{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "In this blog post, I want to show you how you can visualize the contributions of developers to your code base over time. I came across the [Stream Graph visualization](http://leebyron.com/streamgraph/) and it looks like it would fit quite nicely for this purpose. Fortunately, there is already a [D3 template by William Turman](http://bl.ocks.org/WillTurman/4631136) for this that I use in this blog post:\n",
    "\n",
    "![](https://feststelltaste.github.io/software-analytics/notebooks/resources/streamgraph_example.png)\n",
    "\n",
    "So let's prototype some visualizations!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Getting the data\n",
    "At the beginning, we declare some general variables for easy access and to reuse them for other repositories easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "PROJECT = \"intellij-community\"\n",
    "SOURCE_CODE_FILE_EXTENSION = \".java\"\n",
    "TIME_FREQUENCY = \"Q\" # how should data be grouped? 'Q' means quarterly\n",
    "\n",
    "FILENAME_PREFIX = \"vis/interactive_streamgraph/\"\n",
    "FILENAME_SUFFIX = \"_\" + PROJECT + \"_\" + TIME_FREQUENCY"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, I'm using the rather big repository of [IntelliJ](https://github.com/JetBrains/intellij-community) which is written in Java.\n",
    "\n",
    "We import the existing Git log file with file statistics that was generated using\n",
    "```bash\n",
    "git log --numstat --pretty=format:\"%x09%x09%x09%h%x09%at%x09%aN\" > git_numstat.log\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>additions</th>\n",
       "      <th>deletions</th>\n",
       "      <th>filename</th>\n",
       "      <th>sha</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>author</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>platform/smRunner/src/com/intellij/execution/t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>platform/smRunner/testSrc/com/intellij/executi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  additions deletions                                           filename  \\\n",
       "0       NaN       NaN                                                NaN   \n",
       "1        12         3  platform/smRunner/src/com/intellij/execution/t...   \n",
       "2        45         0  platform/smRunner/testSrc/com/intellij/executi...   \n",
       "3         7         6  platform/testRunner/src/com/intellij/execution...   \n",
       "4         9         0  platform/testRunner/src/com/intellij/execution...   \n",
       "\n",
       "           sha     timestamp            author  \n",
       "0  db2987a9533  1.507984e+09  Sergey Simonchik  \n",
       "1          NaN           NaN               NaN  \n",
       "2          NaN           NaN               NaN  \n",
       "3          NaN           NaN               NaN  \n",
       "4          NaN           NaN               NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "logfile = \"../../{}/git_numstat.log\".format(PROJECT)\n",
    "git_log = pd.read_csv(\n",
    "    logfile,\n",
    "    sep=\"\\t\", \n",
    "    header=None,\n",
    "    names=[\n",
    "        'additions', \n",
    "        'deletions', \n",
    "        'filename', \n",
    "        'sha', \n",
    "        'timestamp', \n",
    "        'author'])\n",
    "git_log.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The logfile contains the added and deleted lines of code for each file in each commit of an author. \n",
    "\n",
    "This file has over 1M entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1025412"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(git_log)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The repository itself has over 200k individual commits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "205799"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "git_log['sha'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and almost 400 different contributors (Note: I created a separate `.mailmap` file locally to avoid multiple author names for the same person)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "371"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "git_log['author'].value_counts().size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We mold the raw data to get a nice list of all committed files including additions and deletions by each author. You can find details about this approach in [Reading a Git repo's commit history with Pandas efficiently](https://www.feststelltaste.de/reading-a-git-repos-commit-history-with-pandas-efficiently/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>additions</th>\n",
       "      <th>deletions</th>\n",
       "      <th>filename</th>\n",
       "      <th>sha</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>author</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>platform/smRunner/src/com/intellij/execution/t...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>platform/smRunner/testSrc/com/intellij/executi...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>1.507984e+09</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  additions deletions                                           filename  \\\n",
       "1        12         3  platform/smRunner/src/com/intellij/execution/t...   \n",
       "2        45         0  platform/smRunner/testSrc/com/intellij/executi...   \n",
       "3         7         6  platform/testRunner/src/com/intellij/execution...   \n",
