final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydriller import Repository\n",
    "import datetime\n",
    "\n",
    "repo = 'lucene'\n",
    "url = \"C:\\\\Users\\\\Ashwitha Kassetty\\\\Documents\\\\SE_Data\\\\lucene\\\\.git\"\n",
    "\n",
    "commits = list(Repository(url).traverse_commits())\n",
    "no_of_commits = []\n",
    "total_commits = []\n",
    "i=0\n",
    "delta = datetime.timedelta(weeks=4)\n",
    "while i < len(commits):\n",
    "#     print(commits[i].author_date)\n",
    "    date1 = commits[i].author_date\n",
    "    j = i+1\n",
    "    while j<len(commits) and commits[j].author_date -date1 <= delta:\n",
    "        j+=1\n",
    "    if j>=len(commits):\n",
    "        break\n",
    "    date2 = commits[j].author_date\n",
    "    date3 = commits[j-1].author_date\n",
    "    total_commits.append(j)\n",
    "    i = j+1\n",
    "total_commits.append(j) \n",
    "\n",
    "no_of_commits = [0]+[total_commits[0]] +[total_commits[i] - total_commits[i-1] for i in range(1, len(total_commits))]\n",
    "total_commits = [0] + total_commits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "35494\n"
     ]
    }
   ],
   "source": [
    "print(total_commits[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reached till commits:  0\n",
      "CR_count: 14\n",
      "diff_count: 6\n",
      "congruence: 0.42857142857142855\n",
      "reached till commits:  34\n",
      "CR_count: 10\n",
      "diff_count: 4\n",
      "congruence: 0.4\n",
      "reached till commits:  54\n",
      "CR_count: 3\n",
      "diff_count: 3\n",
      "congruence: 1.0\n",
      "reached till commits:  59\n",
      "CR_count: 9\n",
      "diff_count: 5\n",
      "congruence: 0.5555555555555556\n",
      "reached till commits:  72\n",
      "CR_count: 33\n",
      "diff_count: 13\n",
      "congruence: 0.3939393939393939\n",
      "reached till commits:  118\n",
      "CR_count: 8\n",
      "diff_count: 4\n",
      "congruence: 0.5\n",
      "reached till commits:  142\n",
      "CR_count: 5\n",
      "diff_count: 3\n",
      "congruence: 0.6\n",
      "reached till commits:  156\n",
      "CR_count: 10\n",
      "diff_count: 4\n",
      "congruence: 0.4\n",
      "reached till commits:  186\n",
      "CR_count: 12\n",
      "diff_count: 4\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  220\n",
      "CR_count: 5\n",
      "diff_count: 3\n",
      "congruence: 0.6\n",
      "reached till commits:  257\n",
      "CR_count: 2\n",
      "diff_count: 2\n",
      "congruence: 1.0\n",
      "reached till commits:  262\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  286\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  317\n",
      "CR_count: 5\n",
      "diff_count: 3\n",
      "congruence: 0.6\n",
      "reached till commits:  329\n",
      "CR_count: 9\n",
      "diff_count: 5\n",
      "congruence: 0.5555555555555556\n",
      "reached till commits:  364\n",
      "CR_count: 2\n",
      "diff_count: 2\n",
      "congruence: 1.0\n",
      "reached till commits:  373\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  395\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  409\n",
      "CR_count: 2\n",
      "diff_count: 2\n",
      "congruence: 1.0\n",
      "reached till commits:  421\n",
      "CR_count: 2\n",
      "diff_count: 2\n",
      "congruence: 1.0\n",
      "reached till commits:  424\n",
      "CR_count: 5\n",
      "diff_count: 3\n",
      "congruence: 0.6\n",
      "reached till commits:  433\n",
      "CR_count: 9\n",
      "diff_count: 3\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  507\n",
      "CR_count: 14\n",
      "diff_count: 4\n",
      "congruence: 0.2857142857142857\n",
      "reached till commits:  546\n",
      "CR_count: 14\n",
      "diff_count: 4\n",
      "congruence: 0.2857142857142857\n",
      "reached till commits:  574\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  587\n",
