append(url)\n",
    "                if year == current_year:\n",
    "                    break\n",
    "\n",
    "        if year == 2014 and month <= 12: #Before this date, the links doesn't have /before acesso_a_informacao\n",
    "            if year == 2014 and month == 4:\n",
    "                url_total = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/{}/{}/passageiros/Pass_Transp_{}.xlsx\".format(year_str, month_list[month - 1], month_list_abr[month - 1] + str(year % 100)))\n",
    "            elif year == 2014 and month == 10 or month == 11:\n",
    "                url_total = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/{}/{}/passageiros/Pass_Transp_{}.xls\".format(year_str, month_list[month - 1], month_list_abr[month - 1] + str(year % 100)))\n",
    "            elif year == 2014 and month == 12:\n",
    "                url_total = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/{}/{}/passageiros/Pass_Transp_{}.xlsx\".format(year_str, month_list[month - 1], month_list_abr[month - 1] + str(year % 100)))\n",
    "            else:\n",
    "                url_total = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/{}/{}/passageiros/Pass_Transp_{}.xls\".format(year_str, month_list[month - 1], month_list_abr[month - 1] + str(year % 100)))   \n",
    "        else:\n",
    "            url_total = (\"http://www.prefeitura.sp.gov.br/cidade/secretarias/upload/transportes/SPTrans/acesso_a_informacao/{}/{}/passageiros/Pass_Transp_{}.xls\".format(year_str, month_list[month - 1], month_list_abr[month - 1] + str(year % 100)))\n",
    "        \n",
    "        http = urllib3.PoolManager()\n",
    "        r = http.request('GET', url_total)\n",
    "        \n",
    "        if r.status < 400:\n",
    "            print (\"url from Total {} exists. Saving...\".format(month_list_abr[month - 1] + \"/\" + year_str))\n",
    "            dataset_m[year_str + month_str] = pd.read_excel(url_total)\n",
    "            last_month = month\n",
    "        else:\n",
    "            print (\"Mês Total {} não encontrado\".format(month_list_abr[month - 1] + \"/\" + year_str))\n",
    "            print (url_total)\n",
    "            errors.append(url_total)\n",
    "            if year == current_year:\n",
    "                break\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Para o Mês de Janeiro de 2014, somando-se dia a dia chegamos em 225.130.349 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 225.130.349 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Fevereiro de 2014, somando-se dia a dia chegamos em 234.365.831 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 234.365.831 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Marco de 2014, somando-se dia a dia chegamos em 241.120.083 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 241.120.083 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Abril de 2014, somando-se dia a dia chegamos em 243.628.063 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 243.628.063 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Maio de 2014, somando-se dia a dia chegamos em 246.013.104 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 246.013.104 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Junho de 2014, somando-se dia a dia chegamos em 219.429.563 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 219.429.563 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Julho de 2014, somando-se dia a dia chegamos em 230.935.626 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 230.935.626 passageiros\n",
      "Diferença de 00 passageiros\n",
      "\n",
      "Para o Mês de Agosto de 2014, somando-se dia a dia chegamos em 254.004.951 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 260.075.038 passageiros\n",
      "Diferença de -6.070.087 passageiros\n",
      "\n",
      "Para o Mês de Setembro de 2014, somando-se dia a dia chegamos em 256.728.802 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 256.714.285 passageiros\n",
      "Diferença de 14.517 passageiros\n",
      "\n",
      "Para o Mês de Outubro de 2014, somando-se dia a dia chegamos em 267.526.295 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 267.487.508 passageiros\n",
      "Diferença de 38.787 passageiros\n",
      "\n",
      "Para o Mês de Novembro de 2014, somando-se dia a dia chegamos em 238.763.570 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 238.752.325 passageiros\n",
      "Diferença de 11.245 passageiros\n",
      "\n",
      "Para o Mês de Dezembro de 2014, somando-se dia a dia chegamos em 230.767.700 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 230.725.528 passageiros\n",
      "Diferença de 42.172 passageiros\n",
      "\n",
      "Para o Mês de Janeiro de 2015, somando-se dia a dia chegamos em 214.885.734 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 214.868.759 passageiros\n",
      "Diferença de 16.975 passageiros\n",
      "\n",
      "Para o Mês de Fevereiro de 2015, somando-se dia a dia chegamos em 207.178.267 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 207.161.916 passageiros\n",
      "Diferença de 16.351 passageiros\n",
      "\n",
      "Para o Mês de Marco de 2015, somando-se dia a dia chegamos em 254.067.306 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 253.923.300 passageiros\n",
      "Diferença de 144.006 passageiros\n",
      "\n",
      "Para o Mês de Abril de 2015, somando-se dia a dia chegamos em 236.604.880 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 236.588.277 passageiros\n",
      "Diferença de 16.603 passageiros\n",
      "\n",
      "Para o Mês de Maio de 2015, somando-se dia a dia chegamos em 246.043.325 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 246.024.098 passageiros\n",
      "Diferença de 19.227 passageiros\n",
      "\n",
      "Para o Mês de Junho de 2015, somando-se dia a dia chegamos em 240.977.643 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 240.934.936 passageiros\n",
      "Diferença de 42.707 passageiros\n",
      "\n",
      "Para o Mês de Julho de 2015, somando-se dia a dia chegamos em 234.527.665 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 234.482.321 passageiros\n",
      "Diferença de 45.344 passageiros\n",
      "\n",
      "Para o Mês de Agosto de 2015, somando-se dia a dia chegamos em 253.204.966 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 253.166.165 passageiros\n",
      "Diferença de 38.801 passageiros\n",
      "\n",
      "Para o Mês de Setembro de 2015, somando-se dia a dia chegamos em 246.192.134 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 246.152.120 passageiros\n",
      "Diferença de 40.014 passageiros\n",
      "\n",
      "Para o Mês de Outubro de 2015, somando-se dia a dia chegamos em 256.039.895 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 255.994.448 passageiros\n",
      "Diferença de 45.447 passageiros\n",
      "\n",
      "Para o Mês de Novembro de 2015, somando-se dia a dia chegamos em 239.160.193 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 239.124.588 passageiros\n",
      "Diferença de 35.605 passageiros\n",
      "\n",
      "Para o Mês de Dezembro de 2015, somando-se dia a dia chegamos em 234.498.455 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 234.449.058 passageiros\n",
      "Diferença de 49.397 passageiros\n",
      "\n",
      "Para o Mês de Janeiro de 2016, somando-se dia a dia chegamos em 206.633.452 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 206.576.942 passageiros\n",
      "Diferença de 56.510 passageiros\n",
      "\n",
      "Para o Mês de Fevereiro de 2016, somando-se dia a dia chegamos em 223.188.556 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 223.120.532 passageiros\n",
      "Diferença de 68.024 passageiros\n",
      "\n",
      "Para o Mês de Marco de 2016, somando-se dia a dia chegamos em 257.936.118 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 257.844.976 passageiros\n",
      "Diferença de 91.142 passageiros\n",
      "\n",
      "Para o Mês de Abril de 2016, somando-se dia a dia chegamos em 244.713.060 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 244.619.611 passageiros\n",
      "Diferença de 93.449 passageiros\n",
      "\n",
      "Para o Mês de Maio de 2016, somando-se dia a dia chegamos em 249.439.621 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 246.493.286 passageiros\n",
      "Diferença de 2.946.335 passageiros\n",
      "\n",
      "Para o Mês de Junho de 2016, somando-se dia a dia chegamos em 248.146.976 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 248.039.105 passageiros\n",
      "Diferença de 107.871 passageiros\n",
      "\n",
      "Para o Mês de Julho de 2016, somando-se dia a dia chegamos em 230.565.446 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 230.472.166 passageiros\n",
      "Diferença de 93.280 passageiros\n",
      "\n",
      "Para o Mês de Agosto de 2016, somando-se dia a dia chegamos em 261.386.742 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 261.359.175 passageiros\n",
      "Diferença de 27.567 passageiros\n",
      "\n",
      "Para o Mês de Setembro de 2016, somando-se dia a dia chegamos em 250.449.157 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 250.447.269 passageiros\n",
      "Diferença de 1.888 passageiros\n",
      "\n",
      "Para o Mês de Outubro de 2016, somando-se dia a dia chegamos em 252.565.932 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 251.011.430 passageiros\n",
      "Diferença de 1.554.502 passageiros\n",
      "\n",
      "Para o Mês de Novembro de 2016, somando-se dia a dia chegamos em 245.533.068 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 245.532.671 passageiros\n",
      "Diferença de 397 passageiros\n",
      "\n",
      "Para o Mês de Dezembro de 2016, somando-se dia a dia chegamos em 240.135.967 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 237.512.164 passageiros\n",
      "Diferença de 2.623.803 passageiros\n",
      "\n",
      "Para o Mês de Janeiro de 2017, somando-se dia a dia chegamos em 209.830.524 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 209.830.436 passageiros\n",
      "Diferença de 88 passageiros\n",
      "\n",
      "Para o Mês de Fevereiro de 2017, somando-se dia a dia chegamos em 219.369.088 passageiros.\n",
      "Na planilha consolidada no Site da SPTrans o valor fornecido foi de 219.369.013 passageiros\n",
      "Diferença de 75 passageiros\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#------ Verifying Numbers\n",
    "   \n",
    "# Let's check if the sum of the days of month hits with the worksheet's total\n",
    "import time\n",
    "\n",
    "total = {}\n",
    "total_paying = {}\n",
    "total_integration = {}\n",
    "total_free_passengers = {}\n",
    "total_free_students = {}\n",
    "\n",
    "xTicks = []\n",
    "\n",
    "ytotal = []\n",
    "ytotal_paying = []\n",
    "ytotal_integration = []\n",
    "ytotal_free_passengers = []\n",
    "ytotal_free_students = []\n",
    "\n",
    "for year in range(2014, current_year + 1):\n",
    "    for month in range(1, 13):\n",
    "        \n",
    "        if year == current_year and month == last_month:\n",
    "            break\n",
    "\n",
    "        total_month = 0\n",
    "        total_paying_month = 0\n",
    "        total_integration_month = 0\n",
    "        total_free_passengers_month = 0\n",
    "        total_free_students_month = 0\n",
    "        \n",
    "        for day in range(1, calendar.monthrange(year, month)[1] + 1):\n",
    "            year_str = str(year)\n",
    "            month_str = str(month)\n",
    "            day_str = str(day)\n",
    "            month_str = month_str.zfill(2)\n",
    "            day_str = day_str.zfill(2)\n",
    "            date_str = year_str + month_str + day_str\n",
    "            \n",
    "            total_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -1 ].sum() + total_month\n",
    "            \n",
    "            if time.strptime(date_str, \"%Y%m%d\") >= time.strptime(\"20150409\", \"%Y%m%d\"): \n",
    "                 total_paying_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -5 ].sum() + total_paying_month\n",
    "                 total_integration_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -4 ].sum() + total_integration_month\n",
    "                 total_free_passengers_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -3 ].sum() + total_free_passengers_month\n",
    "                 total_free_students_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -2 ].sum() + total_free_students_month\n",
    "            else:            \n",
    "                 total_paying_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -4 ].sum() + total_paying_month\n",
    "                 total_integration_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -3 ].sum() + total_integration_month\n",
    "                 total_free_passengers_month = dataset_d[date_str].iloc[:,dataset_d[date_str].shape[1] -2 ].sum() + total_free_passengers_month\n",
    "        \n",
    "            empresa_today = dataset_d[date_str].groupby(by=[\"EMPRESA\"])[dataset_d[date_str].columns.values[-1]].sum()\n",
    "            tipo_today = dataset_d[date_str].groupby(by=[\"TIPO\"])[dataset_d[date_str].columns.values[-1]].sum()\n",
    "            area_today = dataset_d[date_str].groupby(by=[\"AREA\"])[dataset_d[date_str].columns.values[-1]].sum()\n",
    "            linha_today = dataset_d[date_str].iloc[:, [1, 2, 3, 4, -1]]\n",
    "            \n",
    "            if year == 2014 and month == 1 and day == 1: \n",
    "                empresa = empresa_today\n",
    "                tipo = tipo_today\n",
    "                area = area_today\n",
    "                linha = linha_today\n",
    "            else: \n",
    "                empresa = pd.concat([empresa_today, empresa], axis=1).fillna(0).sum(axis=1)\n",
    "                tipo = pd.concat([tipo_today, tipo], axis=1).fillna(0).sum(axis=1)\n",
    "                area = pd.concat([area_today, area], axis=1).fillna(0).sum(axis=1)\n",
    "                linha_today.columns.values[-1] = \"PASSAGEIROS\"\n",
    "                linha.columns.values[-1] = \"PASSAGEIROS\"\n",
    "                linha = pd.concat([linha_today, linha], axis=0).fillna(0)\n",
    "                linha = linha.groupby(by=[\"TIPO\", \"AREA\", \"EMPRESA\", \"LINHA\"])[linha.columns.values[-1]].sum()\n",
    "                linha = linha.reset_index()\n",
    "                \n",
    "                #20141203 começam a ter linhas sem nada mas com quantidade de passageiros\n",
    "                \n",
    "        total[year_str+month_str] = int(total_month)\n",
    "        total_paying[year_str+month_str] = int(total_paying_month)\n",
    "        total_integration[year_str+month_str] = int(total_integration_month)\n",
    "        total_free_passengers[year_str+month_str] = int(total_free_passengers_month)\n",
    "        total_free_students[year_str+month_str] = int(total_free_students_month)\n",
    "        \n",
    "        locale.format('%.2d', dataset_m[year_str + month_str].iloc[:,dataset_m[year_str + month_str].shape[1] -1].sum(), True)\n",
    "        \n",
    "        print (\"Para o Mês de {} de {}, somando-se dia a dia chegamos em {} passageiros.\".format(month_list[month - 1].title(), year, locale.format('%.2d', total[year_str+month_str], True) ))\n",
    "        print (\"Na planilha consolidada no Site da SPTrans o valor fornecido foi de {} passageiros\".format(locale.format('%.2d', dataset_m[year_str + month_str].iloc[:,dataset_m[year_str + month_str].shape[1] -1].sum(), True)))\n",
    "        print (\"Diferença de {} passageiros\".format( locale.format('%.2d', total[year_str+month_str] - dataset_m[year_str + month_str].iloc[:,dataset_m[year_str + month_str].shape[1] -1 ].sum(), True) ))\n",
    "        print (\"\")\n",
    "        \n",
    "        xTicks.append(month_list_abr[month - 1].title() + \" \" + year_str) # for plot\n",
    "        \n",
    "        ytotal.append(total_month/10**6)\n",
    "        ytotal_paying.append(total_paying_month/10**6)\n",
    "        ytotal_integration.append(total_integration_month/10**6)\n",
    "        ytotal_free_passengers.append(total_free_passengers_month/10**6)\n",
    "        ytotal_free_students.append(total_free_students_month/10**6)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#------ Creating a Index Renaming the Columns and Sorting \n",
    "empresa = empresa.reset_index()\n",
    "empresa.columns = [\"EMPRESA\", \"PASSAGEIROS\"]\n",
    "empresa = empresa.sort_values(\"PASSAGEIROS\", ascending=False)\n",
    "\n",
    "tipo = tipo.reset_index()\n",
    "tipo.columns = [\"TIPO\", \"PASSAGEIROS\"]\n",
    "tipo = tipo.sort_values(\"PASSAGEIROS\", ascending=False)\n",
    "\n",
    "area = area.reset_index()\n",
    "area.columns = [\"AREA\", \"PASSAGEIROS\"]\n",
    "area = area.sort_values(\"PASSAGEIROS\", ascending=False)\n",
    "\n",
    "linha = linha.drop(linha.index[[0]]) #Deleting the first line with error values \n",
    "linha = linha.sort_values(\"PASSAGEIROS\", ascending=False) #Sorting max => min\n",
    "linha = linha.reset_index() # Creating a new index\n",
    "linha = linha.drop(linha.columns[[0]], axis=1) #Deleting the the column create before (this way in can have a index in order =) )\n",
    "\n",
    "linha_linha = linha.groupby(by=[\"LINHA\"])[linha.columns.values[-1]].sum()\n",
    "linha_linha = linha_linha.reset_index()\n",
    "\n",
    "for index, row in linha_linha.iterrows():\n",
    "    valor = row[0].split(' ')[0]\n",
    "    linha_linha.set_value(index,'LINHANUM', valor) # Let's strip the LINHA COLUMN to get only the code of line and create a n ew column\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Na linha 101210 - JD MONTE BELO/TERM JD BRITANIA temos um uma relação de 206397.02 Passageiros por km \n",
      "Na linha 101510 - CHAC MARIA TRINDADE/T JD BRITA temos um uma relação de 48380.01 Passageiros por km \n",
      "Na linha 101610 - CEMITERIO DO HORTO/CENTER NORT temos um uma relação de 1213331.52 Passageiros por km \n",
      "Na linha 101710 - PERUS/VILA IORIO temos um uma relação de 954603.81 Passageiros por km \n",
      "Na linha 101810 - VILA ROSA/SANTANA temos um uma relação de 721793.37 Passageiros por km \n",
      "Na linha 102110 - COHAB BRASILANDI/TERM PIRITUBA temos um uma relação de 164193.54 Passageiros por km \n",
      "Na linha 102410 - JD CAROMBE/CONEX PETRONIO PORT temos um uma relação de 1323839.23 Passageiros por km \n",
      "Na linha 102510 - JARDIM CAROMBÉ/LAPA temos um uma relação de 431723.56 Passageiros por km \n",
      "Na linha 102610 - VILA IARA/CONEX PETRON PORTELA temos um uma relação de 288082.88 Passageiros por km \n",
      "Na linha 103410 - MORRO GRANDE/CONEXAO VILA LORI temos um uma relação de 1241327.41 Passageiros por km \n",
      "Na linha 103610 - COHAB BRASILANDIA/CONEXAO VILA temos um uma relação de 1165206.23 Passageiros por km \n",
      "Na linha 106A10 - METRO SANTANA / ITAIM BIBI temos um uma relação de 1284940.27 Passageiros por km \n",
      "Na linha 107T10 - CID UNIVERSIT/ METRO TUCURUVI temos um uma relação de 456171.02 Passageiros por km \n",
      "Na linha 115610 - VILA SABRINA/PC DO CORREIO temos um uma relação de 638943.74 Passageiros por km \n",
      "Na linha 115631 - VILA SABRINA/PÇA DO CORREIO temos um uma relação de 32236.32 Passageiros por km \n",
      "Na linha 117710 - TERM.A.E.CARVALHO-EST.LUZ temos um uma relação de 248947.04 Passageiros por km \n",
      "Na linha 117731 - TERM A E CARVALHO/EST DA LUZ temos um uma relação de 23492.47 Passageiros por km \n",
      "Na linha 117742 - ENG.GOULART-TERM.D.PEDRO II temos um uma relação de 16944.89 Passageiros por km \n",
      "Na linha 117810 - SAO MIGUEL-PCA DO CORREIO temos um uma relação de 461289.40 Passageiros por km \n",
      "Na linha 117831 - SAO MIGUEL/PÇA DO CORREIO temos um uma relação de 259466.57 Passageiros por km \n",
      "Na linha 117832 - ABEL TAVARES/PÇA DO CORREIO temos um uma relação de 18883.73 Passageiros por km \n",
      "Na linha 117833 - PÇA DO CORREIO/SAO MIGUEL temos um uma relação de 13518.73 Passageiros por km \n",
      "Na linha 117842 - CJ.HAB.VILA SILVIA-PCA.CORREIO temos um uma relação de 8918.60 Passageiros por km \n",
      "Na linha 118C10 - JD PERY ALTO/METRO ST CECILIA temos um uma relação de 904116.02 Passageiros por km \n",
      "Na linha 118Y10 - LAUZANE PAULISTA/LAPA temos um uma relação de 760835.15 Passageiros por km \n",
      "Na linha 119C10 - VILA SABRINA/TERM PRINC ISABEL temos um uma relação de 387147.91 Passageiros por km \n",
      "Na linha 119L10 - VILA SULINA/TERMINAL LAPA temos um uma relação de 54733.33 Passageiros por km \n",
      "Na linha 120610 - PQ VILA MARIA/CORREIO temos um uma relação de 303251.30 Passageiros por km \n",
      "Na linha 121G10 - PQ NOVO MUNDO/JACANA temos um uma relação de 368752.87 Passageiros por km \n",
      "Na linha 128Y10 - JD PERY ALTO/LAPA temos um uma relação de 467522.15 Passageiros por km \n",
      "Na linha 129F10 - CONEX PETRON PORT/M BARRA FUND temos um uma relação de 1421749.27 Passageiros por km \n",
      "Na linha 129F41 - CON PETRON PORT/PCA DO CORREIO temos um uma relação de 55418.68 Passageiros por km \n",
      "Na linha 139A10 - CONEXAO VILA LORIO/LAPA temos um uma relação de 261671.39 Passageiros por km \n",
      "Na linha 148L10 - CACHOEIRINHA/LAPA temos um uma relação de 1027681.40 Passageiros por km \n",
      "Na linha 148P10 - JD PERY/LAPA temos um uma relação de 669388.73 Passageiros por km \n",
      "Na linha 170110 - JOVA RURAL / ANEHEMBI temos um uma relação de 348964.95 Passageiros por km \n",
      "Na linha 170121 - JOVA RURAL/METRO TUCURUVI temos um uma relação de 182564.79 Passageiros por km \n",
      "Na linha 170122 - JOVA RURAL/METRO TUCURUVI temos um uma relação de 36372.60 Passageiros por km \n",
      "Na linha 170210 - JOVA RURAL/TIETE temos um uma relação de 760043.27 Passageiros por km \n",
      "Na linha 170310 - CAMPO LIMPO/TERM PARADA INGLES temos um uma relação de 341424.28 Passageiros por km \n",
      "Na linha 170510 - JD SAO JOAO /METRO TUCURUVI temos um uma relação de 1687594.19 Passageiros por km \n",
      "Na linha 170910 - JD JOAMAR/METRO TUCURUVI temos um uma relação de 1189804.93 Passageiros por km \n",
      "Na linha 170921 - JD JOAMAR/METRO SANTANA temos um uma relação de 91817.60 Passageiros por km \n",
      "Na linha 172010 - JD GUANCA/CANTAREIRA temos um uma relação de 920764.40 Passageiros por km \n",
      "Na linha 172021 - VILA SABRINA/METRO TUCURUVI temos um uma relação de 682161.28 Passageiros por km \n",
      "Na linha 172110 - VILA EDE/METRO CARANDIRU temos um uma relação de 603849.20 Passageiros por km \n",
      "Na linha 172210 - JD MARINA/TUCURUVI temos um uma relação de 1177967.10 Passageiros por km \n",
      "Na linha 172610 - VILA ZILDA/METRO SANTANA temos um uma relação de 828715.16 Passageiros por km \n",
      "Na linha 172J10 - JD BRASIL/TATUAPE temos um uma relação de 1286663.13 Passageiros por km \n",
      "Na linha 172K10 - JD TREMEMBE/TATUAPE temos um uma relação de 765747.20 Passageiros por km \n",
      "Na linha 172N10 - SHOP CENTER NORTE/METRO BELEM temos um uma relação de 738594.35 Passageiros por km \n",
      "Na linha 172N21 - FAC UNINOVE/METRO BELEM temos um uma relação de 45077.47 Passageiros por km \n",
      "Na linha 172N22 - CATUMBI/METRO BELEM temos um uma relação de 97062.72 Passageiros por km \n",
      "Na linha 172P10 - VILA ZILDA/METRO BELEM temos um uma relação de 1004675.67 Passageiros por km \n",
      "Na linha 172R10 - JD BRASIL/METRO BELEM temos um uma relação de 1660413.00 Passageiros por km \n",
      "Na linha 172U10 - CEM P PINHEIROS/MOOCA temos um uma relação de 607684.63 Passageiros por km \n",
      "Na linha 172X10 - PQ NOVO MUNDO/TATUAPE temos um uma relação de 1456939.73 Passageiros por km \n",
