Obtain Data from EIA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Drilling Activity Prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Content\n",
    "- Obtain data from EIA (Energy Information Administration)\n",
    "- Build DataFrame with data obtained from EIA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtain data from EIA (Energy Information Administration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "API Overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "EIA_key = \"YOURKEYHERE\"\n",
    "url = \"http://api.eia.gov/category/?api_key=\"+EIA_key+\"&category_id=371\"\n",
    "response = requests.get(url)\n",
    "data_raw = response.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'request': {'category_id': 371, 'command': 'category'},\n",
       " 'category': {'category_id': '371',\n",
       "  'parent_category_id': None,\n",
       "  'name': 'EIA Data Sets',\n",
       "  'notes': '',\n",
       "  'childcategories': [{'category_id': 0, 'name': 'Electricity'},\n",
       "   {'category_id': 40203, 'name': 'State Energy Data System (SEDS)'},\n",
       "   {'category_id': 714755, 'name': 'Petroleum'},\n",
       "   {'category_id': 714804, 'name': 'Natural Gas'},\n",
       "   {'category_id': 711224, 'name': 'Total Energy'},\n",
       "   {'category_id': 717234, 'name': 'Coal'},\n",
       "   {'category_id': 829714, 'name': 'Short-Term Energy Outlook'},\n",
       "   {'category_id': 964164, 'name': 'Annual Energy Outlook'},\n",
       "   {'category_id': 1292190, 'name': 'Crude Oil Imports'},\n",
       "   {'category_id': 2123635, 'name': 'U.S. Electric System Operating Data'},\n",
       "   {'category_id': 2134384, 'name': 'International Energy Data'},\n",
       "   {'category_id': 2251604, 'name': 'CO2 Emissions'},\n",
       "   {'category_id': 2631064, 'name': 'International Energy Outlook'},\n",
       "   {'category_id': 2889994, 'name': 'U.S. Nuclear Outages'}],\n",
       "  'childseries': []}}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "API Data download Example: Obtain Oil Price in USD/bbl in time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "seriesid = 'PET.RWTC.D'\n",
    "response2 = requests.get('http://api.eia.gov/series/?api_key='+EIA_key+'&series_id='+seriesid)\n",
    "API_data = response2.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Cushing, OK WTI Spot Price FOB, Daily\n",
      "description:      Cushing, OK WTI Spot Price FOB\n",
      "units:      Dollars per Barrel\n",
      "source:      Thomson-Reuters\n",
      "start:      19860102\n",
      "end:      20211025\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "for key in ['name','description','units','source','start','end','updated']:\n",
    "    print(key+\":     \", API_data['series'][0].get(key))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['20211025', 84.64],\n",
       " ['20211022', 84.53],\n",
       " ['20211021', 82.64],\n",
       " ['20211020', 84.4],\n",
       " ['20211019', 83.19],\n",
       " ['20211018', 82.62],\n",
       " ['20211015', 82.39],\n",
       " ['20211014', 81.43],\n",
       " ['20211013', 80.67],\n",
       " ['20211012', 80.75]]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "API_data['series'][0]['data'][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oil_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-10-25</td>\n",
       "      <td>84.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-10-22</td>\n",
       "      <td>84.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-10-21</td>\n",
       "      <td>82.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-10-20</td>\n",
       "      <td>84.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-10-19</td>\n",
       "      <td>83.19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  oil_price\n",
       "0 2021-10-25      84.64\n",
       "1 2021-10-22      84.53\n",
       "2 2021-10-21      82.64\n",
       "3 2021-10-20      84.40\n",
       "4 2021-10-19      83.19"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "oil = pd.DataFrame(\n",
    "    columns=['date','oil_price'],\n",
    "    data=np.array([API_data['series'][0]['data']][0])\n",
    ")\n",
    "oil['date'] = pd.to_datetime(oil['date'],format='%Y%m%d')\n",
    "oil['oil_price'] = oil['oil_price'].astype('float')\n",
    "oil.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Function to download tables from API and convert into pandas data frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def download_convert(seriesid='',timeformat='%Y%m%d',column1='col1',column2='col2'):\n",
    "    data = requests.get('http://api.eia.gov/series/?api_key='+EIA_key+'&series_id='+seriesid).json()\n",
    "    for key in ['name','description','units','source','start','end','updated']:\n",
    "        print(key+\":     \", data['series'][0].get(key))\n",
    "    df = pd.DataFrame(\n",
    "        columns=[column1,column2],\n",
    "        data=np.array([data['series'][0]['data']][0]))\n",
    "    df[column1] = pd.to_datetime(df[column1],format=timeformat)\n",
    "    df[column2] = df[column2].replace({'NA':np.nan}) if df[(df[column2] == 'NA')][column2].count() > 0 else df[column2]\n",
    "    df[column2] = df[column2].astype('float')    \n",
    "    return(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obtain Gas Price in USD/MMBTU cubic feet in time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Henry Hub Natural Gas Spot Price, Daily\n",
      "description:      Henry Hub Natural Gas Spot Price\n",
      "units:      Dollars per Million Btu\n",
      "source:      Thomson-Reuters\n",
      "start:      19970107\n",
      "end:      20211026\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gas_price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-10-26</td>\n",
       "      <td>5.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-10-25</td>\n",
       "      <td>5.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-10-22</td>\n",
       "      <td>5.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-10-21</td>\n",