       "4         9         0  platform/testRunner/src/com/intellij/execution...   \n",
       "5        16         3  platform/testRunner/src/com/intellij/execution...   \n",
       "\n",
       "           sha     timestamp            author  \n",
       "1  db2987a9533  1.507984e+09  Sergey Simonchik  \n",
       "2  db2987a9533  1.507984e+09  Sergey Simonchik  \n",
       "3  db2987a9533  1.507984e+09  Sergey Simonchik  \n",
       "4  db2987a9533  1.507984e+09  Sergey Simonchik  \n",
       "5  db2987a9533  1.507984e+09  Sergey Simonchik  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commits = git_log[['additions', 'deletions', 'filename']]\\\n",
    "    .join(git_log[['sha', 'timestamp', 'author']]\\\n",
    "    .fillna(method='ffill'))\\\n",
    "    .dropna()\n",
    "commits.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We further do some basic filtering (because we only want the Java source code) and some data type conversions. Additionally, we calculate a new column that holds the number of `modifications` (added and deleted lines of source code)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th {\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>additions</th>\n",
       "      <th>deletions</th>\n",
       "      <th>filename</th>\n",
       "      <th>sha</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>author</th>\n",
       "      <th>modifications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>platform/smRunner/src/com/intellij/execution/t...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>platform/smRunner/testSrc/com/intellij/executi...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     additions  deletions  \\\n",
       "timestamp                                   \n",
       "2017-10-14 12:26:59       12.0        3.0   \n",
       "2017-10-14 12:26:59       45.0        0.0   \n",
       "2017-10-14 12:26:59        7.0        6.0   \n",
       "2017-10-14 12:26:59        9.0        0.0   \n",
       "2017-10-14 12:26:59       16.0        3.0   \n",
       "\n",
       "                                                              filename  \\\n",
       "timestamp                                                                \n",
       "2017-10-14 12:26:59  platform/smRunner/src/com/intellij/execution/t...   \n",
       "2017-10-14 12:26:59  platform/smRunner/testSrc/com/intellij/executi...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "\n",
       "                             sha           timestamp            author  \\\n",
       "timestamp                                                                \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "\n",
       "                     modifications  \n",
       "timestamp                           \n",
       "2017-10-14 12:26:59           15.0  \n",
       "2017-10-14 12:26:59           45.0  \n",
       "2017-10-14 12:26:59           13.0  \n",
       "2017-10-14 12:26:59            9.0  \n",
       "2017-10-14 12:26:59           19.0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commits = commits[commits['filename'].str.endswith(SOURCE_CODE_FILE_EXTENSION)]\n",
    "commits['additions'] = pd.to_numeric(commits['additions'], errors='coerce').dropna()\n",
    "commits['deletions'] = pd.to_numeric(commits['deletions'], errors='coerce').dropna()\n",
    "commits['timestamp'] = pd.to_datetime(commits['timestamp'], unit=\"s\")\n",
    "commits = commits.set_index(commits['timestamp'])\n",
    "commits['modifications'] = commits['additions'] + commits['deletions']\n",
    "commits.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next step is optional and some basic data cleaning. It just filters out any nonsense commits that were cause by wrong timestamp configuration of some committers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>additions</th>\n",
       "      <th>deletions</th>\n",
       "      <th>filename</th>\n",
       "      <th>sha</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>author</th>\n",
       "      <th>modifications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>platform/smRunner/src/com/intellij/execution/t...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>platform/smRunner/testSrc/com/intellij/executi...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-14 12:26:59</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>platform/testRunner/src/com/intellij/execution...</td>\n",
       "      <td>db2987a9533</td>\n",
       "      <td>2017-10-14 12:26:59</td>\n",
       "      <td>Sergey Simonchik</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     additions  deletions  \\\n",
       "timestamp                                   \n",
       "2017-10-14 12:26:59       12.0        3.0   \n",
       "2017-10-14 12:26:59       45.0        0.0   \n",
       "2017-10-14 12:26:59        7.0        6.0   \n",
       "2017-10-14 12:26:59        9.0        0.0   \n",
       "2017-10-14 12:26:59       16.0        3.0   \n",
       "\n",
       "                                                              filename  \\\n",
       "timestamp                                                                \n",
       "2017-10-14 12:26:59  platform/smRunner/src/com/intellij/execution/t...   \n",
       "2017-10-14 12:26:59  platform/smRunner/testSrc/com/intellij/executi...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "2017-10-14 12:26:59  platform/testRunner/src/com/intellij/execution...   \n",
       "\n",
       "                             sha           timestamp            author  \\\n",