      "Na linha 172Y10 - VILA CONSTANÇA/METRO BELEM temos um uma relação de 832911.72 Passageiros por km \n",
      "Na linha 173010 - CENTER NORTE/SANTANA temos um uma relação de 371910.98 Passageiros por km \n",
      "Na linha 173210 - VILA SABRINA/METRO SANTA CECIL temos um uma relação de 436631.66 Passageiros por km \n",
      "Na linha 173810 - VILA CONSTANCIA/METRO CARANDIR temos um uma relação de 479710.11 Passageiros por km \n",
      "Na linha 174110 - VILA DIONIZIA/METRO SANTANA temos um uma relação de 1018785.75 Passageiros por km \n",
      "Na linha 174210 - JD ANTARTICA/METRO SANTANA temos um uma relação de 819792.06 Passageiros por km \n",
      "Na linha 174310 - JD PERY ALTO/METRO TIETE temos um uma relação de 913130.96 Passageiros por km \n",
      "Na linha 174410 - LAUZANE PAULISTA/METRO SANTANA temos um uma relação de 1006513.77 Passageiros por km \n",
      "Na linha 174510 - VL NV CACHOEIRINHA/SHOP C NORT temos um uma relação de 470128.75 Passageiros por km \n",
      "Na linha 174M10 - JD BRASIL/MUSEU IPIRANGA temos um uma relação de 383944.00 Passageiros por km \n",
      "Na linha 175610 - PEDRA BRANCA/METRO SANTANA temos um uma relação de 601547.34 Passageiros por km \n",
      "Na linha 175710 - CONJ BANCARIOS/METRO SANTANA temos um uma relação de 172871.12 Passageiros por km \n",
      "Na linha 175810 - JD ANTARTICA/METRO SANTANA temos um uma relação de 892816.70 Passageiros por km \n",
      "Na linha 175910 - JD PERY/METRO SANTANA temos um uma relação de 1052461.71 Passageiros por km \n",
      "Na linha 175P10 - EDU CHAVES/ANA ROSA temos um uma relação de 686206.94 Passageiros por km \n",
      "Na linha 175T10 - METRO SANTANA/METRO JABAQUARA temos um uma relação de 956852.39 Passageiros por km \n",
      "Na linha 176010 - COHAB ANTARTICA/SHOP C NORTE temos um uma relação de 369062.74 Passageiros por km \n",
      "Na linha 176410 - JD CORISCO/METRO SANTANA temos um uma relação de 571335.28 Passageiros por km \n",
      "Na linha 176441 - CEMIT PQ DA CANT/MET P INGLESA temos um uma relação de 12199.99 Passageiros por km \n",
      "Na linha 176510 - JD CABUÇU/METRO TUCURUVI temos um uma relação de 466525.43 Passageiros por km \n",
      "Na linha 176610 - JD CABUÇU/METRO SANTANA temos um uma relação de 71695.76 Passageiros por km \n",
      "Na linha 176710 - EDU CHAVES/METRO TUCURUVI temos um uma relação de 883398.48 Passageiros por km \n",
      "Na linha 177110 - VILA ZILDA/METRO SANTANA temos um uma relação de 419083.09 Passageiros por km \n",
      "Na linha 177210 - JD FILHOS DA TERRA/METRO TUCUR temos um uma relação de 817398.67 Passageiros por km \n",
      "Na linha 177310 - VILA AYROSA/METRO SANTANA temos um uma relação de 376099.56 Passageiros por km \n",
      "Na linha 177510 - VILA ALBERTINA/CENTER NORTE temos um uma relação de 166697.63 Passageiros por km \n",
      "Na linha 177810 - JACANA/METRO SANTANA temos um uma relação de 147723.47 Passageiros por km \n",
      "Na linha 177H10 - METRO SANTANA/BUTANTA- USP temos um uma relação de 328488.58 Passageiros por km \n",
      "Na linha 177Y10 - CASA VERDE/PINHEIROS temos um uma relação de 1170181.40 Passageiros por km \n",
      "Na linha 178010 - JD HEBRON/TERM PARADA INGLESA temos um uma relação de 1063357.61 Passageiros por km \n",
      "Na linha 178210 - V NOVA GALVAO/METRO SANTANA temos um uma relação de 212477.19 Passageiros por km \n",
      "Na linha 178310 - CACHOEIRA/METRO SANTANA temos um uma relação de 480571.53 Passageiros por km \n",
      "Na linha 178322 - JARDIM LABITARY/METRO SANTANA temos um uma relação de 14346.49 Passageiros por km \n",
      "Na linha 178341 - JD LABITARY/METRO PARD INGLESA temos um uma relação de 24268.46 Passageiros por km \n",
      "Na linha 178510 - VILA AURORA/METRO SANTANA temos um uma relação de 769390.37 Passageiros por km \n",
      "Na linha 178610 - VILA ALBERTINA/METRO SANTANA temos um uma relação de 1035239.83 Passageiros por km \n",
      "Na linha 178710 - VILA MARIETA/METRO SANTANA temos um uma relação de 649197.94 Passageiros por km \n",
      "Na linha 178810 - JD FONTALIS/METRO SANTANA temos um uma relação de 476751.84 Passageiros por km \n",
      "Na linha 178851 - JD CAMPO LIMPO/METRO SANTANA temos um uma relação de 30238.34 Passageiros por km \n",
      "Na linha 178A10 - IMIRIM/LAPA temos um uma relação de 488625.25 Passageiros por km \n",
      "Na linha 178L10 - LAUZANE PAULISTA/HOSP CLINICAS temos um uma relação de 654635.29 Passageiros por km \n",
      "Na linha 178T10 - METRO SANTANA/CEASA temos um uma relação de 534189.53 Passageiros por km \n",
      "Na linha 178Y10 - VILA AMELIA/METRO JD SAO PAULO temos um uma relação de 1274136.39 Passageiros por km \n",
      "Na linha 178Y21 - CJ DOS BANCARIOS/M JD SAO PAUL temos um uma relação de 135088.99 Passageiros por km \n",
      "Na linha 179X10 - JD FONTALIS/BOM RETIRO temos um uma relação de 604806.38 Passageiros por km \n",
      "Na linha 189L10 - VILA LORIO/LAPA temos um uma relação de 1843685.63 Passageiros por km \n",
      "Na linha 199D10 - VILA LORIO/PINHEIROS temos um uma relação de 355617.52 Passageiros por km \n",
      "Na linha 199D10 - VILA LORIO/TERMINAL PINHEIROS temos um uma relação de 449168.98 Passageiros por km \n",
      "Na linha 200210 - TERM P D PEDRO II/TERM BANDEIR temos um uma relação de 571659.85 Passageiros por km \n",
      "Na linha 200410 - JD MIRIAM/GUAIANAZES temos um uma relação de 2201726.65 Passageiros por km \n",
      "Na linha 200510 - JD ROMANO/SAO MIGUEL temos um uma relação de 352858.68 Passageiros por km \n",
      "Na linha 200610 - CIDADE KEMEL I /ITAIM PAULISTA temos um uma relação de 2828624.66 Passageiros por km \n",
      "Na linha 200710 - CIDADE KEMEL II/SAO MIGUEL temos um uma relação de 1222316.32 Passageiros por km \n",
      "Na linha 200810 - JD N SRA CAMINHO/ESTACAO ITAIM temos um uma relação de 2450869.99 Passageiros por km \n",
      "Na linha 200841 - JD. MIRIAM/ITAIM PAULISTA temos um uma relação de 1512824.98 Passageiros por km \n",
      "Na linha 200910 - JD ROBRU/GUAIANAZES temos um uma relação de 1896984.15 Passageiros por km \n",
      "Na linha 201010 - JD BRASIL/METRO TIETE temos um uma relação de 560810.73 Passageiros por km \n",
      "Na linha 201021 - PÇA AUGUSTA VITORIA/METRO SANT temos um uma relação de 22450.40 Passageiros por km \n",
      "Na linha 201110 - EDU CHAVES/METRO SANTANA temos um uma relação de 741826.87 Passageiros por km \n",
      "Na linha 201210 - VILA EDE/METRO TIETE temos um uma relação de 63915.54 Passageiros por km \n",
      "Na linha 201310 - JD ROBRU/EST ITAIM PAULISTA temos um uma relação de 1114287.33 Passageiros por km \n",
      "Na linha 201410 - JD PERI ALTO/METRO BARRA FUNDA temos um uma relação de 600837.25 Passageiros por km \n",
      "Na linha 201610 - JD DAS OLIVEIRAS/SAO MIGUEL temos um uma relação de 498125.23 Passageiros por km \n",
      "Na linha 201710 - JD ROBRU/SAO MIGUEL temos um uma relação de 229116.83 Passageiros por km \n",
      "Na linha 201810 - JD CAMPOS/SAO MIGUEL CIRCULAR temos um uma relação de 235483.21 Passageiros por km \n",
      "Na linha 201910 - PQ PAINEIRAS/SHOPPING PENHA temos um uma relação de 498457.66 Passageiros por km \n",
      "Na linha 202010 - HORTO FLORESTAL/M PARADA INGLE temos um uma relação de 185734.71 Passageiros por km \n",
      "Na linha 202110 - JD BANDEIRANTES/EST GUAIANAZES temos um uma relação de 2178365.64 Passageiros por km \n",
      "Na linha 202210 - JD DOS IPES/TERM A E CARVALHO temos um uma relação de 178089.06 Passageiros por km \n",
      "Na linha 202310 - CACHOEIRA/METRO TUCURUVI temos um uma relação de 353736.76 Passageiros por km \n",
      "Na linha 202410 - CACHOEIRA/DIB - CIRCULAR temos um uma relação de 15239.09 Passageiros por km \n",
      "Na linha 202510 - CACHOEIRA/DIB - CIRCULAR temos um uma relação de 626183.56 Passageiros por km \n",
      "Na linha 202610 - JAÇANA/PARQUE NOVO MUNDO temos um uma relação de 96861.97 Passageiros por km \n",
      "Na linha 202810 - VILA AYROSA/METRO TUCURUVI temos um uma relação de 165181.91 Passageiros por km \n",
      "Na linha 202910 - JD FONTALIS/METRO TUCURUVI temos um uma relação de 352475.61 Passageiros por km \n",
      "Na linha 203010 - LAUZANE PAULISTA/METRO SANTANA temos um uma relação de 61554.94 Passageiros por km \n",
      "Na linha 203110 - JD CAMARGO NOVO/TERM A E CARVA temos um uma relação de 466170.56 Passageiros por km \n",
      "Na linha 203210 - PQ EDU CHAVES/METRO CARANDIRU temos um uma relação de 200505.26 Passageiros por km \n",
      "Na linha 204110 - VILA NOVA SILVIA-TERM PENHA temos um uma relação de 96665.87 Passageiros por km \n",
      "Na linha 205810 - SAO MIGUEL-GUAIANAZES temos um uma relação de 388354.64 Passageiros por km \n",
      "Na linha 205910 - SAO MIGUEL-GUAIANAZES temos um uma relação de 1871719.86 Passageiros por km \n",
      "Na linha 206010 - T.A.E.CARVALHO/METRO A. ALVIM temos um uma relação de 80741.84 Passageiros por km \n",
      "Na linha 207610 - JD DAS OLIVEIRAS/TERM PENHA temos um uma relação de 306674.65 Passageiros por km \n",
      "Na linha 207910 - JD NELIA/TERM ARICANDUVA temos um uma relação de 355515.46 Passageiros por km \n",
      "Na linha 208010 - CID KEMEL/TERM ARICANDUVA temos um uma relação de 415766.40 Passageiros por km \n",
      "Na linha 208810 - CJ ENCOST NORTE/T A E CARVALHO temos um uma relação de 234081.29 Passageiros por km \n",
      "Na linha 208M10 - METRO SANTANA/TERM PINHEIROS temos um uma relação de 134342.75 Passageiros por km \n",
      "Na linha 208V10 - TERM A E CARVALHO-PÇA DA SE temos um uma relação de 408323.67 Passageiros por km \n",
      "Na linha 209P10 - CACHOEIRINHA/TERM PINHEIROS temos um uma relação de 1210585.03 Passageiros por km \n",
      "Na linha 210010 - TERM V CARRAO/PCA DA SE CIRC temos um uma relação de 1004590.24 Passageiros por km \n",
      "Na linha 210110 - PCA SILVIO ROMERO/PCA DA SE temos um uma relação de 47701.47 Passageiros por km \n",
      "Na linha 210141 - PCA SILVIO ROMERO/TERM VILA PR temos um uma relação de 18275.85 Passageiros por km \n",
      "Na linha 210410 - METRO SANTANA/TERM PQ D PEDRO  temos um uma relação de 650818.70 Passageiros por km \n",
      "Na linha 210510 - JD FILHOS DA TERRA/LGO DA CONC temos um uma relação de 301153.77 Passageiros por km \n",
      "Na linha 211L10 - MANDAQUI/LAPA temos um uma relação de 231461.05 Passageiros por km \n",
      "Na linha 211V10 - VILA PARANAGUA-ESTACAO DA LUZ temos um uma relação de 80706.96 Passageiros por km \n",
      "Na linha 212310 - VILA MEDEIROS/METRO LIBERDADE temos um uma relação de 439991.29 Passageiros por km \n",
      "Na linha 212710 - JD BRASIL/METRO LIBERDADE temos um uma relação de 447804.90 Passageiros por km \n",
      "Na linha 213C10 - ITAIM PAULISTA/VILA CALIFORNIA temos um uma relação de 296668.36 Passageiros por km \n",
      "Na linha 213C31 - ITAIM PAULISTA/VILA CALIFORNIA temos um uma relação de 162793.25 Passageiros por km \n",
      "Na linha 216110 - PQ EDU CHAVES/PCA DO CORREIO temos um uma relação de 275940.97 Passageiros por km \n",
      "Na linha 217110 - PC DA ALEGRIA/PQ D PEDRO II temos um uma relação de 62894.59 Passageiros por km \n",
      "Na linha 217510 - JD GUANCA/PCA DA SE temos um uma relação de 79380.98 Passageiros por km \n",
      "Na linha 218210 - JD BRASIL/PCA DO CORREIO temos um uma relação de 609378.83 Passageiros por km \n",
      "Na linha 220110 - DIVISA DE FERRAZ/GUAIANAZES temos um uma relação de 1541009.85 Passageiros por km \n",
      "Na linha 220210 - HOSP ITAIM/GUAIAZAZES temos um uma relação de 3045756.35 Passageiros por km \n",
      "Na linha 220310 - BURGO PAULISTA/SHOP PENHA temos um uma relação de 253694.44 Passageiros por km \n",
      "Na linha 220410 - JD GUANÇA/PÇA DA SÉ temos um uma relação de 9883.41 Passageiros por km \n",
      "Na linha 229010 - TERM S MATEUS/TERM.PD PEDRO II temos um uma relação de 1112469.25 Passageiros por km \n",
      "Na linha 229021 - T SÃO MATEUS/T PQ D PEDRO II temos um uma relação de 71264.91 Passageiros por km \n",
      "Na linha 233A10 - JD HELENA-CERET temos um uma relação de 176952.17 Passageiros por km \n",
      "Na linha 233C10 - TERM.A.E.CARVALHO-CERET temos um uma relação de 317510.83 Passageiros por km \n",
      "Na linha 236310 - JD.DANFER-PQ.D.PEDRO II temos um uma relação de 458534.42 Passageiros por km \n",
      "Na linha 243510 - JD COIMBRA-PÇA DA SE temos um uma relação de 232837.03 Passageiros por km \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Na linha 245110 - VL S FRANCISCO/PQ D PEDRO II temos um uma relação de 199756.99 Passageiros por km \n",
      "Na linha 246010 - CEM.SAUDADE/T PQ.D.PEDRO II temos um uma relação de 861633.79 Passageiros por km \n",
      "Na linha 246310 - BURGO PAULISTA-TERM.ARICANDUVA temos um uma relação de 134939.49 Passageiros por km \n",
      "Na linha 250110 - JD VERONIA-PQUE D PEDRO temos um uma relação de 216596.46 Passageiros por km \n",
      "Na linha 252210 - VILA PROGRESSO-SHOP.ARICANDUVA temos um uma relação de 269598.74 Passageiros por km \n",
      "Na linha 252310 - VILA PROGRESSO-T PRINC ISABEL temos um uma relação de 705784.02 Passageiros por km \n",
      "Na linha 253F10 - TERM.A.E.CARVALHO-T.SAO MATEUS temos um uma relação de 186518.57 Passageiros por km \n",
      "Na linha 255110 - TERM.A.E.CARVALHO-TERM.D.PEDRO temos um uma relação de 219852.38 Passageiros por km \n",
      "Na linha 255210 - VILA MARA-TERM.D.PEDRO II temos um uma relação de 614883.81 Passageiros por km \n",
      "Na linha 255241 - JD S MARTINHO/T PQ D PEDRO II temos um uma relação de 29198.19 Passageiros por km \n",
      "Na linha 258210 - VILA NOVA CURUÇA/TER P D PEDRO temos um uma relação de 428457.61 Passageiros por km \n",
      "Na linha 258221 - VILA ROBERTINA/PQ D PEDRO II temos um uma relação de 13514.03 Passageiros por km \n",
      "Na linha 258310 - VILA CURUCA/TERM P D PEDRO temos um uma relação de 185572.65 Passageiros por km \n",
      "Na linha 259010 - UNIAO DE VILA NOVA/PQ D PEDRO  temos um uma relação de 577159.65 Passageiros por km \n",
      "Na linha 262610 - JD NAZARE/ TERM P D PEDRO temos um uma relação de 433574.47 Passageiros por km \n",
      "Na linha 262810 - JD NAZARE/TERM ARICANDUVA temos um uma relação de 98970.10 Passageiros por km \n",
      "Na linha 263C10 - JD HELENA/COHAB II temos um uma relação de 270466.95 Passageiros por km \n",
      "Na linha 263J10 - PENHA/CJ JOSE BONIFACIO temos um uma relação de 531638.18 Passageiros por km \n",
      "Na linha 266610 - JD CAMARGO VELHO/TER P D PEDRO temos um uma relação de 410375.67 Passageiros por km \n",
      "Na linha 266621 - JD CAMARGO VELH/T P D PEDRO II temos um uma relação de 9682.46 Passageiros por km \n",
      "Na linha 267810 - OLIVEIRINHA/TERM P D PEDRO temos um uma relação de 506839.04 Passageiros por km \n",
      "Na linha 267841 - J CAMARGO NOVO/TERM ARICANDUVA temos um uma relação de 28297.60 Passageiros por km \n",
      "Na linha 270210 - VILA AMERICANA/METRO A ALVIN temos um uma relação de 1233190.54 Passageiros por km \n",
      "Na linha 270221 - JD PEDRO J NUNES/METRO A ALVIM temos um uma relação de 40689.15 Passageiros por km \n",
      "Na linha 270310 - JD ETELVINA/METRO ITAQUERA temos um uma relação de 2056241.13 Passageiros por km \n",
      "Na linha 270321 - Metro Itaquera temos um uma relação de 85584.08 Passageiros por km \n",
      "Na linha 270322 - JD GIANETTI/METRO ITAQUERA temos um uma relação de 66696.56 Passageiros por km \n",
      "Na linha 270410 - JD ROBRU/METRO ITAQUERA temos um uma relação de 1012879.45 Passageiros por km \n",
      "Na linha 270510 - JD FANGANIELO/METRO ITAQUERA temos um uma relação de 595650.92 Passageiros por km \n",
      "Na linha 270610 - CEM DA SAUDADE/METRO V MATILDE temos um uma relação de 400999.72 Passageiros por km \n",
      "Na linha 270710 - CHABILANDIA/METRO ITAQUERA temos um uma relação de 1386201.50 Passageiros por km \n",
      "Na linha 270731 - CHABILANDIA/METRO ITQUERA temos um uma relação de 36480.77 Passageiros por km \n",
      "Na linha 270810 - JD LAJEADO/METRO ITAQUERA temos um uma relação de 1114971.78 Passageiros por km \n",
      "Na linha 270910 - VILA UNIAO/METRO PATRIARCA temos um uma relação de 598573.07 Passageiros por km \n",
      "Na linha 270931 - VILA UNIAO/METRO PATRIARCA temos um uma relação de 462615.67 Passageiros por km \n",
      "Na linha 271010 - METRO PATRIARCA/BURGO PAULISTA temos um uma relação de 733304.95 Passageiros por km \n",
      "Na linha 271031 - METRO PATRIARCA/VL.S FRANCISCO temos um uma relação de 72015.28 Passageiros por km \n",
      "Na linha 271110 - PONTE RASA/METRO PATRIARCA temos um uma relação de 1141793.66 Passageiros por km \n",
      "Na linha 271210 - JD SAO NICOLAU/METRO A ALVIN temos um uma relação de 549241.33 Passageiros por km \n",
      "Na linha 271310 - METRO PENHA-CHAC BELA VISTA temos um uma relação de 65446.31 Passageiros por km \n",
      "Na linha 271410 - VL RUI BARBOSA/METRO V MATILDE temos um uma relação de 761114.16 Passageiros por km \n",
      "Na linha 271510 - VILA SILVIA/METRO PATRIARCA temos um uma relação de 1093109.01 Passageiros por km \n",
      "Na linha 271610 - CHAC CRUZ DO SUL/METRO PENHA temos um uma relação de 1342099.51 Passageiros por km \n",
      "Na linha 271710 - METRO GUILHERMINA/CANGAIBA temos um uma relação de 415562.54 Passageiros por km \n",
      "Na linha 271810 - VILA SILVIA/METRO PENHA temos um uma relação de 1558669.27 Passageiros por km \n",
      "Na linha 271910 - ERMELINO MATARAZZO/METR V MATI temos um uma relação de 1984433.53 Passageiros por km \n",
      "Na linha 271A10 - TERM PENHA/METRO SANTANA temos um uma relação de 544781.64 Passageiros por km \n",
      "Na linha 271A51 - CANGAIBA/METRO SANTANA temos um uma relação de 320735.93 Passageiros por km \n",
      "Na linha 271C10 - PQ VILA MARIA/PCA DA REPUBLICA temos um uma relação de 105471.17 Passageiros por km \n",
      "Na linha 271F10 - METRO BELEM/SHOP CENTER NORTE temos um uma relação de 803752.64 Passageiros por km \n",
      "Na linha 271M10 - PQ NOVO MUNDO/METRO SANTANA temos um uma relação de 544871.48 Passageiros por km \n",
      "Na linha 271P10 - CANGAIBA/EST DA LUZ temos um uma relação de 299320.20 Passageiros por km \n",
      "Na linha 272010 - JD BELEM/METRO GUILHERMINA temos um uma relação de 1386749.97 Passageiros por km \n",
      "Na linha 272031 - METRO GUILHERMINA/JD BELEM temos um uma relação de 179681.78 Passageiros por km \n",
      "Na linha 272110 - JD NAZARE/METRO ITAQUERA temos um uma relação de 663029.50 Passageiros por km \n",
      "Na linha 272210 - JD VERONIA/METR GUILHERMINA temos um uma relação de 1303945.49 Passageiros por km \n",
      "Na linha 272231 - JD VERONIA/METRO GUILHERMINA temos um uma relação de 373665.29 Passageiros por km \n",
      "Na linha 272310 - UNIAO DE V NOVA/METRO ITAQUERA temos um uma relação de 1075596.12 Passageiros por km \n",
      "Na linha 272410 - METRO A ALVIN/CONJ ARAUCARIA temos um uma relação de 1159884.28 Passageiros por km \n",
      "Na linha 272510 - JD SAO CARLOS/METRO A ALVIN temos um uma relação de 498267.12 Passageiros por km \n",
      "Na linha 272610 - LIMOEIRO/METRO PENHA temos um uma relação de 599314.67 Passageiros por km \n",
      "Na linha 272710 - CONJ A E CARV/METRO A ALVIN temos um uma relação de 1452840.42 Passageiros por km \n",
      "Na linha 272810 - JD CASTELO/METRO PENHA temos um uma relação de 2525652.99 Passageiros por km \n",
      "Na linha 272N10 - PQ NOVO MUNDO/METRO BRAS temos um uma relação de 78340.80 Passageiros por km \n",
      "Na linha 273010 - VILA JACUI/METRO A ALVIN temos um uma relação de 957248.04 Passageiros por km \n",
      "Na linha 273110 - VILA PROGRESSO/METRO ITAQUERA temos um uma relação de 996059.98 Passageiros por km \n",
      "Na linha 273210 - VILA REGINA/METRO A ALVIN temos um uma relação de 764552.77 Passageiros por km \n",
      "Na linha 273310 - PQ GUARANI/METRO ITAQUERA CIRC temos um uma relação de 1087185.59 Passageiros por km \n",
      "Na linha 273410 - JD CAMPOS/METRO ITAQUERA temos um uma relação de 751404.53 Passageiros por km \n",
      "Na linha 273510 - JD KERALUX/METRO PENHA temos um uma relação de 684662.49 Passageiros por km \n",
      "Na linha 273521 - JD SAO FRANCISCO/METRO PENHA temos um uma relação de 295751.11 Passageiros por km \n",
      "Na linha 273D10 - PQ D JOAO NERY-METRO A ALVIN temos um uma relação de 237325.95 Passageiros por km \n",
      "Na linha 273F10 - VILA MARA-METRO ITAQUERA temos um uma relação de 120202.53 Passageiros por km \n",
      "Na linha 273G10 - JD HELENA-METRO A ALVIN temos um uma relação de 1286766.70 Passageiros por km \n",
      "Na linha 273G21 - JD SAO MARTINHO/CPTM VILA MARA temos um uma relação de 39509.24 Passageiros por km \n",
      "Na linha 273J10 - JD ROMANO/METRO PENHA temos um uma relação de 565598.20 Passageiros por km \n",
      "Na linha 273L10 - JD MORENO-METRO A ALVIN temos um uma relação de 413883.16 Passageiros por km \n",
      "Na linha 273N10 - CID KEMEL II/MTR V MATILDE temos um uma relação de 371468.59 Passageiros por km \n",
      "Na linha 273N41 - ITAIM PAULISTA/MT VLA MATILDE temos um uma relação de 8859.44 Passageiros por km \n",
      "Na linha 273R10 - JD ROBRU-METRO A ALVIN temos um uma relação de 940701.71 Passageiros por km \n",
      "Na linha 273R42 - JD ROBRU-METRO ITAQUERA temos um uma relação de 90778.18 Passageiros por km \n",
      "Na linha 273V10 - PARADA XV NOVEMBRO-METRO PENHA temos um uma relação de 106364.58 Passageiros por km \n",
      "Na linha 273X10 - JD OLIVEIRAS/MT ARTUR ALVIN temos um uma relação de 1028707.66 Passageiros por km \n",
      "Na linha 274010 - PEDRA BRANCA/METRO SANTANA temos um uma relação de 172748.02 Passageiros por km \n",
      "Na linha 274P10 - PENHA/METRO VL MARIANA temos um uma relação de 247953.78 Passageiros por km \n",
      "Na linha 275510 - GUAIANAZES-METRO PENHA temos um uma relação de 311189.59 Passageiros por km \n",
      "Na linha 275610 - GUAIANAZES-METRO PATRIARCA temos um uma relação de 221087.22 Passageiros por km \n",
      "Na linha 276210 - ERMELINO MATARAZZO-MET.TATUAPE temos um uma relação de 316450.07 Passageiros por km \n",
      "Na linha 276510 - VILA CISPER-METRO TATUAPE temos um uma relação de 1431624.73 Passageiros por km \n",
      "Na linha 276610 - J CAMARGO VELHO/METRO ITAQUERA temos um uma relação de 812649.92 Passageiros por km \n",
      "Na linha 276641 - JD INDAIA/METRO ITAQUERA temos um uma relação de 12695.16 Passageiros por km \n",
      "Na linha 276710 - CID PEDR J NUNES-METRO TATUAPE temos um uma relação de 193045.24 Passageiros por km \n",
      "Na linha 276810 - VILA MARA-METRO PENHA temos um uma relação de 161827.71 Passageiros por km \n",
      "Na linha 276910 - JD ROMANO/METRO TATUAPE temos um uma relação de 232681.40 Passageiros por km \n",
      "Na linha 277010 - GUAIANAZES-METRO VILA MATILDE temos um uma relação de 262100.27 Passageiros por km \n",
      "Na linha 277210 - JD NAZARE/METRO PENHA temos um uma relação de 149224.61 Passageiros por km \n",
      "Na linha 278010 - JD CAMARGO NOVO/METRO ITAQUERA temos um uma relação de 369538.52 Passageiros por km \n",
      "Na linha 278A10 - PENHA/CEASA temos um uma relação de 203526.62 Passageiros por km \n",
      "Na linha 297A10 - BAIRRO DO LIMAO/M BARRA FUNDA temos um uma relação de 1225508.72 Passageiros por km \n",
      "Na linha 300110 - ITAIM PTA/TERM.SAO MIGUEL temos um uma relação de 517770.89 Passageiros por km \n",
      "Na linha 300210 - JD MABEL/SAO MIGUEL temos um uma relação de 955713.23 Passageiros por km \n",
      "Na linha 300310 - JD S MARTINHO/CPTM VILA MARA temos um uma relação de 182933.69 Passageiros por km \n",
      "Na linha 300410 - JD S MARTINHO/CPTM V MARA temos um uma relação de 182959.71 Passageiros por km \n",
      "Na linha 300610 - JD FANGANIELO/ES CPTM GUAIANAZ temos um uma relação de 2821132.80 Passageiros por km \n",
      "Na linha 301310 - TERM CIDADE TIRADEN/METALURGIC temos um uma relação de 297363.30 Passageiros por km \n",