       "      <td>4.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-10-20</td>\n",
       "      <td>4.87</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gas_price\n",
       "0 2021-10-26       5.59\n",
       "1 2021-10-25       5.72\n",
       "2 2021-10-22       5.10\n",
       "3 2021-10-21       4.94\n",
       "4 2021-10-20       4.87"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gas = download_convert('NG.RNGWHHD.D',timeformat='%Y%m%d',column1='date',column2='gas_price')\n",
    "gas.rename(columns={'var1':'gas_date', 'var2':'gas_price'},inplace=True)\n",
    "gas.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rotary Rig Count in time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil Rotary Rigs in Operation, Monthly\n",
      "description:      None\n",
      "units:      Number of Rigs\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oilrig_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>407.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-01</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>381.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>367.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>353.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  oilrig_count\n",
       "0 2021-09-01         407.0\n",
       "1 2021-08-01         400.0\n",
       "2 2021-07-01         381.0\n",
       "3 2021-06-01         367.0\n",
       "4 2021-05-01         353.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OilRig = download_convert(seriesid='TOTAL.PANRPUS.M',timeformat='%Y%m',column1='date',column2='oilrig_count')\n",
    "OilRig.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Natural Gas Rotary Rigs in Operation, Monthly\n",
      "description:      None\n",
      "units:      Number of Rigs\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasrig_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>101.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-01</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "        date  gasrig_count\n",
       "0 2021-09-01         101.0\n",
       "1 2021-08-01         100.0\n",
       "2 2021-07-01         102.0\n",
       "3 2021-06-01          97.0\n",
       "4 2021-05-01         100.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasRig = download_convert(seriesid='TOTAL.NGNRPUS.M',timeformat='%Y%m',column1='date',column2='gasrig_count')\n",
    "GasRig.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil and Natural Gas Rotary Rigs in Operation, Onshore, Monthly\n",
      "description:      None\n",
      "units:      Number of Rigs\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>onshore_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>502.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-01</td>\n",
       "      <td>486.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>468.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>451.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>439.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  onshore_count\n",
       "0 2021-09-01          502.0\n",
       "1 2021-08-01          486.0\n",
       "2 2021-07-01          468.0\n",
       "3 2021-06-01          451.0\n",
       "4 2021-05-01          439.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OnshoreRig = download_convert(seriesid='TOTAL.OGNRPON.M',timeformat='%Y%m',column1='date',column2='onshore_count')\n",
    "OnshoreRig.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil and Natural Gas Rotary Rigs in Operation, Offshore, Monthly\n",
      "description:      None\n",
      "units:      Number of Rigs\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>offshore_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-01</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  offshore_count\n",
       "0 2021-09-01             6.0\n",
       "1 2021-08-01            15.0\n",
       "2 2021-07-01            16.0\n",
       "3 2021-06-01            13.0\n",
       "4 2021-05-01            14.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OffshoreRig = download_convert(seriesid='TOTAL.OGNRPOF.M',timeformat='%Y%m',column1='date',column2='offshore_count')\n",
    "OffshoreRig.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly\n",
      "description:      None\n",
      "units:      Number of Rigs\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>totalrig_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-01</td>\n",
       "      <td>508.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-01</td>\n",
       "      <td>501.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>483.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>464.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>453.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  totalrig_count\n",
       "0 2021-09-01           508.0\n",
       "1 2021-08-01           501.0\n",
       "2 2021-07-01           483.0\n",
       "3 2021-06-01           464.0\n",
       "4 2021-05-01           453.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TotalRig = download_convert(seriesid='TOTAL.OGNRPUS.M',timeformat='%Y%m',column1='date',column2='totalrig_count')\n",
    "TotalRig.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oil, gas and Dry Wells Drilled in time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil, Natural Gas, and Dry Wells Drilled, Total, Monthly\n",
      "description:      None\n",
      "units:      Number of Wells\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      201212\n",
      "updated:      2016-04-25T13:57:43-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>totalwell_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>3158.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-11-01</td>\n",
       "      <td>3294.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-10-01</td>\n",
       "      <td>3527.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-09-01</td>\n",
