Github Insights.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GitHub Insights\n",
    "\n",
    "In this notebook, I'll explore the information retrieved about my GitHub repositories and commits."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import libraries and data\n",
    "\n",
    "I'll import the necessary libraries as I'll use the **seaborn** library to plot the insights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "repos = pd.read_csv('repos_info.csv')\n",
    "commits = pd.read_csv('commits_info.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Analysis\n",
    "\n",
    "Let's begin by exploring the repos and commit datasets. Then, I'll check the repos on the basis of forks, stars and watchers. Finally, I'll check the commit messages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total repos till date: 36\n",
      "Total commits till date: 408\n"
     ]
    }
   ],
   "source": [
    "print(\"Total repos till date: {}\".format(repos.shape[0]))\n",
    "print(\"Total commits till date: {}\".format(commits.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Forks count</th>\n",
       "      <th>Issues count</th>\n",
       "      <th>Stars count</th>\n",
       "      <th>Watchers count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.600000e+01</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>36.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.477609e+08</td>\n",
       "      <td>3.361111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.222222</td>\n",
       "      <td>4.222222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.373380e+07</td>\n",
       "      <td>11.097368</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.978189</td>\n",
       "      <td>10.978189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.966238e+07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.263164e+08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.685917e+08</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.755507e+08</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.928580e+08</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>64.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Id  Forks count  Issues count  Stars count  Watchers count\n",
       "count  3.600000e+01    36.000000          36.0    36.000000       36.000000\n",
       "mean   1.477609e+08     3.361111           0.0     4.222222        4.222222\n",
       "std    4.373380e+07    11.097368           0.0    10.978189       10.978189\n",
       "min    4.966238e+07     0.000000           0.0     0.000000        0.000000\n",
       "25%    1.263164e+08     0.000000           0.0     0.000000        0.000000\n",
       "50%    1.685917e+08     1.000000           0.0     1.000000        1.000000\n",
       "75%    1.755507e+08     3.000000           0.0     3.000000        3.000000\n",
       "max    1.928580e+08    67.000000           0.0    64.000000       64.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "repos.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From above, I infered the following:\n",
    "1. I've had maximum forks as 67 while the minimum are 0.\n",
    "2. The number of watchers and stars go hand in hand.\n",
    "3. I've had no issues reported in any repository."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Two most common commit messages: Update README.md and Initial commit\n"
     ]
    }
   ],
   "source": [
    "print(\"Two most common commit messages: {}\".format(' and '.join(commits['Message'].value_counts().index[:2])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that sometimes I do tend to update readme files on GitHub itself and use its default message as the commit message."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Commits per repository\n",
    "\n",
    "I'll begin by checking how many commits I've done in each repository."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "commits_count = pd.DataFrame(pd.merge(repos, \n",
    "         commits, \n",
    "         left_on='Id', \n",
    "         right_on='Repo Id', \n",
    "         how = 'left').groupby('Id').size().reset_index())\n",
    "commits_count.columns = ['Id', 'Commits count']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, I'll combine the repos dataset with the commits count to help visualize them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "repos = pd.merge(repos, commits_count, on = 'Id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Commits per repository')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 12))\n",
    "sns.barplot(repos['Name'], repos['Commits count'])\n",
    "plt.xticks(rotation = 90)\n",
    "plt.xlabel(\"Repository\", fontsize = 16)\n",
    "plt.ylabel(\"Commits\", fontsize = 16)\n",
    "plt.title(\"Commits per repository\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I've had the maximum commits in **IEEE MyEvent App**, which was an Android application for event management. The second most committed repository is the one associated with **IBM's Applied Data Science Capstone** course called **Coursera_Capstone**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Yearly analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'll analyse my yearly stats. I expect to see the maximum commits in the years 2018 and 2019 as I really started working on my own personal projects this time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "commits['Year'] = commits['Date'].apply(lambda x: x.split('-')[0])\n",
    "yearly_stats = commits.groupby('Year').count()['Commit Id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Commits in each year')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 12))\n",
    "sns.barplot(yearly_stats.index, yearly_stats.values)\n",
    "plt.xlabel(\"Year\", fontsize = 16)\n",
    "plt.ylabel(\"Commits\", fontsize = 16)\n",
    "plt.title(\"Commits in each year\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appers that I've had the maximum number of commits in the **Year 2019**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monthly commits in 2019\n",
    "\n",