      "Na linha 301510 - JD ROMANO/JARDIM DAS OLIVEIRAS temos um uma relação de 21276.09 Passageiros por km \n",
      "Na linha 301910 - TERM CIDADE TIRADENTES/VILA PA temos um uma relação de 342854.93 Passageiros por km \n",
      "Na linha 302010 - CONJ JOSE BONIFACIO/SHOP ARICA temos um uma relação de 228862.52 Passageiros por km \n",
      "Na linha 302031 - C.J. BONIFACIO/SHOP.ARICANDUVA temos um uma relação de 245179.35 Passageiros por km \n",
      "Na linha 302110 - PQ BANCARIO/TERM VILA PRUDENTE temos um uma relação de 284003.51 Passageiros por km \n",
      "Na linha 302310 - PQ SAO RAFAEL/SHOP ARICANDUVA temos um uma relação de 94560.45 Passageiros por km \n",
      "Na linha 302310 - SHOP ARICANDUVA/PQ SAO RAFAEL temos um uma relação de 558247.93 Passageiros por km \n",
      "Na linha 302410 - VLA INDUSTRIAL/TER VL PRUDENTE temos um uma relação de 408924.16 Passageiros por km \n",
      "Na linha 302510 - JD WILMA FLOR/EST GUAIANAZES C temos um uma relação de 554070.16 Passageiros por km \n",
      "Na linha 302610 - VILA IOLANDA II/EST GUAIANZ CP temos um uma relação de 1627727.82 Passageiros por km \n",
      "Na linha 302710 - VILA MINERVA/SHOP ARICANDUVA temos um uma relação de 407360.82 Passageiros por km \n",
      "Na linha 302910 - JD DAS ROSAS/METRO TATUAPE temos um uma relação de 1215963.06 Passageiros por km \n",
      "Na linha 303110 - J ALTO PAULISTAN/METRO ITAQUER temos um uma relação de 508708.84 Passageiros por km \n",
      "Na linha 303210 - TERM VILA CARRAO/CIRCULAR temos um uma relação de 138932.41 Passageiros por km \n",
      "Na linha 303310 - GUAIANAZES/SAO MATEUS temos um uma relação de 888988.93 Passageiros por km \n",
      "Na linha 304610 - VILA GUARANI/TATUAPE temos um uma relação de 1317794.05 Passageiros por km \n",
      "Na linha 305110 - ERM MATARAZZO/TERM A E CARVALH temos um uma relação de 134540.19 Passageiros por km \n",
      "Na linha 305310 - JD ITAPOLIS/METRO BELEM temos um uma relação de 1224968.69 Passageiros por km \n",
      "Na linha 305410 - JD PALANQUE/JD TIETE temos um uma relação de 510454.16 Passageiros por km \n",
      "Na linha 306310 - GUAIANAZES-TERM SAO MATEUS temos um uma relação de 408726.62 Passageiros por km \n",
      "Na linha 306341 - GUAIANAZES-TERM SAO MATEUS temos um uma relação de 44538.39 Passageiros por km \n",
      "Na linha 306410 - CIDADE TIRADENTES/EST GUAIANAZ temos um uma relação de 2675834.64 Passageiros por km \n",
      "Na linha 306441 - S ETELVINA II B6/T CID TIRADEN temos um uma relação de 58356.82 Passageiros por km \n",
      "Na linha 306910 - J RECANTO VERDE SOL/T S MATEUS temos um uma relação de 464268.37 Passageiros por km \n",
      "Na linha 307C10 - CONJ ENCOSTA NORTE/MT ARTUR AL temos um uma relação de 444785.75 Passageiros por km \n",
      "Na linha 309810 - JD SAO FRANCISCO/SHOP ARICANDU temos um uma relação de 865921.49 Passageiros por km \n",
      "Na linha 309910 - NOVE DE JULHO/JD DA CONQUISTA temos um uma relação de 952833.09 Passageiros por km \n",
      "Na linha 311210 - VILA INDUSTRIAL/METRO BELEM temos um uma relação de 766636.85 Passageiros por km \n",
      "Na linha 311C10 - PQUE S LUCAS/BOM RETIRO temos um uma relação de 534639.69 Passageiros por km \n",
      "Na linha 312N10 - TERM CID TIRADENTES/SAO MIGUEL temos um uma relação de 584582.77 Passageiros por km \n",
      "Na linha 313410 - SHOP ARICANDUVA/METRO TAMANDUA temos um uma relação de 796932.78 Passageiros por km \n",
      "Na linha 313910 - JD VILA FORMOSA/PCA CLOVIS temos um uma relação de 175515.39 Passageiros por km \n",
      "Na linha 313931 - JD.VILA FORMOSA/PÇA CLOVIS temos um uma relação de 14648.31 Passageiros por km \n",
      "Na linha 314110 - TERM SAO MATEUS/TERM P D PEDRO temos um uma relação de 571759.04 Passageiros por km \n",
      "Na linha 314J10 - STA MADALENA/METRO LIBERDADE temos um uma relação de 407313.45 Passageiros por km \n",
      "Na linha 314V10 - VILA EMA/METRO LIBERDADE temos um uma relação de 248800.27 Passageiros por km \n",
      "Na linha 316010 - TERM.V.PRUDENTE/ TERM D PEDRO temos um uma relação de 1069126.49 Passageiros por km \n",
      "Na linha 316110 - JD COLORADO/TERM P D PEDRO II temos um uma relação de 447458.05 Passageiros por km \n",
      "Na linha 320610 - METRO PENHA/CONJ CHAPARRAL temos um uma relação de 127341.85 Passageiros por km \n",
      "Na linha 330110 - TERM SAO MIGUEL/TERM PQ D PEDR temos um uma relação de 398127.30 Passageiros por km \n",
      "Na linha 339010 - TERM S MATEUS/TERM P D PEDRO temos um uma relação de 519666.49 Passageiros por km \n",
      "Na linha 341410 - VILA DALILA/TERM P D PEDRO temos um uma relação de 411382.22 Passageiros por km \n",
      "Na linha 342C10 - JD MARILIA/PENHA temos um uma relação de 316681.33 Passageiros por km \n",
      "Na linha 342M10 - TERM SAO MATEUS/TERM PENHA temos um uma relação de 1232442.09 Passageiros por km \n",
      "Na linha 342N10 - COHAB JUSC.KUBISC/PENHA temos um uma relação de 192041.05 Passageiros por km \n",
      "Na linha 345910 - ITAIM PAULISTA/TERM P D PEDRO temos um uma relação de 747364.67 Passageiros por km \n",
      "Na linha 345921 - CEM DA SAUDADE/TERM P D PEDRO temos um uma relação de 53158.53 Passageiros por km \n",
      "Na linha 345923 - METRO BRESSER/ITAIM PAULISTA temos um uma relação de 36086.08 Passageiros por km \n",
      "Na linha 345924 - ITAIM PAULISTA/T.PQ D.PEDROII temos um uma relação de 27678.28 Passageiros por km \n",
      "Na linha 346210 - VILA SANTANA/T PQ D PEDRO II temos um uma relação de 211870.24 Passageiros por km \n",
      "Na linha 346241 - CID A E CARVALHO-T PQ D PEDRO  temos um uma relação de 23359.02 Passageiros por km \n",
      "Na linha 351F10 - JACANA/TERM CARRAO temos um uma relação de 294875.20 Passageiros por km \n",
      "Na linha 352A10 - JD.HELENA-TERM.SAO MATEUS temos um uma relação de 444885.64 Passageiros por km \n",
      "Na linha 353910 - CIDADE TIRADENTES/TERM P D PED temos um uma relação de 287618.57 Passageiros por km \n",
      "Na linha 354M10 - TERM SAO MIGUEL/TERM SAO MATEU temos um uma relação de 541056.88 Passageiros por km \n",
      "Na linha 357410 - JD.ETELVINA-TERM.PQ.D.PEDRO II temos um uma relação de 334176.20 Passageiros por km \n",
      "Na linha 357431 - JD.ETELVINA/T.PQ.D.PEDRO temos um uma relação de 39526.18 Passageiros por km \n",
      "Na linha 364A10 - IPIRANGA/SHOP ARICANDUVA temos um uma relação de 779051.05 Passageiros por km \n",
      "Na linha 368610 - JD.SAOPAULO-TERM.D.PEDRO II temos um uma relação de 329646.11 Passageiros por km \n",
      "Na linha 371210 - JD SAO JOAO/METRO ITAQUERA temos um uma relação de 838725.81 Passageiros por km \n",
      "Na linha 371241 - JD SAO PEDRO/METRO ITAQUERA temos um uma relação de 348349.89 Passageiros por km \n",
      "Na linha 371810 - METRO A ALVIN/NOVA AMERICA temos um uma relação de 981629.46 Passageiros por km \n",
      "Na linha 372110 - JD MARILIA/METRO A ALVIM temos um uma relação de 1262942.79 Passageiros por km \n",
      "Na linha 372141 - JD MARILIA/METRO ARTHUR ALVIM temos um uma relação de 2210495.75 Passageiros por km \n",
      "Na linha 372210 - COHAB J BONIFACIO/METRO PENHA temos um uma relação de 265891.87 Passageiros por km \n",
      "Na linha 372510 - METRO V MATILDE/VILA DALILA temos um uma relação de 1394291.45 Passageiros por km \n",
      "Na linha 372541 - METRO VL MATILDE/VL ARICANDUVA temos um uma relação de 890218.18 Passageiros por km \n",
      "Na linha 372810 - METRO A ALVIN/PQ SAVOY CITY temos um uma relação de 903614.00 Passageiros por km \n",
      "Na linha 372841 - METR ARTUR ALVIM/PQ NOVA SAVOY temos um uma relação de 194508.01 Passageiros por km \n",
      "Na linha 372910 - SHOP ARICANDUVA/METRO CARRAO temos um uma relação de 1520356.01 Passageiros por km \n",
      "Na linha 372F10 - FAC SAO JUDAS TADEU/METR BRESS temos um uma relação de 3409400.04 Passageiros por km \n",
      "Na linha 372U10 - VILA SANTA ISABEL/METRO TATUAP temos um uma relação de 1978809.17 Passageiros por km \n",
      "Na linha 373110 - SHOP ARICANDUVA/METRO V MATILD temos um uma relação de 1105466.76 Passageiros por km \n",
      "Na linha 373210 - COHAB JOSE BONIFACIO/METRO ITA temos um uma relação de 1299476.32 Passageiros por km \n",
      "Na linha 373410 - CIDADE LIDER/METRO A ALVIM temos um uma relação de 2173055.89 Passageiros por km \n",
      "Na linha 373510 - METRO A ALVIN/JD SAO JOAO CIRC temos um uma relação de 781635.94 Passageiros por km \n",
      "Na linha 373521 - METRO ARTUR ALVIM/JD S JOAO temos um uma relação de 134251.59 Passageiros por km \n",
      "Na linha 373541 - JD SÃO JOSE/METRO ARTUR ALVIM temos um uma relação de 316978.75 Passageiros por km \n",
      "Na linha 373610 - JD N S P CARMO/METRO A ALVIM temos um uma relação de 1986837.17 Passageiros por km \n",
      "Na linha 373710 - SHOP ARICANDUVA/METR GUILHERM  temos um uma relação de 1392913.36 Passageiros por km \n",
      "Na linha 373721 - JD.SANTA MARIA/M.GUILHERMINA E temos um uma relação de 82995.29 Passageiros por km \n",
      "Na linha 373731 - M.GUILHERMINA/M.PATRIARCA CIRC temos um uma relação de 549657.55 Passageiros por km \n",
      "Na linha 373810 - COHAB JUSCELINO/METRO ITAQUERA temos um uma relação de 776083.94 Passageiros por km \n",
      "Na linha 373910 - RECANTO VERDE SOL/METRO ITAQUE temos um uma relação de 812792.22 Passageiros por km \n",
      "Na linha 373931 - SAO TEODORO/METRO ITAQUERA temos um uma relação de 59575.89 Passageiros por km \n",
      "Na linha 373L10 - JD LIMOEIRO/METRO ITAQUERA temos um uma relação de 389012.46 Passageiros por km \n",
      "Na linha 373M10 - JD GUAIRACA/SHOP METR TATUAPE temos um uma relação de 196876.61 Passageiros por km \n",
      "Na linha 373T10 - JD ITAPOLIS/METRO BRESSER temos um uma relação de 848706.17 Passageiros por km \n",
      "Na linha 374110 - EST DOM BOSCO/METRO ITAQUERA temos um uma relação de 2019065.58 Passageiros por km \n",
      "Na linha 374210 - JD DAS LARANJEIRAS/M ITAQUERA temos um uma relação de 665102.09 Passageiros por km \n",
      "Na linha 374310 - SAO MATEUS/METRO ITAQUERA temos um uma relação de 702419.12 Passageiros por km \n",
      "Na linha 374510 - JD IMPERADOR/TATUAPE temos um uma relação de 641573.42 Passageiros por km \n",
      "Na linha 374610 - JD IMPERADOR/METRO BELEM temos um uma relação de 510619.06 Passageiros por km \n",
      "Na linha 374631 - JD IMPERADOR/METRO BELEM temos um uma relação de 89190.11 Passageiros por km \n",
      "Na linha 374910 - GUAIANAZES-TERM CARRAO temos um uma relação de 180864.59 Passageiros por km \n",
      "Na linha 374M10 - CPTM ERM MAT/METRO ITAQUERA temos um uma relação de 362193.79 Passageiros por km \n",
      "Na linha 374V10 - VILA VERDE / METRO ITAQUERA temos um uma relação de 956095.50 Passageiros por km \n",
      "Na linha 375110 - COHAB PRESTES MAIA/METR ITAQUE temos um uma relação de 593800.53 Passageiros por km \n",
      "Na linha 375121 - COHAB P MAIA/METRO ITAQUERA temos um uma relação de 85419.13 Passageiros por km \n",
      "Na linha 375410 - INACIO MONTEIRO/METRO ITAQUERA temos um uma relação de 977514.89 Passageiros por km \n",
      "Na linha 375610 - BARRO BRANCO/METRO ITAQUERA temos um uma relação de 829003.30 Passageiros por km \n",
      "Na linha 375V10 - CENT PLZ SHOP/MET ST CRUZ CIRC temos um uma relação de 120306.52 Passageiros por km \n",
      "Na linha 376110 - 3A DIVISAO/METRO CARRAO temos um uma relação de 567172.13 Passageiros por km \n",
      "Na linha 376210 - JD IVA/METRO TATUAPE temos um uma relação de 1118653.75 Passageiros por km \n",
      "Na linha 376310 - TERM VL CARRAO/METRO TATUAPE temos um uma relação de 2466137.77 Passageiros por km \n",
      "Na linha 376610 - COHAB II/METRO ITAQUERA temos um uma relação de 1077135.83 Passageiros por km \n",
      "Na linha 376810 - VILA YOLANDA/METRO ITAQUERA temos um uma relação de 526822.87 Passageiros por km \n",
      "Na linha 377310 - RES SANTA BARBARA/METRO CARRAO temos um uma relação de 468361.98 Passageiros por km \n",
      "Na linha 377810 - JD STA TEREZINHA/METRO CARRAO temos um uma relação de 845316.07 Passageiros por km \n",
      "Na linha 378510 - COHAB BARRO BRANCO/METRO ITAQU temos um uma relação de 417938.58 Passageiros por km \n",
      "Na linha 378710 - CID.TIRADENTES/METRO ITAQUERA temos um uma relação de 494165.04 Passageiros por km \n",
      "Na linha 378910 - CIDADE TIRADENTES/METRO ITAQUE temos um uma relação de 731899.61 Passageiros por km \n",
      "Na linha 379110 - SHOP ARICANDUVA/METRO A ALVIM temos um uma relação de 1378220.77 Passageiros por km \n",
      "Na linha 379510 - JD SAO CARLOS/METRO ITAQUERA temos um uma relação de 350232.92 Passageiros por km \n",
      "Na linha 379610 - GLEBA DO PESSEGO/METRO ITAQUER temos um uma relação de 751034.55 Passageiros por km \n",
      "Na linha 390110 - Jd. Danfer/Metro Penha temos um uma relação de 181065.54 Passageiros por km \n",
      "Na linha 390210 - Jd. das Oliveiras/Guaianazes temos um uma relação de 672213.68 Passageiros por km \n",
      "Na linha 390310 - C.A.E.Carvalho/Shop.Penha temos um uma relação de 160233.70 Passageiros por km \n",
      "Na linha 390E10 - TERM PENHA/TERM PQ D PEDRO II temos um uma relação de 562330.41 Passageiros por km \n",
      "Na linha 400110 - ITAQUERA/TERM VILA CARRAO temos um uma relação de 423277.99 Passageiros por km \n",
      "Na linha 400210 - GUAIANAZES/TERM VILA CARRAO temos um uma relação de 411915.48 Passageiros por km \n",
      "Na linha 400310 - PRESTES MAIA/ E. T. ITAQUERA  temos um uma relação de 257386.34 Passageiros por km \n",
      "Na linha 400410 - T CID TIRADENTES/BARRO BRANCO temos um uma relação de 673214.16 Passageiros por km \n",
      "Na linha 400510 - T CID TIRADENTES/BARRO BRANCO temos um uma relação de 928178.20 Passageiros por km \n",
      "Na linha 400610 - JD NOVA VITORIA/CIRCULAR temos um uma relação de 483467.23 Passageiros por km \n",
      "Na linha 400621 - JARDIM NOVA VITORIA/CIRCULAR temos um uma relação de 10125.45 Passageiros por km \n",
      "Na linha 400710 - COHAB JUSCELINO/TERM V CARRAO temos um uma relação de 436154.49 Passageiros por km \n",
      "Na linha 400810 - JD CIBELE/TERM VILA CARRAO temos um uma relação de 257570.50 Passageiros por km \n",
      "Na linha 401010 - JD NSA SRA DO CARMO/T V CARRAO temos um uma relação de 112695.25 Passageiros por km \n",
      "Na linha 401110 - JD LIMOEIRO/TERM SAO MATEUS temos um uma relação de 871736.46 Passageiros por km \n",
      "Na linha 401210 - JD DA CONQUISTA/T SAO MAETEUS temos um uma relação de 1141912.52 Passageiros por km \n",
      "Na linha 401310 - JD SANTO ANDRE/TERM SAO MATEUS temos um uma relação de 1024701.45 Passageiros por km \n",
      "Na linha 401410 - JD VILA CARRAO/TER VILA CARRAO temos um uma relação de 386860.68 Passageiros por km \n",
      "Na linha 401510 - T SAO MATEUS/JD RODOLFO PIRANI temos um uma relação de 230783.66 Passageiros por km \n",
      "Na linha 401610 - T SAO MATEUS/JD RODOLFO PIRANI temos um uma relação de 208286.64 Passageiros por km \n",
      "Na linha 401710 - VILA YOLANDA/METALURGICOS temos um uma relação de 660109.72 Passageiros por km \n",
      "Na linha 401810 - METALURGICOS/TERM SAO MATEUS temos um uma relação de 1043880.26 Passageiros por km \n",
      "Na linha 402410 - COHAB FAZE DO CAR/E.T.ITAQUERA temos um uma relação de 706322.41 Passageiros por km \n",
      "Na linha 402510 - VILA CALIFORNIA/METRO TATUAPE temos um uma relação de 693945.72 Passageiros por km \n",
      "Na linha 402710 - HOSP SAO MATEUS/JD SANTO ANDRE temos um uma relação de 1271003.40 Passageiros por km \n",
      "Na linha 402741 - PQ DAS FLORES/SAO MATEUS temos um uma relação de 108494.61 Passageiros por km \n",
      "Na linha 402810 - HOSP SAO MATEUS/PQ DAS FLORES temos um uma relação de 355343.01 Passageiros por km \n",
      "Na linha 402910 - SAO MATEUS/VLA PRUDENTE temos um uma relação de 1274675.38 Passageiros por km \n",
      "Na linha 403010 - FAZENDA DA JUTA/SHOP ARICANDUV temos um uma relação de 633473.03 Passageiros por km \n",
      "Na linha 403110 - PQ STA MADALENA/CENTRAL PLAZ S temos um uma relação de 808296.79 Passageiros por km \n",
      "Na linha 403210 - VILA DAS MERCES/OBJETIVO UNIP temos um uma relação de 509651.01 Passageiros por km \n",
      "Na linha 403310 - JD GUAIRACA/NOVA CONQUISTA temos um uma relação de 573008.74 Passageiros por km \n",
      "Na linha 403A10 - EST JOSE BONIFACIO/TERM PENHA temos um uma relação de 304737.29 Passageiros por km \n",
      "Na linha 405110 - JD SAO PAULO/CPTM GUAIANAZES temos um uma relação de 1722123.68 Passageiros por km \n",
      "Na linha 405210 - CPTM GUAIANAZES/METRO ITAQUERA temos um uma relação de 999474.30 Passageiros por km \n",
      "Na linha 405310 - GUAIANAZES/CPTM JOSE BONIFACIO temos um uma relação de 446986.44 Passageiros por km \n",
      "Na linha 405510 - CPTM GUAIANAZES/VILA SOLANGE temos um uma relação de 839494.74 Passageiros por km \n",
      "Na linha 405610 - TERM S MATEUS/PQ BOA ESPERANÇA temos um uma relação de 619296.38 Passageiros por km \n",
      "Na linha 407A10 - SHOP C L ARICANDUVA/METR BELEM temos um uma relação de 404592.17 Passageiros por km \n",
      "Na linha 407C10 - INACIO MONTEIRO/METR PATRIARCA temos um uma relação de 117446.48 Passageiros por km \n",
      "Na linha 407E10 - JD SANTO ANDRE/METRO CARRAO temos um uma relação de 522194.59 Passageiros por km \n",
      "Na linha 407F10 - TERM SAO MATEUS/METRO BELEM temos um uma relação de 438341.59 Passageiros por km \n",
      "Na linha 407G10 - JD NOVA VITORIA/METRO CARRAO temos um uma relação de 1013011.55 Passageiros por km \n",
      "Na linha 407H10 - JD SAO FRANCISCO/METR ITAQUERA temos um uma relação de 615711.52 Passageiros por km \n",
      "Na linha 407I10 - COHAB I/METRO BRESSER temos um uma relação de 269419.26 Passageiros por km \n",
      "Na linha 407J10 - JD SOARES/METRO TATUAPE temos um uma relação de 584705.65 Passageiros por km \n",
      "Na linha 407K10 - TERM SAO MATEUS/METRO CARRAO temos um uma relação de 514888.58 Passageiros por km \n",
      "Na linha 407L10 - BARRO BRANCO/M GUILHERMINA ESP temos um uma relação de 590950.33 Passageiros por km \n",
      "Na linha 407M10 - VILA MONUMENTO/VILA MADALENA temos um uma relação de 138197.74 Passageiros por km \n",
      "Na linha 407N10 - T CID TIRADENTES/METRO PENHA temos um uma relação de 1139540.37 Passageiros por km \n",
      "Na linha 407N21 - JD ROSELI/METRO PENHA temos um uma relação de 14229.70 Passageiros por km \n",
      "Na linha 407P10 - TERM CID TIRADENTES/M TATUAPE temos um uma relação de 463503.74 Passageiros por km \n",
      "Na linha 407R10 - TERM VILA CARRAO/METRO BELEM temos um uma relação de 722341.48 Passageiros por km \n",
      "Na linha 407T10 - JD REDIL/METRO ITAQUERA temos um uma relação de 1170628.86 Passageiros por km \n",
      "Na linha 407W10 - JD. IV CENTERNARIO/METR CARRAO temos um uma relação de 282686.54 Passageiros por km \n",
      "Na linha 407Y10 - PQ SAVOY CITY/METRO V PRUDENTE temos um uma relação de 85497.27 Passageiros por km \n",
      "Na linha 408510 - COHAB FAZE DO CARMO/M ITAQUERA temos um uma relação de 455633.66 Passageiros por km \n",
      "Na linha 408610 - CID TIRADENTES/TERM CID TIRADE temos um uma relação de 260757.07 Passageiros por km \n",
      "Na linha 408A10 - MACHADO DE ASSIS/CARD ALMEIDA  temos um uma relação de 469302.33 Passageiros por km \n",
      "Na linha 409210 - SETOR IIB/TERM CID TIRADENTES temos um uma relação de 385014.76 Passageiros por km \n",
      "Na linha 409310 - CIDADE TIRADENTES/METRO PENHA temos um uma relação de 765411.25 Passageiros por km \n",
      "Na linha 411110 - VILA MONUMENTO/PÇA REPUBLICA temos um uma relação de 162420.47 Passageiros por km \n",
      "Na linha 411210 - STA MARGARIDA MARIA/PCA REPUBL temos um uma relação de 226311.93 Passageiros por km \n",
      "Na linha 411310 - GENTIL DE MOURA/PCA REPUBLICA temos um uma relação de 823168.97 Passageiros por km \n",
      "Na linha 411410 - VILA GUMERCINDO/TER PQ D PEDRO temos um uma relação de 100720.04 Passageiros por km \n",
      "Na linha 411431 - VI GUMERCINDO/T PQ D PEDRO II temos um uma relação de 14932.76 Passageiros por km \n",
      "Na linha 411510 - SHOP PLAZA SUL/PÇ REPUBLICA temos um uma relação de 159217.10 Passageiros por km \n",
      "Na linha 414P10 - VILA INDUSTRIAL/PENHA temos um uma relação de 601001.26 Passageiros por km \n",
      "Na linha 421010 - T CID TIRADENTES/T PQ D PEDRO temos um uma relação de 454925.10 Passageiros por km \n",
      "Na linha 422110 - JD PLANALTO/TERM P D PEDRO temos um uma relação de 248528.69 Passageiros por km \n",
      "Na linha 422210 - PQ STA MADALENA/PÇA J MENDES temos um uma relação de 114020.75 Passageiros por km \n",
      "Na linha 425E10 - JD. ESTER/TERM. SAPOPEMBA temos um uma relação de 224658.03 Passageiros por km \n",
      "Na linha 428410 - V CALIFORNIA/T PQ D PEDRO II temos um uma relação de 85019.83 Passageiros por km \n",
      "Na linha 428610 - VILA INDUSTRIAL/PÇA DO CORREIO temos um uma relação de 80190.01 Passageiros por km \n",
      "Na linha 428810 - VILA INDUSTRIAL/T P D PEDRO II temos um uma relação de 226290.40 Passageiros por km \n",
      "Na linha 431010 - E.T.ITAQUERA/TERM PQ D PEDRO   temos um uma relação de 1736772.69 Passageiros por km \n",
      "Na linha 431021 - ARTUR ALVIM/PARQUE DOM PEDRO temos um uma relação de 25385.39 Passageiros por km \n",
      "Na linha 431110 - TER SAO MATEUS/T PQ D PEDRO II temos um uma relação de 460521.42 Passageiros por km \n",
      "Na linha 431210 - JD MARILIA/TERM PQ D PEDRO II temos um uma relação de 411055.40 Passageiros por km \n",
      "Na linha 431310 - T CID TIRADENTES/T PQ D PEDRO  temos um uma relação de 864887.27 Passageiros por km \n",
      "Na linha 431410 - INACIO MONTEIRO/T PQ D PEDRO  temos um uma relação de 303044.86 Passageiros por km \n",
      "Na linha 431510 - T VILA CARRAO/T PQ D PEDRO II  temos um uma relação de 669619.32 Passageiros por km \n",
      "Na linha 449110 - ZOOLOGICO/TERM P D PEDRO temos um uma relação de 454729.85 Passageiros por km \n",
      "Na linha 470610 - J MARIA ESTELA II/MT V MARIANA temos um uma relação de 327671.41 Passageiros por km \n",
      "Na linha 470810 - JD CLIMAX/METRO VILA MARIANA temos um uma relação de 528690.03 Passageiros por km \n",
      "Na linha 470910 - PQ BRISTOL/METRO V MARIANA temos um uma relação de 502105.45 Passageiros por km \n",
      "Na linha 471610 - SACOMA/METRO SANTA CRUZ temos um uma relação de 951580.01 Passageiros por km \n",
      "Na linha 471710 - JD MARIA ESTELA/METRO STA CRUZ temos um uma relação de 82906.00 Passageiros por km \n",
      "Na linha 471810 - JD CELESTE/METRO STA CRUZ temos um uma relação de 84438.51 Passageiros por km \n",
      "Na linha 472110 - SHOP PLAZA SUL/METRO JABAQUARA temos um uma relação de 366645.15 Passageiros por km \n",
      "Na linha 472410 - METRO PATRIARCA/VILA NHOCUNE temos um uma relação de 231965.01 Passageiros por km \n",
      "Na linha 472510 - VILA BRASILINA/SH C IBIRAPUERA temos um uma relação de 128361.25 Passageiros por km \n",
      "Na linha 472610 - MOOCA / METRO TATUAPE temos um uma relação de 1129497.98 Passageiros por km \n",
      "Na linha 472631 - MOOCA/METRO TATUAPE temos um uma relação de 46660.87 Passageiros por km \n",
      "Na linha 472710 - JD CLIMAX/METRO PÇ ARVORE temos um uma relação de 540215.75 Passageiros por km \n",
      "Na linha 472910 - PQ BANCARIO/METRO BELEM temos um uma relação de 446012.54 Passageiros por km \n",
      "Na linha 473210 - VILA LIVIERO/METRO SAUDE temos um uma relação de 436878.27 Passageiros por km \n",
      "Na linha 473231 - VILA LIVIERO/METRO SAUDE temos um uma relação de 798924.52 Passageiros por km \n",
      "Na linha 473410 - VILA MORAES/METRO SAUDE temos um uma relação de 1758469.25 Passageiros por km \n",
      "Na linha 473421 - VILA MORAES/METRO SAUDE temos um uma relação de 74615.06 Passageiros por km \n",
      "Na linha 473510 - SAO MATEUS/METRO CARRAO temos um uma relação de 418781.16 Passageiros por km \n",