       "timestamp                                                                \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "2017-10-14 12:26:59  db2987a9533 2017-10-14 12:26:59  Sergey Simonchik   \n",
       "\n",
       "                     modifications  \n",
       "timestamp                           \n",
       "2017-10-14 12:26:59           15.0  \n",
       "2017-10-14 12:26:59           45.0  \n",
       "2017-10-14 12:26:59           13.0  \n",
       "2017-10-14 12:26:59            9.0  \n",
       "2017-10-14 12:26:59           19.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commits = commits[commits['timestamp'] <= 'today']\n",
    "initial_commit_date = commits[-1:]['timestamp'].values[0]\n",
    "commits = commits[commits['timestamp'] >= initial_commit_date]\n",
    "commits.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summarizing the data\n",
    "In this section, we group the data to achieve a meaningful visualization with Stream Graphs. We do this by grouping all relevant data of the commits by author and quarters (`TIME_FREQUENCY` is set to `Q` = quarterly). We reset the index because we don't need it in the following."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>modifications</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2012-03-31</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adam Batkin</td>\n",
       "      <td>2015-12-31</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Adrian Teng</td>\n",
       "      <td>2014-12-31</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aleksandr Samofalov</td>\n",
       "      <td>2016-03-31</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aleksandr Samofalov</td>\n",
       "      <td>2016-06-30</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    author  timestamp  modifications\n",
       "0  (dboulytchev@gmail.com) 2012-03-31          126.0\n",
       "1              Adam Batkin 2015-12-31            2.0\n",
       "2              Adrian Teng 2014-12-31           10.0\n",
       "3      Aleksandr Samofalov 2016-03-31           29.0\n",
       "4      Aleksandr Samofalov 2016-06-30           26.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modifications_over_time = commits[['author', 'timestamp', 'modifications']].groupby(\n",
    "    [commits['author'], \n",
    "     pd.Grouper(freq=TIME_FREQUENCY)]).sum().reset_index()\n",
    "modifications_over_time.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also do some primitive outlier treatment by limiting the number of modifications to lower than the 99% quantile of the whole data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "modifications         697744.00\n",
       "modifications_norm     51262.46\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modifications_over_time['modifications_norm'] = modifications_over_time['modifications'].clip_upper(\n",
    "    modifications_over_time['modifications'].quantile(0.99))\n",
    "modifications_over_time[['modifications', 'modifications_norm']].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we pivot the DataFrame to get the modifications for each author over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>author</th>\n",
       "      <th>(dboulytchev@gmail.com)</th>\n",
       "      <th>Adam Batkin</th>\n",
       "      <th>Adrian Teng</th>\n",
       "      <th>Aleksandr Samofalov</th>\n",
       "      <th>Aleksey Pivovarov</th>\n",
       "      <th>Aleksey Rostovskiy</th>\n",
       "      <th>Aleksey Zezukin</th>\n",
       "      <th>Alex Ruiz</th>\n",
       "      <th>Alexander Chernikov</th>\n",
       "      <th>Alexander Doroshko</th>\n",
       "      <th>...</th>\n",
       "      <th>shanavas</th>\n",
       "      <th>shkate</th>\n",
       "      <th>siosio</th>\n",
       "      <th>spLeaner</th>\n",
       "      <th>stsypanov</th>\n",
       "      <th>svloyso</th>\n",
       "      <th>sweinreuter</th>\n",
       "      <th>unknown</th>\n",
       "      <th>vadim.lomshakov</th>\n",
       "      <th>yole</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-03-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-06-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-09-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 344 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "author      (dboulytchev@gmail.com)  Adam Batkin  Adrian Teng  \\\n",
       "timestamp                                                       \n",
       "2004-12-31                      NaN          NaN          NaN   \n",
       "2005-03-31                      NaN          NaN          NaN   \n",
       "2005-06-30                      NaN          NaN          NaN   \n",
       "2005-09-30                      NaN          NaN          NaN   \n",
       "2005-12-31                      NaN          NaN          NaN   \n",
       "\n",
       "author      Aleksandr Samofalov  Aleksey Pivovarov  Aleksey Rostovskiy  \\\n",
       "timestamp                                                                \n",
       "2004-12-31                  NaN                NaN                 NaN   \n",
       "2005-03-31                  NaN                NaN                 NaN   \n",
       "2005-06-30                  NaN                NaN                 NaN   \n",
       "2005-09-30                  NaN                NaN                 NaN   \n",
       "2005-12-31                  NaN                NaN                 NaN   \n",
       "\n",