    "As I observed that the maximum commmits occured in 2019, I'll see their distribution in each month."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "commits['Month'] = commits['Date'].apply(lambda x: x.split('-')[1])\n",
    "monthly_stats = commits[commits['Year'] == '2019'].groupby('Month').count()['Commit Id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Commits in each month of 2019')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KZZ/LdNc3AAAAALa4zbzLGwAAAAD7IEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAzZttkDAID1cI8/uMdmD4H9zD/90j9t9hAAALYsM5QAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwJCFB6WqullVvb6qPlpV51bVEVV1UFWdWlXnzY8HLnpcAAAAAKzNZsxQekmSN3X3dyU5PMm5SZ6c5LTuvkOS0+bXAAAAAGxBCw1KVXXTJPdM8ook6e6vdfflSR6c5KR5s5OSHLvIcQEAAACwdoueoXS7JLuS/FlVva+qXl5VN0pycHdfPG9zSZKDFzwuAAAAANZo0UFpW5LvT/Ky7r5rki9lxelt3d1JerWdq+r4qtpZVTt37dq14YMFAAAA4KoWHZQ+leRT3f2u+fXrMwWmz1TVIUkyP1662s7dfUJ37+juHdu3b1/IgAEAAAD4ZgsNSt19SZJ/rao7zouOTnJOklOSHDcvOy7JyYscFwAAAABrt20T3vOXkry6qq6X5Pwkj84Utl5bVY9NcmGSh23CuAAAAABYg4UHpe5+f5Idq6w6etFjAQAAAGDcoq+hBAAAAMA+TlACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMCQbZs9AAAAALg2ec4jH7rZQ2A/89uvev3C39MMJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIdsW/YZVdUGSLya5MskV3b2jqg5K8hdJDktyQZKHdfdlix4bAAAAAHu3WTOUjuruu3T3jvn1k5Oc1t13SHLa/BoAAACALWirnPL24CQnzc9PSnLsJo4FAAAAgD3YjKDUSd5SVe+tquPnZQd398Xz80uSHLzajlV1fFXtrKqdu3btWsRYAQAAAFhh4ddQSvLD3f3pqvrWJKdW1UeXr+zurqpebcfuPiHJCUmyY8eOVbcBAAAAYGMtfIZSd396frw0yRuS3C3JZ6rqkCSZHy9d9LgAAAAAWJuFBqWqulFV3XjpeZIfTfLhJKckOW7e7LgkJy9yXAAAAACs3aJPeTs4yRuqaum9/7y731RV70ny2qp6bJILkzxsweMCAAAAYI0WGpS6+/wkh6+y/HNJjl7kWAAAAAC4ejbjLm8AAAAA7MMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABiybbMHAADA2px5zyM3ewjsZ44868zNHgIA+ygzlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGbEpSq6oCqel9VvXF+fbuqeldVfayq/qKqrrcZ4wIAAABg7zZrhtKvJDl32evnJ3lRd98+yWVJHrspowIAAABgrxYelKrq0CTHJHn5/LqS3DvJ6+dNTkpy7KLHBQAAAMDabMYMpRcn+Y0kX59f3zzJ5d19xfz6U0luvdqOVXV8Ve2sqp27du3a+JECAAAAcBULDUpV9YAkl3b3e6/O/t19Qnfv6O4d27dvX+fRAQAAALAW2xb8fvdI8qCqun+SGyS5SZKXJLlZVW2bZykdmuTTCx4XAAAAAGu00BlK3f2b3X1odx+W5OFJ/qG7fybJ6UkeOm92XJKTFzkuAAAAANZus+7yttKTkvxaVX0s0zWVXrHJ4wEAAABgNxZ9yts3dPcZSc6Yn5+f5G6bNRYAAAAA1m6rzFACAAAAYB9xjYJSVd2pqn6iqm61XgMCAAAAYGtbc1CqqpdW1R8ve/3jST6Q5HVJzqmqH9yA8QEAAACwxYzMULpfkrcve/2MJG9McniSdyd52jqOCwAAAIAtaiQoHZLkgiSpqkOTfE+S53b3h5L8fhIzlAAAAACuBUaC0peTfMv8/MgkX0iyc37970luvI7jAgAAAGCL2jaw7dlJHldVn0zyuCSndvfX53W3S3Lxeg8OAAAAgK1nJCj9dpI3ZboQ9+VJfmHZumMzXUcJAAAAgP3cmoNSd7+nqm6T5LuSnNfdX1i2+oQk/7LegwMAAABg61nzNZSq6qlJbtrd710Rk5LpdLhHrOvIAAAAANiSRi7K/bQkh+5m3a3m9QAAAADs50aCUu1h3YFJvnoNxwIAAADAPmCP11CqqnslufeyRT9fVQ9YsdkNkxyT5CPrOzQAAAAAtqK9XZT7yCS/Mz/vJI9eZZuvJTknyS+v47gAAIBroZc+8W82ewjsZx7/ggdu9hBgv7THU966+xndfZ3uvk6mU97uvvR62c8Nuvv7u/sdixkyAAAAAJtpbzOUvmGOSgAAAABcy+3tGkq3SXJxd//H/HyPuvuT6zYyAAAAALakvc1Q+kSSI5K8O8kFma6jtCcHrMOYAAAAANjC9haUHpPk48ue7y0oAQAAALCf22NQ6u6Tlj0/ccNHAwAAAMCW50LbAAAAAAxZ813ekqSqfizJTyb5tiQ3WLG6u/vI9RoYAAAAAFvTmmcoVdVvJPm7JA9IcqMkV674+fpGDBAAAACArWVkhtLjk/xJksd395UbNB4AAAAAtriRayjdJMnrxCQAAACAa7eRoPTmJHffqIEAAAAAsG8YPeXtDVXVSd6S5LKVG3T3+es1MAAAAAC2ppGg1Em+mOQ5SZ69m20OuMYjAgAAAGBLGwlKJyb5oSQvSvLRJF/biAEBAAAAsLWNBKWjkjyuu0/coLEAAAAAsA8YuSj3riSf2aiBAAAAALBvGAlKv5/kF6tqZB8AAAAA9jMjp7wdmOTOSc6pqlNz1bu8dXc/bd1GBgAAAMCWNBKUfnvZ8+9cZX0nEZQAAAAA9nNrDkrd7VQ3AAAAAIauoQQAAAAAQ6e8JUmqqpIckuQGK9d19/nrMSgAAAAAtq41B6WqunmSP0zykD3sd8B6DAoAAACArWtkhtIrkhyV5KVJPprkaxsyIgAAAAC2tJGgdFSSX+nuEzdoLAAAAADsA0Yuyv35JJ/ZqIEAAAAAsG8YCUp/kOQX5otyAwAAAHAtteZT3rr7hVV1qyTnVNVbk1x21U36aes6OgAAAAC2nJG7vN0/yeOSXD/JHVfZpJMISgAAAAD7uZFT3l6Y5D1JDk9y/e6+zoqfAzZmiAAAAABsJSN3ebtNkl/u7g9t1GAAAAAA2PpGZii9L8mtNmogAAAAAOwbRoLSLyf59aq6x0YNBgAAAICtb+SUt79OcpMkZ1XVl5JcvmJ9d/dt121kAAAAAGxJI0HptEx3cgMAAADgWmzNQam7H7WB4wAAAABgHzFyDSUAAAAAGAtKVfW9VfX6qtpVVVfMj6+tqu/dqAECAAAAsLWs+ZS3qvrBJGcm+UqSU5JckuSWSR6Y5Jiqumd3v3dDRgkAAADAljFyUe7nJvlwkqO7+4tLC6vqxkneOq//0fUdHgAAAABbzcgpb3dP8tzlMSlJ5tfPT3LEeg4MAAAAgK1pJCj1NVwPAAAAwH5gJCi9K8lvzae4fUNV3SjJk5K8cz0HBgAAAMDWNHINpd9KckaSC6vqjUkuznRR7vsnuVGSI9d9dAAAAABsOWsOSt397qq6e5KnJrlvkoOSfD7J6Ume1d0f2pghAgAAALCV7DEoVdV1khyT5BPd/eHu/mCSh67Y5nuTHJZEUAIAAAC4FtjbNZQemeQ1Sb60h22+mOQ1VfWIdRsVAAAAAFvWWoLSn3X3J3a3QXdfkOQVSY5bx3EBAAAAsEXtLSh9f5K3rOE4b02y45oPBwAAAICtbm9B6cZJLlvDcS6btwUAAABgP7e3oPTZJLddw3FuM28LAAAAwH5ub0HpbVnbtZEeNW8LAAAAwH5ub0HpxUmOrqoXVdX1Vq6squtW1YuT3DvJizZigAAAAABsLdv2tLK731FVT0zygiQ/U1VvSXLhvPq2Se6T5OZJntjd79zQkQIAAACwJewxKCVJd7+4qs5O8qQkD0lyw3nVV5KckeR53f2PGzZCAAAAALaUvQalJOnus5KcVVXXSXKLefHnuvvKDRsZAAAAAFvSmoLSku7+epJLN2gsAAAAAOwD9nZRbgAAAAD4JoISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMWGpSq6ga7KvgyAAAWA0lEQVRV9e6q+kBVfaSqnjEvv11VvauqPlZVf1FV11vkuAAAAABYu0XPUPpqknt39+FJ7pLkx6rq7kmen+RF3X37JJcleeyCxwUAAADAGi00KPXk3+eX151/Osm9k7x+Xn5SkmMXOS4AAAAA1m7h11CqqgOq6v1JLk1yapKPJ7m8u6+YN/lUklsvelwAAAAArM3Cg1J3X9ndd0lyaJK7Jfmute5bVcdX1c6q2rlr164NGyMAAAAAu7dpd3nr7suTnJ7kiCQ3q6pt86pDk3x6N/uc0N07unvH9u3bFzRSAAAAAJZb9F3etlfVzebnN0xynyTnZgpLD503Oy7JyYscFwAAAABrt23vm6yrQ5KcVFUHZIpZr+3uN1bVOUn+b1U9O8n7krxiweMCAAAAYI0WGpS6+4NJ7rrK8vMzXU8JAAAAgC1u066hBAAAAMC+SVACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIYISAAAAAEMEJQAAAACGCEoAAAAADBGUAAAAABgiKAEAAAAwRFACAAAAYIigBAAAAMAQQQkAAACAIds2ewDAxvvkM793s4fAfuY2T/3QZg8BAADYRGYoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYISgAAAAAMEZQAAAAAGCIoAQAAADBEUAIAAABgiKAEAAAAwBBBCQAAAIAhghIAAAAAQwQlAAAAAIYsNChV1bdV1elVdU5VfaSqfmVeflBVnVpV582PBy5yXAAAAACs3aJnKF2R5Indfackd0/yuKq6U5InJzmtu++Q5LT5NQAAAABb0EKDUndf3N1nz8+/mOTcJLdO8uAkJ82bnZTk2EWOCwAAAIC127RrKFXVYUnumuRdSQ7u7ovnVZckOXg3+xxfVTuraueuXbsWMk4AAAAAvtmmBKWq+pYkf5nkCd39heXruruT9Gr7dfcJ3b2ju3ds3759ASMFAAAAYKWFB6Wqum6mmPTq7v6refFnquqQef0hSS5d9LgAAAAAWJtF3+Wtkrwiybnd/cJlq05Jctz8/LgkJy9yXAAAAACs3bYFv989kvxskg9V1fvnZb+V5HlJXltVj01yYZKHLXhcAAAAAKzRQoNSd78tSe1m9dGLHAsAAAAAV8+m3eUNAAAAgH2ToAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAAAgCGCEgAAAABDBCUAAAAAhghKAAAAAAwRlAAAAAAYIigBAAAAMERQAgAAAGCIoAQAAADAEEEJAAD+f3v3HnRbWdcB/PuTY0IyogapmYJTXIZKFBBHk8BEw254weCMCniJyjRt0rIxdczRzMsfklckVC7qaGgy4kiEIjKZchMQEDHBSZOLYioomPjrj70OZ/NyzuFdL+/77n14P5+ZM3vv51l7rd+eec561/6u9awNAIwiUAIAAABglHWzLmDW9nnZCbMugbuZ8990xKxLAAAAgBXlCiUAAAAARhEoAQAAADCKQAkAAACAUQRKAAAAAIwiUAIAAABglFUNlKrq+Kq6rqq+PNV2/6o6o6quHB7vt5o1AQAAADDOal+h9L4kBy9oe3mSM7t71yRnDq8BAAAAmFOrGih199lJbljQfEiS9w/P35/kKatZEwAAAADjzMM9lB7Q3d8enl+T5AGbW7Cqjq6q86rqvOuvv351qgMAAADgduYhULpNd3eS3kL/sd29b3fvu9NOO61iZQAAAABsMA+B0rVV9aAkGR6vm3E9AAAAAGzBPARKpyY5cnh+ZJKPz7AWAAAAAO7EqgZKVfXBJJ9PsntVfbOqnpfkDUmeWFVXJjloeA0AAADAnFq3mhvr7vWb6XrCatYBAAAAwNLNw5Q3AAAAALYiAiUAAAAARhEoAQAAADCKQAkAAACAUQRKAAAAAIwiUAIAAABgFIESAAAAAKMIlAAAAAAYRaAEAAAAwCgCJQAAAABGESgBAAAAMIpACQAAAIBRBEoAAAAAjCJQAgAAAGAUgRIAAAAAowiUAAAAABhFoAQAAADAKAIlAAAAAEYRKAEAAAAwikAJAAAAgFEESgAAAACMIlACAAAAYBSBEgAAAACjCJQAAAAAGEWgBAAAAMAoAiUAAAAARhEoAQAAADCKQAkAAACAUQRKAAAAAIwiUAIAAABgFIESAAAAAKMIlAAAAAAYRaAEAAAAwCgCJQAAAABGESgBAAAAMIpACQAAAIBRBEoAAAAAjCJQAgAAAGAUgRIAAAAAowiUAAAAABhFoAQAAADAKAIlAAAAAEYRKAEAAAAwikAJAAAAgFEESgAAAACMIlACAAAAYBSBEgAAAACjCJQAAAAAGEWgBAAAAMAoAiUAAAAARhEoAQAAADCKQAkAAACAUQRKAAAAAIwiUAIAAABgFIESAAAAAKMIlAAAAAAYRaAEAAAAwCgCJQAAAABGESgBAAAAMIpACQAAAIBRBEoAAAAAjCJQAgAAAGAUgRIAAAAAowiUAAAAABhFoAQAAADAKAIlAAAAAEYRKAEAAAAwikAJAAAAgFEESgAAAACMIlACAAAAYBSBEgAAAACjCJQAAAAAGEWgBAAAAMAoAiUAAAAARhEoAQAAADCKQAkAAACAUQRKAAAAAIwiUAIAAABgFIESAAAAAKMIlAAAAAAYRaAEAAAAwCgCJQAAAABGESgBAAAAMMrcBEpVdXBVXVFVX6uql8+6HgAAAAA2bS4CparaJsnbkzw5yZ5J1lfVnrOtCgAAAIBNmYtAKcl+Sb7W3V/v7p8k+VCSQ2ZcEwAAAACbUN096xpSVYcmObi7nz+8fnaSR3f3Cxcsd3SSo4eXuye5YlULZcck35l1EbDCjHPWAuOctcA4Zy0wzlkLjPPVt3N373RnC61bjUqWS3cfm+TYWdexVlXVed2976zrgJVknLMWGOesBcY5a4FxzlpgnM+veZny9q0kD5l6/ctDGwAAAABzZl4CpXOT7FpVD6uqn0tyeJJTZ1wTAAAAAJswF1PeuvunVfXCJKcn2SbJ8d196YzL4o5MN2QtMM5ZC4xz1gLjnLXAOGctMM7n1FzclBsAAACArce8THkDAAAAYCshUAIAAABgFIHSGlBVN866BlhuVXVrVX1p6t8uW1j2wKr6xOpVByuvqrqqTpp6va6qrl+usV5VZ1WVn+hl7lTVU4bxv8cS3ntcVe05PL+6qnZc/gpheaz0fh5mzffUrd9c3JSbu5+qWtfdP511Hdyt/bi7H7GcK6yqbbr71rvwfuOe1XRTkl+vqu26+8dJnpjkW2NWYMyylVqf5Jzh8dWLfdOwj3/+ilUFy+8u7+cBVpIrlNaIqtq+qs6sqguq6pKqOmRo36WqLq+q91TVpVX1b1W13dB329npqtqxqq6ees/nhnVdUFWPHdoPHNpPTXJZVf19Vb1kqobXVdWLV/uzs3ZU1TZV9aaqOreqLq6qP5nqvk9VnVZVV1TVu6rqHsN7bqyqt1TVRUkeM33Guqr2raqzhuf7VdXnq+rCqvqPqtp9aD+qqk6tqk8nObOqTqiqp0zVdPKG/2+wAj6Z5PeG5+uTfHBDx2LH7ND2N8Pfhouq6g1T639GVX2xqr5aVfuv0meCzaqq7ZM8Lsnzkhw+tB1YVWcvch/vyju2NkvZz59dVY+YWu6cqtprVauGRVo4k6Cq3lZVRw3Pr66q10x9h91jaL93VR0/HKNc6Fh7dgRKa8fNSZ7a3XsneXySt1RVDX27Jnl7d/9akv9N8vQ7Wdd1SZ44rOuwJMdM9e2d5MXdvVuS45MckSTDgd3hSU4KLI/tauN0t48Nbc9L8v3uflSSRyX546p62NC3X5IXJdkzya8kedrQfu8kX+juvbr7nC1s7ytJ9u/uRyZ5VZLXT/XtneTQ7j4gyT8nOSpJqmqHJI9Nctpd+6iwWR9KcnhVbZvk4Um+MNW3qDFbVU9OckiSR3f3XkneOLXcuu7eL8lLMuJKEFhBhyT5VHd/Ncl3q2qfof2u7uNhXi1lPz99LLJbkm27+6JVqxiW13eG753vTPLSoe0VST49HKM8PsmbquresypwLTPlbe2oJK+vqt9K8rMkD07ygKHvqu7+0vD8/CS73Mm67pnkbcOZj1uT7DbV98XuvipJuvvqqvpuVT1y2NaF3f3dZfk0sOkpb09K8vCqOnR4vUMmgelPMhmbX0+SqvpgJme4/yWTMXzKIra3Q5L3V9WuSTqT/wcbnNHdNyRJd3+2qt5RVTtlEs6eYkoRK6W7L67J/cPWZ3IWe9qixmySg5K8t7t/NKzzhqnlPjo8LuZvA6yG9UneOjz/0PD6E7nr+3iYS0vcz38kySur6mVJnpvkfatSLKyM6WORDScLnpTkD6tqQ8C0bZKHJrl8lWtb8wRKa8czk+yUZJ/u/r9h+tq2Q98tU8vdmmS74flPs/Eqtm2nlvnLJNcm2Wvov3mq76YF2z0ukzMkD8zkiiVYSZXkRd19+u0aqw7M5EBr2obXNy+4b9Lmxv1rk3ymu586HNidNdW3cNyfkORZmVyV95xRnwDGOzXJm5McmOQXptrHjNnN2fD34dY4ZmDGqur+SX47yW9UVSfZJpN9+WlZ/D4etkaj9vPd/aOqOiOTK/r+KMk+gfk1feyd3P74O9n0sUgleXp3X7HCtXEnTHlbO3ZIct0QJj0+yc6LeM/V2fgH6NCp9h2SfLu7f5bk2Zkc0G3Ox5IcnMn0o9O3sBwsh9OT/FlV3TOZXOY9dfnrflX1sGH65WGZ3NB1U67OxnE/Pf1zh2y8EeZRd1LH+zKZIpTuvmxE/bAUxyd5TXdfsqB9sWP2jCTPqaqfT2770g7z6NAkJ3b3zt29S3c/JMlVSfbP4vfxsDVayn7+uExuS3Fud39vZcuDu+QbSfasqntV1X2TPGER7zk9yYs23MJlmBHDDAiU7uaqal0mqe7JSfatqksyua/RVxbx9jdn8uX8wiTTP6v7jiRHDje43CNbONPd3T9J8pkkH3aGkFVwXJLLklxQVV9O8u5sPJNxbpK3ZXIp7FWZhJ2b8pokb62q8zI5E7LBG5P8w/D/YYtXanT3tcN23rvEzwGL1t3f7O5jNtG1qDHb3Z/K5Oz3eVX1pWy8PwHMm/W54777lKF9sft42OosZT/f3ecn+UEcizCnNnxP7e7/TvLhJF8eHi9cxNtfm8kUz4ur6tLhNTNQ3QuvEObuZPhFh/cMNyybxfbvkeSCJM/o7itnUQOstuFKj0uS7N3d3591PQB3Z8O05pd29+/PuhaYF1X1S5lMgdtjmFUAc2XW31NZHq5Quhurqj/N5KdF/25G298zydeSnClMYq2oqoMyOUP+T8IkAGC1VdURmfwa3CuEScyjWX9PZfm4QgkAAACAUVyhBAAAAMAoAiUAAAAARhEoAQAAADCKQAkAWPOq6qiq6uHfbpvoP2Cq/6AVrOG5W6jtV1diuwAASyFQAgDY6IdJnr2J9iOHvpV0VJI7BEoAAPNIoAQAsNFHkzyrqmpDQ1Vtl+TQJKfMrCoAgDkjUAIA2OjEJDsnedxU21MzOWa6Q6BUVc+qqouq6uaq+k5VnVhVD1qwzNVVdVJVHV5Vl1fVTVV1XlU9bmqZs5IckOQ3p6bWnbVgcztW1clV9YOq+p+qOqaqtl2ejw0AMI5ACQBgo28kOTu3n/Z2RJKPJblxesGqOjqTAOryJE9L8vIkv5Pks1W1/YL17p/kr5K8MslhSbZJ8omquu/Q/4IkFya5OMljhn8vWLCOE5P817Ctdyb58yR/u8TPCQBwl6ybdQEAAHPmhCRvqaq/SHK/JAclefL0AlW1TZLXJjmruw+fav9Kks9lci+kY6becp8kj+ju7w3LXZPk3CS/m+QD3X1ZVf0gybru/s/N1PWB7n718Pzfq+rRSdYnefVmlgcAWDGuUAIAuL2PJLlXkj9I8swk1yQ5c8Eyuyf5xSQnTzd29zmZXOV0wILlP78hTBpcMjw+dERdpy14fcnI9wMALBtXKAEATOnuH1bVv2Yy7W2XJCd398+m7tOdJPcfHr+9iVVcM9W/wQ0LtnHLsL4x90C6YcHrWzIJvgAAVp1ACQDgjk7I5Iqge2QyrWyhDeHOAzfR98Ak569QXQAAc8GUNwCAOzojyYeTvKu7L91E/xVJrk1y+HRjVT02k1+JO2sJ27wlyXZLeB8AwKpzhRIAwALdfWs2fWXSbf1V9aok766qk5KclOTBSV6X5Mokxy9hs5cleUFVHZbJr7n9sLuvWMJ6AABWnEAJAGAJuvvYqvpRkpcl+XiSG5N8Mslfd/dNS1jlP2Zys+/jkmyf5LNJDlyeagEAlld196xrAAAAAGAr4h5KAAAAAIwiUAIAAABgFIESAAAAAKMIlAAAAAAYRaAEAAAAwCgCJQAAAABGESgBAAAAMIpACQAAAIBR/h+4Z6/WZQFvjgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "month_mapper = { '01': 'January', '02': 'February', '03': 'March', '04': 'April', '05': 'May', '06': 'June'}\n",
    "labels = []\n",
    "for value in monthly_stats.index:\n",
    "    labels.append(month_mapper[value])\n",
    "\n",
    "plt.figure(figsize = (20, 12))\n",
    "plot = sns.barplot(monthly_stats.index, monthly_stats.values)\n",
    "plt.xlabel(\"Month\", fontsize = 16)\n",
    "plot.set_xticklabels(labels)\n",
    "plt.ylabel(\"Commits\", fontsize = 16)\n",
    "plt.title(\"Commits in each month of 2019\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I've had the **maximum commits** during the month of **March** and **minimum commits** during the month of **January**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Everyday commits in March 2019\n",
    "\n",
    "I'd also like to check the number of commits I've done across each day of 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "commits['Date only'] = pd.to_datetime(commits['Date'].apply(lambda date: date.split('T')[0]))\n",
    "commit_stats = commits[(commits['Year'] == '2019')\n",