      "Na linha 474210 - JD CLIMAX/METRO SAO JUDAS temos um uma relação de 270192.46 Passageiros por km \n",
      "Na linha 475M10 - JD DA SAUDE/T AMARAL GURGEL temos um uma relação de 188356.74 Passageiros por km \n",
      "Na linha 475R10 - JD SAO SAVERIO/TERM P D PEDRO temos um uma relação de 715356.33 Passageiros por km \n",
      "Na linha 475R21 - JD SAO SAVERIO/METRO PÇ ARVORE temos um uma relação de 3971.17 Passageiros por km \n",
      "Na linha 476A10 - IPIRANGA/TERM STO AMARO temos um uma relação de 293930.88 Passageiros por km \n",
      "Na linha 476G10 - JARDIM ELBA/IBIRAPUERA temos um uma relação de 520843.01 Passageiros por km \n",
      "Na linha 476G41 - VILA INDUSTRIAL/METRO ANA ROSA temos um uma relação de 443519.70 Passageiros por km \n",
      "Na linha 476L10 - LAR ESCOLA S FRANCISC/CIRCULAR temos um uma relação de 5858.05 Passageiros por km \n",
      "Na linha 477A10 - SACOMA/CEASA temos um uma relação de 901050.49 Passageiros por km \n",
      "Na linha 477P10 - IPIRANGA/RIO PEQUENO temos um uma relação de 325668.97 Passageiros por km \n",
      "Na linha 477U10 - HELIOPOLIS/SHOP IGUATEMI CIRC temos um uma relação de 304654.12 Passageiros por km \n",
      "Na linha 478P10 - SACOMA/POMPEIA temos um uma relação de 406051.01 Passageiros por km \n",
      "Na linha 501010 - CIDADE VARGAS/SANTO AMARO temos um uma relação de 548091.89 Passageiros por km \n",
      "Na linha 501110 - ELDORADO/SANTO AMARO temos um uma relação de 650307.87 Passageiros por km \n",
      "Na linha 501210 - JD GUACURI/JABAQUARA temos um uma relação de 805462.45 Passageiros por km \n",
      "Na linha 501310 - JD LUSO/SANTO AMARO temos um uma relação de 1441973.26 Passageiros por km \n",
      "Na linha 501331 - JD MIRIAM/SANTO AMARO temos um uma relação de 259240.35 Passageiros por km \n",
      "Na linha 501510 - JD SAO JORGE/JABAQUARA temos um uma relação de 927787.02 Passageiros por km \n",
      "Na linha 501810 - SHOP. INTERLAGOS - JABAQUARA temos um uma relação de 544822.10 Passageiros por km \n",
      "Na linha 501831 - SHOPPING INTERLAGOS/JABAQUARA temos um uma relação de 294188.77 Passageiros por km \n",
      "Na linha 502010 - HOSP HELIOP/TERM SACOMA temos um uma relação de 2783574.83 Passageiros por km \n",
      "Na linha 502110 - AGUA FUNDA/TERM SACOMA temos um uma relação de 710206.44 Passageiros por km \n",
      "Na linha 502210 - VILA STA MARGARIDA/JABAQUARA temos um uma relação de 1682069.08 Passageiros por km \n",
      "Na linha 502410 - VILA MISSIONARIA/SANTO AMARO temos um uma relação de 784606.70 Passageiros por km \n",
      "Na linha 502431 - VILA MISSIONARIA/SANTO AMARO temos um uma relação de 589007.79 Passageiros por km \n",
      "Na linha 502510 - JD GUAIRACA/METRO TAMANDUATEI temos um uma relação de 15972.40 Passageiros por km \n",
      "Na linha 502610 - CJ.TEOT.VILELA/JD.SAO ROBERTO temos um uma relação de 223655.57 Passageiros por km \n",
      "Na linha 502810 - CJ HAB HELIOP/MUSEU IPIRANGA temos um uma relação de 62460.51 Passageiros por km \n",
      "Na linha 502910 - JD PATENTE/TERM SACOMA temos um uma relação de 1152753.12 Passageiros por km \n",
      "Na linha 502J10 - VILA PEDREIRA/PQ.DO IBIRAPUERA temos um uma relação de 461498.25 Passageiros por km \n",
      "Na linha 502J21 - ESTACAO AUTODROMO/VILA JOANIZA temos um uma relação de 65403.51 Passageiros por km \n",
      "Na linha 502J22 - ESTACAO AUTODROMO/VILA JOANIZA temos um uma relação de 37419.98 Passageiros por km \n",
      "Na linha 503010 - JD MARIA ESTELA/TERM SACOMA temos um uma relação de 436475.37 Passageiros por km \n",
      "Na linha 503110 - VILA ARAPUA/TERM SACOMA temos um uma relação de 3356656.49 Passageiros por km \n",
      "Na linha 503121 - VILA CONDE DO PINHAL/TERM SACO temos um uma relação de 1091003.89 Passageiros por km \n",
      "Na linha 503210 - VILA ARAPUA/TERM SACOMA temos um uma relação de 686381.02 Passageiros por km \n",
      "Na linha 503310 - VILA BRASILINA/TERM SACOMA temos um uma relação de 376113.42 Passageiros por km \n",
      "Na linha 503410 - VILA LIVIERO/TERM SACOMA temos um uma relação de 670312.41 Passageiros por km \n",
      "Na linha 503431 - TERM SACOMA/VILA LIVIERO temos um uma relação de 369388.77 Passageiros por km \n",
      "Na linha 503510 - VILA ARAPUA/TERM SACOMA temos um uma relação de 688692.77 Passageiros por km \n",
      "Na linha 503610 - JD CELESTE/TERM SACOMA temos um uma relação de 286677.75 Passageiros por km \n",
      "Na linha 503810 - PQ. BRISTOL/TERM SACOMA temos um uma relação de 936041.90 Passageiros por km \n",
      "Na linha 507T10 - TERM SAPOPEMBA/METRO CARRAO temos um uma relação de 1036536.52 Passageiros por km \n",
      "Na linha 508L10 - TERM.PRIN.ISABEL/ACLIMACAO temos um uma relação de 290323.25 Passageiros por km \n",
      "Na linha 509110 - JD UBIRAJARA/MOEMA CIRCULAR temos um uma relação de 200799.13 Passageiros por km \n",
      "Na linha 509J10 - J SELMA VIA JOANIZA/T P ISABEL temos um uma relação de 404018.85 Passageiros por km \n",
      "Na linha 509J21 - VILA MISSIONARIA/MOEMA temos um uma relação de 39207.26 Passageiros por km \n",
      "Na linha 509M10 - JD. MIRIAM/TERM. PRINC. ISABEL temos um uma relação de 376469.99 Passageiros por km \n",
      "Na linha 509M21 - JD. MIRIAM/MOEMA temos um uma relação de 94703.62 Passageiros por km \n",
      "Na linha 510010 - EST.FEP.PINHEIROS/PCA DA SE temos um uma relação de 352617.58 Passageiros por km \n",
      "Na linha 510310 - TERM. SACOMA/MOEMA temos um uma relação de 522818.45 Passageiros por km \n",
      "Na linha 510321 - TERM SACOMA/ METRO STA CRUZ temos um uma relação de 236951.66 Passageiros por km \n",
      "Na linha 510510 - TERM. SACOMA/TERM.MERCADO temos um uma relação de 1603833.28 Passageiros por km \n",
      "Na linha 510610 - LGO.SAO FRANCISCO/JD. SELMA temos um uma relação de 350083.20 Passageiros por km \n",
      "Na linha 510621 - SHOPPING IBIRAPUERA/JD SELMA temos um uma relação de 183145.88 Passageiros por km \n",
      "Na linha 510631 - METRO ANA ROSA/JD SELMA temos um uma relação de 312304.08 Passageiros por km \n",
      "Na linha 510710 - TERM SACOMA/TERM CORREIO temos um uma relação de 659981.50 Passageiros por km \n",
      "Na linha 510810 - JD CELESTE/TERM PQ D PEDRO II temos um uma relação de 1146239.66 Passageiros por km \n",
      "Na linha 510910 - TERM V PRUDENTE/TERM MERCADO temos um uma relação de 380.62 Passageiros por km \n",
      "Na linha 511010 - TERM SAO MATEUS/TERM MERCADO temos um uma relação de 1038930.26 Passageiros por km \n",
      "Na linha 511021 - SAO MATEUS/TERMINAL MERCADO temos um uma relação de 50464.87 Passageiros por km \n",
      "Na linha 511022 - FAZENDA DA JUTA/TERM MERCADO temos um uma relação de 14052.55 Passageiros por km \n",
      "Na linha 511023 - JD PLANALTO/TERM MERCADO temos um uma relação de 50917.56 Passageiros por km \n",
      "Na linha 511024 - SAO MATEUS/VILA PRUDENTE temos um uma relação de 40061.00 Passageiros por km \n",
      "Na linha 511041 - SAO MATEUS/METRO TAMANDUATEI temos um uma relação de 260592.51 Passageiros por km \n",
      "Na linha 511110 - TERM.STO.AMARO-TERM.D.PEDRO II temos um uma relação de 1154222.72 Passageiros por km \n",
      "Na linha 511910 - TERM CAPELINHA-LG.S.FRANCISCO temos um uma relação de 830304.11 Passageiros por km \n",
      "Na linha 511922 - TE JOAO DIAS/LGO SAO FRANCISCO temos um uma relação de 65452.06 Passageiros por km \n",
      "Na linha 511923 - TE JOAO DIAS/INST LUCY MONTORO temos um uma relação de 101438.51 Passageiros por km \n",
      "Na linha 512310 - JD MIRIAM/HOSP SAO PAULO temos um uma relação de 1117055.76 Passageiros por km \n",
      "Na linha 512710 - VILA GUACURI/RIO PEQUENO temos um uma relação de 326561.90 Passageiros por km \n",
      "Na linha 512810 - JD APURA/SHOP MORUMBI temos um uma relação de 798281.37 Passageiros por km \n",
      "Na linha 512910 - JD. MIRIAM/CHAC. STA. MARIA temos um uma relação de 676166.22 Passageiros por km \n",
      "Na linha 512941 - JD MIRIAM/SANTO AMARO temos um uma relação de 730825.70 Passageiros por km \n",
      "Na linha 513110 - CIDADE ADEMAR/PCA. DA SE temos um uma relação de 328079.96 Passageiros por km \n",
      "Na linha 513L10 - TERM SACOMA/PENHA temos um uma relação de 371151.72 Passageiros por km \n",
      "Na linha 514110 - TERM. SAPOPEMBA/PCA DO CORREIO temos um uma relação de 241569.73 Passageiros por km \n",
      "Na linha 514210 - TERM.SAPOPEMBA/T.PQ.D.PEDRO II temos um uma relação de 564088.28 Passageiros por km \n",
      "Na linha 514310 - TERM.SAPOPEMBA/T.D.PEDRO II temos um uma relação de 234129.63 Passageiros por km \n",
      "Na linha 514331 - TERM SAPOPEMBA/TERM P D PEDRO  temos um uma relação de 1208.88 Passageiros por km \n",
      "Na linha 514410 - TERM.SAPOPEMBA/T.PRINC.ISABEL temos um uma relação de 323870.65 Passageiros por km \n",
      "Na linha 514510 - TERM.SAPOPEMBA/PCA.ALMEIDA JR. temos um uma relação de 236700.45 Passageiros por km \n",
      "Na linha 514541 - CJ.TEOT VILELA/PCA ALMEIDA JR temos um uma relação de 43658.93 Passageiros por km \n",
      "Na linha 514T10 - TERM SACOMA/JD ITAPOLIS temos um uma relação de 705112.81 Passageiros por km \n",
      "Na linha 514T21 - JD COLORADO/METRO VILA PRUDENT temos um uma relação de 67327.74 Passageiros por km \n",
      "Na linha 514T22 - METRO VILA PRUDENTE/JD ITAPOLI temos um uma relação de 4583.16 Passageiros por km \n",
      "Na linha 515410 - STO AMARO/EST DA LUZ temos um uma relação de 451548.72 Passageiros por km \n",
      "Na linha 516410 - V.STA.CATARINA/LGO.S.FRANCISCO temos um uma relação de 218687.89 Passageiros por km \n",
      "Na linha 516421 - CIDADE LEONOR/HOSP SAO PAULO temos um uma relação de 120987.66 Passageiros por km \n",
      "Na linha 516441 - VILA GUARANI - CIRCULAR temos um uma relação de 113238.69 Passageiros por km \n",
      "Na linha 516N10 - JD MIRIAM/ITAIM BIBI temos um uma relação de 479227.37 Passageiros por km \n",
      "Na linha 517510 - BALNEARIO S FRANCISCO/PCA DA S temos um uma relação de 267516.30 Passageiros por km \n",
      "Na linha 517810 - JD MIRIAM/LGO S FRANCISCO temos um uma relação de 475382.73 Passageiros por km \n",
      "Na linha 517821 - JD MIRIAM/PQ DO IBIRAPUERA temos um uma relação de 13002.31 Passageiros por km \n",
      "Na linha 517J10 - JD SELMA/PINHEIROS temos um uma relação de 570969.69 Passageiros por km \n",
      "Na linha 518510 - TERM GUARAPIRANGA/PQ D PEDRO  temos um uma relação de 671298.73 Passageiros por km \n",
      "Na linha 519410 - J S JORGE AT J APURA/L S FCISC temos um uma relação de 82691.67 Passageiros por km \n",
      "Na linha 519M10 - SAO MATEUS/MUSEU DO IPIRANGA temos um uma relação de 180590.99 Passageiros por km \n",
      "Na linha 524L10 - PQ SAO LUCAS/TATUAPE temos um uma relação de 393128.40 Passageiros por km \n",
      "Na linha 524M10 - MASC.MORAES/SHOP.ARICANDUVA temos um uma relação de 1490475.39 Passageiros por km \n",
      "Na linha 527R10 - VILA IMPERIO/REAL PARQUE temos um uma relação de 656154.20 Passageiros por km \n",
      "Na linha 529010 - DIV DIADEMA/PCA JOAO MENDES temos um uma relação de 614495.34 Passageiros por km \n",
      "Na linha 530010 - TERM STO AMARO/PQ DOM PEDRO temos um uma relação de 1158811.00 Passageiros por km \n",
      "Na linha 531710 - CENTRO SESC-LGO.SAO FRANCISCO temos um uma relação de 216819.78 Passageiros por km \n",
      "Na linha 531810 - Chac.Santna-Pca.Se temos um uma relação de 804322.37 Passageiros por km \n",
      "Na linha 531821 - Chacara Santana - Praca da Se temos um uma relação de 27218.07 Passageiros por km \n",
      "Na linha 531822 - PRACA DA SE / BORBA GATO temos um uma relação de 21204.82 Passageiros por km \n",
      "Na linha 536210 - Pq Res Cocaia - Pça da Sé temos um uma relação de 442439.20 Passageiros por km \n",
      "Na linha 536221 - Grajaú - Pça da Sé temos um uma relação de 13287.23 Passageiros por km \n",
      "Na linha 536222 - JARDIM ELIANA / PRACA DA SE temos um uma relação de 15251.79 Passageiros por km \n",
      "Na linha 536223 - PQ RES COCAIA/BORBA GATO temos um uma relação de 131727.22 Passageiros por km \n",
      "Na linha 536241 - Pq Res Cocaia - Detran temos um uma relação de 35416.69 Passageiros por km \n",
      "Na linha 537010 - TERM VARGINHA/LGO S FRANCISCO temos um uma relação de 677542.00 Passageiros por km \n",
      "Na linha 537021 - Detran temos um uma relação de 64031.23 Passageiros por km \n",
      "Na linha 537022 - TERM VARGINHA/BORBA GATO temos um uma relação de 2062.71 Passageiros por km \n",
      "Na linha 539110 - TERM JD ANGELA/PCA DA SE temos um uma relação de 722582.54 Passageiros por km \n",
      "Na linha 539121 - TERM GUARAP - LGO S FRANCISCO temos um uma relação de 32175.95 Passageiros por km \n",
      "Na linha 539122 - TERM JD ANGELA/MOEMA temos um uma relação de 15061.16 Passageiros por km \n",
      "Na linha 546A10 - JD APURA/SANTO AMARO temos um uma relação de 544003.84 Passageiros por km \n",
      "Na linha 546A31 - JD APURA/SANTO AMARO temos um uma relação de 505846.50 Passageiros por km \n",
      "Na linha 546J10 - JD SELMA/STO AMARO temos um uma relação de 741770.53 Passageiros por km \n",
      "Na linha 546J31 - JD SELMA/SANTO AMARO temos um uma relação de 712508.76 Passageiros por km \n",
      "Na linha 546J41 - JD SELMA/COLEGIO SANTA MARIA temos um uma relação de 253.76 Passageiros por km \n",
      "Na linha 546L10 - JD. LUSO/TERMINAL STO AMARO temos um uma relação de 548563.24 Passageiros por km \n",
      "Na linha 546L41 - JD. LUSO/COLEGIO STA. MARIA temos um uma relação de 5518.91 Passageiros por km \n",
      "Na linha 546T10 - VILA GUACURI/TERM STO AMARO temos um uma relação de 1243754.90 Passageiros por km \n",
      "Na linha 561110 - ELDORADO/PCA JOAO MENDES temos um uma relação de 251681.96 Passageiros por km \n",
      "Na linha 561410 - ELDORADO/PCA JOAO MENDES temos um uma relação de 160867.38 Passageiros por km \n",
      "Na linha 561410 - ELDORADO/PRACA JOAO MENDES temos um uma relação de 70121.30 Passageiros por km \n",
      "Na linha 563010 - Jd Eliana - Brás temos um uma relação de 843088.79 Passageiros por km \n",
      "Na linha 563021 - JD ELIANA/DETRAN temos um uma relação de 47244.05 Passageiros por km \n",
      "Na linha 563210 - Vila São José - L S Francisco temos um uma relação de 259481.00 Passageiros por km \n",
      "Na linha 563221 - Jd Iporanga - L São Francisco temos um uma relação de 7294.41 Passageiros por km \n",
      "Na linha 563251 - Jd Alpino - Lgo São Francisco temos um uma relação de 7572.31 Passageiros por km \n",
      "Na linha 565210 - JD IV CENTENARIO/LGO S FRANCIS temos um uma relação de 289028.01 Passageiros por km \n",
      "Na linha 565221 - JD IV CENTENARIO/LGO S FRANCIS temos um uma relação de 7243.95 Passageiros por km \n",
      "Na linha 570110 - VILA SANTA CATARINA/METRO CONC temos um uma relação de 795775.72 Passageiros por km \n",
      "Na linha 570121 - V SANTA CATARINA/EST BERRINI temos um uma relação de 20985.79 Passageiros por km \n",
      "Na linha 570210 - CIDADE JULIA/METRO JABAQUARA temos um uma relação de 1145360.43 Passageiros por km \n",
      "Na linha 570510 - TERM SACOMA/METRO VERGUEIRO temos um uma relação de 315729.66 Passageiros por km \n",
      "Na linha 573A10 - METRO BRESSER/VILA ALPINA temos um uma relação de 645367.69 Passageiros por km \n",
      "Na linha 573H10 - HOSP.SAPOPEMBA/METRO BRESSER temos um uma relação de 944508.32 Passageiros por km \n",
      "Na linha 573T10 - TERM.SAPOPEMBA/METRO CARRAO temos um uma relação de 870426.64 Passageiros por km \n",
      "Na linha 573T21 - JD TIETE/T SAPOPEMBA-TEOT VILE temos um uma relação de 15477.65 Passageiros por km \n",
      "Na linha 573T31 - TERM SAPOPEMBA/TEOTONIO VILELA temos um uma relação de 71379.00 Passageiros por km \n",
      "Na linha 574A10 - AMERICANOPOLIS/LGO CAMBUCI temos um uma relação de 607414.07 Passageiros por km \n",
      "Na linha 574C10 - TERM.SAO MATEUS/DIV.S.CAETANO temos um uma relação de 490675.30 Passageiros por km \n",
      "Na linha 574J10 - METRO CONCEICAO/T VILA CARRAO temos um uma relação de 884125.44 Passageiros por km \n",
      "Na linha 574R10 - TERM.SAPOPEMBA/METRO BELEM temos um uma relação de 956984.88 Passageiros por km \n",
      "Na linha 574W10 - JD. WALKIRIA/METRO BELEM temos um uma relação de 494392.32 Passageiros por km \n",
      "Na linha 575210 - V. MISSIONARIA/METRO CONCEICAO temos um uma relação de 1457031.62 Passageiros por km \n",
      "Na linha 575710 - JD. MIRIAM/METRO CONCEICAO temos um uma relação de 1189566.30 Passageiros por km \n",
      "Na linha 575751 - PEDREIRA/METRO CONCEIÇAO temos um uma relação de 800380.29 Passageiros por km \n",
      "Na linha 575910 - PQ PRIMAVERA/METRO CONCEICAO temos um uma relação de 599653.08 Passageiros por km \n",
      "Na linha 575931 - PQ PRIMAVERA/METRO CONCEICAO temos um uma relação de 803933.46 Passageiros por km \n",
      "Na linha 575A10 - DIV.S.CAETANO/SHOP MET.TATUAPE temos um uma relação de 492125.60 Passageiros por km \n",
      "Na linha 575C10 - VILA MATIAS/METRO CONCEICAO temos um uma relação de 117444.67 Passageiros por km \n",
      "Na linha 576C10 - METRO JABAQUARA/TERM.STO AMARO temos um uma relação de 687310.21 Passageiros por km \n",
      "Na linha 576J10 - METRO JABAQUARA/STO AMARO temos um uma relação de 337742.37 Passageiros por km \n",
      "Na linha 576M10 - V CLARA/PINHEIROS temos um uma relação de 506780.62 Passageiros por km \n",
      "Na linha 577T10 - JD. MIRIAM/VL. GOMES temos um uma relação de 532592.72 Passageiros por km \n",
      "Na linha 579110 - ELDORADO/METRO PARAISO temos um uma relação de 388382.34 Passageiros por km \n",
      "Na linha 600010 - TERM PARELHEIROS/TERM SANTO AM temos um uma relação de 982308.05 Passageiros por km \n",
      "Na linha 600021 - CIDADE DUTRA/AMA temos um uma relação de 2227.93 Passageiros por km \n",
      "Na linha 600023 - Term. Parelheiros /AMA temos um uma relação de 1476.48 Passageiros por km \n",
      "Na linha 600024 - T. Parelheiros AMA/T.Sto Amaro temos um uma relação de 238.12 Passageiros por km \n",
      "Na linha 600110 - TERM.CAPELINHA-TERM.JOAO DIAS temos um uma relação de 685563.88 Passageiros por km \n",
      "Na linha 600210 - CIDADE DUTRA/AME temos um uma relação de 108503.79 Passageiros por km \n",
      "Na linha 600310 - TERM GRAJAU/TERM VARGINHA temos um uma relação de 2302151.03 Passageiros por km \n",
      "Na linha 600610 - SHOPPING INTERLAGOS/JD HERCULA temos um uma relação de 724376.11 Passageiros por km \n",
      "Na linha 600710 - PQ STO ANTONIO/JD STO AMARO temos um uma relação de 592622.19 Passageiros por km \n",
      "Na linha 600810 - JD PLANALTO/SANTO AMARO temos um uma relação de 1003444.98 Passageiros por km \n",
      "Na linha 600821 - PQUE EUROPA/TERM GUARAPIRANGA temos um uma relação de 992.92 Passageiros por km \n",
      "Na linha 601010 - JD SAO LUIZ/SANTO AMARO temos um uma relação de 951324.20 Passageiros por km \n",
      "Na linha 601210 - JD ANGELA/SANTO AMARO temos um uma relação de 360809.46 Passageiros por km \n",
      "Na linha 601231 - PQ INDEPENDENCIA/JD ANGELA temos um uma relação de 106232.68 Passageiros por km \n",
      "Na linha 601310 - JD NAKAMURA-TERM STO AMARO temos um uma relação de 664744.49 Passageiros por km \n",
      "Na linha 601321 - ETEC/JARDIM ANGELA temos um uma relação de 16624.11 Passageiros por km \n",
      "Na linha 601410 - JD JACIRA-TERM STO AMARO temos um uma relação de 534557.01 Passageiros por km \n",
      "Na linha 601510 - VILA CALU/SANTO AMARO temos um uma relação de 530782.50 Passageiros por km \n",
      "Na linha 601610 - JD NORONHA/TERM GRAJAU temos um uma relação de 1250437.18 Passageiros por km \n",
      "Na linha 601641 - JD PORTO VELHO/TERM GRAJAU temos um uma relação de 1225718.95 Passageiros por km \n",
      "Na linha 601710 - JD NAKAMURA/SANTO AMARO temos um uma relação de 683638.50 Passageiros por km \n",
      "Na linha 601910 - T.GUARAPIRANGA/JD.GODOFREDO temos um uma relação de 477648.08 Passageiros por km \n",
      "Na linha 602010 - CHAC BOSQUE DO SOL/PARELHEIROS temos um uma relação de 29095.68 Passageiros por km \n",
      "Na linha 602051 - ESTRADA DO JUSA/PARELHEIROS temos um uma relação de 1851.02 Passageiros por km \n",
      "Na linha 602110 - TERMINAL VARGINHA/JARDIM NOVA  temos um uma relação de 76190.26 Passageiros por km \n",
      "Na linha 602210 - PQ CEREJEIRA/SANTO AMARO temos um uma relação de 324590.48 Passageiros por km \n",
      "Na linha 602510 - JD GUARUJA/SANTO AMARO temos um uma relação de 347582.25 Passageiros por km \n",
      "Na linha 602610 - Jd Icaraí - Term Santo Amaro temos um uma relação de 218493.63 Passageiros por km \n",
      "Na linha 602631 - Jd Icaraí - Term Santo Amaro temos um uma relação de 12014.05 Passageiros por km \n",
      "Na linha 602710 - Jd Graúna - Term Santo Amaro temos um uma relação de 848949.08 Passageiros por km \n",
      "Na linha 602810 - RIVIERA/SANTO AMARO temos um uma relação de 703981.08 Passageiros por km \n",
      "Na linha 603010 - FACULDADE OSEC/TERM STO AMARO temos um uma relação de 988024.25 Passageiros por km \n",
      "Na linha 603110 - Jd S Bernardo - Term Sto Amaro temos um uma relação de 2906214.48 Passageiros por km \n",
      "Na linha 603410 - Pq Res Cocaia - Term Sto Amaro temos um uma relação de 985189.79 Passageiros por km \n",
      "Na linha 603510 - JD GILDA/SANTO AMARO temos um uma relação de 492549.37 Passageiros por km \n",
      "Na linha 603521 - V GILDA/TERM GUARAPIRANGA temos um uma relação de 395676.92 Passageiros por km \n",
      "Na linha 603610 - JD MACEDONIA/SANTO AMARO temos um uma relação de 576986.90 Passageiros por km \n",
      "Na linha 603710 - JD MITSUTANI/SANTO AMARO temos um uma relação de 580415.72 Passageiros por km \n",
      "Na linha 603810 - JD DAS ROSAS/SANTO AMARO temos um uma relação de 1005961.53 Passageiros por km \n",
      "Na linha 603910 - VALO VELHO/SANTO AMARO temos um uma relação de 1042432.27 Passageiros por km \n",
      "Na linha 603921 - TERMINAL CAPELINHA/COHAB temos um uma relação de 2502.76 Passageiros por km \n",
      "Na linha 604110 - JD JANGADEIRO/SANTO AMARO temos um uma relação de 987541.73 Passageiros por km \n",
      "Na linha 604121 - MONTE AZUL/TERM JOAO DIAS temos um uma relação de 116777.62 Passageiros por km \n",
      "Na linha 604210 - JD TRES ESTRELAS/SANTO AMARO temos um uma relação de 606407.66 Passageiros por km \n",
      "Na linha 604221 - JD SONIA/INGA temos um uma relação de 291690.82 Passageiros por km \n",
      "Na linha 604310 - JD CAPELINHA/SANTO AMARO temos um uma relação de 929141.37 Passageiros por km \n",
      "Na linha 604410 - JD STO EDUARDO/SANTO AMARO temos um uma relação de 734225.53 Passageiros por km \n",
      "Na linha 604510 - VALO VELHO/SANTO AMARO temos um uma relação de 805306.54 Passageiros por km \n",
      "Na linha 604521 - VALO VELHO/CAPAO REDONDO temos um uma relação de 40197.22 Passageiros por km \n",
      "Na linha 604610 - JD SAO BENTO NOVO/SANTO AMARO temos um uma relação de 548926.26 Passageiros por km \n",
      "Na linha 604710 - JD LIDIA/SANTO AMARO temos um uma relação de 711680.66 Passageiros por km \n",
      "Na linha 604810 - JD.ANGELA-STO.AMARO temos um uma relação de 996535.76 Passageiros por km \n",
      "Na linha 604910 - VALO VELHO/STO AMARO temos um uma relação de 519716.82 Passageiros por km \n",
      "Na linha 605010 - J VALE DAS VIRTUDES/SANTO AMAR temos um uma relação de 329402.51 Passageiros por km \n",
      "Na linha 605110 - JD ITAJAI/TERM VARGINHA temos um uma relação de 474216.17 Passageiros por km \n",
      "Na linha 605131 - JD.ITAJAI/TERM.VARGINHA temos um uma relação de 165939.31 Passageiros por km \n",
      "Na linha 605210 - J SETE SETEMBRO/TERM VARGINHA temos um uma relação de 1143671.90 Passageiros por km \n",
      "Na linha 605231 - JD ALMEIDA PRADO/TERM VARGINHA temos um uma relação de 191208.34 Passageiros por km \n",
      "Na linha 605310 - JD ELLUS/TERM GRAJAU temos um uma relação de 302201.35 Passageiros por km \n",