      "CR_count: 7\n",
      "diff_count: 3\n",
      "congruence: 0.42857142857142855\n",
      "reached till commits:  607\n",
      "CR_count: 9\n",
      "diff_count: 3\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  643\n",
      "CR_count: 10\n",
      "diff_count: 4\n",
      "congruence: 0.4\n",
      "reached till commits:  695\n",
      "CR_count: 9\n",
      "diff_count: 5\n",
      "congruence: 0.5555555555555556\n",
      "reached till commits:  733\n",
      "CR_count: 21\n",
      "diff_count: 7\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  778\n",
      "CR_count: 7\n",
      "diff_count: 3\n",
      "congruence: 0.42857142857142855\n",
      "reached till commits:  787\n",
      "CR_count: 15\n",
      "diff_count: 9\n",
      "congruence: 0.6\n",
      "reached till commits:  816\n",
      "CR_count: 16\n",
      "diff_count: 4\n",
      "congruence: 0.25\n",
      "reached till commits:  897\n",
      "CR_count: 9\n",
      "diff_count: 3\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  964\n",
      "CR_count: 10\n",
      "diff_count: 4\n",
      "congruence: 0.4\n",
      "reached till commits:  1025\n",
      "CR_count: 16\n",
      "diff_count: 4\n",
      "congruence: 0.25\n",
      "reached till commits:  1088\n",
      "CR_count: 8\n",
      "diff_count: 4\n",
      "congruence: 0.5\n",
      "reached till commits:  1120\n",
      "CR_count: 140\n",
      "diff_count: 30\n",
      "congruence: 0.21428571428571427\n",
      "reached till commits:  1455\n",
      "CR_count: 23\n",
      "diff_count: 9\n",
      "congruence: 0.391304347826087\n",
      "reached till commits:  1499\n",
      "CR_count: 8\n",
      "diff_count: 4\n",
      "congruence: 0.5\n",
      "reached till commits:  1529\n",
      "CR_count: 36\n",
      "diff_count: 14\n",
      "congruence: 0.3888888888888889\n",
      "reached till commits:  1634\n",
      "CR_count: 17\n",
      "diff_count: 5\n",
      "congruence: 0.29411764705882354\n",
      "reached till commits:  1688\n",
      "CR_count: 8\n",
      "diff_count: 4\n",
      "congruence: 0.5\n",
      "reached till commits:  1724\n",
      "CR_count: 4\n",
      "diff_count: 2\n",
      "congruence: 0.5\n",
      "reached till commits:  1737\n",
      "CR_count: 8\n",
      "diff_count: 4\n",
      "congruence: 0.5\n",
      "reached till commits:  1750\n",
      "CR_count: 3\n",
      "diff_count: 3\n",
      "congruence: 1.0\n",
      "reached till commits:  1761\n",
      "CR_count: 25\n",
      "diff_count: 5\n",
      "congruence: 0.2\n",
      "reached till commits:  1816\n",
      "CR_count: 30\n",
      "diff_count: 8\n",
      "congruence: 0.26666666666666666\n",
      "reached till commits:  1867\n",
      "CR_count: 18\n",
      "diff_count: 8\n",
      "congruence: 0.4444444444444444\n",
      "reached till commits:  1890\n",
      "CR_count: 38\n",
      "diff_count: 18\n",
      "congruence: 0.47368421052631576\n",
      "reached till commits:  1947\n",
      "CR_count: 65\n",
      "diff_count: 31\n",
      "congruence: 0.47692307692307695\n",
      "reached till commits:  2046\n",
      "CR_count: 15\n",
      "diff_count: 7\n",
      "congruence: 0.4666666666666667\n",
      "reached till commits:  2095\n",
      "CR_count: 22\n",
      "diff_count: 6\n",
      "congruence: 0.2727272727272727\n",
      "reached till commits:  2138\n",
      "CR_count: 38\n",
      "diff_count: 8\n",
      "congruence: 0.21052631578947367\n",
      "reached till commits:  2200\n",
      "CR_count: 29\n",
      "diff_count: 7\n",
      "congruence: 0.2413793103448276\n",
      "reached till commits:  2243\n",
      "CR_count: 25\n",
      "diff_count: 5\n",
      "congruence: 0.2\n",
      "reached till commits:  2297\n",
      "CR_count: 43\n",
      "diff_count: 23\n",