       "author      Aleksey Zezukin  Alex Ruiz  Alexander Chernikov  \\\n",
       "timestamp                                                     \n",
       "2004-12-31              NaN        NaN                  NaN   \n",
       "2005-03-31              NaN        NaN                  NaN   \n",
       "2005-06-30              NaN        NaN                  NaN   \n",
       "2005-09-30              NaN        NaN                  NaN   \n",
       "2005-12-31              NaN        NaN                  NaN   \n",
       "\n",
       "author      Alexander Doroshko  ...   shanavas  shkate  siosio  spLeaner  \\\n",
       "timestamp                       ...                                        \n",
       "2004-12-31                 NaN  ...        NaN     NaN     NaN       NaN   \n",
       "2005-03-31                 NaN  ...        NaN     NaN     NaN       NaN   \n",
       "2005-06-30                 NaN  ...        NaN     NaN     NaN       NaN   \n",
       "2005-09-30                 NaN  ...        NaN     NaN     NaN       NaN   \n",
       "2005-12-31                 NaN  ...        NaN     NaN     NaN       NaN   \n",
       "\n",
       "author      stsypanov  svloyso  sweinreuter  unknown  vadim.lomshakov  yole  \n",
       "timestamp                                                                    \n",
       "2004-12-31        NaN      NaN          NaN      NaN              NaN   NaN  \n",
       "2005-03-31        NaN      NaN          NaN      NaN              NaN   NaN  \n",
       "2005-06-30        NaN      NaN          NaN      NaN              NaN   NaN  \n",
       "2005-09-30        NaN      NaN          NaN      NaN              NaN   NaN  \n",
       "2005-12-31        NaN      NaN          NaN      NaN              NaN   NaN  \n",
       "\n",
       "[5 rows x 344 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modifications_per_authors_over_time = modifications_over_time.reset_index().pivot_table(\n",
    "    index=modifications_over_time['timestamp'], \n",
    "    columns=modifications_over_time['author'], \n",
    "    values='modifications_norm')\n",
    "modifications_per_authors_over_time.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ugly visualization\n",
    "At this point, we could already plot the data with the built-in `plot` function of Pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1e3297a5898>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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O2dPO5nmlpPUDm1Z87ve+73c/o+iZp5m1LcRpz5VzzzcWyHIVcdSShFsIIUbI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\nmbWugm43dKROwaTN2CLj0PF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2MW64d6va6n1Go+m9nDm/PyQIxKaYmOzv2q/u6xrr+Ize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RhjafThLx5u3X/GN1And5AwLEUbc2IUTKj6EnQWCsxrDHDrT7/1qTb++ue7Ke+W6JihRaOVUQk6\n/lS8inldQ/gDxcQiIU4aO0I0eYwrwrvoVbt4U9aTKZvo0znwbF+LXRMhd91eevbOIxG1k7twB7fs\neeALj+uLcmf9HeQt2kEybqZ312Iya3Zhz5yks3UVJW1n8ap6nCflBVgykty27y5Of2Mb79TW0FZg\n493V7Wwe8nKe1MzD6mo2m028MPF9tsVPoV9x4ZDGkSMmEqkUYZOIOZLmhb/+ezse/2A6h3uaaab5\nynHnr37Iyo4kHaVqtCoZczATSZMiLMv84J1HUASBiDmJMVrMZEYJMIHN1/+F+xMjPehTMFqQi1iQ\nSaKtAk1qJ2LMh9gXIiomiDuGsQeySGmXYkwuQK9rIuBoAc/Q+3Y0zhzSKR0R/RgF+UEURcAT1aMO\nN6PSWFA0dgL2Plq0G9gwtpMF7zah03yNikQXQWsKy+TUqu9IvBuXO0SwdQjDZB1tzu2oEh4MgCcT\nMsemTtYr6TT3fO8iHBO9FPSGWOZ9T7XPCfU1ejyFxcTUuaRkBXtEQ2m0goTSzrgjSl7UwDnmFt7W\nzsdn1VLUWYikCeIXZAz5HUT8uYQ6x6l2LOeY790PJiuvAMKnoI820VGm8KZjBStCBynel2TesUZU\nShp7ZIRlB3+PNXgupSfv4K9VdexZmMWGgb3c07KBM21vUe13TSnxpRaS0JtJaZ/nhfVn4Ep7iHbo\nSOr7aTCGqInYSKsUmgxxFkeyyDEFKOKTc1ud+HHiJw10UUYUM8vYxVre5gH7mRQmm+k2dnLzA630\nXmejyehlz5JSlu3r5qLtu7n5hIsZz+nG6q8hw19IOO4jMVqIwRBAP5zPYWcF8xPHAYGYJYhfhqyU\nhYA5Exigun7qfvC5iilKdGAf7gbHTNbqnmeLdiWSepDkRARZm4cs1jPkbOWIKYbjiuUsSPYSzOhD\nF12EFTeplgG0eXGOV+TDONzt/h53bb6T5HUGVpY+zLLok4AACCj/iIOVf6igCij/53+ARMDNXcv+\ngxWHdzFjMEjcuIEMg42JkX3s8BfiK7NyRfxlbL7V3GLtIWn5+Dk+fbiOIlFhQbyFOmVKfOY4BTxm\n2MiE4qRYGeCcxDucgImnR0/mMeMhYpYvTyT6vtq3uO3ApVSu20KDPEYy7kJzPBPb7EN8t+Xv3D3r\njA9d//dFDk5pLCbp2IduwMu+Fbmc+OYwO3//XWY/tOdz9f3Eg7cxt1uitVKLaTJKLMeCGDzCXeec\n/YXH4wr6+M1Z6/jxC32oNBvwuZ/G4LFyfF4FM146jsPT9Kk2xg7/nXkpGC4uRjRGiQ2Ukyq3I3X0\nYlMt4P6sEi7yPc1jJwTZtPtVzrTZ2CLPITPZTJVOT69YiGp/HY7FR8hfu5ueHcsoXXaEvEU7uOdo\nhPudG2nLn/WFx/iZUBR+33orjvmHCPtz6d43g6p1uxBE6GrcyNzhxdxnGGePNAeXK8w9j/yShEFh\n77wNvDvnEJemYpwcbqeFXH5nzaE9cAIN4QXvmw9hpHJyDyHnYjRGkahZQ64nwZH6V+DCL65t8A+m\nV7inmWaarxziWAOmBAzMKEJEh6BUoYt3ohGTVNXupap6Py1WF9rEGJ7RbsYckDMY+HTDn0D28CBJ\nFUwqbqwhLYqoImgbQ2Nyo1E5SKUDqIYHCcfaCKs3o06+SUpbij5xAXbdRkRXPpIiYQ5lIcpJpEQM\nbdYgsclstDEJSUlhEJeii/Xy2okrMSsh2rzZGIWlJAxZVI2NcveCs9AmI6gEK2PRPoRoFpJ6jKQu\ni05tHpnsIaxTM56tIceT5pmz53NwwWxOev0o8w8HCRsVdqyw8Pz5tbyxai0+21J0fgcZQ1rKhmsx\nJc/EbzuK0ZlBWlBQQj3YxSjt+jK0+/pI6mYjSsdwuUT0xknifcWYtDb8iVHi8lSAn8x1YQmsR5MK\nMJrdxnMrzyBfHmDdSzK20SEyJj9QIBRQmHv8WU58YgfXv9xAsTTAi4VrmbfKy37zUn6VM4+U5gUg\njS52iCMrKhkTXZx+9ChX//0ZOt1tqBQoHK9g0N6GGsiO5tJWWoOaT88TFoEyupgV7cN7cBOxiIML\nsw9REiujXyvwlytryA/NJSaK7F8wlXay/oVXWBo5zL0nX4EmsZ+UdinJ/EyS/Q4Klr+LKHdwTDeD\nKgbYOLyQhBYCmVlYJBfPVzThs4LLB2MOeKKwAbvkxus2E7MG0AspRlRuYpYQ4wYJQRAI2VL06qbm\ndtzYwaodjfw26xR08SF0sXmYurupizZzyDSHYgZJiEZeLy0j/Uo10dFSEv5cEoEcEgEXyaCLZDCb\nZCiLZDiTVDgDKepAitqRojbkuBlbXis/Nt6EI0/HXxfa0STfJmFYRpbmFNKCRGOTiid0J3Fu8h1u\n92dQ5s18fz5PG17AtZ5aHuvV8evEZr4V24JRifOI4VR+o7mYp0wzGGoKITb00t8o8zvdpXSI+Xwn\n+jyPTsClI2u+8Pvz4/hT0VZy+1ZgEOyoJzII7x8kETcxN38r4j+dcTgwazGq1B6QL0AnZOMfSdNe\nIrJ4v59bb7zkc/U7eeRVdCkYKilBQwbqyCZ8WoWo2f4v2+kTUU7tqedHzc9y+/F7ua//5/zRex1/\njl3KHZaruFv5Mbtnj6MIaly+Veg0aYR+ie