      "Na linha 605510 - JD SAO BERNARDO/SHOP INTERLAGO temos um uma relação de 276293.25 Passageiros por km \n",
      "Na linha 605610 - PQ SANTA CECILIA/TERM GRAJAU temos um uma relação de 1489297.67 Passageiros por km \n",
      "Na linha 605641 - VILA NATAL/TERM GRAJAU temos um uma relação de 25270.03 Passageiros por km \n",
      "Na linha 605710 - VILA NATAL/TERM GRAJAU temos um uma relação de 2029552.56 Passageiros por km \n",
      "Na linha 605810 - JD NORONHA/TERM VARGINHA temos um uma relação de 789255.41 Passageiros por km \n",
      "Na linha 605910 - JD UNIVERSAL/SANTO AMARO temos um uma relação de 559372.53 Passageiros por km \n",
      "Na linha 606110 - JD MARILDA/TERM GRAJAU temos um uma relação de 908549.59 Passageiros por km \n",
      "Na linha 606210 - JD CASTRO ALVES/SANTO AMARO temos um uma relação de 1022967.11 Passageiros por km \n",
      "Na linha 606251 - JD CASTRO ALVES/TERM STO AMARO temos um uma relação de 825898.99 Passageiros por km \n",
      "Na linha 606310 - JD VARGINHA/TERM VARGINHA temos um uma relação de 1917886.48 Passageiros por km \n",
      "Na linha 606341 - JD VARGINHA/TERM VARGINHA temos um uma relação de 1343404.56 Passageiros por km \n",
      "Na linha 606342 - CHACARA STO AMARO/TER VARGINHA temos um uma relação de 280305.00 Passageiros por km \n",
      "Na linha 606343 - VILA DA PAZ/TERMINAL VARGINHA temos um uma relação de 6783.02 Passageiros por km \n",
      "Na linha 606910 - JD SAO BERNARDO/SANTO AMARO temos um uma relação de 468825.18 Passageiros por km \n",
      "Na linha 607110 - JD ORION/TERM SANTO AMARO temos um uma relação de 406015.79 Passageiros por km \n",
      "Na linha 607122 - JD PRIMAVERA/TERM SANTO AMARO temos um uma relação de 2661.19 Passageiros por km \n",
      "Na linha 607210 - JD SAO NICOLAU/TERM. VARGINHA temos um uma relação de 1228314.18 Passageiros por km \n",
      "Na linha 607221 - JD IPORA/TERM VARGINHA temos um uma relação de 23847.88 Passageiros por km \n",
      "Na linha 607222 - JD MANACA DA SERRA/T VARGINHA temos um uma relação de 5652.82 Passageiros por km \n",
      "Na linha 607223 - TERM VARGINHA/BALNEARIO S JOSE temos um uma relação de 245609.90 Passageiros por km \n",
      "Na linha 607310 - JD SANTA TEREZINHA/TERM VARGIN temos um uma relação de 411427.70 Passageiros por km \n",
      "Na linha 607321 - JD SILVEIRA/TERM VARGINHA temos um uma relação de 10128.03 Passageiros por km \n",
      "Na linha 607410 - JD GAIVOTAS/EST JURUBATUBA temos um uma relação de 604540.79 Passageiros por km \n",
      "Na linha 607510 - JD REC CAMPO BELO/T VARGINHA temos um uma relação de 945348.78 Passageiros por km \n",
      "Na linha 607541 - JD ALMEIDA/TERM VARGINHA temos um uma relação de 6693.24 Passageiros por km \n",
      "Na linha 607610 - JD PROGRESSO/TERM STO AMARO temos um uma relação de 831449.12 Passageiros por km \n",
      "Na linha 607641 - JD SATELITE II/TERM STO AMARO temos um uma relação de 54580.33 Passageiros por km \n",
      "Na linha 607810 - CANTINHO DO CEU/SHOP INTERLAGO temos um uma relação de 886047.14 Passageiros por km \n",
      "Na linha 607A10 - JD APURA/SOCORRO temos um uma relação de 554243.22 Passageiros por km \n",
      "Na linha 607A21 - JD APURA/ESTAÇAO JURUBATUBA temos um uma relação de 98704.97 Passageiros por km \n",
      "Na linha 607C10 - JD MIRIAM/SHOPP MORUMBI temos um uma relação de 1411299.45 Passageiros por km \n",
      "Na linha 607G10 - VILA GUARANI/SHOPPING MORUMBI temos um uma relação de 266094.27 Passageiros por km \n",
      "Na linha 607M10 - TERM GRAJAU/SHOP MORUMBI temos um uma relação de 417048.07 Passageiros por km \n",
      "Na linha 608010 - JD LUCELIA/SHOP INTERLAGOS temos um uma relação de 636170.73 Passageiros por km \n",
      "Na linha 608310 - TERM GRAJAU/JD ELIANA temos um uma relação de 1359705.73 Passageiros por km \n",
      "Na linha 608410 - JD CHACARA DO SOL/TERM VARGINH temos um uma relação de 908456.71 Passageiros por km \n",
      "Na linha 608421 - JD MORAES PRADO/TERM VARGINH temos um uma relação de 37583.56 Passageiros por km \n",
      "Na linha 609110 - VARGEM GRANDE/TERM STO AMARO temos um uma relação de 530211.42 Passageiros por km \n",
      "Na linha 609121 - VARGEM GRANDE/TERM PARELHEIROS temos um uma relação de 6493.46 Passageiros por km \n",
      "Na linha 609151 - COLONIA / TERM STO AMARO temos um uma relação de 10300.55 Passageiros por km \n",
      "Na linha 609210 - JD DAS PEDRAS/TERM GRAJAU temos um uma relação de 604497.17 Passageiros por km \n",
      "Na linha 609310 - VARGEM GRANDE/TERM VARGINHA temos um uma relação de 805125.06 Passageiros por km \n",
      "Na linha 609910 - PAPAI NOEL - TERM.PARELHEIROS temos um uma relação de 286940.85 Passageiros por km \n",
      "Na linha 609F10 - Chac.Santana -Pca Princ.Isabel temos um uma relação de 606297.17 Passageiros por km \n",
      "Na linha 609F21 - Chac.Santana-Pca.Isabel temos um uma relação de 77399.64 Passageiros por km \n",
      "Na linha 609J10 - AEROPORTO/METRO SÃO JUDAS temos um uma relação de 122765.72 Passageiros por km \n",
      "Na linha 611010 - CONJ HAB PALMARES/CHAC MONTE A temos um uma relação de 691628.93 Passageiros por km \n",
      "Na linha 611510 - CANTINHO DO CEU/TERM GRAJAU temos um uma relação de 1923853.20 Passageiros por km \n",
      "Na linha 611541 - PQ RES DOS LAGOS/TERM GRAJAU temos um uma relação de 46389.39 Passageiros por km \n",
      "Na linha 611610 - JD PRAINHA/TERM GRAJAU temos um uma relação de 1440696.87 Passageiros por km \n",
      "Na linha 611810 - JD ICARAI/SANTO AMARO temos um uma relação de 549141.06 Passageiros por km \n",
      "Na linha 612010 - JD LUCELIA/TERM GRAJAU temos um uma relação de 1267972.19 Passageiros por km \n",
      "Na linha 620010 - TERM STO AMARO/TERM BANDEIRA temos um uma relação de 1418753.60 Passageiros por km \n",
      "Na linha 623210 - VILA IDA/PCA RAMOS AZEVEDO temos um uma relação de 170712.79 Passageiros por km \n",
      "Na linha 625010 - JD JAQUELINE/TERM BANDEIRA temos um uma relação de 141167.88 Passageiros por km \n",
      "Na linha 625810 - JD SAO FRANCISCO/CHAC STO ANTO temos um uma relação de 1099151.11 Passageiros por km \n",
      "Na linha 625831 - PQ FIGUEIRA G/T GUARAPIRANGA temos um uma relação de 199308.69 Passageiros por km \n",
      "Na linha 626210 - CEASA/TERM.BANDEIRA temos um uma relação de 434894.41 Passageiros por km \n",
      "Na linha 626221 - VILA LEOPOLDINA/PINHEIROS temos um uma relação de 40955.60 Passageiros por km \n",
      "Na linha 627J10 - JD MIRIAM/METRO SAO JUDAS temos um uma relação de 336300.41 Passageiros por km \n",
      "Na linha 629110 - SHOP MORUMBI/TERM BANDEIRA temos um uma relação de 503251.24 Passageiros por km \n",
      "Na linha 633810 - JD. MIRIAM/TERM. PRINC. ISABEL temos um uma relação de 266428.46 Passageiros por km \n",
      "Na linha 635810 - JD. LUSO/TERM. BANDEIRA temos um uma relação de 380783.19 Passageiros por km \n",
      "Na linha 635841 - V. IMPERIO/TERM. BANDEIRA temos um uma relação de 11081.69 Passageiros por km \n",
      "Na linha 636610 - JD. MIRIAM/TERM. BANDEIRA temos um uma relação de 322578.96 Passageiros por km \n",
      "Na linha 637A10 - TERM JD ANGELA/PINHEIROS temos um uma relação de 1231270.85 Passageiros por km \n",
      "Na linha 637A21 - VILA REMO/PINHEIROS temos um uma relação de 90482.72 Passageiros por km \n",
      "Na linha 637A22 - TERM.JD.ANGELA/ITAIM BIBI temos um uma relação de 62142.69 Passageiros por km \n",
      "Na linha 637A25 - PIRAPORINHA/PINHEIROS temos um uma relação de 92561.13 Passageiros por km \n",
      "Na linha 637A26 - TERM GUARAPIRANGA/PINHEIROS temos um uma relação de 33092.78 Passageiros por km \n",
      "Na linha 637G10 - Grajaú - Butantã temos um uma relação de 297071.82 Passageiros por km \n",
      "Na linha 637G51 - Jd Eliana - Grajaú temos um uma relação de 37455.00 Passageiros por km \n",
      "Na linha 637J10 - Vila São José - Pinheiros temos um uma relação de 174934.46 Passageiros por km \n",
      "Na linha 637P10 - TERM.STO.AMARO-PINHEIROS temos um uma relação de 934959.07 Passageiros por km \n",
      "Na linha 637R10 - JD ARACATI-ITAIM BIBI temos um uma relação de 939142.21 Passageiros por km \n",
      "Na linha 637V10 - Pq América - Pinheiros temos um uma relação de 346506.16 Passageiros por km \n",
      "Na linha 640010 - TERM.JOAO DIAS-TERM.BANDEIRA temos um uma relação de 458893.85 Passageiros por km \n",
      "Na linha 640310 - TERM.JOAO DIAS-BANDEIRA temos um uma relação de 450057.53 Passageiros por km \n",
      "Na linha 641210 - PARAISOPOLIS/TERM PRINC ISABEL temos um uma relação de 179316.06 Passageiros por km \n",
      "Na linha 641221 - PARAISOPOLIS/ITAMIM BIBI temos um uma relação de 5603.04 Passageiros por km \n",
      "Na linha 641410 - SOCORRO/TERM BANDEIRA temos um uma relação de 468860.00 Passageiros por km \n",
      "Na linha 641810 - REAL PARQUE/TERM BANDEIRA temos um uma relação de 59843.90 Passageiros por km \n",
      "Na linha 641831 - Pca da Se temos um uma relação de 4384.68 Passageiros por km \n",
      "Na linha 642210 - V CRUZEIRO/TERM BANDEIRA temos um uma relação de 238089.95 Passageiros por km \n",
      "Na linha 645010 - TERM.CAPELINHA-TERM.BANDEIRA temos um uma relação de 1270704.77 Passageiros por km \n",
      "Na linha 645021 - TERM.CAPELINHA-ITAIM BIBI temos um uma relação de 82662.21 Passageiros por km \n",
      "Na linha 645051 - TERM CAPELINHA/ITAIM temos um uma relação de 13113.96 Passageiros por km \n",
      "Na linha 645110 - TERM CAPELINHA - TERM BANDEIRA temos um uma relação de 1032109.41 Passageiros por km \n",
      "Na linha 645121 - TERM CAPELINHA - PÇA 14 BIS temos um uma relação de 48523.97 Passageiros por km \n",
      "Na linha 645510 - TERM CAPELINHA - L S FRANCISCO temos um uma relação de 699787.12 Passageiros por km \n",
      "Na linha 645521 - TERM CAPELINHA - IBIRAPUERA temos um uma relação de 34531.59 Passageiros por km \n",
      "Na linha 647510 - JD.VAZ DE LIMA/PCA DA SE temos um uma relação de 298806.47 Passageiros por km \n",
      "Na linha 647A10 - VALO VELHO/PINHEIROS temos um uma relação de 443063.50 Passageiros por km \n",
      "Na linha 647C10 - TERM JOÃO DIAS - HOSP CLINICAS temos um uma relação de 283160.28 Passageiros por km \n",
      "Na linha 647P10 - COHAB ADVENTISTA/PINHEIROS temos um uma relação de 668869.51 Passageiros por km \n",
      "Na linha 648P10 - TERM CAPELINHA - PINHEIROS temos um uma relação de 458139.38 Passageiros por km \n",
      "Na linha 648P21 - TERM CAPELINHA - ITAIM BIBI temos um uma relação de 16950.57 Passageiros por km \n",
      "Na linha 650010 - TERM.STO.AMARO-TERM.BANDEIRA temos um uma relação de 1119011.36 Passageiros por km \n",
      "Na linha 650510 - TERM GUARAPIRANGA/TERM BANDEIR temos um uma relação de 1076500.78 Passageiros por km \n",
      "Na linha 669A10 - TERM STO AMARO-TERM PRI ISABEL temos um uma relação de 842100.32 Passageiros por km \n",
      "Na linha 672610 - JD GAIVOTA/METRO ANA ROSA temos um uma relação de 1765181.33 Passageiros por km \n",
      "Na linha 675A10 - PQ.STO AMARO/METRO SAO JUDAS temos um uma relação de 509294.45 Passageiros por km \n",
      "Na linha 675G10 - Pq Res Cocaia - M Jabaquara temos um uma relação de 402110.05 Passageiros por km \n",
      "Na linha 675G22 - COLG STA MARIA/PQ RESID COCAIA temos um uma relação de 5022.61 Passageiros por km \n",
      "Na linha 675G41 - JD CASTRO ALVES/ MTO JABAQUARA temos um uma relação de 54771.11 Passageiros por km \n",
      "Na linha 675I10 - TERM JOAO DIAS - METRO S JUDAS temos um uma relação de 860857.50 Passageiros por km \n",
      "Na linha 675K10 - TERM JD ANGELA-METRO STA CRUZ temos um uma relação de 1839624.06 Passageiros por km \n",
      "Na linha 675K23 - VILA REMO/HOSPITAL DO SERVIDOR temos um uma relação de 86755.04 Passageiros por km \n",
      "Na linha 675L10 - T.STO AMARO/M.SANTA CRUZ temos um uma relação de 1203685.77 Passageiros por km \n",
      "Na linha 675M10 - Centro Sesc - M Jabaquara temos um uma relação de 326882.76 Passageiros por km \n",
      "Na linha 675N10 - STO AMARO/METRO ANA ROSA temos um uma relação de 442943.52 Passageiros por km \n",
      "Na linha 675P10 - SHOP SP MARKET/METRO CONCEIÇAO temos um uma relação de 284085.02 Passageiros por km \n",
      "Na linha 675R10 - Grajaú - M Jabaquara temos um uma relação de 251311.75 Passageiros por km \n",
      "Na linha 675V10 - JD.CAMPO FORA/METRO JABAQUARA temos um uma relação de 842312.27 Passageiros por km \n",
      "Na linha 675X10 - Grajaú - M Vl Mariana temos um uma relação de 863589.75 Passageiros por km \n",
      "Na linha 675Z10 - JD GUARUJA-METRO JABAQUARA temos um uma relação de 561774.75 Passageiros por km \n",
      "Na linha 677A10 - TERM JD ANGELA/METRO ANA ROSA temos um uma relação de 993173.11 Passageiros por km \n",
      "Na linha 677V10 - Jd Nv Horizonte - M Jabaquara temos um uma relação de 121479.50 Passageiros por km \n",
      "Na linha 677Y10 - JD GUARUJA/VILA GUARANI temos um uma relação de 438017.12 Passageiros por km \n",
      "Na linha 680110 - JD.IBIRAPUERA-TERM JOAO DIAS temos um uma relação de 2734577.48 Passageiros por km \n",
      "Na linha 680151 - JD IBIRAPUERA/TERM JOAO DIAS temos um uma relação de 403825.69 Passageiros por km \n",
      "Na linha 680310 - JD.CAPELINHA-TERM JOAO DIAS temos um uma relação de 905496.44 Passageiros por km \n",
      "Na linha 680410 - JD.INGA-TERM JOAO DIAS temos um uma relação de 1483664.25 Passageiros por km \n",
      "Na linha 680510 - TERM CAPELINHA-TERM JOAO DIAS temos um uma relação de 1103416.78 Passageiros por km \n",
      "Na linha 680531 - TERM CAPELINHA/TERM JOAO DIAS temos um uma relação de 582807.36 Passageiros por km \n",
      "Na linha 680610 - JD NOVO HORIZONTE-T.JOAO DIAS temos um uma relação de 955073.12 Passageiros por km \n",
      "Na linha 681210 - JD CAPELA/SANTO AMARO temos um uma relação de 316210.42 Passageiros por km \n",
      "Na linha 681310 - JD LIDIA-TERM CAPELINHA temos um uma relação de 820862.61 Passageiros por km \n",
      "Na linha 681510 - JD COMERCIAL-TERM CAPELINHA temos um uma relação de 763936.08 Passageiros por km \n",
      "Na linha 681610 - JD MITSUTANI-TERM CAPELINHA temos um uma relação de 715982.56 Passageiros por km \n",
      "Na linha 681631 - JARDIM MITSUTANI/TERM CAPELINH temos um uma relação de 672626.46 Passageiros por km \n",
      "Na linha 681710 - JD SAO BENTO-TERM CAPELINHA temos um uma relação de 658938.24 Passageiros por km \n",
      "Na linha 681810 - JD VALE DAS VIRTUDES-T.CAPELIN temos um uma relação de 930802.97 Passageiros por km \n",
      "Na linha 682010 - JD DAS ROSAS-TERM CAPELINHA temos um uma relação de 1172385.95 Passageiros por km \n",
      "Na linha 682031 - JD.ROSAS/TERM. CAPELINHA temos um uma relação de 1713676.53 Passageiros por km \n",
      "Na linha 682110 - JD JANGADEIRO-TERM CAPELINHA temos um uma relação de 1013907.09 Passageiros por km \n",
      "Na linha 682210 - JD MACEDONIA-TERM CAPELINHA temos um uma relação de 1030066.28 Passageiros por km \n",
      "Na linha 682310 - JD. GUARUJA-TERM. CAPELINHA temos um uma relação de 420686.86 Passageiros por km \n",
      "Na linha 682410 - PQ FERNANDA-TERM CAPELINHA temos um uma relação de 683979.91 Passageiros por km \n",
      "Na linha 682510 - VALO VELHO-TERM CAPELINHA temos um uma relação de 778333.01 Passageiros por km \n",
      "Na linha 682610 - JD STO EDUARDO-TERM CAPELINHA temos um uma relação de 723619.87 Passageiros por km \n",
      "Na linha 683510 - VALO VELHO- TERM CAPELINHA temos um uma relação de 628519.02 Passageiros por km \n",
      "Na linha 683531 - VALO VELHO/TERM.CAPELINHA temos um uma relação de 511944.74 Passageiros por km \n",
      "Na linha 683610 - CAPAO REDONDO-TERM JOAO DIAS temos um uma relação de 782079.65 Passageiros por km \n",
      "Na linha 683710 - JD DAS PALMAS-TERM CAPELINHA temos um uma relação de 900432.26 Passageiros por km \n",
      "Na linha 684010 - JD JACIRA-TERM CAPELINHA temos um uma relação de 1382354.45 Passageiros por km \n",
      "Na linha 691310 - TERM BANDEIRA/TERM VARGINHA temos um uma relação de 1167840.27 Passageiros por km \n",
      "Na linha 691321 - Itaim Bibi temos um uma relação de 89389.54 Passageiros por km \n",
      "Na linha 695D10 - Jd Sta Bárbara - M Jabaquara temos um uma relação de 279419.20 Passageiros por km \n",
      "Na linha 695H10 - JD HERPLIN/METRO PC DA ARVORE temos um uma relação de 442376.73 Passageiros por km \n",
      "Na linha 695T10 - TERM.CAPELINHA/METRO V.MARIANA temos um uma relação de 1588800.70 Passageiros por km \n",
      "Na linha 695V10 - TERM CAPELINHA-METRO ANA ROSA temos um uma relação de 658573.82 Passageiros por km \n",
      "Na linha 695X10 - TERM VARGINHA/METRO JABAQUARA temos um uma relação de 890222.84 Passageiros por km \n",
      "Na linha 695X22 - TERM.VARG./SHOPPING INTERLAGOS temos um uma relação de 104311.36 Passageiros por km \n",
      "Na linha 695Y10 - TERM PARELHEIROS/METRO PC ARVO temos um uma relação de 534345.64 Passageiros por km \n",
      "Na linha 695Y22 - TERM PARELHEIROS/ BORBA GATO temos um uma relação de 1396.20 Passageiros por km \n",
      "Na linha 695Y41 - TERM PARELHEIROS/COL STA MARIA temos um uma relação de 2415.60 Passageiros por km \n",
      "Na linha 696010 - TERM VARGINHA/TERM STO AMARO temos um uma relação de 1069315.89 Passageiros por km \n",
      "Na linha 696021 - ETVITOR MANZINI/TERM VARGINHA temos um uma relação de 58747.69 Passageiros por km \n",
      "Na linha 697010 - TERM GRAJAU/TERM STO AMARO temos um uma relação de 1209569.01 Passageiros por km \n",
      "Na linha 6L0110 - MARSILAC/TERM VARGINHA temos um uma relação de 249067.93 Passageiros por km \n",
      "Na linha 6L0122 - VILA PROGRESSO/TERM VARGINHA temos um uma relação de 33222.03 Passageiros por km \n",
      "Na linha 6L0123 - EMBURA / TERM VARGINHA temos um uma relação de 17191.15 Passageiros por km \n",
      "Na linha 6L0210 - EUCALIPTOS/TERM PARELHEIROS temos um uma relação de 29254.55 Passageiros por km \n",
      "Na linha 6L0310 - CIPO MEIO / TERM PARELHEIROS temos um uma relação de 67242.02 Passageiros por km \n",
      "Na linha 6L0410 - JD ORIENTAL/TERM PARELHEIROS temos um uma relação de 342714.44 Passageiros por km \n",
      "Na linha 6L0441 - JD FONTES/TERM PARELH temos um uma relação de 46156.50 Passageiros por km \n",
      "Na linha 6L0442 - JD ORIENTAL/TERM PARELH temos um uma relação de 42960.15 Passageiros por km \n",
      "Na linha 6L0510 - BARRAGEM/TERM PARELHEIROS temos um uma relação de 447595.53 Passageiros por km \n",
      "Na linha 6L0521 - CID NOVA AMERICA/TERM PARELHEI temos um uma relação de 2921.38 Passageiros por km \n",
      "Na linha 6L0710 - JD SANTA FE/TERM VARGINHA temos um uma relação de 219948.63 Passageiros por km \n",
      "Na linha 6L0810 - PAPAI NOEL/TERM PARELHEIROS temos um uma relação de 510608.48 Passageiros por km \n",
      "Na linha 6L1010 - PQ FLORESTAL/TERM VARGINHA temos um uma relação de 161867.17 Passageiros por km \n",
      "Na linha 6L1041 - MESSIANICA/TERM VARGINHA temos um uma relação de 94248.31 Passageiros por km \n",
      "Na linha 6L1110 - ILHA DO BORORE/TERM STO AMARO temos um uma relação de 245615.81 Passageiros por km \n",
      "Na linha 700110 - VILA GILDA/TERM JD ANGELA temos um uma relação de 1221410.37 Passageiros por km \n",
      "Na linha 700210 - JD ROSA MARIA/HOSP CLINICAS temos um uma relação de 285399.17 Passageiros por km \n",
      "Na linha 700410 - JD JACIRA/TERM GUIDO temos um uma relação de 836252.64 Passageiros por km \n",
      "Na linha 700510 - JD VERA CRUZ/JD ANGELA temos um uma relação de 356378.97 Passageiros por km \n",
      "Na linha 700551 - JD VERA CRUZ/M CAPAO REDONDO temos um uma relação de 1072459.80 Passageiros por km \n",
      "Na linha 700610 - JD HORIZONTE AZUL/JD ANGELA temos um uma relação de 609488.36 Passageiros por km \n",
      "Na linha 700651 - JD HORIZON AZUL/M CAPAO REDON  temos um uma relação de 1236527.94 Passageiros por km \n",
      "Na linha 700910 - JD SAO LOURENÇO/JD ANGELA temos um uma relação de 298619.02 Passageiros por km \n",
      "Na linha 701110 - JD DOS REIS/JD ANGELA temos um uma relação de 529480.42 Passageiros por km \n",
      "Na linha 701131 - JD DOS REIS/JD ANGELA temos um uma relação de 346756.85 Passageiros por km \n",
      "Na linha 701210 - PQ DO LAGO/TERM GUARAPIRANGA temos um uma relação de 603664.89 Passageiros por km \n",
      "Na linha 701310 - PQ ARARIBA/PINHEIROS temos um uma relação de 380952.53 Passageiros por km \n",
      "Na linha 701410 - E T ÁGUA ESPRAIADA/T STO AMARO temos um uma relação de 1266.30 Passageiros por km \n",
      "Na linha 701610 - METRO JABAQUARA/JARDIM ANGELA temos um uma relação de 892446.22 Passageiros por km \n",
      "Na linha 701621 - VILA SANTA LUCIA/TER STO AMARO temos um uma relação de 80354.55 Passageiros por km \n",
      "Na linha 701A10 - PQ EDU CHAVES/METRO V MADALENA temos um uma relação de 476177.84 Passageiros por km \n",
      "Na linha 701U10 - JACANA/BUTANTA USP temos um uma relação de 301822.36 Passageiros por km \n",
      "Na linha 702110 - JD MARACA/TERM JOAO DIAS temos um uma relação de 564071.27 Passageiros por km \n",
      "Na linha 702210 - JD CAIÇARA/TERM SANTO AMARO temos um uma relação de 659928.65 Passageiros por km \n",
      "Na linha 702310 - JD NAKAMURA/TERM SANTO AMARO temos um uma relação de 951308.62 Passageiros por km \n",
      "Na linha 702C10 - JD BONFIGLIOLI/BELEM temos um uma relação de 524471.69 Passageiros por km \n",
      "Na linha 702U10 - BUTANTA USP/PARQUE D. PEDRO II temos um uma relação de 525639.81 Passageiros por km \n",
      "Na linha 704010 - PARAISOPOLIS/PINHEIROS temos um uma relação de 870269.43 Passageiros por km \n",
      "Na linha 704021 - PARAISOPOLIS/PINHEIROS temos um uma relação de 34865.35 Passageiros por km \n",
      "Na linha 704910 - PARQUE DO LAGO/T CAMPO LIMPO temos um uma relação de 741281.02 Passageiros por km \n",
      "Na linha 705010 - JD DAS ROSAS/TERM CAMPO LIMPO temos um uma relação de 624300.58 Passageiros por km \n",
      "Na linha 705110 - JD ROSANA/TERM CAMPO LIMPO temos um uma relação de 1119938.64 Passageiros por km \n",
      "Na linha 705210 - JD HELGA/TERM CAMPO LIMPO temos um uma relação de 1046234.01 Passageiros por km \n",
      "Na linha 705310 - JD MACEDONIA/TERM CAMPO LIMPO temos um uma relação de 2315236.03 Passageiros por km \n",
      "Na linha 705321 - JD MARIA SAMPAIO/T CAMPO LIMPO temos um uma relação de 1731473.84 Passageiros por km \n",
      "Na linha 705322 - JD MARIA SAMPAIO/T CAMPO LIMPO temos um uma relação de 829121.69 Passageiros por km \n",
      "Na linha 705410 - JD MACEDONIA/TERM CAMPO LIMPO temos um uma relação de 965898.04 Passageiros por km \n",
      "Na linha 705510 - JD GUARUJA/TERM CAMPO LIMPO temos um uma relação de 1251628.20 Passageiros por km \n",
      "Na linha 705710 - JD MITSUTANI/TERM CAMPO LIMPO temos um uma relação de 711040.60 Passageiros por km \n",
      "Na linha 705910 - PQ DO ENGENHO/TERM CAMPO LIMPO temos um uma relação de 405415.81 Passageiros por km \n",
      "Na linha 706010 - VALO VELHO/TERM CAMPO LIMPO temos um uma relação de 462513.14 Passageiros por km \n",
      "Na linha 706210 - INOCOOP C LIMPO/T CAMPO LIMPO temos um uma relação de 1429870.64 Passageiros por km \n",
      "Na linha 706231 - CAMPO LIMPO/TERM CAMPO LIMPO temos um uma relação de 850705.02 Passageiros por km \n",
      "Na linha 706241 - METRO CAMPO LIMPO/HORTO DO YPE temos um uma relação de 296042.75 Passageiros por km \n",
      "Na linha 706310 - JD MACEDONIA/TERM CAMPO LIMPO temos um uma relação de 1142260.33 Passageiros por km \n",
      "Na linha 707A10 - JD ANGELA/METRO PÇA DA ARVORE temos um uma relação de 861013.54 Passageiros por km \n",
      "Na linha 707A23 - PIRAPORINHA/MOEMA temos um uma relação de 54067.14 Passageiros por km \n",
      "Na linha 709A10 - E. T. AGUA ESPRAIADA/M. ANA RO temos um uma relação de 7196.85 Passageiros por km \n",
      "Na linha 709A10 - TERM SANTO AMARO/IBIRAPUERA temos um uma relação de 24.07 Passageiros por km \n",
      "Na linha 709G10 - TERM GUARAPIRANGA/ITAIM BIBI temos um uma relação de 251199.02 Passageiros por km \n",