    "                       & (commits['Month'] == '03')]['Date only'].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Commits in March, 2019')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtBYejqrqR6vqjVV1TlV9pqoOXPQMAAAAAKxv7yWc80VJTh5jPLSqrpPkBkuYAQAAAIB1LDQcVdWPJLlHkkcnyRjjsiSXLXIGAAAAAGaz6FvVbp3kwiR/U1Ufq6qXV9U+a3eqqiOr6qNV9dELL7xwwSMCAAAAkCw+HO2d5C5JXjrGuHOSS5L8t7U7jTGOG2NsH2Ns37Jly4JHBAAAACBZfDj6YpIvjjE+NP3+jZmEJAAAAAA2mYWGozHGV5P8a1XdbvrSwUnOXuQMAAAAAMxmGU9Ve1KS106fqHZukscsYQYAAAAA1rHwcDTG+HiS7Ys+LwAAAADzWfQaRwAAAABcTQhHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0Np70SesqvOSXJzk8iTfH2NsX/QMAAAAAKxv4eFo6l5jjIuWdG4AAAAAZuBWNQAAAABay7jiaCR5Z1WNJC8bYxy3doeqOjLJkUmydevWBY8HLMJrj7//skfYoV979DuWPQKwIIe/6fhlj7BDJz3k0csegRkd8aYPLnuEHTrhIQcuewQAruaWccXRfxpj3CXJIUmeUFX3WLvDGOO4Mcb2Mcb2LVu2LH5CAAAAABYfjsYYX5p+viDJiUnutugZAAAAAFjfQsNRVe1TVfuufJ3kfknOWuQMAAAAAMxm0Wsc3SzJiVW1cu6/HWOcvOAZAAAAAJjBQsPRGOPcJHda5DkBAAAA2DXLWBwbAAAAgKsB4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSuUjiqqttX1UOqav+NGggAAACAzWHmcFRVL6mq/7Xq+yOSfCLJG5KcXVV3neNYe1XVx6rqpLmmBQAAAGBh5rni6JAkH1j1/bOTnJTkTkk+nOTYOY51dJLPzLE/AAAAAAs2Tzi6RZLzkqSqfiLJzyV53hjjU0lenGSmK46m7z0sycvnmhQAAACAhdp7jn3/PckNp18flOTbST46/f47Sfad8TgvTPK0ne1fVUcmOTJJtm7dOseILMJ5L/6lZY+wQ9uO+vtlj7Awb3/FocseoXXIb75t2SNwDXLIWx647BFab3/gW5Y9wsIcdsKLlz1C661HHLXsEeBq47+ccO6yR9ihvzviNsseAeAab54rjs5M8oSqukOSJyQ5ZYzxg+m2Wyf5ynoHqKrDk1wwxjhjZ/uNMY4bY2wfY2zfsmXLHCMCAAAAsFHmueLo95OcnMmC2N9K8turtv1SJuscrefuSR5YVYcmuV6SG1XVa8YYj5hjDgAAAAAWYOZwNMb4SFVtTfIzST47xvj2qs3HJfnnGY7x9CRPT5KqumeS3xWNAAAAADanmW9Vq6pnJvmRMcYZa6JRMrmN7eEbOhkAAAAASzXPGkfHJvmJHWzbf7p9ZmOMU8cYh8/zHgAAAAAWZ55wVDvZduMk372KswAAAACwiex0jaPpOkT3XvXS46ZPRlvt+kkOS/LpjR0NAAAAgGVab3Hsg5L89+nXI8ljmn0uS3J2kqM2cC4AAAAAlmynt6qNMZ49xrjWGONamdyqdsDK96s+rjfGuMsY44OLGRkAAACARVjviqMfmsYjAAAAAK4h1lvjaGuSr4wxvjf9eqfGGP+yYZMBAAAAsFTrXXH0hSQHJvlwkvMyWedoZ/bagJkAAAAA2ATWC0e/keTzq75eLxwBAAAAsIfYaTgaY7xy1dfH7/ZpAAAAANg0LHgNAAAAQGvmp6olSVU9IMnDktwyyfXWbB5jjIM2ajAAAAAAlmvmK46q6mlJ3pbk8CT7JLl8zccPdseAAAAAACzHPFccPTHJy5I8cYxx+W6aBwAAAIBNYp41jm6U5A2iEQAAAMA1wzzh6B1JDthdgwAAAACwucx7q9qJVTWSvDPJN9fuMMY4d6MGAwAAAGC55glHI8nFSf4oyXN3sM9eV3kiAAAAADaFecLR8Ul+IckLkpyT5LLdMRAAAAAAm8M84eheSZ4wxjh+N80CAAAAwCYyz+LYFyb52u4aBAAAAIDNZZ5w9OIkj6+qed4DAAAAwNXUPLeq3TjJHZKcXVWn5MpPVRtjjGM3bDIAAAAAlmqecPT7q77+6Wb7SCIcAQAAAOwhZg5HYwy3qAEAAABcg4hBAAAAALTmuVUtSVJVleQWSa63dtsY49yNGAoAAACA5Zs5HFXVTZP8ZZIH7+R9e23EUAAAAAAs3zxXHL0iyb2SvCTJOUku2y0TAQAAALApzBOO7pXk6DHG8btpFgAAAAA2kXkWx/5Gkq/trkEAAAAA2FzmCUd/keS3p4tjAwAAALCHm/lWtTHG86tq/yRnV9W7knzzyruMYzd0OgAAAACWZp6nqh2a5AlJrpvkds0uI4lwBAAAALCHmOdWtecn+UiSOyW57hjjWms+9to9IwIAAACwDPM8VW1rkqPGGJ/aXcMAAAAAsHnMc8XRx5Lsv7sGAQAAAGBzmSccHZXkd6vq7rtrGAAAAAA2j3luVfv7JDdKclpVXZLkW2u2jzHGrTZsMgAAAACWap5w9O5MnpwGAAAAwDXAzOFojPHo3TgHAAAAAJvMPGscAQAAAHANMlc4qqo7VtUbq+rCqvr+9PPrq+qOu2tAAAAAAJZj5lvVququSd6b5NIkb0ny1SQ3T/KLSQ6rqnuMMc7YLVMCAAAAsHDzLI79vCRnJTl4jHHxyotVtW+Sd023329jxwMAAABgWea5Ve2AJM9bHY2SZPr9nyQ5cCMHAwAAAGC55glH4ypuBwAAAOBqZJ5w9KEkz5jemvZDVbVPkmOSnL6RgwEAAACwXPOscfSMJKcmOb+qTkrylUwWxz40yT5JDtrw6QAAAABYmpnD0Rjjw1V1QJJnJrl/kpsk+UaS9yR5zhjjU7tnRAAAAACWYafhqKquleSwJF8YY5w1xvhkkoeu2eeOSbYlEY4AAAAA9iDrrXH0iCSvS3LJTva5OMnrqurhGzYVAAAAAEs3Szj6mzHGF3a0wxjjvCSvSPKoDZwLAAAAgCVbLxzdJck7ZzjOu5Jsv+rjAAAAALBZrBeO9k3yzRmO883pvgAAAADsIdYLRxcludUMx9k63RcAAACAPcR64ej9mW3tokdP9wUAAABgD7FeOHphkoOr6gVVdZ21G6vq2lX1wiT3TvKC3TEgAAAAAMux9842jjE+WFVPTfLnSX6tqt6Z5Pzp5lsluW+SmyZ56hjj9N06KQAAAAALtdNwlCRjjBdW1ZlJjkny4CTXn266NMmpSf54jPG+3TYhAAAAAEuxbjhKkjHGaUlOq6prJdlv+vLXxxiX77bJAAAAAFiqmcLRijHGD5JcsJtmAQAAAGATWW9xbAAAAACuoYQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWgsNR1V1var6cFV9oqo+XVXPXuT5AQAAAJjd3gs+33eT3HuM8Z2qunaS91fV28cYpy94DgAAAADWsdBwNMYYSb4z/fba04+xyBkAAAAAmM3C1ziqqr2q6uNJLkhyyhjjQ4ueAQAAAID1LfpWtYwxLk/y81X1o0lOrKo7jDHOWr1PVR2Z5Mgk2bp166JHBAAA4Brkc3/xtWWPsEO3fdLNlj0CM7rgJW9f9gg79GNPPGSX37u0p6qNMb6V5D1JHtBsO26MsX2MsX3Lli2LHw4AAACAhT9Vbcv0SqNU1fWT3DfJOYucAQAAAIDZLPpWtVskeWVV7ZVJtHr9GOOkBc8AAAAAwAwW/VS1Tya58yLPCQAAAMCuWdoaRwAAAABsbsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtBYajqrqllX1nqo6u6o+XVVHL/L8AAAAAMxu7wWf7/tJnjrGOLOq9k1yRlWdMsY4e8FzAAAAALCOhV5xNMb4yhjjzOnXFyf5TJIfX+QMAAAAAMw/gcglAAAgAElEQVRm0Vcc/VBVbUty5yQfarYdmeTIJNm6desVtl340tfs/uF20ZbfecSyR2BGH3rZ4cseYYf+4+NOWvYIzOglr7n/skdoPfER75hpvz94/QN28yS77jm/fPKyR1iIQ088dtkj7NDbHvzsZY8AMLMXnfjVZY+wQ0c/+Obr7vPmN1y0gEl2zYMett+yR+Aa4msvOn3ZI+zQzY4+YNkjLNVSFseuqhsmeVOSJ48xvr12+xjjuDHG9jHG9i1btix+QAAAAAAWH46q6tqZRKPXjjFOWPT5AQAAAJjNop+qVklekeQzY4znL/LcAAAAAMxn0Vcc3T3JI5Pcu6o+Pv04dMEzAAAAADCDhS6OPcZ4f5Ja5DkBAAAA2DVLWRwbAAAAgM1POAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAIDWQsNRVf11VV1QVWct8rwAAAAAzG/RVxwdn+QBCz4nAAAAALtgoeFojHFakm8s8pwAAAAA7Jq9lz1Ap6qOTHJkkmzdunXJ0wAAbF6Hv/ENyx5hh0566MPW3edBbzx5AZPsmjc/1IXyMKsPvvLCZY+wQwc+asuyR1iIr/75Z5c9wg7d/Kk/tewRuAo25eLYY4zjxhjbxxjbt2y5ZvyPHAAAAGCz2ZThCAAAAIDlE44AAAAAaC00HFXV65J8MMntquqLVfWbizw/AAAAALNb6OLYY4yHL/J8AAAAAOw6t6oBAAAA0BKOAAAAAGgJRwAAAAC0hCMAAAAAWsIRAAAAAC3hCAAAAICWcAQAAABASzgCAAAAoCUcAQAAANASjgAAAABoCUcAAAAAtIQjAAAAAFrCEQAAAAAt4QgAAACAlnAEAAAAQEs4AgAAAKAlHAEAAADQEo4AAAAAaAlHAAAAALSEIwAAAABawhEAAAAALeEIAAAAgJZwBAAAAEBLOAIAAACgJRwBAAAA0BKOAAAAAGgJRwDA/2/v3oMlr+s7jT8fGEUUFcFrBMQrJJa7eEu0EhKNbjRqNKtRE2uNs2iMtfEaKxoTsmLWqHE3xk0KTVlWvEQRASvKxgiLd00WRZEVlZtZUUTxhsjqBuTy2T/6d+R47OH0GZjz+727n1fVqZnTfZh53jNDn57vdPeRJEmS5vLgSJIkSZIkSXN5cCRJkiRJkqS5PDiSJEmSJEnSXB4cSZIkSZIkaS4PjiRJkiRJkjSXB0eSJEmSJEmay4MjSZIkSZIkzeXBkSRJkiRJkuby4EiSJEmSJElzeXAkSZIkSZKkuTw4kiRJkiRJ0lweHEmSJEmSJGkuD44kSZIkSZI0lwdHkiRJkiRJmsuDI0mSJEmSJM3lwZEkSZIkSZLm8uBIkiRJkiRJc3lwJEmSJEmSpLk8OJIkSZIkSdJcHhxJkiRJkiRpLg+OJEmSJEmSNJcHR5IkSZIkSZrLgyNJkiRJkiTN5cGRJEmSJEmS5vLgSJIkSZIkSXN5cCRJkiRJkqS5PDiSJEmSJEnSXB4cSZIkSZIkaS4PjiRJkiRJkjSXB0eSJEmSJEmay4MjSZIkSZIkzeXBkSRJkiRJkuby4EiSJEmSJElzeXAkSZIkSZKkuTw4kiRJkiRJ0lweHEmSJEmSJGkuD44kSZIkSZI0lwdHkiRJkiRJmsuDI0mSJEmSJM3lwZEkSZIkSZLm8uBIkiRJkiRJc3lwJEmSJEmSpLk8OJIkSZIkSdJcHhxJkiRJkiRpLg+OJEmSJEmSNJcHR5IkSZIkSZrLgyNJkiRJkiTN5cGRJEmSJEmS5vLgSJIkSZIkSXN5cCRJkiRJkqS5PDiSJEmSJEnSXB4cSZIkSZIkaS4PjiRJkiRJkjTXth8cVdUjq+q8qvpiVf3hdv/8kiRJkiRJWsy2HhxV1d7AscCvAj8D/FZV/cx2NkiSJEmSJGkx2/2Io58Fvtjd/6e7fwgcDzxumxskSZIkSZK0gOru7fvJqn4DeGR3P2N4/6nAz3X3szd83DOBZw7vHgactwezbgt8ew/++Htaej/kb0jvh/wN6f2QvyG9H9wwBen9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf8N29N+lu2+32Qft2MMRu6W73wC8YTt+rqr6VHc/YDt+rj0hvR/yN6T3Q/6G9H7I35DeD26YgvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2Qv2FK/dv9VLWLgYPXvX/QcJkkSZIkSZImZrsPjs4A7llVd62qmwK