       "      <td>3218.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>3404.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  totalwell_count\n",
       "0 2010-12-01           3158.0\n",
       "1 2010-11-01           3294.0\n",
       "2 2010-10-01           3527.0\n",
       "3 2010-09-01           3218.0\n",
       "4 2010-08-01           3404.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TotalWells = download_convert(seriesid='TOTAL.OGTWPUS.M',timeformat='%Y%m',column1='date',column2='totalwell_count')\n",
    "TotalWells.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Wells Drilled, Total, Crude Oil, Monthly\n",
      "description:      None\n",
      "units:      Number of Wells\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      201212\n",
      "updated:      2016-04-25T13:57:43-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oilwell_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>1374.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-11-01</td>\n",
       "      <td>1462.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-10-01</td>\n",
       "      <td>1577.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-09-01</td>\n",
       "      <td>1431.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>1490.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  oilwell_count\n",
       "0 2010-12-01         1374.0\n",
       "1 2010-11-01         1462.0\n",
       "2 2010-10-01         1577.0\n",
       "3 2010-09-01         1431.0\n",
       "4 2010-08-01         1490.0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OilWells = download_convert(seriesid='TOTAL.PATWPUS.M',timeformat='%Y%m',column1='date',column2='oilwell_count')\n",
    "OilWells.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Wells Drilled, Total, Natural Gas, Monthly\n",
      "description:      None\n",
      "units:      Number of Wells\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      201212\n",
      "updated:      2016-04-25T13:57:43-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gaswell_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>1471.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-11-01</td>\n",
       "      <td>1466.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-10-01</td>\n",
       "      <td>1550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-09-01</td>\n",
       "      <td>1431.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>1506.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gaswell_count\n",
       "0 2010-12-01         1471.0\n",
       "1 2010-11-01         1466.0\n",
       "2 2010-10-01         1550.0\n",
       "3 2010-09-01         1431.0\n",
       "4 2010-08-01         1506.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasWells = download_convert(seriesid='TOTAL.NGTWPUS.M',timeformat='%Y%m',column1='date',column2='gaswell_count')\n",
    "GasWells.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Natural Gas Imports, Exports, consumption, Production and storage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Natural Gas Imports, Monthly\n",
      "description:      None\n",
      "units:      Billion Cubic Feet\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202107\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasimports_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>227.779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>207.859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>204.890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>208.369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>238.724</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gasimports_amount\n",
       "0 2021-07-01            227.779\n",
       "1 2021-06-01            207.859\n",
       "2 2021-05-01            204.890\n",
       "3 2021-04-01            208.369\n",
       "4 2021-03-01            238.724"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasImports = download_convert(seriesid='TOTAL.NGIMPUS.M',timeformat='%Y%m',column1='date',column2='gasimports_amount')\n",
    "GasImports.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Total Natural Gas Exports, Monthly\n",
      "description:      None\n",
      "units:      Billion Cubic Feet\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202107\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasexports_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>565.564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>539.252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>578.132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>564.418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>595.411</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gasexports_amount\n",
       "0 2021-07-01            565.564\n",
       "1 2021-06-01            539.252\n",
       "2 2021-05-01            578.132\n",
       "3 2021-04-01            564.418\n",
       "4 2021-03-01            595.411"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasExports = download_convert(seriesid='TOTAL.NGEXPUS.M',timeformat='%Y%m',column1='date',column2='gasexports_amount')\n",
    "GasExports.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Natural Gas Consumption, Total, Monthly\n",
      "description:      None\n",
      "units:      Billion Cubic Feet\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202107\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasconsumption_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>2381.773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>2213.947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>2093.859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>2237.206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>2606.980</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gasconsumption_amount\n",
       "0 2021-07-01               2381.773\n",
       "1 2021-06-01               2213.947\n",
       "2 2021-05-01               2093.859\n",
       "3 2021-04-01               2237.206\n",