      "Na linha 709M10 - TERMIN STO AMARO/TERM PINHEIRO temos um uma relação de 218882.72 Passageiros por km \n",
      "Na linha 709P10 - TERM GUIDO/PINHEIROS temos um uma relação de 462181.21 Passageiros por km \n",
      "Na linha 714C10 - COHAB EDUCANDARIO/LGO POLVORA temos um uma relação de 98649.19 Passageiros por km \n",
      "Na linha 715M10 - JD MA LUIZA/LGO DA POLVORA temos um uma relação de 733597.39 Passageiros por km \n",
      "Na linha 715M21 - METRO BUTANTA/JD MARIA LUIZA temos um uma relação de 17996.82 Passageiros por km \n",
      "Na linha 718110 - CID.UNIVERSITARIA/T.PR.ISABEL temos um uma relação de 198090.61 Passageiros por km \n",
      "Na linha 719P10 - PINHEIROS/METRO ARMENIA temos um uma relação de 637881.28 Passageiros por km \n",
      "Na linha 719R10 - RIO PEQUENO/METRO BARRA FUNDA temos um uma relação de 500681.47 Passageiros por km \n",
      "Na linha 724510 - MORUMBI SHOPPING/EST LUZ temos um uma relação de 284275.21 Passageiros por km \n",
      "Na linha 726710 - APIACAS/PÇA RAMOS AZEVEDO temos um uma relação de 402397.80 Passageiros por km \n",
      "Na linha 727210 - VILA POMPEIA/P.RAMOS AZEV.CIRC temos um uma relação de 246200.46 Passageiros por km \n",
      "Na linha 728110 - LAPA/P.RAMOS AZEVEDO CIRCULAR temos um uma relação de 294048.71 Passageiros por km \n",
      "Na linha 728210 - PQ CONTINENTAL/M VILA MADALENA temos um uma relação de 90577.97 Passageiros por km \n",
      "Na linha 736G10 - JD INGA/BORBA GATO temos um uma relação de 401418.76 Passageiros por km \n",
      "Na linha 736I10 - JD INGA/STO AMARO temos um uma relação de 991659.65 Passageiros por km \n",
      "Na linha 736I21 - JD INGA/METRO VILA DAS BELEZAS temos um uma relação de 84548.53 Passageiros por km \n",
      "Na linha 737A10 - TERM JD ANGELA - TERM ST AMARO temos um uma relação de 1743877.36 Passageiros por km \n",
      "Na linha 741110 - USP/PCA DA SE temos um uma relação de 127543.70 Passageiros por km \n",
      "Na linha 745810 - JD BOA VISTA/ESTACAO DA LUZ temos um uma relação de 466397.06 Passageiros por km \n",
      "Na linha 745M10 - CAMPO LIMPO/SHOP SP MARKET temos um uma relação de 764899.12 Passageiros por km \n",
      "Na linha 745M21 - COHAB ADVENTISTA/CAMPO LIMPO temos um uma relação de 117752.03 Passageiros por km \n",
      "Na linha 746C10 - JD TABOAO/STO AMARO temos um uma relação de 1375624.68 Passageiros por km \n",
      "Na linha 746H10 - JD JAQUELINE/STO AMARO temos um uma relação de 905669.35 Passageiros por km \n",
      "Na linha 746K10 - PARAISOPOLIS/BROOKLIN temos um uma relação de 259526.75 Passageiros por km \n",
      "Na linha 746P10 - PARAISOPOLIS/STO AMARO temos um uma relação de 1090505.62 Passageiros por km \n",
      "Na linha 746P31 - PARAISOPOLIS/STO AMARO temos um uma relação de 43.29 Passageiros por km \n",
      "Na linha 746R10 - REAL PARQUE/STO AMARO temos um uma relação de 281537.00 Passageiros por km \n",
      "Na linha 746V10 - JD REBOUCAS/STO AMARO temos um uma relação de 352957.82 Passageiros por km \n",
      "Na linha 748A10 - JD DABRIL/LAPA temos um uma relação de 384172.54 Passageiros por km \n",
      "Na linha 748A41 - JD PERI PERI/LAPA temos um uma relação de 118462.86 Passageiros por km \n",
      "Na linha 748R10 - JD JOAO XXIII/METRO BARRA FUND temos um uma relação de 570297.05 Passageiros por km \n",
      "Na linha 754510 - JD JOAO XXIII/PC RAMOS DE AZEV temos um uma relação de 761284.69 Passageiros por km \n",
      "Na linha 754521 - BUTANTA - PÇA RAMOS temos um uma relação de 39290.29 Passageiros por km \n",
      "Na linha 755010 - TERM STO AMARO/M SANTA CECILIA temos um uma relação de 591590.07 Passageiros por km \n",
      "Na linha 756A10 - JD PAULO VI/STO AMARO temos um uma relação de 490851.56 Passageiros por km \n",
      "Na linha 760010 - BERRINI/ESTAÇÃO ARMENIA temos um uma relação de 196941.53 Passageiros por km \n",
      "Na linha 771P10 - JD JOAO XXIII/CENTER NORTE temos um uma relação de 92121.68 Passageiros por km \n",
      "Na linha 772510 - RIO PEQUENO/METRO VILA MADALEN temos um uma relação de 106291.02 Passageiros por km \n",
      "Na linha 775A10 - JD ADALGIZA/METRO VILA MARIANA temos um uma relação de 135509.60 Passageiros por km \n",
      "Na linha 775F10 - JD DAS PALMAS/HOSP CLINICAS temos um uma relação de 339691.51 Passageiros por km \n",
      "Na linha 775F31 - JD DAS PALMAS/PQ DO POVO temos um uma relação de 11579.86 Passageiros por km \n",
      "Na linha 775N10 - RIO PEQUENO/METRO V MARIANA temos um uma relação de 317751.60 Passageiros por km \n",
      "Na linha 775P10 - JD GUARAU/METRO ANA ROSA temos um uma relação de 224902.46 Passageiros por km \n",
      "Na linha 775V10 - RIO PEQUENO/METRO STA CRUZ temos um uma relação de 167322.62 Passageiros por km \n",
      "Na linha 778J10 - JD ARPOADOR/METRO BARRA FUNDA temos um uma relação de 282027.21 Passageiros por km \n",
      "Na linha 778J41 - COHAB RAP.TAVARES-BARRA FUNDA temos um uma relação de 279955.72 Passageiros por km \n",
      "Na linha 778R10 - COH RAP TAVARES/TER PRINC ISAB temos um uma relação de 468155.46 Passageiros por km \n",
      "Na linha 778R21 - COHAB RAPOSO TAVARES/TERM PRIN temos um uma relação de 25048.59 Passageiros por km \n",
      "Na linha 790310 - JD JOAO XXIII/EDUCANDARIO temos um uma relação de 208870.79 Passageiros por km \n",
      "Na linha 800010 - TERM LAPA/PCA RAMOS temos um uma relação de 2318366.10 Passageiros por km \n",
      "Na linha 800110 - VILA PIAUI/TERM LAPA temos um uma relação de 244831.92 Passageiros por km \n",
      "Na linha 800210 - DOMITILA/TERM LAPA temos um uma relação de 286898.29 Passageiros por km \n",
      "Na linha 800310 - V REMEDIOS/TERM LAPA temos um uma relação de 421066.98 Passageiros por km \n",
      "Na linha 800410 - SANTA MONICA/TERM LAPA temos um uma relação de 468044.10 Passageiros por km \n",
      "Na linha 800610 - JD DONARIA/TERM PIRITUBA temos um uma relação de 415342.91 Passageiros por km \n",
      "Na linha 800710 - VILA CLARICE/TERM PIRITUBA temos um uma relação de 705332.63 Passageiros por km \n",
      "Na linha 800810 - STA MONICA/TERMPIRITUBA temos um uma relação de 845090.62 Passageiros por km \n",
      "Na linha 800910 - CID DABRIL III/TERMPIRITUBA temos um uma relação de 147490.05 Passageiros por km \n",
      "Na linha 800931 - CID DABRIL III/TERMPIRITUBA temos um uma relação de 215689.22 Passageiros por km \n",
      "Na linha 801010 - PERUS/PQ RESIDENCIAL LAPA temos um uma relação de 569886.66 Passageiros por km \n",
      "Na linha 801210 - CIDADE UNIVERSIT/METRO BUTANTA temos um uma relação de 199660.64 Passageiros por km \n",
      "Na linha 801310 - MORRO DOCE/LAPA temos um uma relação de 571920.68 Passageiros por km \n",
      "Na linha 801322 - Lapa temos um uma relação de 101601.37 Passageiros por km \n",
      "Na linha 801341 - JD PAINEIRAS/TERM JD BRITANIA temos um uma relação de 278214.92 Passageiros por km \n",
      "Na linha 801410 - MORRO DOCE/PERUS temos um uma relação de 280394.45 Passageiros por km \n",
      "Na linha 801510 - CEM.PERUS/TERM.PIRITUBA temos um uma relação de 524252.83 Passageiros por km \n",
      "Na linha 801521 - CEMITE DE PERUS/EST DE PERUS temos um uma relação de 95344.27 Passageiros por km \n",
      "Na linha 801610 - JD.RINCAO/TERM.PIRITUBA temos um uma relação de 966309.83 Passageiros por km \n",
      "Na linha 801710 - CPTM VILA AURORA/TERM PIRITUBA temos um uma relação de 162477.53 Passageiros por km \n",
      "Na linha 801710 - VOITH/TERMPIRITUBA temos um uma relação de 57782.00 Passageiros por km \n",
      "Na linha 801810 - VILA SONIA/BUTANTA temos um uma relação de 170235.59 Passageiros por km \n",
      "Na linha 801910 - PQ CONTINENTAL/BUTANTA temos um uma relação de 385083.12 Passageiros por km \n",
      "Na linha 802010 - BUTANTA/SHOP MORUMBI temos um uma relação de 71277.26 Passageiros por km \n",
      "Na linha 802110 - JD. MARIA LUIZA/BUTANTA temos um uma relação de 106781.10 Passageiros por km \n",
      "Na linha 802210 - CID UNIV/METRO BUTANTA temos um uma relação de 160568.07 Passageiros por km \n",
      "Na linha 802310 - CDHU RAPOSO TAVARES/BUTANTA temos um uma relação de 82173.55 Passageiros por km \n",
      "Na linha 802510 - JD ROSA MARIA/BUTANTA temos um uma relação de 144846.69 Passageiros por km \n",
      "Na linha 802610 - JD INGA/BUTANTA temos um uma relação de 103624.06 Passageiros por km \n",
      "Na linha 802710 - VILA DALVA/BUTANTA temos um uma relação de 133719.36 Passageiros por km \n",
      "Na linha 803810 - JAGUARE/LAPA temos um uma relação de 402278.38 Passageiros por km \n",
      "Na linha 804010 - SOL NASCENTE/LAPA temos um uma relação de 476591.04 Passageiros por km \n",
      "Na linha 804310 - VILA NOVA ESPERANÇA/LAPA temos um uma relação de 138058.06 Passageiros por km \n",
      "Na linha 804710 - JARAGUA/LAPA temos um uma relação de 406629.51 Passageiros por km \n",
      "Na linha 804731 - VILA AURORA/LAPA temos um uma relação de 16081.35 Passageiros por km \n",
      "Na linha 804741 - JARAGUA/METRO VILA MADALENA temos um uma relação de 106721.00 Passageiros por km \n",
      "Na linha 804751 - RECANTO DOS HUMILDES/LAPA temos um uma relação de 13595.58 Passageiros por km \n",
      "Na linha 805010 - PQ MORRO DOCE/LAPA temos um uma relação de 274817.82 Passageiros por km \n",
      "Na linha 805021 - ANHANGUERA/LAPA temos um uma relação de 15595.23 Passageiros por km \n",
      "Na linha 805031 - PQ MORRO DOCE/LAPA temos um uma relação de 143515.75 Passageiros por km \n",
      "Na linha 805032 - MORRO DOCE/LAPA temos um uma relação de 4640.00 Passageiros por km \n",
      "Na linha 805510 - PERUS/LAPA temos um uma relação de 442928.88 Passageiros por km \n",
      "Na linha 805551 - PERUS/BARRA FUNDA temos um uma relação de 208695.23 Passageiros por km \n",
      "Na linha 805L10 - TERM.PRINC.ISABEL/ACLIMACAO temos um uma relação de 356434.07 Passageiros por km \n",
      "Na linha 806010 - VILA PIAUI/LAPA temos um uma relação de 405823.82 Passageiros por km \n",
      "Na linha 806210 - PQ S DOMINGOS/LAPA temos um uma relação de 68682.57 Passageiros por km \n",
      "Na linha 806510 - VILA CLARICE/LAPA temos um uma relação de 86373.55 Passageiros por km \n",
      "Na linha 807210 - PQ IPE/BUTANTA temos um uma relação de 371927.52 Passageiros por km \n",
      "Na linha 807310 - JD GUARAU/BUTANTA temos um uma relação de 194210.00 Passageiros por km \n",
      "Na linha 807510 - TERM CAMPO LIMPO/METRO BUTANTA temos um uma relação de 815407.25 Passageiros por km \n",
      "Na linha 807710 - JD JOAO XXIII/METRO BUTANTA temos um uma relação de 169960.46 Passageiros por km \n",
      "Na linha 807810 - JD DAS PALMAS/METRO CAMPO LIMP temos um uma relação de 182597.80 Passageiros por km \n",
      "Na linha 807A10 - T CAMPO LIMPO/TERM SANTO AMARO temos um uma relação de 1203939.18 Passageiros por km \n",
      "Na linha 807J10 - TERM CAMPO LIMPO/SHOP MORUMBI temos um uma relação de 377355.18 Passageiros por km \n",
      "Na linha 807M10 - T CAMPO LIMPO/SHOPPING MORUMBI temos um uma relação de 775350.00 Passageiros por km \n",
      "Na linha 807P10 - PARAISOPOLIS/SANT0 AMARO temos um uma relação de 260184.03 Passageiros por km \n",
      "Na linha 809A10 - JD D ABRIL/PINHEIROS temos um uma relação de 415305.34 Passageiros por km \n",
      "Na linha 809D10 - COHAB EDUCANDARIO/PINHEIROS temos um uma relação de 324755.30 Passageiros por km \n",
      "Na linha 809H10 - JD BOA VISTA/LAPA temos um uma relação de 325678.60 Passageiros por km \n",
      "Na linha 809J10 - JD COLOMBO/PINHEIROS temos um uma relação de 89024.00 Passageiros por km \n",
      "Na linha 809L10 - CAMPO LIMPO/LAPA temos um uma relação de 557962.89 Passageiros por km \n",
      "Na linha 809N10 - VILA DALVA/LAPA temos um uma relação de 160075.14 Passageiros por km \n",
      "Na linha 809P10 - TERM CAMPO LIMPO/PINHEIROS temos um uma relação de 1491811.96 Passageiros por km \n",
      "Na linha 809R10 - RIO PEQUENO/PINHEIROS temos um uma relação de 173391.21 Passageiros por km \n",
      "Na linha 809T10 - RAPOSO TAVARES/LAPA temos um uma relação de 174218.60 Passageiros por km \n",
      "Na linha 809U10 - CID UNIVERSITARIA/M BARRA FUN  temos um uma relação de 226142.74 Passageiros por km \n",
      "Na linha 809U21 - M BARRA FUNDA/M VILA MADALENA temos um uma relação de 1010518.82 Passageiros por km \n",
      "Na linha 809V10 - VILA GOMES/PAULISTA temos um uma relação de 215703.63 Passageiros por km \n",
      "Na linha 810010 - TERMPIRITUBA/TERM LAPA temos um uma relação de 848915.73 Passageiros por km \n",
      "Na linha 817C10 - LAPA/H.CLINICAS CIRCULAR temos um uma relação de 612782.02 Passageiros por km \n",
      "Na linha 819410 - PERUS/CACHOEIRINHA temos um uma relação de 366160.87 Passageiros por km \n",
      "Na linha 819910 - PIRITUBA/CVN CACHOEIRINHA temos um uma relação de 1066992.12 Passageiros por km \n",
      "Na linha 819A10 - VILA AURORA/JD PRIMAVERA temos um uma relação de 1151795.53 Passageiros por km \n",
      "Na linha 819R10 - PERUS/TERM PRINC ISABEL temos um uma relação de 430574.24 Passageiros por km \n",
      "Na linha 820010 - TERM PIRITUBA/TERMPIRITUBA temos um uma relação de 440889.40 Passageiros por km \n",
      "Na linha 821510 - JD PAULISTANO/PCA DO CORREIO temos um uma relação de 319564.42 Passageiros por km \n",
      "Na linha 825210 - LAPA/PCA RAMOS DE AZEVEDO temos um uma relação de 27185.21 Passageiros por km \n",
      "Na linha 830010 - TERM PIRITUBA/TERM LAPA temos um uma relação de 843375.55 Passageiros por km \n",
      "Na linha 831910 - PQ CONTINENTAL/PCA RAMOS AZEVE temos um uma relação de 209467.42 Passageiros por km \n",
      "Na linha 831921 - SHOP VILA LOBOS/PQ CONTINENAL temos um uma relação de 2576.61 Passageiros por km \n",
      "Na linha 840010 - TERM PIRITUBA/PCA RAMOS temos um uma relação de 1381138.46 Passageiros por km \n",
      "Na linha 846M10 - JD MARISA/SHOP IBIRAPUERA temos um uma relação de 150639.75 Passageiros por km \n",
      "Na linha 847J10 - CITY JARAGUA/JAGUARE temos um uma relação de 215585.13 Passageiros por km \n",
      "Na linha 847P10 - TERM PIRITUBA/ITAIM BIBI temos um uma relação de 1011444.91 Passageiros por km \n",
      "Na linha 847P42 - VILA BRASILANDIA/ITAIM BIBI temos um uma relação de 167435.35 Passageiros por km \n",
      "Na linha 848L10 - RECANTO DOS HUMILDES/TERM PRIN temos um uma relação de 283369.96 Passageiros por km \n",
      "Na linha 850010 - TERM PIRITUBA/BARRA FUNDA temos um uma relação de 1506611.33 Passageiros por km \n",
      "Na linha 852810 - JD GUARANI/PCA DO CORREIO temos um uma relação de 490159.31 Passageiros por km \n",
      "Na linha 853810 - VILA IARA/PAISSANDU temos um uma relação de 83428.75 Passageiros por km \n",
      "Na linha 854210 - BRASILANDIA/PCA DO CORREIO temos um uma relação de 437870.42 Passageiros por km \n",
      "Na linha 854410 - CID DABRIL 3 GLEBA/PC RAMOS AZ temos um uma relação de 127608.50 Passageiros por km \n",
      "Na linha 854510 - PENTEADO/METRO BARRA FUNDA temos um uma relação de 297759.78 Passageiros por km \n",
      "Na linha 854810 - JD DOS CUNHAS/PCA DO CORREIO temos um uma relação de 250534.91 Passageiros por km \n",
      "Na linha 854910 - TAIPAS/PCA DO CORREIO temos um uma relação de 400974.74 Passageiros por km \n",
      "Na linha 856R10 - LAPA/SOCORRO temos um uma relação de 824834.69 Passageiros por km \n",
      "Na linha 857A10 - T CAMPO LIMPO/METRO SANTA CRUZ temos um uma relação de 528274.02 Passageiros por km \n",
      "Na linha 857C10 - T CAMPO LIMPO/METRO CONCEIÇAO temos um uma relação de 468220.94 Passageiros por km \n",
      "Na linha 857P10 - TERM CAMPO LIMPO/METRO PARAISO temos um uma relação de 1097045.27 Passageiros por km \n",
      "Na linha 857P21 - CAMPO LIMPO/PARAISO temos um uma relação de 11673.38 Passageiros por km \n",
      "Na linha 857R10 - TERM CAMPO LIMPO/ACLIMACAO temos um uma relação de 811608.80 Passageiros por km \n",
      "Na linha 857R41 - E HEBRAICA REBOUÇAS/M PARAISO temos um uma relação de 112059.53 Passageiros por km \n",
      "Na linha 859410 - CID DABRIL/PCA RAMOS AZEVEDO temos um uma relação de 665200.57 Passageiros por km \n",
      "Na linha 859421 - CID PIRITUBA/PCA RAMOS AZEVEDO temos um uma relação de 13130.76 Passageiros por km \n",
      "Na linha 859441 - COHAB PEDRA VERDE/PCA RAMOS AZ temos um uma relação de 20639.59 Passageiros por km \n",
      "Na linha 860010 - TERM PIRITUBA/LGO PAISSANDU temos um uma relação de 769615.08 Passageiros por km \n",
      "Na linha 860022 - TERM PIRITUBA/LGO DO PAISSANDU temos um uma relação de 58873.77 Passageiros por km \n",
      "Na linha 860510 - TERM CAMPO LIMPO/TERM BANDEIRA temos um uma relação de 859349.37 Passageiros por km \n",
      "Na linha 861010 - JD PAULO VI/TERM BANDEIRA  temos um uma relação de 327958.17 Passageiros por km \n",
      "Na linha 861510 - P.LAPA/PARQUE D. PEDRO II temos um uma relação de 721483.57 Passageiros por km \n",
      "Na linha 862210 - MORRO DOCE/PCA RAMOS DE AZEVED temos um uma relação de 524276.58 Passageiros por km \n",
      "Na linha 862231 - MORRO DOCE/PCA RAMOS DE AZEVED temos um uma relação de 12198.60 Passageiros por km \n",
      "Na linha 867710 - JD LIBANO/PCA RAMOS DE AZEVEDO temos um uma relação de 264209.83 Passageiros por km \n",
      "Na linha 868610 - MANGALOT/PCA RAMOS AZEVEDO temos um uma relação de 342281.92 Passageiros por km \n",
      "Na linha 869610 - JARAGUA/PCA RAMOS AZEVEDO temos um uma relação de 139967.08 Passageiros por km \n",
      "Na linha 869641 - JARAGUA/PCA RAMOS AZEVEDO temos um uma relação de 146359.50 Passageiros por km \n",
      "Na linha 870010 - T CAMPO LIMPO/PCA R D AZEVEDO  temos um uma relação de 2109208.05 Passageiros por km \n",
      "Na linha 870021 - LGO DO TABOAO/P RAMOS DE AZEVE temos um uma relação de 36527.61 Passageiros por km \n",
      "Na linha 870022 - H DAS CLINICAS/TER CAMPO LIMPO temos um uma relação de 15165.88 Passageiros por km \n",
      "Na linha 870023 - PÇA RAMOS DE AZEVEDO/BUTANTA temos um uma relação de 48130.26 Passageiros por km \n",
      "Na linha 870510 - SHOP CONTINENTAL/ANHANGABAU temos um uma relação de 925089.96 Passageiros por km \n",
      "Na linha 870710 - RIO PEQUENO/TERM PRINC ISABEL temos um uma relação de 435042.97 Passageiros por km \n",
      "Na linha 874C10 - PQ CONTINENTAL/METR V MARIANA temos um uma relação de 183326.14 Passageiros por km \n",
      "Na linha 874T10 - IPIRANGA/LAPA temos um uma relação de 369571.97 Passageiros por km \n",
      "Na linha 875A10 - AEROPORTO/PERDIZES temos um uma relação de 341171.10 Passageiros por km \n",
      "Na linha 875C10 - LAPA/METRO STA CRUZ temos um uma relação de 1387553.47 Passageiros por km \n",
      "Na linha 875H10 - LAPA/METRO VILA MARIANA temos um uma relação de 867080.87 Passageiros por km \n",
      "Na linha 875P10 - M. BARRA FUNDA/M. ANA ROSA temos um uma relação de 542924.39 Passageiros por km \n",
      "Na linha 877T10 - VILA ANASTACIO/METRO PARAISO temos um uma relação de 339101.52 Passageiros por km \n",
      "Na linha 888P10 - PERUS/COHAB TAIPAS temos um uma relação de 551882.12 Passageiros por km \n",
      "Na linha 900210 - JD PERY ALTO/TERM V N CACHOEIR temos um uma relação de 1675388.28 Passageiros por km \n",
      "Na linha 900410 - JD ELISA MARIA/TERM V N CACHOE temos um uma relação de 3173406.07 Passageiros por km \n",
      "Na linha 900510 - JD PRINCESA/TERM V N CACHOEIR temos um uma relação de 2127983.93 Passageiros por km \n",
      "Na linha 900541 - JD.VISTA ALEGRE/T.CACHOEIRINHA temos um uma relação de 132083.20 Passageiros por km \n",
      "Na linha 900542 - SITIO D FRANCOS/T V N CACHOEIR temos um uma relação de 47517.48 Passageiros por km \n",
      "Na linha 900610 - VILA PENTEADO/TERM V N CACHOEI temos um uma relação de 1302383.89 Passageiros por km \n",
      "Na linha 900810 - PQ TAIPAS/TERM V N CACHOEIR temos um uma relação de 1200442.27 Passageiros por km \n",
      "Na linha 900821 - Term. Nova Cachoeirinha temos um uma relação de 7273.87 Passageiros por km \n",
      "Na linha 900841 - ESTANCIA JARAGUA/TERM V N CACH temos um uma relação de 26323.74 Passageiros por km \n",
      "Na linha 900910 - COHAB BRASILANDIA/TERM V N CAC temos um uma relação de 1136592.52 Passageiros por km \n",
      "Na linha 901110 - CITY JARAGUA/TERM V N CACHOEIR temos um uma relação de 751996.98 Passageiros por km \n",
      "Na linha 901121 - ESTACAO JARAGUA/CITY JARAGUA temos um uma relação de 359783.83 Passageiros por km \n",
      "Na linha 901210 - ITABERABA/TERM LAPA temos um uma relação de 201381.49 Passageiros por km \n",
      "Na linha 901410 - MORRO GRANDE/TERMINAL LAPA temos um uma relação de 717021.92 Passageiros por km \n",
      "Na linha 901442 - BNH PORTUGUESA/TERMINAL LAPA temos um uma relação de 18654.55 Passageiros por km \n",
      "Na linha 901510 - VILA ZATT/TERM PIRITUBA temos um uma relação de 1503777.98 Passageiros por km \n",
      "Na linha 901810 - VILA MIRANTE/TERM PIRITUBA temos um uma relação de 1125800.19 Passageiros por km \n",
      "Na linha 901910 - JD PAULISTA/TERM PIRITUBA temos um uma relação de 1235046.88 Passageiros por km \n",
      "Na linha 902010 - VILA MIRANTE/TERM PIRITUBA temos um uma relação de 983794.51 Passageiros por km \n",
      "Na linha 902310 - PQUE DE TAIPAS/TERM PIRITUBA temos um uma relação de 989710.72 Passageiros por km \n",
      "Na linha 903210 - JD DAMASCENO/LAPA temos um uma relação de 764919.81 Passageiros por km \n",
      "Na linha 903221 - JD DAMASCENO/TERM CACHOEIRINHA temos um uma relação de 77597.31 Passageiros por km \n",
      "Na linha 904710 - JD PAULISTANO/LAPA temos um uma relação de 880905.64 Passageiros por km \n",
      "Na linha 905010 - TERM LAPA / ITAIM BIBI temos um uma relação de 237353.79 Passageiros por km \n",
      "Na linha 905110 - LAPA / PINHEIROS temos um uma relação de 375362.76 Passageiros por km \n",
      "Na linha 907010 - JD PAINEIRAS/TERM CASA VERDE temos um uma relação de 61287.30 Passageiros por km \n",
      "Na linha 908T10 - TERM PQ D PEDRO II/BUTANTA temos um uma relação de 374039.92 Passageiros por km \n",
      "Na linha 909010 - PQ TIETE/TERM CASA VERDE temos um uma relação de 606557.92 Passageiros por km \n",
      "Na linha 909T10 - TER PINHEIRO/ TER P Q D PEDRO temos um uma relação de 305122.79 Passageiros por km \n",
      "Na linha 916210 - JD.ALMANARA/RIO BRANCO temos um uma relação de 75878.41 Passageiros por km \n",
      "Na linha 916610 - JD SANTA CRUZ/PÇA DO CORREIO temos um uma relação de 134463.79 Passageiros por km \n",
      "Na linha 917H10 - MERCADO PIRITUBA/VLA MARIANA temos um uma relação de 912937.22 Passageiros por km \n",
      "Na linha 917M10 - MORRO GRANDE/METRO ANA ROSA temos um uma relação de 399384.26 Passageiros por km \n",
      "Na linha 917M31 - MORRO GRANDE/METRO ANA ROSA temos um uma relação de 35966.21 Passageiros por km \n",
      "Na linha 918110 - VILA TEREZINHA/LAPA temos um uma relação de 1470803.01 Passageiros por km \n",
      "Na linha 918810 - CAPELA DA LAGOA/LAPA temos um uma relação de 692145.02 Passageiros por km \n",
      "Na linha 918842 - CAPELA DA LAGOA/TERM PIRITUBA temos um uma relação de 17086.66 Passageiros por km \n",
      "Na linha 919110 - JD ELIS MARIA/BOM RETIRO temos um uma relação de 1158287.19 Passageiros por km \n",
      "Na linha 919121 - BARRA FUNDA/BOM RETIRO temos um uma relação de 98512.09 Passageiros por km \n",
      "Na linha 930010 - TERM.CASA VERDE-PQ.D.PEDRO II temos um uma relação de 675675.42 Passageiros por km \n",
      "Na linha 930110 - TERM CASA VERDE/PAISSANDU temos um uma relação de 731433.02 Passageiros por km \n",
      "Na linha 930P10 - TERM PQ D PEDRO II/PINHEIROS temos um uma relação de 1068920.42 Passageiros por km \n",
      "Na linha 935410 - N SRA FATIMA/TERM CORREIO temos um uma relação de 430834.05 Passageiros por km \n",
      "Na linha 938C10 - COHAB TAIPAS/TERM PRINC ISABEL temos um uma relação de 296120.97 Passageiros por km \n",