/CZy8zQ2SJEmSJElawLY+Va27r66qZwOnAnsDf9vdn9/Ohjm25Slxe1B6P+RvSO+H/A3p/ZC/Ib0f3DAF6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/w2T6t/XFsSVJkiRJkpRju5+qJkmSJEmSpBAeHEmSJEmSJGkuD44kSZIkSZI0lwdH0g1UVbcfu0EaS1UdUFUHjN2h5VBV9xu7YdVV1W3HbtgdVXWbqrrV2B3S2KrqVlV1/6q6zdgtqyz1thS8PdV8HhwNqup9YzdsZvhE8Mqq+ruqesqG6143VtdWVNUdq+r1VXVsVR1YVcdU1dlVdUJV3Wnsvs2s/SV53duBwCeHG9iIvzxX1ZlVdXRV3X3slt1RVQ+oqg9V1duq6uCqOq2qvldVZ1TVfcfuW0RV7VdVf1pVnx/av1VVp1fVzrHbFlFVh1TV8VX1LeATzP4f+OZw2aHj1t1wVXX22A2bGf7sH19VH6uqP6qqm6y77t1jti2qqu634e3+wMlVdd+EA6SqurSq3lhVD6uqGrtnd1TVr1bVl6rq48Ov++eBT1TVV6vqYWP3baaqfqqq3lpV3wO+DXyuqr4y3Le4yWb//dR5W7Q9qurwqnpfVb23qu5eVW+uqsuq6pNV9dNj921muD902+H7jwA+B/w5cFZVPXHUuAWl356m35bCctyeVtWtq+pVVXXu8GfqO1V1znDZ/mP33RBTOKtYqa+qdj13RAv4h+6e9MFFVb0LuAA4HTgKuAp4SndfWVVndnfCHe1TgPcCtwCeArwdOA74deDh3f24EfM2VVXXAl/ecPFBwFeB7u67bX/V1lTVl4B3AU8CLgHeAbyzu782atiCquqTwEuB/YFXAy/o7pOGT8wv7+4Hjxq4gKp6D/D3wPuZ/T7cAjgeOBq4uLv/aMS8TVXV/wJeC5zU3dcMl+0NPBF4fnc/aMy+RVTV43d1FfA33X277ezZqqo6jdn/x6cDTwfuD/xad3+nqj7T3ZM/RB1uT08Hrlx38YOGy7q7f3mUsAVV1XnAXwO/BRwKnAS8o7tPH7NrK6rqLGb9+wP/ADy6u08f/rL89qnfr6iqDwJ/2t0fHv6fPpLZ7ehLgNt39zNHDVyAt0Xjq6qPAv8V2A94FfBi4J3AY5h9Tpv0X/yr6uzuvs/w/X9m9neDC4fDpA90978dt3Bz6ben6belsDS3p6cCHwTe0t2XDJfdEXga8LDu/pUx+zYz9bOKVTs4ugb4CLNf/I0e1N37bnPSllTVWd19xLr3/xh4FPBY4LSQG6Uf3Ymoqq909yHrrvuxfVNUVS8E/h3wB9199nDZl7r7ruOWLW79IWNVHcnsE93jgXOYfZJ+w5h9m9nkz1DKndT/vf6OXFWd0d0PrKq9gC909+Ej5m2qqi7o7ntu9bopqaqrmB1cz/sk+BvdfcttTtqSOZ8P/gOzO3ePBU4M+XzwBOC5wKu6+33DZTG3pxtuSw8BfnN42x84fuoHwPATGy7q7oPXXZfwOXnjbemnu/v+w/fPnfptKXhbNAUb7ld8sbvvse66yf/D7PDolgd39+VV9XHgF7v72rXruvve4xZuLv32NP22FJbm9vS87j5sq9dNxdTPKnaM+ZOP4Bzgd7v7go1XVNVFI/Rs1T5VtdfaJ4Pu/rOquhj4KLN/JUmw/umRb72e6yapu/+iqt4J/OXwZ+alzL+zF6G7PwZ8rKqew+xA7MnApA+OgCuq6leAWwNdVb/e3e+uql8Crhm5bVE/qKpf6O6PV9VjgUsBuvvakIdof7pmT499C7B223kws3/R+cxoVVvzWeC/dffnNl5RVQ8foWerblJVN+vuKwC6+21VdQlwKrNHsE1ed79r+NfB/1JVRwEvJOv29Ef/r3b3V5g9AvLVVXU4s9vSBJdV1e8CtwK+W1UvAE4AHg58f9SyxXxrOKj4ELN/ALkQYLgdnfx9ioG3RePbe933X7PhuptuZ8huehnwoao6Fvgn4MSqOhl4KHDKqGWLS789Tb8theW4Pf1yVb2I2SOOvgFQVXcAdnLd/dUpm/RZRcofghvLMex683O2sWN3/Q/gxx66391vZnZn+4djBO2G91TVfgDdffTahVV1D+D80aq2oLu/2t1PZHYifBpw85GTtuonfp27+5ruPqW7/+MYQVv0LGZ/5o8CHgE8tKouA17H7NELCZ4FvGbofhFDd1XdDjh2zLAF/TZwNrM7q6cOb8cwe12Fp46XtSXPBy7fxXX/fjtDdtMbgZ9bf0F3v5/Z0wV/4i+gU9Xd3+/uFwCvYHYQmfKPIDC7c/0Tuvvc7n7ZdsfspqcB9wPuBqw9hP9UZk+h/Z2xorbgKGaPbDmV2f8Pzx4uP4DZo14SeFs0vmPX3Tf90WuGDvdN3z9a1YK6+wRmhyuHAfdidtj1IGaPIn/hmG1bkH57mn5bCstxe/pk4EDgIzV7jaNLgQ8z2/CkMcMWdAwTPqtYqaeqSTe2qtoXuPu8fymUJC1u+FfNW3b3rv4SLUmSpBGs2iOOqKpH1Oyrep08vL2+qh45dtei0vshf8P6fmYvnvh7Sf2wXL8H6/ofMXbXVqT/HuxKVf3nsRtuqPQNqf09cznkbliT3g/5G5L6h88HT68NX5VyeArn5KX3Q/6Gdf132XB5RD8s1e/BoRsuj+iH/D9HNfOkqnri8P2HVdVfVdV/qtnriE7a1PtX6hFHVfVaZg/hfCuzr4IFs6+I9dvABd39vLHaFpHeD/kb0vshf0N6PyzHhl2pDS9Ynih9Q3o/5G9I74f8DSn9VfUK4BeAM4FfA17b3X89XJfwwsyvBH6e0H7I35D+Zwj8PZiCJdnwOuD2zJ6ueTmwD3Ay8GjgG1O/fz31/lU7ODq/u+815/ICzp/6VwJK74f8Den9kL8hvR/yN1TVrp5KVMC+3T35L7yQviG9H/I3pPdD/ob0foCqOhu4b3dfXVX7A8cB53X3CyrgK4Wm90P+hvR+yN+Q3g/Ls6G771NVNwEuAe7U3T+sqh3Amd39b0ZOvF5T7x/9IU/b7IqqeuCcyx8IXLHdMbshvR/yN6T3Q/6G9H7I33AZcM/uvtWGt1sCXx87bkHpG9L7IX9Dej/kb0jvB9jR3VcDdPdlzP6l/1ZVdSIZX9ErvR/yN6T3Q/6G9H5Yjg1r/VcBZ3T3D4f3rwauHTNsQZPun/y/xNzIdgKvr6pbct3TQw4GvjdcN3U7ye6H/A07ye6H/A07ye6H/A1vBe4CfGPOdcdtc8vuSt+Q3g/5G9L7IX9Dej/Av1TVL3X3R2D2VU6Bp1fVy4EnjJu2kPR+yN+Q3g/5G9L7YTk2XFJV+/XsK7b+6HVDq+qOZHwF8kn3r9RT1dYMv/h3Ht69uLsvGbNnq9L7IX9Dej/kb0jvh+XYIEnafTX76qx097/Oue7O3X3x9lctLr0f8jek90P+hvR+WI4Nu1JVtwBu0d3fHLtld0ylf9WeqgZAd1/S3Z/u7k8Dzxq7Z6vS+yF/Q3o/5G9I74fl2LCmqo4Zu+GGSt+Q3g/5G9L7IX9DWn93/+vGv6itbUj4i1p6P+RvSO+H/A3p/bAcG+apqmO6+wdjH7rsrin1r+TB0QaPHTvgBkrvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den94IYpmEy/B0ezr7yRLL0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPeDG6ZgMv0r+RpH61XVXt09+quU7670fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD26Ygin1r9Qjjqrq5lX1oqr6g6q6WVXtBN5dVa+uqv3G7ttMej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I7wc3TMHU+1fqEUdVdQJwEbAvcBhwDvBOZs8dvGN3P3XEvE2l90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fnDDFEy+v7tX5g04a/i2gEu47uCsgM+O3bfs/cuwIb1/GTak9y/DhvT+ZdiQ3r8MG9L7l2FDev8ybEjvX4YN6f3LsCG93w3TeJt6/0o9VW1Nz34H/nH4du39mIdepfdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H5wwxRMtX/VDo4+tfb8wO4+au3Cqro78H9Hq1pcej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I7wc3TMGk+1fqNY6uT1VVB/9ipPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H5wwxRMoX/HmD/5GKrqcOBxwJ2Hiy4GTu7uc8arWlx6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvBzdMwZT7V+qpalX1YuB4Zi8w9cnhrYB3VNUfjtm2iPR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4PbpiCqfev1FPVqup84N7dfdWGy28KfL677zlO2WLS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P7hhCqbev1KPOAKuBX5qzuV3Gq6buvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4PbpiCSfev2mscPR/4QFVdAFw0XHYIcA/g2aNVLS69H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3gxumYNL9K/VUNYCq2gv4WX78BafO6O5rxqtaXHo/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO8HN0zBlPtX7uBoo6p6Zne/YeyO3ZXeD/kb0vshf0N6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7wQ1TMKX+VXuNo3meNXbADZTeD/kb0vshf0N6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7wQ1TMJl+D45mX+IuWXo/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO8HN0zBZPp9qlrVQd391bE7dld6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvBzdMwZT6V+7gqKruBjweOBi4BjgfOK67Lx81bEHp/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H9wwBVPuX6mnqlXVc4G/AW4GPBDYh9lvyulV9ZAR0xaS3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+8ENUzD5/u5emTfgbGDv4fs3Bz48fP8Q4DNj9y17/zJsSO9fhg3p/cuwIb1/GTak9y/DhvT+ZdiQ3r8MG9L7l2FDev8ybEjvd8M03qbev1KPOBrsGL7dB9gPoLu/AtxktKKtSe+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f3ghimYbP+OzT9kqbwROKOqPgEcCfw5QFXdDrh0zLAFpfdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H5wwxRMun8VXxz73sBPA5/r7nPH7tmq9H7I35DeD/kb0vshf0N6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g9umIIp96/cwdGuVNV+3f39sTt2V3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO8HN0zBFPpX8TWOduULYwfcQOn9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO+H/A3p/ZC/Ib0f3DAFo/ev1GscVdXv7+oqhhefmrL0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD26Ygqn3r9ojjl4B3Aa45Ya3/cj4tUjvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