      "congruence: 0.5348837209302325\n",
      "reached till commits:  2344\n",
      "CR_count: 28\n",
      "diff_count: 8\n",
      "congruence: 0.2857142857142857\n",
      "reached till commits:  2375\n",
      "CR_count: 64\n",
      "diff_count: 8\n",
      "congruence: 0.125\n",
      "reached till commits:  2424\n",
      "CR_count: 123\n",
      "diff_count: 21\n",
      "congruence: 0.17073170731707318\n",
      "reached till commits:  2550\n",
      "CR_count: 102\n",
      "diff_count: 22\n",
      "congruence: 0.21568627450980393\n",
      "reached till commits:  2681\n",
      "CR_count: 117\n",
      "diff_count: 35\n",
      "congruence: 0.29914529914529914\n",
      "reached till commits:  2829\n",
      "CR_count: 101\n",
      "diff_count: 27\n",
      "congruence: 0.26732673267326734\n",
      "reached till commits:  2970\n",
      "CR_count: 101\n",
      "diff_count: 21\n",
      "congruence: 0.2079207920792079\n",
      "reached till commits:  3077\n",
      "CR_count: 81\n",
      "diff_count: 33\n",
      "congruence: 0.4074074074074074\n",
      "reached till commits:  3169\n",
      "CR_count: 110\n",
      "diff_count: 32\n",
      "congruence: 0.2909090909090909\n",
      "reached till commits:  3294\n",
      "CR_count: 94\n",
      "diff_count: 34\n",
      "congruence: 0.3617021276595745\n",
      "reached till commits:  3423\n",
      "CR_count: 122\n",
      "diff_count: 30\n",
      "congruence: 0.2459016393442623\n",
      "reached till commits:  3514\n",
      "CR_count: 51\n",
      "diff_count: 17\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  3568\n",
      "CR_count: 82\n",
      "diff_count: 28\n",
      "congruence: 0.34146341463414637\n",
      "reached till commits:  3628\n",
      "CR_count: 72\n",
      "diff_count: 18\n",
      "congruence: 0.25\n",
      "reached till commits:  3709\n",
      "CR_count: 82\n",
      "diff_count: 10\n",
      "congruence: 0.12195121951219512\n",
      "reached till commits:  3772\n",
      "CR_count: 66\n",
      "diff_count: 22\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  3862\n",
      "CR_count: 65\n",
      "diff_count: 21\n",
      "congruence: 0.3230769230769231\n",
      "reached till commits:  3958\n",
      "CR_count: 52\n",
      "diff_count: 10\n",
      "congruence: 0.19230769230769232\n",
      "reached till commits:  4042\n",
      "CR_count: 66\n",
      "diff_count: 10\n",
      "congruence: 0.15151515151515152\n",
      "reached till commits:  4128\n",
      "CR_count: 83\n",
      "diff_count: 11\n",
      "congruence: 0.13253012048192772\n",
      "reached till commits:  4193\n",
      "CR_count: 43\n",
      "diff_count: 15\n",
      "congruence: 0.3488372093023256\n",
      "reached till commits:  4236\n",
      "CR_count: 128\n",
      "diff_count: 32\n",
      "congruence: 0.25\n",
      "reached till commits:  4315\n",
      "CR_count: 102\n",
      "diff_count: 28\n",
      "congruence: 0.27450980392156865\n",
      "reached till commits:  4389\n",
      "CR_count: 67\n",
      "diff_count: 13\n",
      "congruence: 0.19402985074626866\n",
      "reached till commits:  4510\n",
      "CR_count: 142\n",
      "diff_count: 42\n",
      "congruence: 0.29577464788732394\n",
      "reached till commits:  4670\n",
      "CR_count: 174\n",
      "diff_count: 70\n",
      "congruence: 0.40229885057471265\n",
      "reached till commits:  4774\n",
      "CR_count: 85\n",
      "diff_count: 11\n",
      "congruence: 0.12941176470588237\n",
      "reached till commits:  4866\n",
      "CR_count: 122\n",
      "diff_count: 12\n",
      "congruence: 0.09836065573770492\n",
      "reached till commits:  4961\n",
      "CR_count: 144\n",
      "diff_count: 34\n",
      "congruence: 0.2361111111111111\n",
      "reached till commits:  5113\n",
      "CR_count: 92\n",
      "diff_count: 26\n",
      "congruence: 0.2826086956521739\n",