      "Na linha 938L10 - TTVN CACHOEIRINHA/LAPA temos um uma relação de 1387536.66 Passageiros por km \n",
      "Na linha 938P10 - VILA PENTEADO/METRO B FUNDA temos um uma relação de 597466.61 Passageiros por km \n",
      "Na linha 938P21 - VILA PENTEADO/METRO ANA ROSA temos um uma relação de 10646.30 Passageiros por km \n",
      "Na linha 938V10 - JD VISTA ALEGRE/METRO BARRA FU temos um uma relação de 929518.20 Passageiros por km \n",
      "Na linha 948A10 - VL ZATTI/TERM PIRITUBA temos um uma relação de 326693.80 Passageiros por km \n",
      "Na linha 950010 - TERM CACHOEIRINHA/PAISSANDU temos um uma relação de 949683.08 Passageiros por km \n",
      "Na linha 950110 - TERM  CACHOEIRINHA/PAISSANDU temos um uma relação de 1693307.27 Passageiros por km \n",
      "Na linha 957T10 - COHAB TAIPAS/ITAIM BIBI temos um uma relação de 262099.54 Passageiros por km \n",
      "Na linha 958P10 - JD NARDINI/COHAB TAIPAS temos um uma relação de 209834.65 Passageiros por km \n",
      "Na linha 965310 - PEDRA BRANCA/LGO DO PAISSANDU temos um uma relação de 707934.27 Passageiros por km \n",
      "Na linha 967A10 - IMIRIM/PINHEIROS temos um uma relação de 312508.65 Passageiros por km \n",
      "Na linha 970110 - ANHEMBI/METRO BARRA FUNDA temos um uma relação de 141321.62 Passageiros por km \n",
      "Na linha 971710 - COHAB BRASILANDIA/SANTANA temos um uma relação de 427465.93 Passageiros por km \n",
      "Na linha 971A10 - JD PRIMAVERA/METRO SANTANA temos um uma relação de 515879.51 Passageiros por km \n",
      "Na linha 971C10 - COHAB/METRO SANTANA temos um uma relação de 556851.90 Passageiros por km \n",
      "Na linha 971D10 - JD DAMASCENO/CENTER NORTE temos um uma relação de 517242.48 Passageiros por km \n",
      "Na linha 971M10 - VILA PENTEADO/METRO SANTANA temos um uma relação de 709239.14 Passageiros por km \n",
      "Na linha 971R10 - ESTACAO JARAGUA/METRO SANTANA temos um uma relação de 1341203.25 Passageiros por km \n",
      "Na linha 971R21 - JD DAMASCENO/METRO SANTANA temos um uma relação de 40334.89 Passageiros por km \n",
      "Na linha 971R42 - CDHU VOITH/METRO SANTANA temos um uma relação de 155588.48 Passageiros por km \n",
      "Na linha 971R51 - CHICA LUISA/METRO SANTANA temos um uma relação de 15948.00 Passageiros por km \n",
      "Na linha 971T10 - VILA SANTA MARIA/METRO SANTANA temos um uma relação de 899167.81 Passageiros por km \n",
      "Na linha 971V10 - JD VISTA ALEGRE/CENTER NORTE temos um uma relação de 462284.30 Passageiros por km \n",
      "Na linha 971X10 - TERM CACHOEIRINHA/METRO SANTAN temos um uma relação de 2191722.32 Passageiros por km \n",
      "Na linha 975A10 - VILA BRASILANDIA/METRO ANA ROS temos um uma relação de 327888.62 Passageiros por km \n",
      "Na linha 978410 - JD DOS FRANCOS/BARRA FUNDA temos um uma relação de 1195166.88 Passageiros por km \n",
      "Na linha 978510 - TEREZINHA/BARRA FUNDA temos um uma relação de 717374.73 Passageiros por km \n",
      "Na linha 978551 - JD CAROMBE/TTVN CACHOEIRINHA temos um uma relação de 21482.96 Passageiros por km \n",
      "Na linha 978910 - JD DOS GUEDES/BARRA FUNDA temos um uma relação de 981428.50 Passageiros por km \n",
      "Na linha 978A10 - TTVN CACHOEIRINHA/MBARRA FUNDA temos um uma relação de 1794586.30 Passageiros por km \n",
      "Na linha 978J10 - VOITH/PCA PRINC ISABEL temos um uma relação de 297004.07 Passageiros por km \n",
      "Na linha 978L10 - TERM CACHOEIRNHA/TERM P ISABEL temos um uma relação de 552781.16 Passageiros por km \n",
      "Na linha 978T10 - JD GUARANI/METRO BARRA FUNDA temos um uma relação de 1752411.50 Passageiros por km \n",
      "Na linha N10111 - TERM LAPA/TERM PQ D PEDRO II temos um uma relação de 12439.65 Passageiros por km \n",
      "Na linha N10211 - TERM LAPA/TERM PQ D PEDRO II temos um uma relação de 38966.75 Passageiros por km \n",
      "Na linha N10311 - TERM PIRITUBA/TERM LAPA temos um uma relação de 10350.13 Passageiros por km \n",
      "Na linha N10411 - TERM PIRITUBA/TERM LAPA temos um uma relação de 35054.69 Passageiros por km \n",
      "Na linha N10511 - TERM CACHOEIRINHA/TERM LAPA temos um uma relação de 27767.16 Passageiros por km \n",
      "Na linha N10611 - T PQ D PEDRO /MET BARRA FUNDA temos um uma relação de 17561.64 Passageiros por km \n",
      "Na linha N13111 - TERM LAPA/VILA PIAUI temos um uma relação de 1571.77 Passageiros por km \n",
      "Na linha N13211 - TERM PIRITUBA/PQ SAO DOMINGOS temos um uma relação de 1993.48 Passageiros por km \n",
      "Na linha N13311 - TERM PIRITUBA/CID D ABRIL 3ª G temos um uma relação de 1843.07 Passageiros por km \n",
      "Na linha N13411 - TERM CACHOEIRINHA/TAIPAS temos um uma relação de 6851.26 Passageiros por km \n",
      "Na linha N13511 - TERM PIRITUBA/JD DONARIA temos um uma relação de 5851.77 Passageiros por km \n",
      "Na linha N13611 - TERM LAPA/MORRO DOCE temos um uma relação de 2302.02 Passageiros por km \n",
      "Na linha N13711 - TERM PIRITUBA/PERUS temos um uma relação de 3143.69 Passageiros por km \n",
      "Na linha N13811 - TERM CACHOEIRINHA/JD PRINCESA temos um uma relação de 7241.84 Passageiros por km \n",
      "Na linha N13911 - TERM PIRITUBA/JD PAULISTANO temos um uma relação de 8773.75 Passageiros por km \n",
      "Na linha N14011 - TERM PIRITUBA/VILA MIRANTE temos um uma relação de 6265.96 Passageiros por km \n",
      "Na linha N14111 - TERM CACHOEIRINHA/JD CAROMBE temos um uma relação de 4090.84 Passageiros por km \n",
      "Na linha N14211 - TERM PIRITUBA/TERM CASA VERDE temos um uma relação de 1218.34 Passageiros por km \n",
      "Na linha N14311 - METRO BARRA FUNDA/MORRO GRANDE temos um uma relação de 2284.10 Passageiros por km \n",
      "Na linha N20111 - TERM PQ D PEDRO/METRO TUCURUVI temos um uma relação de 9953.84 Passageiros por km \n",
      "Na linha N20211 - MET SANTANA/TERM PINHEIROS temos um uma relação de 10851.31 Passageiros por km \n",
      "Na linha N20311 - MET TUCURUVI/TERM PQ D PEDRO  temos um uma relação de 26571.30 Passageiros por km \n",
      "Na linha N20411 - METRO TUCURUVI/TERM PQ D PEDRO temos um uma relação de 6297.14 Passageiros por km \n",
      "Na linha N20511 - TERM CACHOEIRINHA/TERM PINHEIR temos um uma relação de 13379.96 Passageiros por km \n",
      "Na linha N20611 - TERM CASA VERDE/METRO SANTANA temos um uma relação de 2777.87 Passageiros por km \n",
      "Na linha N20711 - TERM CASA VERDE/TERM PQ D PEDR temos um uma relação de 9586.86 Passageiros por km \n",
      "Na linha N20911 - TERM CACHOEIRINHA/TERM SANTANA temos um uma relação de 17415.85 Passageiros por km \n",
      "Na linha N23111 - TERM CACHOEIRINHA/PEDRA BRANCA temos um uma relação de 2290.03 Passageiros por km \n",
      "Na linha N23211 - METRO TUCURUVI/PQ NOVO MUNDO temos um uma relação de 1367.82 Passageiros por km \n",
      "Na linha N23311 - METRO SANTANA/VILA SABRINA temos um uma relação de 1777.08 Passageiros por km \n",
      "Na linha N23411 - METRO TUCURUVI/LARGO DO PERI temos um uma relação de 1029.75 Passageiros por km \n",
      "Na linha N23511 - METRO SANTANA/PEDRA BRANCA temos um uma relação de 2628.96 Passageiros por km \n",
      "Na linha N23611 - METRO SANTANA/JARDIM ANTARTICA temos um uma relação de 4896.92 Passageiros por km \n",
      "Na linha N23711 - METRO TUCURUVI/EDU CHAVES temos um uma relação de 3085.95 Passageiros por km \n",
      "Na linha N23811 - METRO SANTANA/CEM PQ DOS PINHE temos um uma relação de 3854.47 Passageiros por km \n",
      "Na linha N23911 - METR TUCURUVI/VILA NOVA GALVAO temos um uma relação de 2147.59 Passageiros por km \n",
      "Na linha N24011 - METRO SANTANA/CACHOEIRA temos um uma relação de 2941.94 Passageiros por km \n",
      "Na linha N24111 - METRO SANTANA/VILA ALBERTINA temos um uma relação de 4706.62 Passageiros por km \n",
      "Na linha N24211 - METRO SANTANA/JD CAMPO LIMPO temos um uma relação de 2237.80 Passageiros por km \n",
      "Na linha N24311 - METRO SANTANA/JARDIM BRASIL temos um uma relação de 3812.13 Passageiros por km \n",
      "Na linha N24411 - METRO TUCURUVI/JD FLOR DE MAIO temos um uma relação de 3676.07 Passageiros por km \n",
      "Na linha N24511 - METRO SANTANA/JARDIM PERY ALTO temos um uma relação de 4102.96 Passageiros por km \n",
      "Na linha N30111 - TERM A E CARVALHO/T P D PEDRO  temos um uma relação de 24447.77 Passageiros por km \n",
      "Na linha N30211 - T A E CARVALHO/T PQ D PEDRO II temos um uma relação de 10506.91 Passageiros por km \n",
      "Na linha N30311 - T A E CARVALHO/TERM ARICANDUVA temos um uma relação de 3322.15 Passageiros por km \n",
      "Na linha N30411 - TER SAO MIGUEL/TERM ARICANDUVA temos um uma relação de 8274.52 Passageiros por km \n",
      "Na linha N30511 - TERM SAO MIGUEL/CPTM GUAIANAZE temos um uma relação de 6401.44 Passageiros por km \n",
      "Na linha N30611 - TERM SAO MIGUEL/METRO ITAQUERA temos um uma relação de 10067.01 Passageiros por km \n",
      "Na linha N30711 - TERMP Q D PEDRO II/TERM PINHEI temos um uma relação de 37226.84 Passageiros por km \n",
      "Na linha N30811 - METRO ITAQUERA/TERM PQ D PEDRO temos um uma relação de 30409.88 Passageiros por km \n",
      "Na linha N33111 - TERM A E CARVALHO/OLIVEIRINHA temos um uma relação de 3089.00 Passageiros por km \n",
      "Na linha N33211 - TERM A E CARVALHO/VILA CISPER temos um uma relação de 975.14 Passageiros por km \n",
      "Na linha N33311 - TERM SAO MIGUEL/CIDADE KEMEL temos um uma relação de 2608.97 Passageiros por km \n",
      "Na linha N33411 - T A E CARVALHO/CPTM GUAIANAZES temos um uma relação de 2910.68 Passageiros por km \n",
      "Na linha N33511 - TERM PENHA/ERMELINO MATARAZZO temos um uma relação de 922.39 Passageiros por km \n",
      "Na linha N33611 - T SAO MIGUEL/JD CARMARGO VELHO temos um uma relação de 1312.84 Passageiros por km \n",
      "Na linha N33711 - T SAO MIGUEL/JD CAMARGO VELHO temos um uma relação de 1585.65 Passageiros por km \n",
      "Na linha N33911 - METRO ITAQUERA/ARTUR ALVIM temos um uma relação de 1063.73 Passageiros por km \n",
      "Na linha N34011 - METRO ITQUERA/JD SANTO ANTONIO temos um uma relação de 2857.15 Passageiros por km \n",
      "Na linha N34111 - TERM SAO MIGUEL/VILA CISPER temos um uma relação de 1282.92 Passageiros por km \n",
      "Na linha N34211 - TERM PENHA/JARDIM DANFER temos um uma relação de 958.05 Passageiros por km \n",
      "Na linha N34311 - T A E CARVALHO/METRO ITAQUERA temos um uma relação de 2056.06 Passageiros por km \n",
      "Na linha N34411 - TERM PENHA /VILA CISPER temos um uma relação de 1295.14 Passageiros por km \n",
      "Na linha N40111 - TERM VL CARRAO/T PQ D PEDRO II temos um uma relação de 10578.69 Passageiros por km \n",
      "Na linha N40211 - METRO ITAQUERA/TERM VL CARRAO temos um uma relação de 5672.48 Passageiros por km \n",
      "Na linha N40311 - T CID TIRADENTES/METRO ITAQUER temos um uma relação de 21552.77 Passageiros por km \n",
      "Na linha N40411 - TERM SAO MATEUS/TERM PENHA temos um uma relação de 13498.80 Passageiros por km \n",
      "Na linha N40511 - TERM V CARRAO/METRO ITAQUERA temos um uma relação de 11294.75 Passageiros por km \n",
      "Na linha N40611 - TERM CID TIRADENTES/T S MATEUS temos um uma relação de 16477.17 Passageiros por km \n",
      "Na linha N40711 - TERM V CARRAO/METRO BELEM temos um uma relação de 5038.46 Passageiros por km \n",
      "Na linha N43111 - TER SAO MATEUS/JD DA CONQUISTA temos um uma relação de 3211.95 Passageiros por km \n",
      "Na linha N43211 - TERM SAO MATEUS/JD STO ANDRE temos um uma relação de 5960.75 Passageiros por km \n",
      "Na linha N43311 - TERM V CARRAO/METRO BELEM temos um uma relação de 1699.45 Passageiros por km \n",
      "Na linha N43411 - TERM V CARRAO/JD IV CENTENARIO temos um uma relação de 970.89 Passageiros por km \n",
      "Na linha N43511 - T CID TIRANDENTES/METALURGICOS temos um uma relação de 8054.41 Passageiros por km \n",
      "Na linha N43611 - TE CID TIRADENTES/BARRO BRANCO temos um uma relação de 11424.67 Passageiros por km \n",
      "Na linha N43711 - EST GUAIANAZES/T CID TIRADENTE temos um uma relação de 3728.72 Passageiros por km \n",
      "Na linha N43811 - M ITAQUERA/HOSP STA MARCELINA temos um uma relação de 3120.44 Passageiros por km \n",
      "Na linha N43911 - M ITAQUERA/COHAB FAZ DO CARMO temos um uma relação de 4825.55 Passageiros por km \n",
      "Na linha N44011 - TERM V CARRAO/SAVOY DALILA temos um uma relação de 872.03 Passageiros por km \n",
      "Na linha N44111 - TERM CID TIRANDESTES/VL YOLAND temos um uma relação de 4423.86 Passageiros por km \n",
      "Na linha N50111 - TERM S MATEUS/T PQ D PEDRO II temos um uma relação de 13298.85 Passageiros por km \n",
      "Na linha N50211 - TERM SACOMA/TERM PQ D PEDRO II temos um uma relação de 13797.88 Passageiros por km \n",
      "Na linha N50311 - TER SAO MATEUS/TERM PQ D PEDRO temos um uma relação de 10722.17 Passageiros por km \n",
      "Na linha N50411 - TERM SACOMA/TERM PQ D PEDRO II temos um uma relação de 7491.97 Passageiros por km \n",
      "Na linha N50511 - TERM SACOMA/TERM PINHEIROS temos um uma relação de 9188.27 Passageiros por km \n",
      "Na linha N50611 - TERM SACOMA/METRO VL MADALENA temos um uma relação de 11715.68 Passageiros por km \n",
      "Na linha N50711 - TERM SACOMA/METRO SANTANA temos um uma relação de 2190.68 Passageiros por km \n",
      "Na linha N50811 - TERM SACOMA/TERM PQ D PEDRO II temos um uma relação de 5243.45 Passageiros por km \n",
      "Na linha N53111 - T SAPOPEMBA/TEOTONIO T SACOMA temos um uma relação de 1226.98 Passageiros por km \n",
      "Na linha N53211 - T SAPOPEMBA/TEOTONIO H S MATEU temos um uma relação de 2783.32 Passageiros por km \n",
      "Na linha N53311 - TERM SACOMA/JARDIM PLANALTO temos um uma relação de 1314.94 Passageiros por km \n",
      "Na linha N53411 - TERM SACOMA/VILA ARAPUA temos um uma relação de 6348.54 Passageiros por km \n",
      "Na linha N53511 - TERM SACOMA/JARDIM CELESTE temos um uma relação de 3120.01 Passageiros por km \n",
      "Na linha N53611 - TERM SACOMA/JARDIM ITAPOLIS temos um uma relação de 1944.35 Passageiros por km \n",
      "Na linha N53711 - METRO VL MARIANA/VILA PRUDENTE temos um uma relação de 694.54 Passageiros por km \n",
      "Na linha N53811 - TERM SACOMA/JARDIM CELESTE temos um uma relação de 767.70 Passageiros por km \n",
      "Na linha N53911 - TERM SACOMA/HOSP HELIOPOLIS temos um uma relação de 13738.96 Passageiros por km \n",
      "Na linha N54011 - TERM SAPOP TEOT VILE/JS SAO RO temos um uma relação de 665.52 Passageiros por km \n",
      "Na linha N60111 - TERM GRAJAU/TERM PQ D PEDRO II temos um uma relação de 13407.88 Passageiros por km \n",
      "Na linha N60211 - TERM GRAJAU/TERM SANTO AMARO temos um uma relação de 41716.55 Passageiros por km \n",
      "Na linha N60311 - TERM PINHEIROS/METRO JABAQUARA temos um uma relação de 17392.82 Passageiros por km \n",
      "Na linha N60411 - MET JABAQUARA/T PQ D PEDRO II temos um uma relação de 21600.69 Passageiros por km \n",
      "Na linha N63111 - TERM GRAJAU/TERM STO AMARO temos um uma relação de 4169.77 Passageiros por km \n",
      "Na linha N63211 - TERM GRAJAU/TERM STO AMARO temos um uma relação de 9435.74 Passageiros por km \n",
      "Na linha N63311 - MET JABAQUARA/MORUMBI SHOPING temos um uma relação de 1227.23 Passageiros por km \n",
      "Na linha N63411 - TERM SANTO AMARO/JARDIM LUSO temos um uma relação de 5073.37 Passageiros por km \n",
      "Na linha N63511 - TERM GRAJAU/JARDIM GAIVOTAS temos um uma relação de 26551.47 Passageiros por km \n",
      "Na linha N63611 - TERM GRAJAU/JARDIM NORONHA temos um uma relação de 5639.01 Passageiros por km \n",
      "Na linha N63711 - METRO JABAQUARA/JARDIM MIRIAM temos um uma relação de 3545.79 Passageiros por km \n",
      "Na linha N63811 - TERM GRAJAU/UNISA temos um uma relação de 3528.75 Passageiros por km \n",
      "Na linha N63911 - TERM GRAJAU/VARGEM GRANDE temos um uma relação de 8273.79 Passageiros por km \n",
      "Na linha N64011 - TERM SANTO AMARO/ELDORADO temos um uma relação de 4392.93 Passageiros por km \n",
      "Na linha N70111 - TERM STO AMARO/T PQ D PEDRO II temos um uma relação de 47323.77 Passageiros por km \n",
      "Na linha N70211 - TERM STO AMARO/T PQ D PEDRO II temos um uma relação de 22576.88 Passageiros por km \n",
      "Na linha N70311 - TERM JD ANGELA/TERM STO AMARO temos um uma relação de 74815.83 Passageiros por km \n",
      "Na linha N70411 - TERM CAPELINHA/TERM STO AMARO temos um uma relação de 59114.49 Passageiros por km \n",
      "Na linha N70511 - TERM STO AMARO/TERM PINHEIROS temos um uma relação de 21857.82 Passageiros por km \n",
      "Na linha N70611 - TERM CAMPO LIMPO/TERM PINHEIRO temos um uma relação de 39584.88 Passageiros por km \n",
      "Na linha N73111 - TERM CAPELINHA/TERM STO AMARO temos um uma relação de 11171.46 Passageiros por km \n",
      "Na linha N73211 - T JD ANGELA/TERM ROD JA JACIRA temos um uma relação de 12663.93 Passageiros por km \n",
      "Na linha N73311 - TERM JD ANGELA/VILA GILDA temos um uma relação de 12469.86 Passageiros por km \n",
      "Na linha N73411 - TERM CAPELINHA/VALO VELHO temos um uma relação de 11091.92 Passageiros por km \n",
      "Na linha N73511 - TERM CAPELINHA/JARDIM GUARUJA temos um uma relação de 10012.39 Passageiros por km \n",
      "Na linha N73611 - T JD ANGELA/JD HORIZONTE AZUL temos um uma relação de 11733.89 Passageiros por km \n",
      "Na linha N73711 - TERM JD ANGELA/PARQUE DO LAGO temos um uma relação de 7935.90 Passageiros por km \n",
      "Na linha N73811 - TERM GUARAPIRANGA/PQ DO LAGO temos um uma relação de 3207.90 Passageiros por km \n",
      "Na linha N73911 - TERM CAPELINHA/JD UNIVERSAL temos um uma relação de 4398.67 Passageiros por km \n",
      "Na linha N74011 - TERM JD ANGELA/JD RIVIERA temos um uma relação de 5688.12 Passageiros por km \n",
      "Na linha N74111 - TERM CAPELINHA/VALO VELHO temos um uma relação de 13869.17 Passageiros por km \n",
      "Na linha N74211 - TERM JOAO DIAS/TERM PINHEIROS temos um uma relação de 9746.14 Passageiros por km \n",
      "Na linha N74311 - TERM JOAO DIAS/JARDIM PLANALTO temos um uma relação de 5212.26 Passageiros por km \n",
      "Na linha N74411 - TERM JOAO DIAS/JD VAZ DE LIMA temos um uma relação de 13611.04 Passageiros por km \n",
      "Na linha N74511 - TER CAPELINHA/TERM CAMPO LIMPO temos um uma relação de 45653.17 Passageiros por km \n",
      "Na linha N74611 - TERM CAMPO LIMPO/JARDIM IRENE temos um uma relação de 13556.42 Passageiros por km \n",
      "Na linha N80111 - T METRO BUTANTA/T P D PEDRO II temos um uma relação de 37295.34 Passageiros por km \n",
      "Na linha N80211 - TERM PINHEIROS/T PQ D PEDRO II temos um uma relação de 19357.79 Passageiros por km \n",
      "Na linha N83111 - TERM LAPA/PARQUE DA LAPA temos um uma relação de 694.75 Passageiros por km \n",
      "Na linha N83211 - TERM LAPA/PARQUE CONTINENTAL temos um uma relação de 1513.97 Passageiros por km \n",
      "Na linha N83311 - TERM PINHEIROS/CEASA temos um uma relação de 2355.55 Passageiros por km \n",
      "Na linha N83411 - TERM LAPA/TERMINAL PINHEIROS temos um uma relação de 6015.81 Passageiros por km \n",
      "Na linha N83511 - TERM PINHEIROS/JD JOÃO XXIII temos um uma relação de 3492.23 Passageiros por km \n",
      "Na linha N83611 - TERM PINHEIROS/PQ CONTINENTAL temos um uma relação de 1681.30 Passageiros por km \n",
      "Na linha N83711 - TERM JOAO DIAS/CDHU BUTANTA temos um uma relação de 1805.45 Passageiros por km \n",
      "Na linha N83811 - M VILA MADALENA/CPTM LEOP0LDIN temos um uma relação de 699.46 Passageiros por km \n",
      "Na linha N83911 - METRO BUTANTA/METRO V MARIANA temos um uma relação de 1880.10 Passageiros por km \n",
      "Na linha N84011 - M VILA MARIANA/SANTA CECILIA temos um uma relação de 507.94 Passageiros por km \n",
      "Na linha N84111 - METRO VILA MARIANA/STA CECILIA temos um uma relação de 772.84 Passageiros por km \n",
      "Na linha N84211 - T PINHEIROS/COHAB RAPOSO TAVAR temos um uma relação de 903.43 Passageiros por km \n"
     ]
    }
   ],
   "source": [
    "# Using the GTFS \n",
    "shapes = pd.read_csv('gtfs/shapes.txt', sep=\",\")\n",
    "routes = pd.read_csv('gtfs/routes.txt', sep=\",\")\n",
    "trips = pd.read_csv('gtfs/trips.txt', sep=\",\")\n",
    "\n",
    "i = 0\n",
    "for index, row in shapes.iterrows():\n",
    "    if row[3] == 1 and i == 1: # The last value with total distance made by the line \n",
    "         route_id = trips.loc[trips['shape_id'] == shape_id]['route_id'].values # Searching the Code of line in trips dataset \n",
    "         route_id = route_id[0] # Picking the value in the \n",
    "         route_id = list(route_id) #Spliting the Code Line in list\n",
    "         del route_id[4] # Deleting the \"-\" because in linha_linha dataset there isn't\n",
    "         route_id = \"\".join(route_id) # Reagrouping :)\n",
    "         index_place = linha_linha.loc[linha_linha['LINHANUM'] == route_id].index.values # Picking the index value to that line\n",
    "         linha_linha.set_value(index_place,'DISTTRAJETO', valor_dist) # Adding the total distance in the linha_linha dataset\n",
    "         i = 1\n",
    "    elif row[3] == 1 and i == 0:\n",
    "         i = i + 1\n",
    "    shape_id = row[0]\n",
    "    valor_dist = row[4]\n",
    "\n",
    "for index, row in linha_linha.iterrows():\n",
    "    if np.isnan(row[3]) == False:\n",
    "        print (\"Na linha {} temos um uma relação de {} Passageiros por km \".format(row[0], \"{0:.2f}\".format(1000*row[1]/row[3]) ))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#------ Plotting Total Passengers vs. Month\n",
    "def totalpassengersvsdate():\n",
    "    plt.figure(figsize=(16,8))\n",
    "    x = list(range(0, len(ytotal) ))\n",
    "    plt.xticks(x, xTicks)\n",
    "    plt.xticks(range(len(ytotal)), xTicks, rotation=60) # writes strings with 45 degree angle\n",
    "    colors = []\n",
    "    for i in range(0, len(ytotal)):\n",
    "        if i < 12:\n",
    "            colors.append('#F44336')\n",
    "        elif i >= 12 and i < 24:\n",
    "            colors.append('#FFC107')\n",
    "        elif i >= 24 and i < 36:\n",
    "            colors.append('#4A148C')\n",
    "        else:\n",
    "            colors.append('#48A51A')\n",
    "    plt.bar(x,ytotal, color=colors)\n",
    "    plt.xlabel(\"Data\")\n",
    "    plt.ylabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.gcf().subplots_adjust(bottom=0.25, left=0.1)\n",
    "   # plt.tight_layout()\n",
    "    ano2014 = mpatches.Patch(color='#F44336', label='2014')\n",
    "    ano2015 = mpatches.Patch(color='#FFC107', label='2015')\n",
    "    ano2016 = mpatches.Patch(color='#4A148C', label='2016')\n",
    "    ano2017 = mpatches.Patch(color='#48A51A', label='2017')\n",
    "    plt.legend(handles=[ano2014,ano2015,ano2016,ano2017], \n",
    "               loc='upper center', \n",
    "               bbox_to_anchor=(0.5, -0.25),\n",
    "               fancybox=False, \n",
    "               shadow=False, \n",
    "               ncol=4) \n",
    "    plt.show()\n",
    "\n",
    "#------ Plotting Paying Passenger and Integration Passenger and Free Passengers and Free Pass Students vs Month\n",
    "def typepassengervsdate():\n",
    "    raw_data = {'Date': xTicks,\n",
    "            'Passageiros Pagantes': ytotal_paying,\n",
    "            'Passageiros com Integração': ytotal_integration,\n",
    "            'Passageiros com Gratuidade': ytotal_free_passengers,\n",
    "            'Passageiros Estudantes com Gratuidade': ytotal_free_students}\n",
    "    df = pd.DataFrame(raw_data, columns = ['Date', 'Passageiros Pagantes','Passageiros com Integração', 'Passageiros com Gratuidade', 'Passageiros Estudantes com Gratuidade'])\n",
    "    \n",
    "    # Create the general and the \"subplots\" i.e. the bars\n",
    "    f, ax1 = plt.subplots(1, figsize=(16,8))\n",
    "    \n",
    "    # Set the bar width\n",
    "    bar_width = 0.8\n",
    "    \n",
    "    # positions of the left bar-boundaries\n",
    "    bar_l = [i+1 for i in range(len(df['Passageiros Pagantes']))]\n",