       "4 2021-03-01               2606.980"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasConsumption = download_convert(seriesid='TOTAL.NGTCPUS.M',timeformat='%Y%m',column1='date',column2='gasconsumption_amount')\n",
    "GasConsumption.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      NGPL Production, Monthly\n",
      "description:      None\n",
      "units:      Billion Cubic Feet\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202107\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasproduction_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>244.549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>237.703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>244.674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>236.817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>228.828</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gasproduction_amount\n",
       "0 2021-07-01               244.549\n",
       "1 2021-06-01               237.703\n",
       "2 2021-05-01               244.674\n",
       "3 2021-04-01               236.817\n",
       "4 2021-03-01               228.828"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#weekly NG.NGM_EPG0_FGW_NUS_MMCFD.M\n",
    "GasProduction = download_convert(seriesid='TOTAL.NGELPUS.M',timeformat='%Y%m',column1='date',column2='gasproduction_amount')\n",
    "GasProduction.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Natural Gas in Underground Storage, End of Period, Total, Monthly\n",
      "description:      None\n",
      "units:      Billion Cubic Feet\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202107\n",
      "updated:      2021-10-26T09:57:35-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>gasstorage_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>7188.304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>7018.683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>6770.915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>6354.239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>6188.654</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  gasstorage_amount\n",
       "0 2021-07-01           7188.304\n",
       "1 2021-06-01           7018.683\n",
       "2 2021-05-01           6770.915\n",
       "3 2021-04-01           6354.239\n",
       "4 2021-03-01           6188.654"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GasStorage = download_convert(seriesid='TOTAL.NGUSPUS.M',timeformat='%Y%m',column1='date',column2='gasstorage_amount')\n",
    "GasStorage.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oil Imports, Exports, consumption, Production, storage and storage oil change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Total Petroleum Imports, Monthly\n",
      "description:      None\n",
      "units:      Thousand Barrels per Day\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n",
      "\n",
      "\n",
      "name:      U.S. Imports of Crude Oil and Petroleum Products, Weekly\n",
      "description:      U.S. Imports of Crude Oil and Petroleum Products\n",
      "units:      Thousand Barrels per Day\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19910208\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "#'TOTAL.PAIMPUS.M'\n",
    "# 'PET.WTTIMUS2.W'\n",
    "OilImports_a = download_convert(seriesid='TOTAL.PAIMPUS.M',timeformat='%Y%m',column1='date',column2='oilimports_amount_x')\n",
    "print('\\n')\n",
    "OilImports_b = download_convert(seriesid='PET.WTTIMUS2.W',timeformat='%Y%m%d',column1='date',column2='oilimports_amount_y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For future use (EDA)\n",
    "# OilImports['oilimports_amount'] = OilImports['oilimports_amount_x']\n",
    "# OilImports.loc[OilImports['oilimports_amount'].isnull() == True,'oilimports_amount'] = OilImports['oilimports_amount_y']\n",
    "# OilImports[OilImports['oilimports_amount'].isna() == False][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Total Petroleum Exports, Monthly\n",
      "description:      None\n",
      "units:      Thousand Barrels per Day\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n",
      "\n",
      "\n",
      "name:      U.S. Exports of Crude Oil and Petroleum Products, Weekly\n",
      "description:      U.S. Exports of Crude Oil and Petroleum Products\n",
      "units:      Thousand Barrels per Day\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19910208\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "#'PET.WTTEXUS2.W'\n",
    "#'TOTAL.PAEXPUS.M'\n",
    "OilExports_a = download_convert(seriesid='TOTAL.PAEXPUS.M',timeformat='%Y%m',column1='date',column2='oilexports_amount_x')\n",
    "print('\\n')\n",
    "OilExports_b = download_convert(seriesid='PET.WTTEXUS2.W',timeformat='%Y%m%d',column1='date',column2='oilexports_amount_y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Petroleum Products Supplied/Consumption, United States, Monthly\n",
      "description:      None\n",
      "units:      Thousand Barrels per Day\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n",
      "\n",
      "\n",
      "name:      U.S. Product Supplied of Petroleum Products, Weekly\n",
      "description:      U.S. Product Supplied of Petroleum Products\n",
      "units:      Thousand Barrels per Day\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19901109\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "#'PET.WRPUPUS2.W'\n",
    "#'TOTAL.PATCPUS.M'\n",
    "OilConsumption_a = download_convert(seriesid='TOTAL.PATCPUS.M',timeformat='%Y%m',column1='date',column2='oilconsumption_amount_x')\n",
    "print('\\n')\n",
    "OilConsumption_b = download_convert(seriesid='PET.WRPUPUS2.W',timeformat='%Y%m%d',column1='date',column2='oilconsumption_amount_y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil Production, Total, Monthly\n",
      "description:      None\n",
      "units:      Thousand Barrels per Day\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n",
      "\n",
      "\n",
      "name:      U.S. Field Production of Crude Oil, Weekly\n",