4CgXlH/Nz282v/pf2iDg8+C6SH9MxefpiRfgsLvccx\n55ixhdPUmMZwu/R8Y2Q1m5dL5HX+lZXOHl4XZ+ONJdEpGnpjcwk1zkCnUShas5vevXUkQhlkzN3L\nTdm/5P7OX3DJ4Zc/13x9VjQhHw/0/TeOmYcIembQciCX2SftRk7rGKg/j9rBJdyiD7JHmkFVzhh/\n+uPPGcwx4slazUj1ER5ItLM63cMd2hr+rnfyzPhPaUgt+Eg/aqOaRFSDSp0matJhiUEymPoYjz4/\n0yvc00wzzVeOos4hAibwyVYsUYmk3o0g12PM1GKwTKU7VEljoIhU589kMHiQ2W0JfnLNOdx8//Of\nu7/Cvjh9+SIWKUK0ey4alY+ofxJTlY2frPlPTtr9GvO7OxFjMopvlDAjpK0jmKVMZPUytMkqLIYe\n0qIdbaIDfwYYrOMEOupgaBI0OiTjbFLCixzTXc6G8Z2s3NlH1H4qKilGSasWTs5CTNcjqmfgSx5G\n5XcTN4ZQSyJj6kwW2fdxTJXHuNtOTfM4ZV0xOotEhoucBDPLiQSSuEcELAMarNoM1MoKFFEDOlBi\ng6hSr6FJpZm06bDJCkXOg/TiIh6awOIoIi3pCNmHKC4aIZ0WGR7TMctcSZN/SuAmIijkeeeT0FuI\nWrew9eT38rZ3DZIO9VLX/gayqCCkQUR4f26z/cdZ/WoHtoEL2XH+KK9kLCVr7QSrG9q5iw2cwYs4\ndSreyryCRdEj+BUVOzfm0WCsZ0HEgaIINBmDVEcsVLo6sfLZclrlcAajR0+lLyUiCTJ5wxWUlu/H\nL1aTKXXSY2njZ3cm6PuuiWPGUZoqXcw9Psplj73OkWtmMZEzjDWgwhawM5pqxaFWEzd5iEkZAOSp\nVByytVEVLsIREsDeicelwhmU6S8yIBpTOIfdhBxWjKmp+ZD8mRi1PqLGQmy+CWS7Cb9axCynaTcE\nOLvlKFkbziHZcwRFPA0lI495HX3sramjZmaA3tZ8tlguZFnrjcx988O5p1EtBM0QNQlEjWrieh0J\nnZmU1omkciMLpTjyR8mc9xZ1M5+gtL+a29dfxqXvvkTcsBFX3IIn6208DV7urzub/4hsxhEqoz5V\nw8J4M/OUqVJ6zRTxkP40JmQ7Me0ImoYwBimI9Z/mX9XYzduKjX11F3Je9A3+K/44swaWsFtVwEu5\n+z/3e/Sf6XR58R7UMn+1h+2GEGUTMzE3JLAt2cP/tj3Fz2Z+uDzfI+vm8c0dMuFcDeYhJy3zCigY\nOsicw4cZGRwkJz//M/Vb0jHKhA0iPUH0RgumRA++jA8UP03xCFd2byNHGMJkmEBj9KExBtAagojF\nH6zySyktyaidhDePeEKPpeQop7t30t89Stp4Ksn0MTRJHW3zRDa+3IF1+Mgn+nTvr29gTX+awzVG\nxGwTiUgO9y0+j6uaXiMkFbJLNLKk+SWuLtxLTNGSHr6AJ9a/w7deeQjf0ut40jOf70QOIJi19PiX\nU9EVQlXmo2j1O/Q8m4O5eD2Osh6spUc5haOsGHkXT88M/mfZVZ/o02cmHuOGhueoLGnAXNRLoHse\nzd1plp10iFAwi2jTedR4c/gvU5yedAErsnr46QP3sW9WIWG7ncWFuzk/3sseoYRXLbDTdy59cukn\ndhfWuoikQJVKEDcagSAq57/+sfRZmQ64p5lmmq8Uv/7h5Zzem+bIPANatQ5L0I4iQsQSpTjb//51\npdmTDE8KyKNrCOYNMr+pF6f+o+qCn8ZvbvwaZ/ihdY4DMVdC6F2EkNyDXmugYMV27jiY5Ibl3+WN\n5VPXX/nyk2R5/SghiajShmzoxqQUoYhLSWkdSOpdFOekEQQIjdpISiMY1TMRpAgNVSZMSoi+ESfL\nDPkYwwMYw71MqFfiSnuIG0cQknWQOkwiaCWpjaCWICEbydcnsCZ0DFpm8Py5dlJiNlLHCBnjVpx+\nMDtz0Nk3gJJGFx9AEXYTMU0gyXrSxiDFp+4i2TePpvEYRZNaTrR18LBxI6qoE1OoEEkdJiykMOZ0\nEhkrRumbIGJ0vT9PLmM1ce1M4CUal82mSz2Dr3fvwNIzzOJjbyKpFG79tkJAK/KDzRLung++ftRK\nmgVNT+EaX0DRGUmerqnh7dolnOLZzUuNp1KwPomeOGV7glzxwiP85lojWgXyPWUMu3pICZAbKWdH\nRTEX86+VAqVQNiONpzIgp5FJ405qUUW9qOKzkEvrmV/gw9Kfz27rMJu/Np+8iI4m4yG2n6Bj7nEo\nP3aMDZ593H3y1fzq0cPATCLCODF/CEEvIvSuYDz3ecqS/TxU4GHp9uWYu94mMyfNhMsGHX7G8vPJ\nTnVR1dRPr6mCXMdxusjBMVyOvvJ14u2LEJRuBnRTQdT8SBk7rT1sO3cG86UeWp0aZnkT2L2FJMbr\nyalewoHccnivrPWNVb/ghsyH0CUlRCGBSoqjSyTQx1MYo2lyh1NYIynU6TDgAVqAbYw54OjganKX\njOIoPMp/R/6XXXPPx3X8RcT0RrKjZ+LLfZ1Y/TB3113EtyPPUhvr5BjFPGg4Ha9sI6bxoDoWwRSf\nRPMp7y2doEU6PMTD7lUU5iS4IPYWa1JHKBs5kRf1HnocX6ycpxgWWBuayy0LNvO75guwW/fjjwUw\nDQ+hnZ1JXvF2skKbGLd8EEj15ZcyafgLpugFoHkMerzsW5rJ2ncmeP7mS/jPB3Z8ar+3/+wKNg4o\n7F9kwZywEs/MQYoc509nfHBg+7f+X2KdOVVFRpZVJGM2UuEM4iMlCD4juiEZW6uHhDSCp0DhcFkp\nTfnLuaFLxDajAVN5HkLjEQT9maRsfyTcG6I3V6C6wctdN3+f63/yu4/4peo7iDoNowUzcBSMkOgt\noXi2B7W9A9fgeoYLM3Cb0kQVHWOCnavim0kNnckfN+zke1vu4eE1P+Q+zyJuDO5nwqqhu38j5abn\nkd1JZn1tgEBsgp7XMtDZTsBVMoq5oJVydycP+o8Q6qziZ5VfI2LN/Ihfn8TVh55ltmoAXfYYuowh\ntIujKAp4m5fQ7g+w/IQ2xseLMB77GuWTer5jTDMmujhLc4QrH36SHbW1SLVGro5sJqbouDH7P3ix\n4gQUlQoFEQ0CCiIKAul/evTW56BMhomJKkSDeWr+Ul9M2+CfmQ64p5lmmq8UjkDHlJR7UTn6cApd\nvIS0apR4SkGf20c0mImoktDlDhBrM2NNZ+I35CCJvWR6hj93f7aJPgACGcW4dRoiooaQfRSNfZJE\nxIlrwU7uaw9zXebVyM4sHjrtgy3o7z37IIZQnOTkGCHxCbTWPPDHMbjHkVJaJiYVRFFF2rgejbSH\nLXXnc8rEu6zd6ydsXwHhbci2g8BKqsK9TNokbP4cQCDLZyTo7EclxVB7BSSjGvbrAcUAACAASURB\nVF08hT0pIPgMaMQ0SUc+YuI0DNIYulAPEdOzpJNGZKuPso270OvSHxrrWH8tgj5OKtWErAhEZCe0\nDSCZN6JKNVJcBhptHF9fPgVGNwPRNgBEdyFSfD262AHaytTv521X7IKCvl50UpyXzpE4ajFgkdP8\n6Hwt1+9KULv7wyFZgecQroeacK1J8twZBbycs4b87AHaVeVc2L+NuYPd/O2SBTQa61kUyUSVVmg2\njjEnpmd28VHKVR8vEw+Q9Ocy0rSRISVJGhlXQo+YmMCpAW9sCXI8xNhoCdWuejpiKzGbBunIaue7\nf5Tp/Q8VLcZBBtwWCjwhLvvdU+y9rQpJ04qs3oAiqEkN52Et7EHXUMcBzSwWpVoQIg7S+hDqSIi8\npIEudw7yGjUv5nRTkrSgigyTpVvCCYYmtmnqQOhD5U2j080iLr6M1zhOUQKMIw7spi5G9d2s2ZfF\n/1adz7yRXaS08xFVLSwZa2Ozex2XOrbwjH8haUHLb7Ou+dh5ENNJliQbmR3uwJmMolZSiCQQlBgV\n7V7W7XiHBp+R4bpTyZy7g/VVD+HVLWSwbSsW3zrsoTOJureSru/njjkXI4hpYhoPmqYQxmTgY4Ps\nuMOBSWPFELGhlnKQ1CN4zcPoRqcO9xo9XiY8cNfci1igNHNF/GXWx128kFjPg+btqM0fH7pL4RTn\nBFfgELVYCeOSximWRpiRHsYo9HHX2EU0hUZYVKqwTaUQVdeQ2h3Cespebup8hBssN3zI3h2nn8fN\nT9UTtlaj8jUw4U/Tk+dlyZ5RbvnxN7jp14994v0FYB88hgiM5VZg7tWgDq4kmvrgfMNVbW9irewg\n0DeX+EFwN7RT5gsDYXwW6CvQ0VxYQseajcgamV3OBSQtRhSblr801/CNgIeiuTv4OyVUNwdR5FPJ\nUu2ktcbEhle60PYf+Fi/Sjq8eDJAHkxQfGIn298tpW64FylZTCQS5pSeXZxpa+AN7UKOp8v4prSZ\ny5KvEx5Zw11n7ed7z/yWe074MbeOLea/Jw8yaEvT3Xwe5cbH8VmdDBoKmbHpOEbepO1IIenmxbhK\nJMylzbgWvMO98XoizbN4Vr2anZVLPuLfeQ2vskw6jt41ji5jCF3dVICbSuqJ+fIJjbmY9OgIF46w\ndEUbA/2zKWq/GEMowdUGkUm9jf/wv8kJO15jV+0JyNUxvhN5jr2qWdxXdRERk4mqRD+C8l6YrSgI\n7z2KijJ1ykFRGDRl0mKaQW1kjJRpBGlyKuDWxb8c8ZvpgHuaaab5SlHa7mM4EzyjI7jT2SR15ahT\n+9C40xhtY/jbFiCoJWxljYQs1WSNdKMRxunPFcgfiLL9pZdYe/rpn7m/vH4/o04QE3piHhPq5CSR\nyQDFSweR9lxAcO7b2MsPc9/obTzatol9Vcveb3vneVNbqmI8yvdffByNL4XekI0+8zAxXz6qoVHU\nmkxQafE5xzEqYUI9RiLWCiy+I3RV7+SFQoXv/X/svXeUJFd5v/9Ud1d1jpNzTjthdydsztqVViut\nIhISCsgSEmAMGES0MQgbsIXAmGRAYCQkQBIKaJHErrTanNPM7MzsTp6ePNMz0zmnqt8fgxUsCclf\n+9jg3z7n3DPnTFfduvXe29Vv3fvez7tviuqJIN+/4l7+4bF+0ioHrugY2RUR4q5pRFcj/RVFqOLz\nxKx6ckNNpDQuEmofCgeJOOapvuIooiS8022STqlwa2UykwautB3niKaJSSlIQWYx6ZSeqGGSrNIJ\nkkktszPQKGUwFoqTLirA5N2OOj2DyzHO8+tupTA9wWUvqpDD85TMduOsT/KrKh1LAyb6XXdSWPQj\n/nGDnlsKolz7jAa1/Hq7JDnOhv2/IGdoI3vvWuD53LVUpIbxzoqsPrWPfasMGBSFgqkiZvPmCKpV\nFETq2F9exgf49VvuK+EuYarncqaII5AgJ6ZDSM3hUAnMhzfiUhlABYpiJT7ehCp/kHhTPvVDmZwx\nuTmxuZ7iiIa+jC523ZjNX/0wiDkc5obzp/FmRLD4wRi0Ehr1UXRNNyOdyxiWirkqdZJbA9cSNcdx\nqx2YU3p2Vw2wJasWr83LMl8e7jw3ScmDVYgwIeYhGOaJROZQC2oC1iTD2jQtYQd2sYrK6DBdBh9r\nZ4exbIjhy5xCH16NVc4hv3cCTU6SiZocOPnHx7Oskjiua+O4ru0tn+Vnj/JJ509o7orgmtjLxcnN\n5K1ykll+GkNmJhdPCGTMrkAXvR7Z/hL0LOqUS2+oIyakkPJKMUQMaGPZKEIJOnIgCSkxjUqeJyXW\nYY+m0OjO4M4YR5xaVIIRu52cx8D55tu5JnqAT0d/TWu8icP+RtxCkHzBikkIkZ12U5qcpUpewCK8\nrjwyp9gYVBfwO91alsaHuC38El/NWk9t1xqyq/fRZ55DdIkUz5eQUXqaZbOjdOaWvt54SeJAQ5Q1\ng40kbOcwelV0tS3nyhfaqek690ftOj87S2V/gNF8AdHpQzZZUac6eHl1zeIBqSRtOc+TTOgp+pkL\nKeBjrEDFvrpsZq1NKIrAK1UrmSyuQjFoQHjzd/VYy042/76fyq1etlc+y4m5y8j3bSViixMejzOe\nK9DUscBPv//33PvxL7923je/fDc7pxWOrbQgOTIIz5XxzJrruO/wM4iqCn6cV86H/acxCHEGhXI0\nPSM8uvQ6Phr/DXfFT+KeXcJ339fLp5/7Nv+4/gt81dfG3/s7cVqjOE/fScW6n9Gk8xBBzwUaEJcn\nqV5+DJ/XQN9LBeSWNGOqHMCx5DQfSrVzi7OW6ekS7GIIfbYbbcYUuqXeP5hIIurNJzTSQHDOiG/6\nItE8O7miB9taF6UGL8P9q2gev4V4cJ67dCZSVgMPdP+aUmcn52uvIt3k4y8jz3BCXc8RDLQ8+/If\n/0K8gYKtq+kzF1IyGSC/dI6JhVoAdP9NyW/UDzzwwH9LRX8qPPzwww/cd99/fTfpJS5xiT89Hvz8\nB1hxbobOZTZC1iKs2kxUSiNR41nyC4MYciaZubCEZFiPrWQEUyCXiDeB2a4joHio74+zV+9n/bb3\nlqjh61+8lxVnxxmo1hOzhRH9d6FJd4ISxugwYxzPomBhG9NpP9bSCzRp+yk76+dUcdOb6lE0Iscb\nWjmyfCVrfafILb9IaKQO/2QMvfZqtIkpvnHT9Wz2nObKAwlSooO44VV+XT+NIgi0jRkQQ0s5UWth\nc+cZ0qpMoslBMovNRKf1pMQa4pkDGLyjTNnrsellyq9/nNy6YXKa+siumUCtfmdnG2D+5JXMKlqy\n/Ak2Gg+yy7IRbWcAa6IWBAd+zQVKm88Tnq7CezFBOhlnQUiQHduErLbgzdjHS1dchldl5+4jQ0jj\nPazvfpG4Qebrt2rQKwJDrvupccQ5P3c1reoOXs1LM9qYYvmAghR/8x7+TP8YDSeGKJYlcpxBbnvh\nWZ6+rZ7DjilaQtk4PGbO5vVTkFCzMX8eyagin9dXMGIzVYyfex9984WESZMb02FOLWBPigTDGwgn\nylCE12dOBUFAHYmjLhiiXhhidrqaMeM0mBNc/bQHZ32SGclDW7eIMZGmsqOXv/v4p1l/bhK17GDB\n5sSRF2FuMpOYYGet6gy9UimecBrFYECRrAwap1GEBXwaaHFVImuMSIqFldoODifXIpAkYtFi8hYR\nKJyjxzxMfbCK3ICJpFZLv3EaY2YGNksGv5mu4zKfG7WcT2x6L8nGPM4ba7APTxHlzbKI78atOWdx\nr8rEXqbwa/92MnL7KJ4OUts3yrg3RUSzDlP+IPkVg4z71JjcGtLiOnTqCAFLEq0pBxMlGNStSIbt\naNJLQahGwII6PYkidBAzdCJW7iOnoZO54DhGf5Sktg0p2YhJ0RHJTSEEA4sNmvFz1pdBf+FytiVO\ns01uZ3u6n7WpLtpSfRSk5lkQrLRLNRySWjmkaeVIupiTlgxGY2WEut0M5rWwST6HosrgaWmcy8z5\nzKbN6D35WIfT6BtnWOKZ4fe2TW+yxUh+GZs7d5NS7UAbH0fxelkoTdPSFeVXA79j1ZV3vK0Nf/gP\nH6Slc572lizScTsp+wrC6il2bbgKgL/pfZqCotOEzrcyHZ1l5q4CdkvreeSaz9Be20xHzXICWVkg\nqd/ibP87h4ta2XxyAmv1AA4txIZjqLkRU2KY6SqJpgs+hkxzrLj69fj0i499g+LJOB1tDRQ195Ec\nLieYLVEndWKYLEIxB7md/cyqMunQKOhmQXD5OFe8liuSJ8iX1XRgZ+9SL/cfHuRYSRv7yOOGiJcp\nQ5TU0AqsRefQalJkM0cGblzkMKUvJW/JApk5PQyctREbb0OtVWMu6Ce7eABTwRii2UMi7CA0Vst8\nby0T5wQWZD32rBGs9U6KlnkpKpvGXrKAWpBxdm9i/cyt+AOT3GVwIGZr+N4r30OKTOC3b8K3Mvgm\nZ1u8oP1PfQ80NitHC5dTMuWkKCMMU3lkTg7hswg03fSRdzzvq1/96swDDzzwrtqBl1RKLnGJS/zZ\nkD01gCzAQk41lmkfxkAuqnScWDyNrmCCWNjK1ujNLPFuIhE3oCuYImgO4p3dije7FABL6L3LAxoj\nE4hpmCsoQF9SiKzWErROIedF8MzY8Kd9DAdOsmz0TmZPb0TUB1jeupt/PPrO2rQ5tsXZnPl5A4JW\nT1pXQMjSi0EJY+iCkKUBk+co+5edxp6SWR2EY2XdiAk7FakRogYXaBfTDkd9RhJaL2mNnlkxixpL\nP0ZZIqF6t+jZtxIMFyMqagzSceYVK/iTEIuREhvQJC9QXpJArU4THM2iwbiKhfgUuWIjcX0ZCd1u\nLqyuZ0is5ObRkzgGx2kebkcFPHGTzKyoRpq+muUWD9fvf4m7IgfpTHyahtkGus0SX7hXw2TVW5UA\nDAkf2178Bbf87mdYIgsM27oxp2XyJ3KYKwwzp1FRHK2lQ1pDM4szkEpazcjB+zgzsAqXECc/qiUn\n4cEcTxL37WAusg4E6S3XAogmKvBMLcGgd3O+fiWNERPdBj/ekkxKo3W4RBVP31EGgCTLNAf6SWku\nEteXowS1xF3FSKIG4/xm+iiiIT7E/tJOUgt2SocD6GWZUS0UJxRWnx0jPZ9FpmqEGcWB6FyGzhBA\nNV+OSh7GqTuGTlYgkMas1hLzKBQkFGZ046w4P4JSlUdcf564rgCpoJzm4THCgpktVe89bGq74TxL\nNizwyLJrmVbn0a5bygdKevie41N8fv1H6KkVaekKkffMIUb3bCLqKWTZ5leR23ajjZ4gJV2GTb4L\nMXUDKXETCjo0ydPIqueJZvyKnJ2fIvemx7GvmiBdbSE2HSfygotsnULBLU8QK/gVYuIQSakOQ+Tm\nRUWf3GLichxzSibU7uYHwvU8otvBw/pr+bb+dr6pvoFvqxvYLS6nvzNKpH0OoWMUZV6LY7CEPGcZ\nduM9GCav5wn9Vq5JHqdRW0Gkq4iygknOV59j1JokOFGLtbCba0beqrX93as2YkyEieVpAImZdBlT\n2bDq2AQPfuntJ/TynSMk1BAwlqDFiC2QhS68GLKli0eoKNlLLGzF/mwX6dYqigoG2Vk0Cqo//iL8\nJnQSX6u5Ef9wE9aiiyQbvGijY0RyswhPCkzmQGPHHL965LuvnVI+GGAsT0DrUbA7wuwylbNsZIrg\nQg0vaQzUOndTJ0xxSNeK9vwbNtq2j/Ij402sUPr5REhAjqv418snuH/wCVRa+Iq2jtKwkVl9jJ7j\n9+LcfSeB4QIAcnGxjA6ymGNUU4myMZOsDccJyG4G967D3bWGyWNbuLCrhokZFZaqMxRv2EfTTYPU\nrHLiLsqiN9VE19Raursv49Sp65k4cBfb5t7PrH+YOw05OPJTPPrrr7JgSuC21eNaF/kvOdsAqqFx\n5o0ZlEd6SYdNhIU4fhMYw/89KiWXHO5LXOISfxYcfOFFqgbCjBQJqCPBxYeXUIsU70c0JTDYp4nN\nljEdGUJOh4m6SjFkTpD2RzEnBOb8EDBAztS7Z2H8d3KmZohK4I/qMfj0aJIhEvNu8ttGyYjnMh3s\nZTx0kePzL1A3u5mxYxtJpyQKV+/nux3feds6pZxpYhEL0VEPRrkRMeHhF61rWOfpYMWoDSnmwdlw\nhAGDSH24iVnfFtqLZ9DG3dR5ZvDYBQRVBoKgwe+XiBkWJc5iipFyQwxTUiSk+c9lR4v7rSxIMbJi\nOm40nuUVQytRixUxp5S0xkjIMo6pdJR41MzccIR4OoImq4yEbgNS7BBztVm8Yl/HutAZag9psbrn\nsEQW6FyTZHe+jqXePCYMK8lSFlg6MMwNL+7l3372BVLaDWRM3oAsCHzhBh3HNr99GmUV8NjdzVzQ\np2iIFGCIKYzohyhMKFRmOlEb1aj+kFJ+8ugHmVJFKYjpyVbm0EcEEp5r8MTWIAjqP2oHlaBDGK0l\nmZR4n/IqOcEq4iqBQ6vDrHo1QEkchvRDhP7gJK05PYgvYzHe1JTMIDlmwrH0LNrYOO3aGprTA+Qm\n8smSrWSP9VMSX3wRyknY8AsustIWNhnO0ylWYlZcZABGZSUxwwxTpgAVMQlRshFcWEl9vIHiRB4D\nOplQeAJ9TooekxZ1KorVW4bY2U+mPMfZondWYPh3SoRpNrQ5eWndVnp0NVy1cJiWfafIlOd5tXYZ\n6nSESamSz9f8I3vW5yMlYf2eA3ifCzB/cQMlNYPYdj6GIuxCndpNXP80Ss0PKPvg1yi/8zHKrjhF\nQUmc3tn3MXIgE+HFi2x+eBdXvjDGsq4IbU8ew/NcGVVNQ1Tc8WviJU+hTu0mrclFir+PbMNtiJll\nxAXQ9k7g6QgSbPdA+xjqnnmsF7SIE1HMWbVYdCux6G/DnLodlXItKU096vQEUmyGBedqRsjj5uge\nnrGfoGR2GYXRWrxRI6l9CRRZzQ7jU2+xj9eRxURGO7roLeg1BozxIO2rGzFFoOTiW2N2jh78PdWD\nMYbK1UiTXhL2BAn1eb556+J+jq+MPI7O6CN5poHu1mxOzroITFdhqzrHQye+/6799Ubmc0vZ7Son\n4s+hqnEf/RVODOGtZGrNXFhWQpYPPGd3AfDNz99K/gI4qxzIRpHIVBXDTcvAM4LNk4ev0EJFPgQU\nPeGoD4ekQaV6fV9H6twUPzFcx+Xps/ytv4xgMsXjbZ18eOFl0Gj4mraccr+EVtEwaVQ4P7WFnn0f\nYmzPDcQCOlQoVDBME4tJsfyFeQhXuLA3nsC2+hTiDTKzDVX8XnMdL3I9BxJbuDi+ioWTS4mcriY6\nUE7uVCM3eLexg9UMB3q425hPVaGXh3/yZTpryhjOtRBaqX2Ls62oRPRiDQaxdrFINRikaoxSNUap\nCqNUiVFbgVFbgVkqx6wtJyOeSQYestLDpMI6YqkEYaOAMSTT3fkusVrvgUshJZe4xCX+LHj24c+y\ntMfNudY8FgQjenM2alaS0pwmtyyCMW8c14V6YvMhAkk3UVGNtXgE71wFWr