      "reached till commits:  5193\n",
      "CR_count: 107\n",
      "diff_count: 31\n",
      "congruence: 0.2897196261682243\n",
      "reached till commits:  5298\n",
      "CR_count: 78\n",
      "diff_count: 40\n",
      "congruence: 0.5128205128205128\n",
      "reached till commits:  5411\n",
      "CR_count: 68\n",
      "diff_count: 24\n",
      "congruence: 0.35294117647058826\n",
      "reached till commits:  5502\n",
      "CR_count: 70\n",
      "diff_count: 12\n",
      "congruence: 0.17142857142857143\n",
      "reached till commits:  5618\n",
      "CR_count: 125\n",
      "diff_count: 37\n",
      "congruence: 0.296\n",
      "reached till commits:  5813\n",
      "CR_count: 169\n",
      "diff_count: 43\n",
      "congruence: 0.25443786982248523\n",
      "reached till commits:  5974\n",
      "CR_count: 142\n",
      "diff_count: 42\n",
      "congruence: 0.29577464788732394\n",
      "reached till commits:  6149\n",
      "CR_count: 196\n",
      "diff_count: 14\n",
      "congruence: 0.07142857142857142\n",
      "reached till commits:  6470\n",
      "CR_count: 289\n",
      "diff_count: 35\n",
      "congruence: 0.12110726643598616\n",
      "reached till commits:  6706\n",
      "CR_count: 227\n",
      "diff_count: 77\n",
      "congruence: 0.3392070484581498\n",
      "reached till commits:  6949\n",
      "CR_count: 144\n",
      "diff_count: 12\n",
      "congruence: 0.08333333333333333\n",
      "reached till commits:  7147\n",
      "CR_count: 190\n",
      "diff_count: 70\n",
      "congruence: 0.3684210526315789\n",
      "reached till commits:  7301\n",
      "CR_count: 142\n",
      "diff_count: 36\n",
      "congruence: 0.2535211267605634\n",
      "reached till commits:  7415\n",
      "CR_count: 120\n",
      "diff_count: 40\n",
      "congruence: 0.3333333333333333\n",
      "reached till commits:  7523\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CR_count: 81\n",
      "diff_count: 31\n",
      "congruence: 0.38271604938271603\n",
      "reached till commits:  7620\n"
     ]
    }
   ],
   "source": [
    "from pydriller import Repository\n",
    "import json\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "\n",
    "\n",
    "steps = []\n",
    "congruences = []\n",
    "commits = list(Repository(url).traverse_commits())\n",
    "delta = datetime.timedelta(weeks=4)\n",
    "# step = int(len(commits)/100)\n",
    "# for k in range(0,len(commits), step):\n",
    "for k in range(0, len(no_of_commits)-1):\n",
    "    i = 0\n",
    "    file_to_users = {}  ## for each file how many users commited\n",
    "    file_to_id = {}     ##\n",
    "    tmp_commits = commits[total_commits[k]:total_commits[k+1]]\n",
    "    print(\"reached till commits: \",total_commits[k])\n",
    "#     if(len(tmp_commits)<step):\n",
    "#         break\n",
    "    for commit in tmp_commits:\n",
    "        #print('The commit  has been modified by {} on {} and files changed are {}\\n'.\n",
    "              #format(commit.author.email,commit.committer_date,[x.filename for x in commit.modified_files]))\n",
    "        \n",
    "        \n",
    "        for x in commit.modified_files:\n",
    "            if x.filename not in file_to_users:\n",
    "                file_to_users[x.filename] = set()\n",
    "                file_to_users[x.filename].add(str(commit.author.email))\n",
    "                if x.filename not in file_to_id:\n",
    "                    file_to_id[x.filename] = i\n",
    "                    i = i+1\n",
    "            else:\n",
    "                file_to_users[x.filename].add(str(commit.author.email))\n",
    "                if x.filename not in file_to_id:\n",
    "                    file_to_id[x.filename] = i\n",
    "                    i = i+1\n",
    "\n",
    "\n",
    "    ### Identifing unique users for each files\n",