      "description:      U.S. Field Production of Crude Oil\n",
      "units:      Thousand Barrels per Day\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19830107\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "#monthly TOTAL.PAPRPUS.M\n",
    "# weekly PET.WCRFPUS2.W\n",
    "OilProduction_a = download_convert(seriesid='TOTAL.PAPRPUS.M',timeformat='%Y%m',column1='date',column2='oilproduction_amount_x')\n",
    "print('\\n')\n",
    "OilProduction_b = download_convert(seriesid='PET.WCRFPUS2.W',timeformat='%Y%m%d',column1='date',column2='oilproduction_amount_y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Crude Oil Stocks, Total, End of Period, Monthly\n",
      "description:      None\n",
      "units:      Million Barrels\n",
      "source:      None\n",
      "start:      197301\n",
      "end:      202109\n",
      "updated:      2021-10-26T09:57:35-0400\n",
      "\n",
      "\n",
      "name:      U.S. Ending Stocks of Crude Oil, Weekly\n",
      "description:      U.S. Ending Stocks of Crude Oil\n",
      "units:      Thousand Barrels\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19820820\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    }
   ],
   "source": [
    "#weekly PET.WTTSTUS1.W\n",
    "#monthly TOTAL.COPSPUS.M\n",
    "OilStorage_a = download_convert(seriesid='TOTAL.COPSPUS.M',timeformat='%Y%m',column1='date',column2='oilstorage_amount_x')\n",
    "print('\\n')\n",
    "OilStorage_b = download_convert(seriesid='PET.WCRSTUS1.W',timeformat='%Y%m%d',column1='date',column2='oilstorage_amount_y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      U.S. Crude Oil Stock Change, Monthly\n",
      "description:      U.S. Crude Oil Stock Change\n",
      "units:      Thousand Barrels\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      198101\n",
      "end:      202107\n",
      "updated:      2021-09-30T13:01:56-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oilstoragechange_amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>-9035.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-06-01</td>\n",
       "      <td>-34924.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-05-01</td>\n",
       "      <td>-18979.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-04-01</td>\n",
       "      <td>-16518.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>8748.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  oilstoragechange_amount\n",
       "0 2021-07-01                  -9035.0\n",
       "1 2021-06-01                 -34924.0\n",
       "2 2021-05-01                 -18979.0\n",
       "3 2021-04-01                 -16518.0\n",
       "4 2021-03-01                   8748.0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#'PET.WTTSTUS1.W'\n",
    "#'PET.MCRSCUS1.M'\n",
    "OilStorageChange = download_convert(seriesid='PET.MCRSCUS1.M',timeformat='%Y%m',column1='date',column2='oilstoragechange_amount')\n",
    "OilStorageChange.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Days of Supply of Crude Oil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      U.S. Days of Supply of Crude Oil excluding SPR, Weekly\n",
      "description:      U.S. Days of Supply of Crude Oil excluding SPR\n",
      "units:      Number of Days\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      19820924\n",
      "end:      20211022\n",
      "updated:      2021-10-27T13:11:19-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oildaysofsupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-10-22</td>\n",
       "      <td>28.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-10-15</td>\n",
       "      <td>27.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-10-08</td>\n",
       "      <td>27.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-10-01</td>\n",
       "      <td>27.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-09-24</td>\n",
       "      <td>28.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  oildaysofsupply\n",
       "0 2021-10-22             28.3\n",
       "1 2021-10-15             27.9\n",
       "2 2021-10-08             27.7\n",
       "3 2021-10-01             27.6\n",
       "4 2021-09-24             28.2"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# PET.W_EPC0_VSD_NUS_DAYS.W\n",
    "OilDaysOfSupply = download_convert(seriesid='PET.W_EPC0_VSD_NUS_DAYS.W',timeformat='%Y%m%d',column1='date',column2='oildaysofsupply')\n",
    "OilDaysOfSupply.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "US Resident Population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Resident population including Armed Forces, United States\n",
      "description:      Resident population including Armed Forces, United States See http://www.eia.gov/state/seds/seds-technical-notes-complete.cfm?sid=US for technical notes and documentation.\n",
      "units:      Thousand\n",
      "source:      SEDS, EIA, U.S. Energy Information Administration\n",
      "start:      1960\n",
      "end:      2019\n",
      "updated:      2021-06-24T19:29:04-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>uspopulation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>328330.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>326838.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>325122.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>323072.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>320739.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  uspopulation\n",
       "0 2019-01-01      328330.0\n",
       "1 2018-01-01      326838.0\n",
       "2 2017-01-01      325122.0\n",
       "3 2016-01-01      323072.0\n",
       "4 2015-01-01      320739.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "USPopulation = download_convert(seriesid='SEDS.TPOPP.US.A',timeformat='%Y',column1='date',column2='uspopulation')\n",
    "USPopulation.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CO2 Emissions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name:      Total carbon dioxide emissions from all sectors, petroleum, United States\n",