+Mo26ehG+B4okUD55+\nkh3X3v1Hr3f4xd04dv2eyXw1UYuRpPdKtKkhkMOYM40kXUUEw6MARFJ+5qPjlKcbGPJYMNoi2Mou\nsNXZxz7NMlJaHQCF08Nsz3yeqKscrxNUxhsRlCO8un4V6w9MoFMq0YZf4PGWflrDAntm78cdL8SR\nsZ8Wpw1RY+UHG69h27lR5PQ8gt9H0iAjppoQ6KVNc4GLkdXM6+KEh1cz72x9rSz8exlZ/Ot+7X9t\nuGfqCasT2Pw+Wo1nOahdA2dGsaSXoKiy8et7KGvqIjTaQHBWg8s/jJXtaFJBZi2D/Hr91WTJ89z4\nfIpkdIKVvbvxZ6b5+rUiBUkV7bOf45bEMe58/PnX7KtFxeazp/AsqaY/dQUl6nZeKtPgaRBZ1plC\nJb955u/ZjR5SqjRLB/PwFWg4Z5lneagCg91Ii74TiSTerq0MxAzkJQyYdT7CrquJywUI77BE/3bI\ncYGEfYZSxwV+bvogNb6zDOv9XHFOxUJFCV1GD6ElS2g9N0dh3xBf/cRfs7bdhZi2skAHRS1TeC/m\n4skSWZ/qZFy9gXQ8Tlqcx51rZVIbYUm4Al0iTVxnYZvxFK9qV5EOpEhFnaTZSMjazfHcCWqiBRQv\nVKKJV6JKaUgb/PSbJrDqBay2fA76l7Jp/hwpqYWk2I0hR+K4uYXr5g4zkHibbKfpONct6aOzuYmL\nhmpao+dpOdbFy1NLCNhNbI93czSjhZs1Z+h1LyrQnDKspr2whFJ1N80XYjA8yWhqC5aiIPkt7WQ0\n9pJTPYxBr8Iz0UyPt5nYaT/W08O07u2lps+POZDGWSJyanUpD9zxOYq9J2g97SLYKxMqq6S4oR1t\nfpCzEQVHpBd1uhhF3YZFqERliBJURZHNRrSWPMxyJTrNOjSaDaiUOhCy0KQmkFXniJjbEZueoXTT\nESanRLTJTXRnJrgyfYKkbgmzU2YKlw5y3uBFJBdTKgdL6UVy+yycyap6k6nOVTdw+ZkTRGx5qKI+\nBH8Kb0GIlq44j428zJorPvD62PyXj1Pf5+fcyhJUITsq3Q5CgpuTy5aR73dzbeZPiIUy0Tw9zInS\nLPprprH2N5KR48Nc6KTwVJTT/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rgGQmIRy9ce5cKBdbRZnUiU86LOSKvnMGX2WV7QbaKo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0nC2jxlG5v0jAbYfzVJ5ZKbmTYVPq2XiMRNSChiiVkoSxpI6/KsW5fY1s7g0s6yoZ9m2TjJ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\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FJqmfE6oOIsJ0KENssB8iNgxjiQT1lWj9A8hiB2HtclDewmt1YNGWsiFYQb+3k6Pjb0B8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\nRqPRaBaR/w8VXPP7TX+3pQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1e327d549b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "modifications_per_authors_over_time.plot(kind='area', legend=None, figsize=(12,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But it doesn't look good at all :-/\n",
    "\n",
    "Let's bend the data in a way so that it fits into the Stream Graph D3 template!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Treat missing data\n",
    "The D3.js template that we are using needs a continuous series of timestamp data for each author. We are filling the existing `modifications_per_authors_over_time` DataFrame with the missing values. That means to add all quarters for all authors by introducing a new `time_range` index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2004-12-31', '2005-03-31', '2005-06-30', '2005-09-30',\n",
       "               '2005-12-31', '2006-03-31', '2006-06-30', '2006-09-30',\n",
       "               '2006-12-31', '2007-03-31', '2007-06-30', '2007-09-30',\n",
       "               '2007-12-31', '2008-03-31', '2008-06-30', '2008-09-30',\n",
       "               '2008-12-31', '2009-03-31', '2009-06-30', '2009-09-30',\n",
       "               '2009-12-31', '2010-03-31', '2010-06-30', '2010-09-30',\n",
       "               '2010-12-31', '2011-03-31', '2011-06-30', '2011-09-30',\n",
       "               '2011-12-31', '2012-03-31', '2012-06-30', '2012-09-30',\n",
       "               '2012-12-31', '2013-03-31', '2013-06-30', '2013-09-30',\n",
       "               '2013-12-31', '2014-03-31', '2014-06-30', '2014-09-30',\n",
       "               '2014-12-31', '2015-03-31', '2015-06-30', '2015-09-30',\n",
       "               '2015-12-31', '2016-03-31', '2016-06-30', '2016-09-30',\n",
       "               '2016-12-31', '2017-03-31', '2017-06-30', '2017-09-30',\n",
       "               '2017-12-31'],\n",
       "              dtype='datetime64[ns]', freq='Q-DEC')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_range = pd.DatetimeIndex(\n",
    "    start=modifications_per_authors_over_time.index.min(),\n",
    "    end=modifications_per_authors_over_time.index.max(), \n",
    "    freq=TIME_FREQUENCY)\n",
    "time_range"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To combine the new index with our existing DataFrame, we have to reindex the existing DataFrame and transform the data format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>level_1</th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2004-12-31</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2005-03-31</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2005-06-30</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2005-09-30</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>2005-12-31</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    author    level_1    0\n",
       "0  (dboulytchev@gmail.com) 2004-12-31  0.0\n",
       "1  (dboulytchev@gmail.com) 2005-03-31  0.0\n",
       "2  (dboulytchev@gmail.com) 2005-06-30  0.0\n",
       "3  (dboulytchev@gmail.com) 2005-09-30  0.0\n",
       "4  (dboulytchev@gmail.com) 2005-12-31  0.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_history = pd.DataFrame(\n",
    "    modifications_per_authors_over_time.reindex(time_range).fillna(0).unstack().reset_index()\n",
    ")\n",
    "full_history.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we adjust the column names and ordering to the given CSV format for the D3 template and export the data into a CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key</th>\n",
       "      <th>value</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2004-12-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-03-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-09-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-12-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       key  value       date\n",