    "    unique_users_dict = {}\n",
    "    unique_users = set()\n",
    "    i = 0\n",
    "    for x in file_to_users.keys():\n",
    "        file_to_users[x] = list(file_to_users[x])\n",
    "        for user in file_to_users[x]:\n",
    "            if user not in unique_users_dict:\n",
    "                unique_users_dict[user] = i\n",
    "                i=i+1\n",
    "            unique_users.add(user)\n",
    "\n",
    "\n",
    "    ### Calculation of Actual Coordination - fct (file changed together)\n",
    "    ## Assumption - 1 files - n developers have changed it. So they would have communicated at one point. \n",
    "\n",
    "    list_unique_users = unique_users\n",
    "    AC = [[0]*len(list_unique_users) for x in range(0,len(list_unique_users))]\n",
    "\n",
    "    for key in file_to_users.keys():\n",
    "        users = file_to_users[key]\n",
    "        for i in range(0, len(users)):\n",
    "            for j in range(i+1,len(users)):\n",
    "                AC[unique_users_dict[users[i]]][unique_users_dict[users[j]]] = 1\n",
    "                AC[unique_users_dict[users[j]]][unique_users_dict[users[i]]] = 1\n",
    "\n",
    "\n",
    "    ### Calculation of Coordination needs matrix: TA * TD * TAT\n",
    "\n",
    "    CR = []\n",
    "    TA = [[0]*len(file_to_users.keys()) for x in range(0,len(list_unique_users))]\n",
    "    TD = [[0]*len(file_to_users.keys()) for x in range(0,len(file_to_users.keys()))]   \n",
    "    ### TD - m * m; m = number of files TD[i][j] = ith file and jth file are dependent on each other.\n",
    "    ### if in commit they are changed togteher they are dependent. So we have assumption of undirected graph.\n",
    "\n",
    "    for key in file_to_users.keys():\n",
    "        list_of_users = file_to_users[key]\n",
    "        for x in list_of_users:\n",
    "            TA[unique_users_dict[x]][file_to_id[key]] = 1 \n",
    "\n",
    "    for commit in tmp_commits:\n",
    "        modified_files_in_commit = commit.modified_files\n",
    "        for i in range(0, len(modified_files_in_commit)):\n",
    "            for j in range(i, len(modified_files_in_commit)):\n",
    "                TD[file_to_id[modified_files_in_commit[i].filename]][file_to_id[modified_files_in_commit[j].filename]] = 1\n",
    "                TD[file_to_id[modified_files_in_commit[j].filename]][file_to_id[modified_files_in_commit[i].filename]] = 1\n",
    "\n",
    "\n",
    "    TA = pd.DataFrame(TA)\n",
    "    TD = pd.DataFrame(TD)\n",
    "    AC = pd.DataFrame(AC)\n",
    "    \n",
    "    CR = TA @ TD @ TA.T  \n",
    "    \n",
    "    CR_normalised = CR / CR.max(axis=0)\n",
    "    diff =  (CR_normalised - AC)\n",
    "    \n",
    "    CR_count=0\n",
    "    for i in range(0, len(CR_normalised)):\n",
    "        for j in range(len(CR_normalised[0])):\n",
    "            if CR_normalised[i][j] > 0:\n",
    "                CR_count+=1\n",
    "#     print(\"step:\", step)\n",
    "    print('CR_count:', CR_count)\n",
    "    \n",
    "    diff_count=0\n",
    "    for i in range(0, len(diff)):\n",
    "        for j in range(len(diff[0])):\n",
    "            if diff[i][j] > 0:\n",
    "                diff_count+=1\n",
    "    print('diff_count:', diff_count)\n",
    "    if CR_count!=0:\n",
    "        congruence = diff_count / CR_count\n",
    "        print('congruence:',congruence)\n",
    "        congruences.append(congruence)\n",
    "    else:\n",
    "        congruences.append(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(total_commits[1:], congruences)\n",
    "plt.title(\"Changes in STC as the no. of commits increases\", fontsize = 13)\n",
    "plt.xlabel(\"No/ of commits\", fontsize=13)\n",
    "plt.ylabel(\"Congruence\", fontsize = 13)\n",
    "plt.ylim(0,1)\n",
    "plt.savefig('images/'+repo+'.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "x_axis1 = [0]\n",