      "description:      See http://www.eia.gov/environment/emissions/state/analysis/ for technical notes and documentation.\n",
      "units:      million metric tons CO2\n",
      "source:      EIA, U.S. Energy Information Administration\n",
      "start:      1980\n",
      "end:      2018\n",
      "updated:      2021-10-14T16:18:55-0400\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>usemissions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2379.897795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2336.884160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>2314.860364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>2284.230588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>2244.002699</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  usemissions\n",
       "0 2018-01-01  2379.897795\n",
       "1 2017-01-01  2336.884160\n",
       "2 2016-01-01  2314.860364\n",
       "3 2015-01-01  2284.230588\n",
       "4 2014-01-01  2244.002699"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#EMISS.CO2-TOTV-TT-PE-US.A\n",
    "USEmissions = download_convert(seriesid='EMISS.CO2-TOTV-TT-PE-US.A',timeformat='%Y',column1='date',column2='usemissions')\n",
    "USEmissions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build DataFrame with data obtained from EIA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(left=oil,right=gas, how='left',on='date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_list = [OilRig,GasRig,TotalRig,OnshoreRig,OffshoreRig,TotalWells, OilWells, GasWells,\n",
    "           OilImports_a,OilImports_b,OilExports_a,OilExports_b,OilProduction_a,OilProduction_b,\n",
    "           OilConsumption_a,OilConsumption_b,OilStorage_a,OilStorage_b, OilStorageChange,OilDaysOfSupply,\n",
    "           GasImports,GasExports,GasProduction,GasConsumption,GasStorage, \n",
    "            USPopulation,USEmissions]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "for data in range(len(df_list)):    \n",
    "    df = pd.merge(left=df,right=df_list[data],how='outer',on='date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9598 entries, 0 to 9597\n",
      "Data columns (total 30 columns):\n",
      " #   Column                   Non-Null Count  Dtype         \n",
      "---  ------                   --------------  -----         \n",
      " 0   date                     9598 non-null   datetime64[ns]\n",
      " 1   oil_price                9038 non-null   float64       \n",
      " 2   gas_price                6222 non-null   float64       \n",
      " 3   oilrig_count             410 non-null    float64       \n",
      " 4   gasrig_count             410 non-null    float64       \n",
      " 5   totalrig_count           585 non-null    float64       \n",
      " 6   onshore_count            585 non-null    float64       \n",
      " 7   offshore_count           585 non-null    float64       \n",
      " 8   totalwell_count          456 non-null    float64       \n",
      " 9   oilwell_count            456 non-null    float64       \n",
      " 10  gaswell_count            456 non-null    float64       \n",
      " 11  oilimports_amount_x      585 non-null    float64       \n",
      " 12  oilimports_amount_y      1603 non-null   float64       \n",
      " 13  oilexports_amount_x      585 non-null    float64       \n",
      " 14  oilexports_amount_y      1603 non-null   float64       \n",
      " 15  oilproduction_amount_x   585 non-null    float64       \n",
      " 16  oilproduction_amount_y   2022 non-null   float64       \n",
      " 17  oilconsumption_amount_x  585 non-null    float64       \n",
      " 18  oilconsumption_amount_y  1615 non-null   float64       \n",
      " 19  oilstorage_amount_x      585 non-null    float64       \n",
      " 20  oilstorage_amount_y      2039 non-null   float64       \n",
      " 21  oilstoragechange_amount  487 non-null    float64       \n",
      " 22  oildaysofsupply          2037 non-null   float64       \n",
      " 23  gasimports_amount        583 non-null    float64       \n",
      " 24  gasexports_amount        583 non-null    float64       \n",
      " 25  gasproduction_amount     583 non-null    float64       \n",
      " 26  gasconsumption_amount    583 non-null    float64       \n",
      " 27  gasstorage_amount        554 non-null    float64       \n",
      " 28  uspopulation             60 non-null     float64       \n",
      " 29  usemissions              39 non-null     float64       \n",
      "dtypes: datetime64[ns](1), float64(29)\n",
      "memory usage: 2.3 MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>oil_price</th>\n",
       "      <td>9038.0</td>\n",
       "      <td>44.52</td>\n",
       "      <td>-36.98</td>\n",
       "      <td>145.31</td>\n",
       "      <td>28.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gas_price</th>\n",
       "      <td>6222.0</td>\n",
       "      <td>4.15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>23.86</td>\n",
       "      <td>2.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilrig_count</th>\n",
       "      <td>410.0</td>\n",
       "      <td>497.42</td>\n",
       "      <td>108.00</td>\n",
       "      <td>1596.00</td>\n",
       "      <td>361.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasrig_count</th>\n",
       "      <td>410.0</td>\n",
       "      <td>584.97</td>\n",
       "      <td>70.00</td>\n",
       "      <td>1585.00</td>\n",
       "      <td>388.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalrig_count</th>\n",
       "      <td>585.0</td>\n",
       "      <td>1389.25</td>\n",
       "      <td>250.00</td>\n",
       "      <td>4521.00</td>\n",
       "      <td>746.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>onshore_count</th>\n",
       "      <td>585.0</td>\n",
       "      <td>1285.06</td>\n",
       "      <td>237.00</td>\n",
       "      <td>4238.00</td>\n",
       "      <td>705.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>offshore_count</th>\n",
       "      <td>585.0</td>\n",