       "0  (dboulytchev@gmail.com)    0.0 2004-12-31\n",
       "1  (dboulytchev@gmail.com)    0.0 2005-03-31\n",
       "2  (dboulytchev@gmail.com)    0.0 2005-06-30\n",
       "3  (dboulytchev@gmail.com)    0.0 2005-09-30\n",
       "4  (dboulytchev@gmail.com)    0.0 2005-12-31"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_history.columns = [\"key\", \"date\", \"value\"]\n",
    "full_history = full_history.reindex(columns=[\"key\", \"value\", \"date\"])\n",
    "full_history.to_csv(FILENAME_PREFIX + \"modifications\" + FILENAME_SUFFIX + \".csv\", index=False)\n",
    "full_history.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we use a template in this example, we simply copy it and replace the CSV filename variable with the filename from above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"vis/interactive_streamgraph_template.html\", \"r\") as template:\n",
    "    content = template.read()\n",
    "    content = content.replace(\"${FILENAME}\", \"modifications\" + FILENAME_SUFFIX + \".csv\")\n",
    "    with open(FILENAME_PREFIX + \"modifications\" + FILENAME_SUFFIX + \".html\", \"w\") as output_file:\n",
    "        output_file.write(content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And that's it!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Result 1: Modifications over time\n",
    "\n",
    "Here is the Stream Graph for the IntelliJ Community GitHub Project:\n",
    "\n",
    "![](https://feststelltaste.github.io/software-analytics/notebooks/resources/streamgraph_modifications.jpg)\n",
    "\n",
    "The visualization is also interactive. You can hover over one color to see a committer's \"modifications trail\".\n",
    "\n",
    "![](https://feststelltaste.github.io/software-analytics/notebooks/resources/streamgraph_modifications_highlighted.jpg)\n",
    "\n",
    "You can find the interactive Stream Graph [here](https://feststelltaste.github.io/software-analytics/notebooks/vis/interactive_streamgraph/modifications_intellij-community_Q.html) (but beware, it loads 0.5 MB of data. This has to be improved in the future)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Result 2: Committers over time\n",
    "Another interesting visualization with Stream Graphs is the number of committers over time. With this, you can see how the developer fluctuation in your project was.\n",
    "\n",
    "To achieve this, we set the number 1 for each committer that has contributed code in a quarter. Because we are <strike>lazy</strike> efficient, we reuse the `value` column for that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key</th>\n",
       "      <th>value</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2004-12-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-03-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-06-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-09-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(dboulytchev@gmail.com)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2005-12-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       key  value       date\n",
       "0  (dboulytchev@gmail.com)    0.0 2004-12-31\n",
       "1  (dboulytchev@gmail.com)    0.0 2005-03-31\n",
       "2  (dboulytchev@gmail.com)    0.0 2005-06-30\n",
       "3  (dboulytchev@gmail.com)    0.0 2005-09-30\n",
       "4  (dboulytchev@gmail.com)    0.0 2005-12-31"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_history_committers = full_history.copy()\n",
    "full_history_committers['value'] = full_history_committers['value'].apply(lambda x: min(x,1))\n",
    "full_history_committers.to_csv(FILENAME_PREFIX + \"committer\" + FILENAME_SUFFIX + \".csv\", index=False)\n",
    "\n",
    "with open(\"vis/interactive_streamgraph_template.html\", \"r\") as template:\n",
    "    content = template.read()\n",
    "    content = content.replace(\"${FILENAME}\", \"committer\" + FILENAME_SUFFIX + \".csv\")\n",
    "    with open(FILENAME_PREFIX + \"committer\" + FILENAME_SUFFIX + \".html\", \"w\") as output_file:\n",
    "        output_file.write(content)\n",
    "        \n",
    "full_history_committers.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here you can see the results &ndash; the number of active committers over time:\n",
    "\n",
    "![](https://feststelltaste.github.io/software-analytics/notebooks/resources/streamgraph_committer.jpg)\n",
    "\n",
    "Again, you can have a look at one committer by hovering over the Stream Graph:\n",
    "\n",
    "![](https://feststelltaste.github.io/software-analytics/notebooks/resources/streamgraph_committer_highlighted.jpg)\n",
    "\n",
    "You can find the interactive version of it [here](https://feststelltaste.github.io/software-analytics/notebooks/vis/interactive_streamgraph/committer_intellij-community_Q.html) (again beware, loads 0.5 MB currently)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "Stream Graphs are a good visualization technique for chronological data. The interactive feature of highlighting individual is a nice bonus that enables a more detailed view of the data.\n",
    "\n",
    "Further optimizations should be made regarding the used template: The data format needs a continuous stream of data that leads to huge data files. Additionally, the color schema is hard-coded but should also be dynamically generated.\n",
    "\n",
    "Overall, Pandas and the Stream Graph D3 template give you a quick way for visualizing Git repository contributions :-)"
   ]
  }
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