    "for i in range(1, len(no_of_commits)):\n",
    "    x_axis1.append(x_axis1[i-1] + 1)\n",
    "\n",
    "\n",
    "plt.figure(figsize =(10,6))\n",
    "plt.bar(x_axis1, no_of_commits)\n",
    "plt.xlabel(\"No. of months\", fontsize =18)\n",
    "plt.ylabel(\"No.of commits\", fontsize =18)\n",
    "plt.title(\"No.of commits per month\" , fontsize =20)\n",
    "plt.savefig('images/'+repo+'1.png')\n",
    "plt.show()\n",
    "\n",
    "print(x_axis1)\n",
    "print(no_of_commits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize =(10,6))\n",
    "plt.bar(x_axis1, total_commits)\n",
    "plt.xlabel(\"No. of months\", fontsize =18)\n",
    "plt.ylabel(\"No.of commits\", fontsize =18)\n",
    "plt.title(\"No.of commits as months passed by\", fontsize = 20)\n",
    "plt.savefig('images/'+repo+'2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "noofmonths = x_axis1[1:]\n",
    "noofcommits = no_of_commits[1:]\n",
    "print(len(noofcommits))\n",
    "name = 'csv files/'+repo + '.csv'\n",
    "dict = {'no_of_months': noofmonths, 'no_of_commits': noofcommits, 'congruences': congruences}  \n",
    "       \n",
    "df = pd.DataFrame(dict) \n",
    "    \n",
    "# saving the dataframe \n",
    "df.to_csv(name) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirname = 'csv files\\Current'\n",
    "filenames= []\n",
    "cgr = []\n",
    "curr_cgr_mean = []\n",
    "for filename in os.listdir(dirname):\n",
    "    f = os.path.join(dirname, filename)\n",
    "    filenames.append(filename)\n",
    "    df = pd.read_csv(f)\n",
    "    df = df.fillna(value=0)\n",
    "    curr_cgr_mean.append(df['congruences'].mean())\n",
    "    cgr = cgr + list(df['congruences'])\n",
    "\n",
    "cgr = np.array(cgr)\n",
    "print('Mean Congruence of current projects is:', cgr.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Mean of each current project is:', curr_cgr_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "c_cgr1=[]\n",
    "for x in cgr:\n",
    "    if x!=1.0:\n",
    "        c_cgr1.append(x)\n",
    "print(np.array(c_cgr1).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirname = 'csv files\\Retired'\n",
    "filenames= []\n",
    "r_cgr = []\n",
    "ret_cgr_mean = []\n",
    "for filename in os.listdir(dirname):\n",
    "    f = os.path.join(dirname, filename)\n",
    "    filenames.append(filename)\n",
    "    df = pd.read_csv(f)\n",
    "    df = df.fillna(value=0)\n",
    "    ret_cgr_mean.append(df['congruences'].mean())\n",
    "    r_cgr = r_cgr + list(df['congruences'])\n",
    "    \n",
    "r_cgr = np.array(r_cgr)\n",
    "print('Mean Congruence of Retired projects is:',r_cgr.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Mean of each retired project is:', ret_cgr_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_cgr1=[]\n",
    "for x in r_cgr:\n",
    "    if x!=1.0:\n",
    "        r_cgr1.append(x)\n",
    "print(np.array(r_cgr1).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dirname = 'csv files\\Graduated'\n",
    "filenames= []\n",
    "g_cgr = []\n",
    "gra_cgr_mean = []\n",
    "for filename in os.listdir(dirname):\n",
    "    f = os.path.join(dirname, filename)\n",
    "    filenames.append(filename)\n",
    "    df = pd.read_csv(f)\n",
    "    df = df.fillna(value=0)\n",
    "    gra_cgr_mean.append(df['congruences'].mean())\n",
    "    g_cgr += list(df['congruences'])\n",
    "\n",
    "g_cgr = np.array(g_cgr)\n",
    "print('Mean Congruence of Graduated projects is:', g_cgr.mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Mean of each Graduated project is:', gra_cgr_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "g_cgr1=[]\n",
    "for x in g_cgr:\n",
    "    if x!=1.0:\n",
    "        g_cgr1.append(x)\n",
    "print(np.array(g_cgr1).mean())"
   ]
  }
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