       "      <td>104.22</td>\n",
       "      <td>6.00</td>\n",
       "      <td>283.00</td>\n",
       "      <td>63.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>totalwell_count</th>\n",
       "      <td>456.0</td>\n",
       "      <td>3482.35</td>\n",
       "      <td>1268.00</td>\n",
       "      <td>8556.00</td>\n",
       "      <td>1654.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilwell_count</th>\n",
       "      <td>456.0</td>\n",
       "      <td>1363.82</td>\n",
       "      <td>291.00</td>\n",
       "      <td>3945.00</td>\n",
       "      <td>898.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gaswell_count</th>\n",
       "      <td>456.0</td>\n",
       "      <td>1259.94</td>\n",
       "      <td>454.00</td>\n",
       "      <td>3200.00</td>\n",
       "      <td>626.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilimports_amount_x</th>\n",
       "      <td>585.0</td>\n",
       "      <td>9149.60</td>\n",
       "      <td>3689.51</td>\n",
       "      <td>14696.61</td>\n",
       "      <td>2476.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilimports_amount_y</th>\n",
       "      <td>1603.0</td>\n",
       "      <td>10420.68</td>\n",
       "      <td>5775.00</td>\n",
       "      <td>15217.00</td>\n",
       "      <td>1854.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilexports_amount_x</th>\n",
       "      <td>585.0</td>\n",
       "      <td>1954.24</td>\n",
       "      <td>155.77</td>\n",
       "      <td>9589.40</td>\n",
       "      <td>2262.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilexports_amount_y</th>\n",
       "      <td>1603.0</td>\n",
       "      <td>2552.01</td>\n",
       "      <td>723.00</td>\n",
       "      <td>10134.00</td>\n",
       "      <td>2368.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilproduction_amount_x</th>\n",
       "      <td>585.0</td>\n",
       "      <td>7604.88</td>\n",
       "      <td>3973.59</td>\n",
       "      <td>12966.12</td>\n",
       "      <td>1775.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilproduction_amount_y</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>7342.01</td>\n",
       "      <td>3813.00</td>\n",
       "      <td>13100.00</td>\n",
       "      <td>1901.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilconsumption_amount_x</th>\n",
       "      <td>585.0</td>\n",
       "      <td>18319.93</td>\n",
       "      <td>14504.70</td>\n",
       "      <td>21666.06</td>\n",
       "      <td>1682.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilconsumption_amount_y</th>\n",
       "      <td>1615.0</td>\n",
       "      <td>19212.41</td>\n",
       "      <td>13797.00</td>\n",
       "      <td>22820.00</td>\n",
       "      <td>1383.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilstorage_amount_x</th>\n",
       "      <td>585.0</td>\n",
       "      <td>840.02</td>\n",
       "      <td>233.04</td>\n",
       "      <td>1230.10</td>\n",
       "      <td>261.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilstorage_amount_y</th>\n",
       "      <td>2039.0</td>\n",
       "      <td>945372.14</td>\n",
       "      <td>607781.00</td>\n",
       "      <td>1227678.00</td>\n",
       "      <td>123517.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oilstoragechange_amount</th>\n",
       "      <td>487.0</td>\n",
       "      <td>1206.19</td>\n",
       "      <td>-34924.00</td>\n",
       "      <td>48553.00</td>\n",
       "      <td>11206.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>oildaysofsupply</th>\n",
       "      <td>2037.0</td>\n",
       "      <td>23.42</td>\n",
       "      <td>16.10</td>\n",
       "      <td>42.00</td>\n",
       "      <td>4.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasimports_amount</th>\n",
       "      <td>583.0</td>\n",
       "      <td>203.04</td>\n",
       "      <td>42.51</td>\n",
       "      <td>426.53</td>\n",
       "      <td>103.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasexports_amount</th>\n",
       "      <td>583.0</td>\n",
       "      <td>71.31</td>\n",
       "      <td>1.61</td>\n",
       "      <td>595.41</td>\n",
       "      <td>113.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasproduction_amount</th>\n",
       "      <td>583.0</td>\n",
       "      <td>91.54</td>\n",
       "      <td>59.00</td>\n",
       "      <td>244.67</td>\n",
       "      <td>40.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasconsumption_amount</th>\n",
       "      <td>583.0</td>\n",
       "      <td>1852.22</td>\n",
       "      <td>939.93</td>\n",
       "      <td>3424.30</td>\n",
       "      <td>473.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gasstorage_amount</th>\n",
       "      <td>554.0</td>\n",
       "      <td>6494.04</td>\n",
       "      <td>4446.00</td>\n",
       "      <td>8384.09</td>\n",
       "      <td>829.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uspopulation</th>\n",
       "      <td>60.0</td>\n",
       "      <td>253787.63</td>\n",
       "      <td>180671.00</td>\n",
       "      <td>328330.00</td>\n",
       "      <td>44937.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>usemissions</th>\n",
       "      <td>39.0</td>\n",
       "      <td>2269.59</td>\n",
       "      <td>1978.17</td>\n",
       "      <td>2594.01</td>\n",
       "      <td>162.14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          count       mean        min         max        std\n",
       "oil_price                9038.0      44.52     -36.98      145.31      28.73\n",
       "gas_price                6222.0       4.15       0.00       23.86       2.18\n",
       "oilrig_count              410.0     497.42     108.00     1596.00     361.41\n",
       "gasrig_count              410.0     584.97      70.00     1585.00     388.99\n",
       "totalrig_count            585.0    1389.25     250.00     4521.00     746.52\n",
       "onshore_count             585.0    1285.06     237.00     4238.00     705.22\n",