    "    \n",
    "    # positions of the x-axis ticks (center of the bars as bar labels)\n",
    "    tick_pos = list(range(1, len(xTicks) + 1))\n",
    "    \n",
    "    # Create a bar plot\n",
    "    ax1.bar(bar_l,\n",
    "            df['Passageiros Pagantes'],\n",
    "            width=bar_width,\n",
    "            label='Passageiros Pagantes',\n",
    "            color='#F44336')\n",
    "    \n",
    "    # Create a bar plot\n",
    "    ax1.bar(bar_l,\n",
    "            df['Passageiros com Integração'],\n",
    "            width=bar_width,\n",
    "            bottom=df['Passageiros Pagantes'],\n",
    "            label='Passageiros com Integração',\n",
    "            color='#4A148C')\n",
    "    \n",
    "    # Create a bar plot\n",
    "    ax1.bar(bar_l,\n",
    "            df['Passageiros com Gratuidade'],\n",
    "            width=bar_width,\n",
    "            bottom=[i+j for i,j in zip(df['Passageiros Pagantes'],df['Passageiros com Integração'])],\n",
    "            label='Passageiros com Gratuidade',\n",
    "            color='#48A51A')\n",
    "    \n",
    "    # Create a bar plot\n",
    "    ax1.bar(bar_l,\n",
    "            df['Passageiros Estudantes com Gratuidade'],\n",
    "            width=bar_width,\n",
    "            bottom=[i+j+k for i,j,k in zip(df['Passageiros Pagantes'],df['Passageiros com Integração'], df['Passageiros com Gratuidade'])],\n",
    "            label='Passageiros Estudantes com Gratuidade',\n",
    "            color='#009688')\n",
    "    \n",
    "    # Set the x ticks with names\n",
    "    plt.xticks(tick_pos, df['Date'], rotation = 60)\n",
    "    \n",
    "    # To label don't cut off \n",
    "    plt.gcf().subplots_adjust(bottom=0.25, left=0.1)\n",
    "    \n",
    "    # Set the label and legends\n",
    "    ax1.set_ylabel(\"Total de Passageiros por Categoria \\n (em milhões de Pasageiros)\")\n",
    "    ax1.set_xlabel(\"Data\")\n",
    "    plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.25),\n",
    "              fancybox=True, shadow=False, ncol=4)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "#------ Check which companies carry the most\n",
    "\n",
    "def mostusedcompanies(n_empresas):\n",
    "    if n_empresas > len(empresa[\"EMPRESA\"].tolist()):\n",
    "        n_empresas = len(empresa[\"EMPRESA\"].tolist())\n",
    "    \n",
    "    x = list(range(0, n_empresas))\n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.xticks(x, empresa[\"EMPRESA\"].tolist())\n",
    "    plt.xticks(range(0, n_empresas), empresa[\"EMPRESA\"].tolist()[:n_empresas], rotation=90) \n",
    "    plt.bar(x, (empresa[\"PASSAGEIROS\"]/10**6).tolist()[:n_empresas])\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.tight_layout()\n",
    "    plt.xlabel(\"Empresa\")\n",
    "    plt.ylabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    \n",
    "    plt.show()\n",
    "    \n",
    "    print (empresa)\n",
    "\n",
    "#------ Check concession vs. permission\n",
    "def mostusedtype():\n",
    "    x = list(range(0, len(tipo[\"TIPO\"].tolist())))\n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.xticks(x, tipo[\"TIPO\"].tolist())\n",
    "    plt.xticks(range(len(tipo[\"TIPO\"].tolist())), tipo[\"TIPO\"].tolist())\n",
    "    plt.bar(x, (tipo[\"PASSAGEIROS\"]/10**6).tolist(), color=\"#009688\")\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.tight_layout()\n",
    "    plt.xlabel(\"Tipo\")\n",
    "    plt.ylabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.show()\n",
    "    \n",
    "    print (tipo)\n",
    "\n",
    "#------ Verify usage by Area\n",
    "def mostusedareas():\n",
    "    x = list(range(0, len(area[\"AREA\"].tolist())))\n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.xticks(x, area[\"AREA\"].tolist())\n",
    "    plt.xticks(range(len(area[\"AREA\"].tolist())), area[\"AREA\"].tolist())\n",
    "    plt.bar(x, (area[\"PASSAGEIROS\"]/10**6).tolist(), color=\"#009688\")\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.tight_layout()\n",
    "    plt.xlabel(\"Área\")\n",
    "    plt.ylabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.show()\n",
    "    \n",
    "    print (area)\n",
    "\n",
    "#------ n most used Lines\n",
    "def mostusedlines(n_linhas):\n",
    "    if n_linhas > len(linha[\"LINHA\"].tolist()):\n",
    "        n_linhas = len(linha[\"LINHA\"].tolist())\n",
    "    \n",
    "    plt.figure(figsize=(16,8))\n",
    "    colors = []\n",
    "    for i in range(0, n_linhas):\n",
    "        if linha.ix[i,1] == \"AREA 1\":\n",
    "            colors.append('#EC407A')\n",
    "        elif linha.ix[i,1] == \"AREA 2\":\n",
    "            colors.append('#9C27B0')\n",
    "        elif linha.ix[i,1] == \"AREA 3\":\n",
    "            colors.append('#2196F3')\n",
    "        elif linha.ix[i,1] == \"AREA 4\":\n",
    "            colors.append('#009688')\n",
    "        elif linha.ix[i,1] == \"AREA 5\":\n",
    "            colors.append('#8BC34A')\n",
    "        elif linha.ix[i,1] == \"AREA 6\":\n",
    "            colors.append('#FFC107')\n",
    "        elif linha.ix[i,1] == \"AREA 7\":\n",
    "            colors.append('#FF5722')\n",
    "    plt.barh(range(0, n_linhas), (linha[\"PASSAGEIROS\"]/10**6)[:n_linhas], align='center', color=colors)\n",
    "    plt.yticks(range(0, n_linhas),linha[\"LINHA\"][:n_linhas], rotation = 0)\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.xlabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.ylabel(\"Linha\")\n",
    "    AREA1 = mpatches.Patch(color='#EC407A', label='AREA 1')\n",
    "    AREA2 = mpatches.Patch(color='#9C27B0', label='AREA 2')\n",
    "    AREA3 = mpatches.Patch(color='#2196F3', label='AREA 3')\n",
    "    AREA4 = mpatches.Patch(color='#009688', label='AREA 4')\n",
    "    AREA5 = mpatches.Patch(color='#8BC34A', label='AREA 5')\n",
    "    AREA6 = mpatches.Patch(color='#FFC107', label='AREA 6')\n",
    "    AREA7 = mpatches.Patch(color='#FF5722', label='AREA 7')\n",
    "    plt.legend(handles=[AREA1,AREA2,AREA3,AREA4,AREA5,AREA6,AREA7], loc=1)\n",
    "    plt.show()\n",
    "        \n",
    "    print (linha.head(n_linhas))\n",
    "\n",
    "#------ Check which n lines are most commonly used by AREA\n",
    "def mostusedlinesperarea(n_linhas, area):\n",
    "    if n_linhas > len(linha[\"LINHA\"].tolist()):\n",
    "        n_linhas = len(linha[\"LINHA\"].tolist())\n",
    "    \n",
    "    linha_area = linha.loc[(linha[\"AREA\"] == area)]\n",
    "    \n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.barh(range(0, n_linhas), (linha_area[\"PASSAGEIROS\"]/10**6)[:n_linhas], align='center', color=\"#009688\")\n",
    "    plt.yticks(range(0, n_linhas), linha_area[\"LINHA\"][:n_linhas], rotation = 0)\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.xlabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.ylabel(\"Linha\")\n",
    "    plt.title(\"As {} linhas mais usadas na {}\".format(n_linhas, area.title() ))\n",
    "    plt.show()\n",
    "        \n",
    "    print (linha.head(n_linhas))\n",
    "    \n",
    "    \n",
    "#------Check which n lines are most commonly used by COMPANY\n",
    "\n",
    "def mostusedlinespercompanie(n_linhas, companie):\n",
    "    if n_linhas > len(linha[\"LINHA\"].tolist()):\n",
    "        n_linhas = len(linha[\"LINHA\"].tolist())\n",
    "    \n",
    "    linha_comp = linha.loc[(linha[\"EMPRESA\"] == companie)]\n",
    "    \n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.barh(range(0, n_linhas), (linha_comp[\"PASSAGEIROS\"]/10**6)[:n_linhas], align='center', color=\"#009688\")\n",
    "    plt.yticks(range(0, n_linhas), linha_comp[\"LINHA\"][:n_linhas], rotation = 0)\n",
    "    plt.gcf().subplots_adjust(left=0.3)\n",
    "    plt.xlabel('Quantidade de Passageiros Trasportados \\n (em milhões de Pasageiros)')\n",
    "    plt.ylabel(\"Linha\")\n",
    "    plt.title(\"As {} linhas mais usadas pela Empresa {}\".format(n_linhas, companie.title() ))\n",
    "    plt.show()\n",
    "        \n",
    "    print (linha.head(n_linhas))\n",
    "\n",
    "#------ Plotting the Normal\n",
    "\n",
    "def normal():\n",
    "    positivos = linha_linha[linha_linha.DISTTRAJETO > 0].DISTTRAJETO\n",
    "    aleatorios = pd.Series(np.random.randn(100*len(positivos)), name='normal')\n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.hist(aleatorios, bins=75, width=0.1)\n",
    "    plt.show()\n",
    "\n",
    "#------ Plotting the Histogram of Distances\n",
    "\n",
    "def histdistance ():\n",
    "    positivos = linha_linha[linha_linha.DISTTRAJETO > 0].DISTTRAJETO\n",
    "    plt.figure(figsize=(16,8))\n",
    "    plt.hist(positivos, bins=95, edgecolor = \"black\", color=\"#009688\")\n",
    "    plt.axvline(linha_linha[\"DISTTRAJETO\"].mean(), color='b', linestyle='dashed', linewidth=2)\n",
    "    plt.annotate('Média de {} km por trajeto'.format(\"{0:.2f}\".format(linha_linha[\"DISTTRAJETO\"].mean()/1000)), \n",
    "                xy=(linha_linha[\"DISTTRAJETO\"].mean(), 0), \n",
    "                xytext=(linha_linha[\"DISTTRAJETO\"].mean(), -5.0), \n",
    "                arrowprops = dict(facecolor='black', shrink=0.05))\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA98AAAHuCAYAAACGSr+RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24aea4dac18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#------ Calling the Plots :)\n",
    "\n",
    "totalpassengersvsdate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA98AAAHuCAYAAACGSr+RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae90f7828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "typepassengervsdate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJIAAAJGCAYAAAAAkq8cAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkqRJsZAkSZIkSZKkSfl/XwQKuNS8/csAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae998b0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                     EMPRESA  PASSAGEIROS\n",
      "28                    VIP II  899265380.0\n",
      "16                  SAMBAIBA  713866278.0\n",
      "26                   VIA SUL  489009487.0\n",
      "41               TRANSCOOPER  484127183.0\n",
      "18             SANTA BRIGIDA  478355456.0\n",
      "4                 CAMPO BELO  446670542.0\n",
      "35                 COOPERPAM  394609901.0\n",
      "24                TRANSWOLFF  394313264.0\n",
      "13                NORTE BUSS  338475050.0\n",
      "22                 TRANSPASS  328210240.0\n",
      "5               CIDADE DUTRA  314604959.0\n",
      "23                TRANSUNIÃO  308405970.0\n",
      "2                    ALLIBUS  277548669.0\n",
      "8                 GATO PRETO  239939655.0\n",
      "11                MOBIBRASIL  226229478.0\n",
      "21                 TRANSKUBA  191667758.0\n",
      "36              COOPERTRANSE  174417131.0\n",
      "12                   MOVE-SP  174118446.0\n",
      "14                   PESSEGO  154897029.0\n",
      "7                    EXPRESS  151970525.0\n",
      "34               COOPERLIDER  151020690.0\n",
      "0              A2 TRANPORTES  150473095.0\n",
      "9                     GATUSA  147078920.0\n",
      "27                       VIP  141164318.0\n",
      "39            NOVO HORIZONTE  141159569.0\n",
      "25                      TUPI  129597887.0\n",
      "42            TRANSCOOPER II  125792242.0\n",
      "3                  AMBIENTAL  109988217.0\n",
      "37                     FENIX   91779402.0\n",
      "19                   SPENCER   88988171.0\n",
      "43               UNICCOOPERS   75098238.0\n",
      "20                  TRANSCAP   73691982.0\n",
      "32         COOPER QUART AÇÃO   62975981.0\n",
      "38              NOVA ALIANCA   55751359.0\n",
      "6                   EXPANDIR   54797151.0\n",
      "10                  IMPERIAL   53847606.0\n",
      "53                PAULISTANA   51007997.0\n",
      "33                COOPERALFA   44520293.0\n",
      "1               ALFA RODOBUS   41789508.0\n",
      "55              PAULISTANA I   38457003.0\n",
      "40             PAULISTANA II   36347219.0\n",
      "56           TRANSCOOPER III   23155707.0\n",
      "52            TRANSCOOPER IV    4995854.0\n",
      "45                UNICOOPERS    3089341.0\n",
      "48        GATUSA PREEMBARQUE    2508907.0\n",
      "15                  QUALIBUS    2221531.0\n",
      "54                       769    1119405.0\n",
      "51                       329     752971.0\n",
      "46  COOPERPEOPLE PREEMBARQUE     319244.0\n",
      "47       EXPRESS TRANSPORTES     116573.0\n",
      "31                       639     102832.0\n",
      "50                       559      86457.0\n",
      "44                       452      67189.0\n",
      "49                       449      45972.0\n",
      "17              SAMBAIBA_TUR      25028.0\n",
      "30                       519       7069.0\n",
      "29                       277        100.0\n"
     ]
    }
   ],
   "source": [
    "mostusedcompanies(35) # Number of companies to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJIAAAJGCAYAAAAAkq8cAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae998bf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        TIPO   PASSAGEIROS\n",
      "0  CONCESSAO  5.208255e+09\n",
      "1  PERMISSAO  3.876389e+09\n"
     ]
    }
   ],
   "source": [
    "mostusedtype()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABJIAAAJGCAYAAAAAkq8cAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQwRJAAAAAAz5X4BREaHveuCkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae9419160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     AREA   PASSAGEIROS\n",
      "6  AREA 7  1.489272e+09\n",
      "5  AREA 6  1.403485e+09\n",
      "2  AREA 3  1.285783e+09\n",
      "3  AREA 4  1.113236e+09\n",
      "1  AREA 2  1.075277e+09\n",
      "0  AREA 1  1.042468e+09\n",
      "4  AREA 5  9.385032e+08\n",
      "7  AREA 8  7.366193e+08\n"
     ]
    }
   ],
   "source": [
    "mostusedareas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8UAAAHvCAYAAAB9mn0VAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZmZmZmZmDctFsZmZmZmZmTWsfwO07BXbCyaQRwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24aea142c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         TIPO    AREA        EMPRESA                                    LINHA  \\\n",
      "0   CONCESSAO  AREA 7         VIP II   675K10 - TERM JD ANGELA-METRO STA CRUZ   \n",
      "1   CONCESSAO  AREA 3         VIP II  431010 - E.T.ITAQUERA/TERM PQ D PEDRO     \n",
      "2   CONCESSAO  AREA 6   CIDADE DUTRA     691310 - TERM BANDEIRA/TERM VARGINHA   \n",
      "3   CONCESSAO  AREA 8      TRANSPASS  870010 - T CAMPO LIMPO/PCA R D AZEVEDO    \n",
      "4   CONCESSAO  AREA 7      TRANSKUBA  695T10 - TERM.CAPELINHA/METRO V.MARIANA   \n",
      "5   PERMISSAO  AREA 3     TRANSUNIÃO           220210 - HOSP ITAIM/GUAIAZAZES   \n",
      "6   CONCESSAO  AREA 7         GATUSA    620010 - TERM STO AMARO/TERM BANDEIRA   \n",
      "7   CONCESSAO  AREA 7     CAMPO BELO    645010 - TERM.CAPELINHA-TERM.BANDEIRA   \n",
      "8   CONCESSAO  AREA 6   CIDADE DUTRA                563010 - Jd Eliana - Brás   \n",
      "9   CONCESSAO  AREA 7         VIP II        637A10 - TERM JD ANGELA/PINHEIROS   \n",
      "10  CONCESSAO  AREA 2       SAMBAIBA   971R10 - ESTACAO JARAGUA/METRO SANTANA   \n",
      "11  CONCESSAO  AREA 3         VIP II   345910 - ITAIM PAULISTA/TERM P D PEDRO   \n",
      "12  CONCESSAO  AREA 3         VIP II  431310 - T CID TIRADENTES/T PQ D PEDRO    \n",
      "13  CONCESSAO  AREA 2       SAMBAIBA     209P10 - CACHOEIRINHA/TERM PINHEIROS   \n",
      "14  CONCESSAO  AREA 4      AMBIENTAL  229010 - TERM S MATEUS/TERM.PD PEDRO II   \n",
      "15  CONCESSAO  AREA 1  SANTA BRIGIDA    917H10 - MERCADO PIRITUBA/VLA MARIANA   \n",
      "16  CONCESSAO  AREA 6     MOBIBRASIL  600010 - TERM PARELHEIROS/TERM SANTO AM   \n",
      "17  PERMISSAO  AREA 3     TRANSUNIÃO  306410 - CIDADE TIRADENTES/EST GUAIANAZ   \n",
      "18  CONCESSAO  AREA 8     GATO PRETO                    856R10 - LAPA/SOCORRO   \n",
      "19  CONCESSAO  AREA 5        VIA SUL   574J10 - METRO CONCEICAO/T VILA CARRAO   \n",
      "\n",
      "    PASSAGEIROS  \n",
      "0    37004750.0  \n",
      "1    35672833.0  \n",
      "2    34977087.0  \n",
      "3    30935678.0  \n",
      "4    28059512.0  \n",
      "5    27515687.0  \n",
      "6    26307153.0  \n",
      "7    26039798.0  \n",
      "8    25788227.0  \n",
      "9    25552358.0  \n",
      "10   25295434.0  \n",
      "11   25045054.0  \n",
      "12   24926991.0  \n",
      "13   24576077.0  \n",
      "14   23744240.0  \n",
      "15   23582925.0  \n",
      "16   23003009.0  \n",
      "17   22364598.0  \n",
      "18   21747492.0  \n",
      "19   21721596.0  \n"
     ]
    }
   ],
   "source": [
    "mostusedlines(20) # Number of lines to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8UAAAH7CAYAAADl3T2YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAU9I5oIhyCShAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae937fc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         TIPO    AREA        EMPRESA                                    LINHA  \\\n",
      "0   CONCESSAO  AREA 7         VIP II   675K10 - TERM JD ANGELA-METRO STA CRUZ   \n",
      "1   CONCESSAO  AREA 3         VIP II  431010 - E.T.ITAQUERA/TERM PQ D PEDRO     \n",
      "2   CONCESSAO  AREA 6   CIDADE DUTRA     691310 - TERM BANDEIRA/TERM VARGINHA   \n",
      "3   CONCESSAO  AREA 8      TRANSPASS  870010 - T CAMPO LIMPO/PCA R D AZEVEDO    \n",
      "4   CONCESSAO  AREA 7      TRANSKUBA  695T10 - TERM.CAPELINHA/METRO V.MARIANA   \n",
      "5   PERMISSAO  AREA 3     TRANSUNIÃO           220210 - HOSP ITAIM/GUAIAZAZES   \n",
      "6   CONCESSAO  AREA 7         GATUSA    620010 - TERM STO AMARO/TERM BANDEIRA   \n",
      "7   CONCESSAO  AREA 7     CAMPO BELO    645010 - TERM.CAPELINHA-TERM.BANDEIRA   \n",
      "8   CONCESSAO  AREA 6   CIDADE DUTRA                563010 - Jd Eliana - Brás   \n",
      "9   CONCESSAO  AREA 7         VIP II        637A10 - TERM JD ANGELA/PINHEIROS   \n",
      "10  CONCESSAO  AREA 2       SAMBAIBA   971R10 - ESTACAO JARAGUA/METRO SANTANA   \n",
      "11  CONCESSAO  AREA 3         VIP II   345910 - ITAIM PAULISTA/TERM P D PEDRO   \n",
      "12  CONCESSAO  AREA 3         VIP II  431310 - T CID TIRADENTES/T PQ D PEDRO    \n",
      "13  CONCESSAO  AREA 2       SAMBAIBA     209P10 - CACHOEIRINHA/TERM PINHEIROS   \n",
      "14  CONCESSAO  AREA 4      AMBIENTAL  229010 - TERM S MATEUS/TERM.PD PEDRO II   \n",
      "15  CONCESSAO  AREA 1  SANTA BRIGIDA    917H10 - MERCADO PIRITUBA/VLA MARIANA   \n",
      "16  CONCESSAO  AREA 6     MOBIBRASIL  600010 - TERM PARELHEIROS/TERM SANTO AM   \n",
      "17  PERMISSAO  AREA 3     TRANSUNIÃO  306410 - CIDADE TIRADENTES/EST GUAIANAZ   \n",
      "18  CONCESSAO  AREA 8     GATO PRETO                    856R10 - LAPA/SOCORRO   \n",
      "19  CONCESSAO  AREA 5        VIA SUL   574J10 - METRO CONCEICAO/T VILA CARRAO   \n",
      "\n",
      "    PASSAGEIROS  \n",
      "0    37004750.0  \n",
      "1    35672833.0  \n",
      "2    34977087.0  \n",
      "3    30935678.0  \n",
      "4    28059512.0  \n",
      "5    27515687.0  \n",
      "6    26307153.0  \n",
      "7    26039798.0  \n",
      "8    25788227.0  \n",
      "9    25552358.0  \n",
      "10   25295434.0  \n",
      "11   25045054.0  \n",
      "12   24926991.0  \n",
      "13   24576077.0  \n",
      "14   23744240.0  \n",
      "15   23582925.0  \n",
      "16   23003009.0  \n",
      "17   22364598.0  \n",
      "18   21747492.0  \n",
      "19   21721596.0  \n"
     ]
    }
   ],
   "source": [
    "mostusedlinesperarea(20, \"AREA 3\") # Number of lines and the area to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA8MAAAH7CAYAAADow03fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae94199e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         TIPO    AREA        EMPRESA                                    LINHA  \\\n",
      "0   CONCESSAO  AREA 7         VIP II   675K10 - TERM JD ANGELA-METRO STA CRUZ   \n",
      "1   CONCESSAO  AREA 3         VIP II  431010 - E.T.ITAQUERA/TERM PQ D PEDRO     \n",
      "2   CONCESSAO  AREA 6   CIDADE DUTRA     691310 - TERM BANDEIRA/TERM VARGINHA   \n",
      "3   CONCESSAO  AREA 8      TRANSPASS  870010 - T CAMPO LIMPO/PCA R D AZEVEDO    \n",
      "4   CONCESSAO  AREA 7      TRANSKUBA  695T10 - TERM.CAPELINHA/METRO V.MARIANA   \n",
      "5   PERMISSAO  AREA 3     TRANSUNIÃO           220210 - HOSP ITAIM/GUAIAZAZES   \n",
      "6   CONCESSAO  AREA 7         GATUSA    620010 - TERM STO AMARO/TERM BANDEIRA   \n",
      "7   CONCESSAO  AREA 7     CAMPO BELO    645010 - TERM.CAPELINHA-TERM.BANDEIRA   \n",
      "8   CONCESSAO  AREA 6   CIDADE DUTRA                563010 - Jd Eliana - Brás   \n",
      "9   CONCESSAO  AREA 7         VIP II        637A10 - TERM JD ANGELA/PINHEIROS   \n",
      "10  CONCESSAO  AREA 2       SAMBAIBA   971R10 - ESTACAO JARAGUA/METRO SANTANA   \n",
      "11  CONCESSAO  AREA 3         VIP II   345910 - ITAIM PAULISTA/TERM P D PEDRO   \n",
      "12  CONCESSAO  AREA 3         VIP II  431310 - T CID TIRADENTES/T PQ D PEDRO    \n",
      "13  CONCESSAO  AREA 2       SAMBAIBA     209P10 - CACHOEIRINHA/TERM PINHEIROS   \n",
      "14  CONCESSAO  AREA 4      AMBIENTAL  229010 - TERM S MATEUS/TERM.PD PEDRO II   \n",
      "15  CONCESSAO  AREA 1  SANTA BRIGIDA    917H10 - MERCADO PIRITUBA/VLA MARIANA   \n",
      "16  CONCESSAO  AREA 6     MOBIBRASIL  600010 - TERM PARELHEIROS/TERM SANTO AM   \n",
      "17  PERMISSAO  AREA 3     TRANSUNIÃO  306410 - CIDADE TIRADENTES/EST GUAIANAZ   \n",
      "18  CONCESSAO  AREA 8     GATO PRETO                    856R10 - LAPA/SOCORRO   \n",
      "19  CONCESSAO  AREA 5        VIA SUL   574J10 - METRO CONCEICAO/T VILA CARRAO   \n",
      "\n",
      "    PASSAGEIROS  \n",
      "0    37004750.0  \n",
      "1    35672833.0  \n",
      "2    34977087.0  \n",
      "3    30935678.0  \n",
      "4    28059512.0  \n",
      "5    27515687.0  \n",
      "6    26307153.0  \n",
      "7    26039798.0  \n",
      "8    25788227.0  \n",
      "9    25552358.0  \n",
      "10   25295434.0  \n",
      "11   25045054.0  \n",
      "12   24926991.0  \n",
      "13   24576077.0  \n",
      "14   23744240.0  \n",
      "15   23582925.0  \n",
      "16   23003009.0  \n",
      "17   22364598.0  \n",
      "18   21747492.0  \n",
      "19   21721596.0  \n"
     ]
    }
   ],
   "source": [
    "mostusedlinespercompanie(20, \"GATUSA\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA68AAAHVCAYAAAAevs1nAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae9a08160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "normal()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA6cAAAH4CAYAAAC2W5t7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x24ae91724a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "histdistance() \n",
    "\n",
    "# Lembra mais uma curva normal com assimetria positiva"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arithmetic mean (average) of data: 239.25495018421054\n",
      "Sample standard deviation of data: 15.306941238352449\n",
      "Média de 16008.315216379966 km por trajeto\n",
      "48117.238\n",
      "1472.1552\n",
      "7771.281067989963\n"
     ]
    }
   ],
   "source": [
    "#------ Some Statitics\n",
    "\n",
    "import statistics\n",
    "print (\"Arithmetic mean (average) of data: {}\".format(statistics.mean(ytotal)))\n",
    "print (\"Sample standard deviation of data: {}\".format(statistics.stdev(ytotal)))\n",
    "\n",
    "print(\"Média de {} km por trajeto\".format(linha_linha[\"DISTTRAJETO\"].mean()))\n",
    "print(linha_linha[\"DISTTRAJETO\"].max())\n",
    "print(linha_linha[\"DISTTRAJETO\"].min())\n",
    "print(linha_linha[\"DISTTRAJETO\"].std())\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}