       "offshore_count            585.0     104.22       6.00      283.00      63.63\n",
       "totalwell_count           456.0    3482.35    1268.00     8556.00    1654.50\n",
       "oilwell_count             456.0    1363.82     291.00     3945.00     898.65\n",
       "gaswell_count             456.0    1259.94     454.00     3200.00     626.67\n",
       "oilimports_amount_x       585.0    9149.60    3689.51    14696.61    2476.54\n",
       "oilimports_amount_y      1603.0   10420.68    5775.00    15217.00    1854.46\n",
       "oilexports_amount_x       585.0    1954.24     155.77     9589.40    2262.03\n",
       "oilexports_amount_y      1603.0    2552.01     723.00    10134.00    2368.32\n",
       "oilproduction_amount_x    585.0    7604.88    3973.59    12966.12    1775.59\n",
       "oilproduction_amount_y   2022.0    7342.01    3813.00    13100.00    1901.09\n",
       "oilconsumption_amount_x   585.0   18319.93   14504.70    21666.06    1682.81\n",
       "oilconsumption_amount_y  1615.0   19212.41   13797.00    22820.00    1383.45\n",
       "oilstorage_amount_x       585.0     840.02     233.04     1230.10     261.02\n",
       "oilstorage_amount_y      2039.0  945372.14  607781.00  1227678.00  123517.10\n",
       "oilstoragechange_amount   487.0    1206.19  -34924.00    48553.00   11206.98\n",
       "oildaysofsupply          2037.0      23.42      16.10       42.00       4.06\n",
       "gasimports_amount         583.0     203.04      42.51      426.53     103.02\n",
       "gasexports_amount         583.0      71.31       1.61      595.41     113.08\n",
       "gasproduction_amount      583.0      91.54      59.00      244.67      40.73\n",
       "gasconsumption_amount     583.0    1852.22     939.93     3424.30     473.32\n",
       "gasstorage_amount         554.0    6494.04    4446.00     8384.09     829.14\n",
       "uspopulation               60.0  253787.63  180671.00   328330.00   44937.79\n",
       "usemissions                39.0    2269.59    1978.17     2594.01     162.14"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()[['count','mean','min','max','std']].round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9246    4131.0\n",
       "Name: totalrig_count, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['date'].dt.year == 1981)&(df['date'].dt.month == 8)]['totalrig_count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>oil_price</th>\n",
       "      <th>gas_price</th>\n",
       "      <th>oilrig_count</th>\n",
       "      <th>gasrig_count</th>\n",
       "      <th>totalrig_count</th>\n",
       "      <th>onshore_count</th>\n",
       "      <th>offshore_count</th>\n",
       "      <th>totalwell_count</th>\n",
       "      <th>oilwell_count</th>\n",
       "      <th>...</th>\n",
       "      <th>oilstorage_amount_y</th>\n",
       "      <th>oilstoragechange_amount</th>\n",
       "      <th>oildaysofsupply</th>\n",
       "      <th>gasimports_amount</th>\n",
       "      <th>gasexports_amount</th>\n",
       "      <th>gasproduction_amount</th>\n",
       "      <th>gasconsumption_amount</th>\n",
       "      <th>gasstorage_amount</th>\n",
       "      <th>uspopulation</th>\n",
       "      <th>usemissions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9242</th>\n",
       "      <td>1981-12-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4521.0</td>\n",
       "      <td>4238.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>8029.0</td>\n",
       "      <td>3843.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5268.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.544</td>\n",
       "      <td>4.539</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2076.436</td>\n",
       "      <td>6569.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  oil_price  gas_price  oilrig_count  gasrig_count  \\\n",
       "9242 1981-12-01        NaN        NaN           NaN           NaN   \n",
       "\n",
       "      totalrig_count  onshore_count  offshore_count  totalwell_count  \\\n",
       "9242          4521.0         4238.0           283.0           8029.0   \n",
       "\n",
       "      oilwell_count  ...  oilstorage_amount_y  oilstoragechange_amount  \\\n",
       "9242         3843.0  ...                  NaN                   5268.0   \n",
       "\n",
       "      oildaysofsupply  gasimports_amount  gasexports_amount  \\\n",
       "9242              NaN             92.544              4.539   \n",
       "\n",
       "      gasproduction_amount  gasconsumption_amount  gasstorage_amount  \\\n",
       "9242                  67.0               2076.436             6569.0   \n",
       "\n",
       "      uspopulation  usemissions  \n",
       "9242           NaN          NaN  \n",
       "\n",
       "[1 rows x 30 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['totalrig_count'] == df['totalrig_count'].max())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ffa3ef4640>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid')\n",
    "for rig_count in ['oilwell_count','gaswell_count','totalwell_count']:\n",
    "    df.groupby([df['date'].dt.year,df['date'].dt.month])[rig_count].sum().plot.line(figsize=(14,6))\n",
    "plt.legend() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ffa676c130>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for rig_count in ['oilrig_count','gasrig_count','totalrig_count']:\n",
    "    df.groupby([df['date'].dt.year,df['date'].dt.month])[rig_count].sum().plot.line(figsize=(14,6))\n",
    "plt.legend() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ffa676cc70>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for feature in ['oilimports_amount_y','oilexports_amount_y','oilproduction_amount_y','oilconsumption_amount_y']:\n",
    "    df.groupby([df['date'].dt.year,df['date'].dt.month])[feature].sum().plot.line(figsize=(14,6))\n",
    "plt.legend() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.to_csv('Oil&Gas.csv',index=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}