den94IYpmHZ/d6/MG/DPwP13cd1FY/cte/8ybEjvX4YN6f3LsCG9fxk2pPcvw4b0/mXYkN6/DBvS+5dhQ3r/MmxI73fDNN6m3r9SL45dVYcBl3b3t+Zcd4fu/sYIWQtL74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO+H/A3p/eCGKZh6/0odHEmSJEmSJGlx4z9XbhtV1a2r6lVVdW5VXVpV36mqc4bL9h+7bzPp/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H9wwBVPvX6mDI+AE4LvAQ7r7gO4+EHjocNkJo5YtJr0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPeDG6Zg0v0r9VS1qjqvuw/b6nVTkd4P+RvS+yF/Q3o/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vvBDVMw9f5Ve8TRl6vqRVV1h7ULquoOVfVi4KIRuxaV3g/5G9L7IX9Dej/kb0jvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+8ENUzDp/lU7OHoycCDwkar6blVdCnwYOAB40phhC0rvh/wN6f2QvyG9H/I3pPdD/ob0fsjfkN4P+RvS+yF/Q3o/5G9I74f8Den94IYpmHT/Sj1VDaCqDgcOAk7v7u+vu/yR3X3KeGWLSe+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej/kb0jvh/wN6f3ghimYdH93r8wb8FzgPODdwIXA49Zdd+bYfcvevwwb0vuXYUN6/zJsSO9fhg3p/cuwIb1/GTak9y/DhvT+ZdiQ3r8MG9L73TCNt6n3j/4LtM2/GWcD+w3fPxT4FPC84f3PjN237P3LsCG9fxk2pPcvw4b0/mXYkN6/DBvS+5dhQ3r/MmxI71+GDen9y7Ahvd8N03ibev8OVstePTzkq7svrKqHACdV1V2AGrVsMen9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO+H/A3p/ZC/Ib0f3DAFk+5ftRfH/kZVHbH2zvAb8xjgtsB9RqtaXHo/5G9I74f8Den9kL8hvR/yN6T3Q/6G9H7I35DeD/kb0vshf0N6P+RvSO8HN0zBpPtX6sWxq+og4OruvmTOdT/f3f80QtbC0vshf0N6P+RvSO+H/A3p/ZC/Ib0f8jek90P+hvR+yN+Q3g/5G9L7IX9Dej+4YQqm3r9SB0eSJEmSJEla3Ko9VU2SJEmSJEkL8uBIkiRJkiRJc3lwJEmSVl5V7ayqXvf2g6q6sKr+vqqeVFVb/oomVXVEVR1TVQfsiWZJkqTt4MGRJEnSdZ4IPBh4FPAnwJXAO4DTqmrfLf5YRwAvBTw4kiRJsXaMHSBJkjQhZ3X3F9e9/3dVdSJwIvBq4DnjZEmSJI3DRxxJkiRdj+5+F/Ae4Heq6uYAVfWyqjqzqi6vqm9X1Qer6kFr/01V7QTeNLx7wbqnwB06XL+jql5SVedW1ZVV9bWq+ouqutm2jpMkSdqEB0eSJEmb+0dgH+ABw/t3Bv4SeBywE/gm8NGqus9w/XuBlw/fX3v624OBrw+XvQ04GjgOeDTwSuDpwNv35AhJkqSt8qlqkiRJm/vK8O2dALr7GWtXVNXewCnA54FnAM/r7m9V1b8MH/JjT3+rqiOBJwNP6+63Dhe/v6ouBd5WVUd091l7do4kSdJifMSRJEnS5ta+qloDVNXDq+pDVfUd4GrgKuBewGEL/FiPBH4InDQ8ZW1HVe0A/udw/S/euOmSJEm7z0ccSZIkbe7g4duvV9X9mNKUv7cAAAGtSURBVD117VRmTy/7OnAN8EZgkdcouj1wU+AHu7j+wBuWKkmSdOPx4EiSJGlzjwauAD4N/DGzRxk9vruvWvuAqroNcNkCP9Z3hh/ryF1c/7UblipJknTj8eBIkiTpelTVE4DHAv+9u//f8JXVrmF42trwMb8MHAJ8ad1/euXw7b4bfshTgBcDt+7uD+yxcEmSpBuBB0eSJEnXOaKqbsvsqWSHAI9h9lXRTgNeMnzMKcDzgTdX1ZuYvbbRnwAXb/ixvjB8+3tV9RZmr4P02e7+cFW9g9lrHL0G+CRwLXAo8Cjgxd19/h7aJ0mStCXV3Zt/lCRJ0hKrqp3Am9ZddAXwTeBM4DjgpF53p6mqngP8PnBH4HPMDpWOBujuh6z7uJcCzxw+bi/grt19YVXtBTwHOIrZC2pfCVzI7HWT/qy7v7cHZkqSJG2ZB0eSJEmSJEmaa6+xAyRJkiRJkjRNHhxJkiRJkiRpLg+OJEmSJEmSNJcHR5IkSZIkSZrLgyNJkiRJkiTN5cGRJEmSJEmS5vLgSJIkSZIkSXN5cCRJkiRJkqS5PDiSJEmSJEnSXP8fIyJj1HL8DFsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = []\n",
    "for value in commit_stats.index:\n",
    "    labels.append(value.date())\n",
    "    \n",
    "plt.figure(figsize = (20, 12))\n",
    "plot = sns.barplot(commit_stats.index, commit_stats.values)\n",
    "plt.xlabel(\"Date\", fontsize = 16)\n",
    "plt.xticks(rotation = 90)\n",
    "plot.set_xticklabels(labels)\n",
    "plt.ylabel(\"Commits\", fontsize = 16)\n",
    "plt.title(\"Commits in March, 2019\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I made maximum commits on the **2nd of March 2019**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most popular languages\n",
    "\n",
    "Next, I'll explore languages that I've used in each repository."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_languages = []\n",
    "for languages in repos['Languages']:\n",
    "    if type(languages) == str:\n",
    "        for language in languages.split(','):\n",
    "            list_of_languages.append(language.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Language distribution amongst all repositories')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4Wt3EfnznVNsBGQKMqzMETu9Pcu+pPidljudFhuFVnxm39/0MAdQfT63nSRnCkh9nkaeuTfVdn+Wf3ydNTO833WeJ9R+dJY7N5Z5n43b+KslLM4SVP8xwX6O9p9ZVSf503Ic/yjD09Q1JbjvR56Dxs1w07udvZAivbrvUZx3bDsswrO+63PgpmLcd671g3OZXxhpqkX31qEU+/4bc9PfZDhkC2jPGz3rF+P5vM/6eyjJ+X3h5eXl5rf1XtTbrrRYA4KdTVe2Z4SbDf9VaO3yFt31skl9orf3sSm4XNmdbnhfbk6pqGfbBf93WtQDA9sRQOwBYRFXdMsNNcD+S4aqXeyT5iyQ/SHJk523/WYarKs7O8OSsp2a4uuO5PbcLm7MtzwsAYHUSPAHA4q7L8NSnIzI8ber7GYbNPLW1tpzHjW+NazIMg9krw02Vz8ow1OqtnbcLm7MtzwsAYBUy1A4AAACALub51BQAAAAA+Ik1P9Rut912a+vXr9/WZQAAAACsGaeddtolrbV1m+u35oOn9evXZ+PGjdu6DAAAAIA1o6q+uZx+htoBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuVjR4qqq7VtW/V9UXq+oLVfWCsX3Xqjqxqs4ef+6yxPIHjX3OrqqDVrJ2AAAAAGaz0lc8XZvkha21+yR5aJLnVdV9krw4yUdba/dK8tFx+kaqatckhyV5SJJ9kxy2VEAFAAAAwLa3osFTa+2C1trp4/urknwpyV2SPDHJ28dub0/ypEUWf0ySE1trl7XWLk9yYpID+lcNAAAAwJbYaVttuKrWJ/mlJP+RZPfW2gXjrO8k2X2RRe6S5NsT0+eObYut+5AkhyTJXnvtNVNdD/rzd8zUn35Oe83vbesSAAAAgK2wTW4uXlU7J/nXJH/SWrtycl5rrSVpW7P+1tpbWmv7tNb2Wbdu3dasCgAAAIAttOLBU1XdLEPo9K7W2vvG5gurao9x/h5JLlpk0fOS3HVies+xDQAAAIDt0Eo/1a6SvDXJl1prr5uY9YEkC0+pOyjJ+xdZ/MNJHl1Vu4w3FX/02AYAAADAdmilr3j61SS/m+TXq+qz4+vAJK9Ksn9VnZ3kUeN0qmqfqjoySVprlyU5PMmp4+sVYxsAAAAA26EVvbl4a+3kJLXE7N9YpP/GJL8/MX1UkqP6VAcAAADAPG2Tm4sDAAAAsPYJngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANDFTiu5sao6Ksnjk1zUWrvf2PbeJPceu9w+yXdba3svsuw5Sa5Kcl2Sa1tr+6xI0QAAAABskRUNnpIcneSIJO9YaGitPW3hfVW9NskVm1j+11prl3SrDgAAAIC5WdHgqbX2iapav9i8qqokv5Xk11eyJgAAAAD62J7u8fTwJBe21s5eYn5LckJVnVZVh2xqRVV1SFVtrKqNF1988dwLBQAAAGDztqfg6RlJ3r2J+Q9rrT0wyWOTPK+qHrFUx9baW1pr+7TW9lm3bt286wQAAABgGbaL4KmqdkrylCTvXapPa+288edFSY5Jsu/KVAcAAADAltgugqckj0ry5dbauYvNrKpbV9VtFt4neXSSM1ewPgAAAABmtKLBU1W9O8kpSe5dVedW1bPHWU/P1DC7qrpzVR03Tu6e5OSqOiPJp5N8sLV2/ErVDQAAAMDsVvqpds9Yov3gRdrOT3Lg+P7rSR7QtTgAAAAA5mp7GWoHAAAAwBojeAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXKxo8VdVRVXVRVZ050bahqs6rqs+OrwOXWPaAqjqrqr5aVS9euaoBAAAA2BIrfcXT0UkOWKT971pre4+v46ZnVtWOSd6Q5LFJ7pPkGVV1n66VAgAAALBVVjR4aq19IsllW7Dovkm+2lr7emvtR0nek+SJcy0OAAAAgLnaXu7x9Pyq+tw4FG+XRebfJcm3J6bPHdsWVVWHVNXGqtp48cUXz7tWAAAAAJZhewie/keSn02yd5ILkrx2a1fYWntLa22f1to+69at29rVAQAAALAFtnnw1Fq7sLV2XWvt+iT/mGFY3bTzktx1YnrPsQ0AAACA7dQ2D56qao+JyScnOXORbqcmuVdV3b2qbp7k6Uk+sBL1AQAAALBldlrJjVXVu5Psl2S3qjo3yWFJ9quqvZO0JOck+YOx752THNlaO7C1dm1VPT/Jh5PsmOSo1toXVrJ2AAAAAGazosFTa+0ZizS/dYm+5yc5cGL6uCTHdSoNAAAAgDnb5kPtAAAAAFibBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF2saPBUVUdV1UVVdeZE22uq6stV9bmqOqaqbr/EsudU1eer6rNVtXHlqgYAAABgS6z0FU9HJzlgqu3EJPdrrf1ikq8keckmlv+11trerbV9OtUHAAAAwJysaPDUWvtEksum2k5orV07Tn4qyZ4rWRMAAAAAfWxv93h6VpIPLTGvJTmhqk6rqkM2tZKqOqSqNlbVxosvvnjuRQIAAACwedtN8FRVhya5Nsm7lujysNbaA5M8NsnzquoRS62rtfaW1to+rbV91q1b16FaAAAAADZnuwiequrgJI9P8juttbZYn9baeePPi5Ick2TfFSsQAAAAgJlt8+Cpqg5I8hdJntBa+8ESfW5dVbdZeJ/k0UnOXKwvAAAAANuHFQ2equrdSU5Jcu+qOreqnp3kiCS3SXJiVX22qt409r1zVR03Lrp7kpOr6owkn07ywdba8StZOwAAAACz2WklN9Zae8YizW9dou/5SQ4c3389yQM6lgYAAADAnG3zoXYAAAAArE2CJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQxVYHT1V1n6r6zaq68zwKAgAAAGBtmCl4qqojqupNE9NPSXJGkn9O8sWqevCc6wMAAABglZr1iqfHJvnkxPTLkxyb5AFJPp3ksDnVBQAAAMAqN2vwtEeSc5KkqvZMct8kf9Na+3ySv0/iiicAAAAAkswePP0gyc7j+0cmuTLJxnH6e0luM6e6AAAAAFjldpqx/+lJnldV30ryvCQnttauH+fdPckF8ywOAAAAgNVr1uDp0CTHZ7ih+HeTPGdi3pMy3OcJAAAAAGYLnlprp1bVXkl+PsnZrbUrJ2a/JcnZ8ywOAAAAgNVr1iue0lr7fpLTFmn/4FwqAgAAAGBNmPXm4qmqX6qq91XVJVV1bVU9cGz/66o6YP4lAgAAALAazRQ8VdXDkpySYajdP00tf31ufM8nAAAAAH6KzXrF06uSfDjJfZP82dS805M8cB5FAQAAALD6zXqPpwcmeUprrVVVm5p3SZJ18ykLAAAAgNVu1iuefpjkVkvM2yPJFVtXDgAAAABrxazB08lJ/qSqdpxoW7jy6dlJPjaXqgAAAABY9WYdaveXSf5vkjOS/EuG0OmgqnpdkgclefB8ywMAAABgtZrpiqfW2hlJHpHkwiSHJqkkzx9nP7K1dtZ8ywMAAABgtZr1iqe01k5P8htV9TNJdk3y3dbaD+ZeGQAAAACr2szB04LW2g+TnD/HWgAAAABYQzYbPFXVy5Ic2Vo7f3y/Ka21dvh8SgMAAABgNVvOFU8bkhyf4eqmDZvp25IIngAAAADYfPDUWtthsfcAAAAAsCnLDpKq6uZV9YKqul/PggAAAABYG5YdPLXWfpTkVRmeZAcAAAAAmzTr0LkvJblHj0IAAAAAWFtmDZ5eluQvq+r+PYoBAAAAYO1YzlPtJr0oyc5JPlNV5yS5IMOT7Ba01toj51QbAAAAAKvYrMHTdUm+2KMQAAAAANaWmYKn1tp+neoAAAAAYI2Z9R5PAAAAALAsMwdPVbVHVf23qjq1qr42/vzbqrpTjwIBAAAAWJ1mCp6q6ueSfDbJHyf5XpJPjz9fkOSzVXWvuVcIAAAAwKo0683FX53kyiQPaa2ds9BYVXdLcsIZ30QgAAAgAElEQVQ4/ylzqw4AAACAVWvWoXa/luQvJ0OnJGmtfTPJhnE+AAAAAMwcPN08yVVLzLtqnA8AAAAAMwdPn03yR1V1o+WqqpL84TgfAAAAAGa+x9Mrkhyb5EtV9d4kFyS5U5KnJrlXksfNtzwAAAAAVquZgqfW2vFV9fgkr0xyaJJK0pKcluTxrbUT5l8iAAAAAKvRrFc8pbV2fJLjq+pWSXZJcnlr7QdzrwwAAACAVW2mezxV1VFVdfckaa39oLV23kLoVFV3q6qjehQJAAAAwOoz683FD06ybol5uyU5aKuqAQAAAGDNmDV4SoZ7Oi3mTkmu3opaAAAAAFhDNnuPp6p6cpInTzS9vKoumep2yyQPz3CTcQAAAABY1s3F98oQKiXD1U57J7lmqs81ST6Z5CXzKw0AAACA1WyzwVNr7fVJXp8kVfWNJE9qrZ3RuzAAAAAAVrflXPH0E621u/cqBAAAAIC1ZTn3eHpEktNba98b329Sa+0Tc6kMAAAAgFVtOVc8nZTkoUk+Pb5f6ql2Nc7bcR6FAQAAALC6LSd4+rUkX5x4DwAAAACbtZybi398sfcAAAAAsCkz3Vy8qnZIskNr7dqJtsckuV+Sj7XWPjPn+gAAAABYpWYKnpK8O8k1SX4vSarqOUneOM77cVU9rrX2kTnWBwAAAMAqtcOM/R+a5LiJ6T9PcmSS2yV5X5JD51QXAAAAAKvcrMHTHZOclyRVdc8kd09yRGvtqiRvS3L/+ZYHAAAAwGo1a/B0ZZI7jO/3S3JJa+1z4/R1SX5mTnUBAAAAsMrNeo+nTyZ5cVVdm+RPcuNhd/dMcu68CgMAAABgdZv1iqe/yHDF0wcyXN20YWLe05KcMp+yAAAAAFjtZrriqbV2dpJ7VdUdWmuXTs1+QZLvzK0yAAAAAFa1Wa94SpK01i6tqp2r6q5VtfPY9vnW2sWbW7aqjqqqi6rqzIm2XavqxKo6e/y5yxLLHjT2ObuqDtqS2gEAAABYGTMHT1X1mKramOS7Sc5J8t2q+nRV7b/MVRyd5ICpthcn+Whr7V5JPjpOT2931ySHJXlIkn2THLZUQAUAAADAtjdT8FRVj0nywSQ7Jzk8yR8meWWS2yQ5bjnhU2vtE0kum2p+YpK3j+/fnuRJiyz6mCQnttYua61dnuTE3DTAAgAAAGA7MetT7TYkOSHJ41tr1y80VtUrkhyb5OUZAqFZ7d5au2B8/50kuy/S5y5Jvj0xfe7YdhNVdUiSQ5Jkr7322oJyAAAAANhasw61e0CSN0yGTkkyTr8xyd5bW1BrrSVpW7mOt7TW9mmt7bNu3bqtLQkAAACALTBr8HRNktsuMe824/wtcWFV7ZEk48+LFulzXpK7TkzvObYBAAAAsB2aNXg6KcnhVXX3ycaq2ivDMLx/38I6PpBk4Sl1ByV5/yJ9Ppzk0VW1y3hT8UePbQAAAABsh2YNnl6U5HZJzqqqT1TVe6vq40nOTnL7cf4mVdW7k5yS5N5VdW5VPTvJq5LsX1VnJ3nUOJ2q2qeqjkyS1tplGW5ofur4esXYBgAAAMB2aKabi7fWvlJVv5jkhUkenuSBGZ5Q9/okfzdxg/BNreMZS8z6jUX6bkzy+xPTRyU5apaaAQAAANg2Zn2qXcZw6f/vUAsAAAAAa8jMwVOSVNVtk9wvyV2SnJvkzNbaVfMsDAAAAIDVbebgqapelmGo3c5Jamy+qqpe01p75TyLAwAAAGD1mil4qqqXJ/nLJEcmeU+SC5PsnuQZSV5eVTu11jbMu0gAAAAAVp9Zr3j6/5K8trX25xNtX0jysaq6IskhSTbMqTYAAAAAVrEdZux/uyQfXmLe8eN8AAAAAJg5ePqPJA9eYt6Dx/kAAAAAMPNQuz9OckxVXZvkn3PDPZ5+K8mzkjyxqn4SZrXWrp9XoQAAAACsLrMGT58bf75qfE2qJJ+fmG5bsH4AAAAA1ohZg6FXZAiUAAAAAGCTZgqeWmsbOtUBAAAAwBoz683Ff6Kqdq6qu1XVzeZZEAAAAABrw8zBU1U9vqpOT3JFkq8nuf/YfmRV/fac6wMAAABglZopeKqqJyV5f5JLkrwoww3FF3wjyUHzKw0AAACA1WzWK54OS/K21tqjk/z3qXlnJrnfXKoCAAAAYNWbNXj6hSTvHd9PP93u8iR32OqKAAAAAFgTZg2erkyy2xLz1ie5eKuqAQAAAGDNmDV4OjHJS6rq9hNtrapukeT5ST40t8oAAAAAWNV2mrH/oUk+neSsJMdlGG734iS/mOR2SZ401+oAAAAAWLVmuuKptXZOkgcmOTbJ/kmuS/KIJJ9K8pDW2vnzLhAAAACA1WnWK57SWjs3ybOn26vqFlX1gtba6+dSGQAAAACr2kxXPFXVblVVU223rKoXJvlGktfNszgAAAAAVq/NBk/jlUyvr6qrklyY5NKqeu4475lJvp7kNUm+neSAnsUCAAAAsHosZ6jdy5L8UZKPJDk9yd2TvL6q7pPkeUm+kuSQ1tr/7lYlAAAAAKvOcoKnpyV5Y2vt+QsNVfWsJEcmOTHJf2qt/ahTfQAAAACsUsu5x9Ndkxwz1fa+8efrhE4AAAAALGY5wdPNklw11bYwffF8ywEAAABgrVjOULskuUtV3WNieseJ9u9OdmytfX0ulQEAAACwqi03ePqXJdr/bZG2HRdpAwAAAOCnzHKCp//SvQoAAAAA1pzNBk+ttbevRCEAAAAArC3Lubk4AAAAAMxM8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHSxXQRPVXXvqvrsxOvKqvqTqT77VdUVE31etq3qBQAAAGDzdtrWBSRJa+2sJHsnSVXtmOS8JMcs0vX/tNYev5K1AQAAALBltosrnqb8RpKvtda+ua0LAQAAAGDLbY/B09OTvHuJeb9cVWdU1Yeq6r5LraCqDqmqjVW18eKLL+5TJQAAAACbtF0FT1V18yRPSPLPi8w+PcndWmsPSPIPSf5tqfW01t7SWtuntbbPunXr+hQLAAAAwCZtV8FTkscmOb21duH0jNbala21743vj0tys6rabaULBAAAAGB5trfg6RlZYphdVd2pqmp8v2+G2i9dwdoAAAAAmMF28VS7JKmqWyfZP8kfTLQ9J0laa29K8p+TPLeqrk1ydZKnt9batqgVAAAAgM3bboKn1tr3k9xhqu1NE++PSHLEStcFAAAAwJbZ3obaAQAAALBGCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAEAAADQheAJAAAAgC4ETwAAAAB0IXgCAAAAoAvBEwAAAABdCJ4AAAAA6ELwBAAAAEAXgicAAAAAuhA8AQAAANCF4AkAAACALgRPAAAAAHQheAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKCLnbZ1AbAtfesV99/WJTDa62Wf39YlAAAAMGeueAIAAACgC8ETAAAAAF0IngAAAADoQvAEAAAAQBeCJwAAAAC6EDwBAAAA0IXgCQAAAIAuBE8AAAAAdCF4AgAAAKALwRMAAAAAXQieAAAAAOhC8AQAAABAF4InAAAAALoQPAHA/2vvzuNtq+u6gX++96KCiqgJToGzFuKA4VD2wkotLYdMtHy0shyeSgvT6nF4yiGHrCRLLaMwhygBhzIfLSdSpBwQBURUUDM1DRkURDGG7/PHWke2x8u9CHedde7e7/frtV9nr+Hs/bms17mc+9m/328BAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMIlNVTxV1X9U1SlV9ZGqOmEbx6uq/qyqzqiqk6vqLnPkBAAAAGDHdps7wDb8aHefdTnH7p/kNuPj7kn+YvwKAAAAwCazqUY8XQEPTvLqHrwvyXWr6sZzhwIAAADgO222EU+d5G1V1Un+srsPX3f8pkk+t7D9+XHfFxdPqqrHJ3l8kuy3337TpQV2Kfd8yT3njsDo+F8/fu4IAADABthsI55+uLvvkmFK3ROq6uAr8yLdfXh3H9TdB+299947NyEAAAAAV8imKp66+wvj1zOTvDHJ3dad8oUk+y5sf++4DwAAAIBNZtMUT1V1rarac+15kh9P8tF1p70pyS+Md7e7R5KvdvcXAwAAAMCms5nWeLphkjdWVTLk+rvu/ueq+pUk6e6XJ3lLkp9MckaSryf5pZmyAgAAALADm6Z46u5PJ7nTNva/fOF5J3nCRuYCAAAA4MrZNFPtAAAAAFguiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASiicAAAAAJqF4AgAAAGASu80dAACm8O6D7zV3BEb3es+7544AAMBMjHgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmsdvcAQAArqqXPuWf5o7A6IkveuDcEQCATcSIJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKKJwAAAAAmoXgCAAAAYBKboniqqn2r6tiq+lhVnVpVh27jnB+pqq9W1UfGx+/NkRUAAACAK2a3uQOMLk7ylO4+sar2TPKhqnp7d39s3XnHdfcDZsgHAAAAwHdpU4x46u4vdveJ4/Pzk5yW5KbzpgIAAADgqtgUxdOiqrp5kgOTvH8bh3+wqk6qqrdW1e238xqPr6oTquqEL3/5yxMlBQAAAGB7NlXxVFXXTvL6JE/q7vPWHT4xyc26+05JXpLkHy7vdbr78O4+qLsP2nvvvacLDAAAAMDl2jTFU1VdLUPpdGR3v2H98e4+r7u/Nj5/S5KrVdUNNjgmAAAAAFfQpiieqqqSHJHktO4+7HLOudF4Xqrqbhmyn71xKQEAAAD4bmyWu9rdM8nPJzmlqj4y7nt6kv2SpLtfnuSQJL9aVRcn+UaSn+vuniMsAAAAADu2KYqn7n5vktrBOS9N8tKNSQQAAADAVbUpptoBAAAAsHwUTwAAAABMQvEEAAAAwCQUTwAAAABMQvEEAAAAwCQUTwAAAABMQvEEAAAAwCQUTwAAAABMQvEEAAAAwCQUTwAAAABMYre5AwAAwHfjeY86ZO4IjJ7xt6+b/D1Oe967Jn8Prpjvf8aPzR0B2AUZ8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExC8QQAAADAJBRPAAAAAExit7kDAAAAQJI861nPmjsCo424Fkcfc7fJ34Mr5uEP+8Bkr23EEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACTUDwBAAAAMAnFEwAAAACT2DTFU1Xdr6o+UVVnVNVTt3H8GlV11Hj8/VV1841PCQAAAMAVtSmKp6ramuRlSe6fZP8kj6iq/ded9pgk53b3rZP8SZIXbmxKAAAAAL4bm6J4SnK3JGd096e7+3+SvDbJg9ed8+Akrxqfvy7JvauqNjAjAAAAAN+F6u65M6SqDklyv+5+7Lj980nu3t1PXDjno+M5nx+3PzWec9Y2Xu/xSR4/bt4uyScm/iNsRjdI8h3/bVharvdqcb1Xi+u9Wlzv1eJ6rxbXe7W43qtlVa/3zbp77x2dtNtGJNlo3X14ksPnzjGnqjqhuw+aOwcbw/VeLa73anG9V4vrvVpc79Xieq8W13u1uN7bt1mm2n0hyb4L29877tvmOVW1W5K9kpy9IekAAAAA+K5tluLpg0luU1W3qKqrJ/m5JG9ad86bkvzi+PyQJO/qzTBPEAAAAIBt2hRT7br74qp6YpJ/SbI1ySu6+9Sqek6SE7r7TUmOSPKaqjojyTkZyiku30pPNVxBrvdqcb1Xi+u9Wlzv1eJ6rxbXe7W43qvF9d6OTbG4OAAAAADLZ7NMtQMAAABgySieAAAAAJiE4gkAACZWVS+8IvsA2Lyq6tZVdc9t7L9nVd1qjky7AsXTEhgXYV/c3lpVR86VB9j5qmqfqtpv7TF3HjZeVf3x3BmAq+S+29h3/w1PwYaqqhvMnQHYqV6c5Lxt7D9vPMY2KJ6Ww75V9bQkqaprJHlDktPnjcTUqmrvqnp6VR1eVa9Ye8ydi52rqh5UVacn+UySdyf5jyRvnTUUc3n43AHYearqgVV1s4Xt36uqk6rqTVV1izmzsXNV1a9W1SlJbldVJy88PpPk5LnzMY3xZ/zLSU6pqs9X1Q/NnYmNsfbvMpbWDbv7lPU7x3033/g4uwZ3tVsCVVVJjkxySpIfTfKW7ta2Lrmq+rckxyX5UJJL1vZ39+tnC8VOV1UnJfmxJO/o7gOr6keTPKq7HzNzNDZYVX2uu/edOwc7R1WdnOQe3f31qnpAksOSPCLJgUke1t0/MWtAdpqq2ivJ9ZK8IMlTFw6d393nzJOKqY0/4w/v7o9X1d2T/GF332vuXEyvqk7s7rvMnYNpVNXp3X2byzl2RnffeqMz7Qp2mzsAV15VLf6F9qdJ/jLJ8UneU1V36e4T50nGBrlmd/+fuUMwuYu6++yq2lJVW7r72KpSLC+pqrr+5R0aHyyP7u6vj89/JskR3f2hJB+qql+bMRc7WXd/NclXkzxi/N3th5N0ht/ZFE/L6+Lu/niSdPf7q2rPuQMBO8UJVfW47v6rxZ1V9dgMAwLYBsXTru1F67bPTbL/uL8zjJJgeb25qn6yu98ydxAm9ZWqunaS9yQ5sqrOTHLBzJmYzocy/P29rZLpog3OwrRq/Nn+epJ7J/nzhWO7zxOJKVXV72aYMvuGcdffVNUx3f3cGWMxnX2q6smXt93dh82QiYmMU2fX/v9946r69Pi8u/uWs4ZjZ3tSkjdW1SNzWdF0UJKrJ3nIbKk2OVPtYBdVVecnuVaS/8ll/yDt7r7OfKnY2arqWkm+kWFNvkcm2SvJkd199qzBgKukqn45ydMzLEZ6Znffb9x/YJI/7u57z5mPna+qPpHkTt194bi9R5KPdPft5k3GFKrqmds73t3P3qgsbKyq+nB3Hzh3DqY1Ln9xwLh5ane/a848m53iaQmMawc8M8nB4653J3nOOLQb2IWNn44e1d1fmDsL01s3hfo7mEK9XKrqpkn2SXJSd1867rtRkqt393/OGo6drqqOTfKQ7v7KuH3dJG/obiPUYYkonuA7mWq3HF6R5KO57I5HP5/kbzKsGcESq6oH5bLC8V+7+81z5mESeyZ5W1Wdk+SoJMd093/PnInpnJDh7/Ozxu3FKXemUC+R8Y52X1krlcdPTn86yWeTvHTObEzmq0lOraq3Z/h5vm+SD1TVnyVJd//GnOHYudau6+VxvZfa8XMHgM3GiKclUFUf6e4772gfy6Wq/iDJXTPc0TAZ7oZ0Qne7hesSqqo7JvnZJA9N8vnuvs/MkZhAVT0pySEZ/oH62iRv7O6vzZuKKVTV+zOMfvmvqrpzkndkuOvZHTPcVOCxswZkp6uqX9ze8e5+1UZlYXrrrvezM8xO+BbXG1gliqclUFX/nuS3u/u94/Y9M6wP8YPzJmNK421677wwPWNrkg939x3nTcYUxuk3D0vyc0n2dJ2XW1XdMsO1fnCGETDP7+6PzJuKnamqTl77Oa6qP05yaXf/TlVtybDuj59xWBKmXq2Wqrp9d586dw7YTEy1Ww6/muRV41pPleHWvNv9VI2lcd1cdivmveYMwjTG26o/PMneSY5J8rju/ti8qZhad3+6qv4xyR4Zpk/fNoniabksTqP8sSRPS5LuvrRqWzc1ZFdVVUd398Or6pQMU+y+jZJxJfikf7W8Jsl212yEVaN4WgLjp+B3qqrrjNvnzRyJjfGCJB8eFyutDGs9PXXeSExg3yRPMtplNawb6fS5DNPtnt/d35g1GFN4V1UdneSLSa6X5F1JUlU3znC3UpbHoePXB8yaAtgoPj2AdUy1WwLuare6xn+g3HXc/EB3f2nOPEynqvZJsvvatjteLaequjTJyUn+Mcl5WfcpeXcfNkcudr6quk2GddsuSHL0wiLjBye5Q3e/bM587FzjdPh3dPePzp2FjVFV52f4O7wyjF79+tqhJN3d15krGztfVT0zl13v/53k5WvHuvs5c+WCzcKIp+Xgrnara0uGu1/tluS2VXXb7n7PzJnYiarqgUkOS3KTJGcmuVmS05Lcfs5cTObZC8+vPVsKNsKfJHlad5+ybv+5Se6XRPG0RLr7kqq6tKr28sHgaujuPefOwIb6j4XnF2VYnxEYGfG0BNzVbjVV1QszfFp+apJLx93d3Q+aLxU7W1WdlGH9l3d094HjLdcf1d2PmTkaE6iqJ3b3S+fOwfSq6oPdfdfLOXZKd99hozMxrXHdtgOTvD3DSLckSXf/xmyhmExV7Z7kV5LcOsNI1ld098XzpmIjVNWJ3W2NJ1hgxNNy+EZV/fC6u9pZD2T5/XSS23X3N+cOwqQu6u6zq2pLVW3p7mOr6sVzh2Iyv5xE8bQarrudY3tsWAo20hvGB6vhVRlGvhyX5CczjFQ+dLvfwbKwxhOso3haDu5qt5o+neRqSRRPy+0rVXXtDL+4HllVZ2bhk3Jgl3VCVT2uu/9qcWdVPTbJh2bKxLRel+TC7r4k+da6T9eYNxIT2n9t5GJVHZHkAzPnYSJVdeskN+zu48dd9x733zPJl7r7U7OFg03CVLsl4q52q6GqXpJh8cKbJrlTkndmoXwyZH+5VNU1k1yYoVR+VJLrJDmyu8+ZNRiTqKqLc9kCtN92KBajXSpVdcMkb8xwB7u1oumgJFdP8hA3i1g+VfW+JPfp7q+N29dO8rbu/qF5kzGF9dOtTL9aXlX15mxjzb6qukOGO9M+cJ5ksHkonpZAVX1Phrva/XCGQuK9Ge5qd/aswZhEVW1vNFt396s3LAyTWbgbzrftHr9emORTSZ7R3e/c0GBMqqo+3N0Hzp2DjTOu23bAuHlqd79rzjxMx5qcq6WqLsllI5QX72zng4QlY80+2DFT7ZbDa5O8J8lDx+1HJjkqyX1mS8RkuvtVSVJVh3b3ny4eqyprByyJ7d0NZ5yecUCSI3PZP1iBXVB3H5vk2LlzsCEuqKq7dPeJSVJVPxBrci6t7t46dwY2jDX7YAe2zB2AneLG3f373f2Z8fHcJDecOxST29bIp0dvdAg2Xndf0t0nJXnJ3FnY6Y6ZOwAwmSclOaaqjquq92b4kPCJM2cCrroTqupx63dasw8uY6rdEqiqwzIsWHj0uOuQJHfr7t+aLxVTqapHJPlfGaZWHrdwaM8kl3b3vWcJBlxlC2u4bZM13GDXVlVXS3K7cfMT3X3RnHmAq86afbBjiqdd2MIaMJXkWkkuHbe3JvmauePLqapuluQWSV6Q5KkLh85PcnJ3XzxLMOAqW7eG27MzrN/3LWtTbYFdR1XdNcnn1v7xWVW/kGF5hM8meZabRcBysGYfXD7FE+yiquo3krymu8+dOwuw81loHJZDVZ2Y4W5251TVwRnW5vz1JHdO8v3dfSneQ2IAAA2VSURBVMisAQFgYtZ4WgI1eFRV/e64vW9V3W3uXExunyQfrKqjq+p+VVU7/A5gV+KTIVgOWxdGNf1sksO7+/Xd/btJbj1jLgDYEIqn5fDnSX4ww7o/SfK1JC+bLw4bobv/b5LbJDkiw6Lip1fV86vqVrMGAwAWba2qtTtJ3zvJ4vQbd5gGYOn5n91yuHt336WqPpwk3X1uVV197lBMr7u7qr6U5EtJLk5yvSSvq6q3d/fvzJsO+G4trN2XJNesqvPWDmX4kbd2H+x6/j7Ju6vqrCTfyHhjkKq6dZKvzhkMADaC4mk5XFRVWzP+Y6Wq9s6w0DhLrKoOTfILSc5K8tdJfru7L6qqLUlOT6J4gl1Md+85dwZg5+ru51XVO5PcOMnb+rIFVrdkWOsJAJaa4mk5/FmGW3juU1XPS3JIkt+dNxIb4PpJfqa7P7u4s7svraoHzJQJAFinu9+39ryq9kmye5ILxwcALDV3tVsSVfV9GdYNqCTv7O7TZo7ERKpq9yS/kmFB0lOSHNHdF8+bCgDYnqp6YJLDktwkyZlJ9kvy8e6+/azBAGBiFhdfAlX1mu7+eHe/rLtf2t2nVdVr5s7FZF6V5KAMpdP9k7xo3jgAwBXw3CT3SPLJ7r5Fkvsked/2vwUAdn2m2i2Hb/ukbFzv6QdmysL09u/uOyRJVR2R5AMz5wEAduyi7j67qrZU1ZbuPraqXjx3KACYmuJpF1ZVT0vy9CR7jHc+qvHQ/yQ5fLZgTO2itSfdfXFVbe9cAGBz+EpVXTvJe5IcWVVnJrlg5kwAMDlrPC2BqnpBdz9t7hxsjKq6JJf9olpJ9kjy9bjdOgBsWlV1rSTfyLDUxSOT7JXkyO4+e9ZgADAxxdOSqKoHJTl43PzX7n7znHkAALhMVT05yVHd/YW5swDARrK4+BKoqhckOTTJx8bHoVX1/HlTAQCwYM8kb6uq46rqiVV1w7kDAcBGMOJpCVTVyUnu3N2Xjttbk3y4u+84bzIAABZV1R2T/GyShyb5fHffZ+ZIADApI56Wx3UXnu81WwoAALbnzCRfSnJ2kn1mzgIAk3NXu+XwgiQfrqpjMywwfXCSp84bCQCANVX1a0kenmTvJMckeVx3f2zeVAAwPVPtlkRV3TjJXcfND3T3l+bMAwDAZcY1OY/q7o/MnQUANpLiaRdWVftt73h3/+dGZQEAYMeqap8ku69t+30NgGWneNqFVdUpSTrD9Lo1nWEI9z7dvXWWYAAAfJuqemCSw5LcJMM6TzdLclp3337WYAAwMYuL78K6+w7dfcfx6x2SPDDJ8Um+luRJ86YDAGDBc5PcI8knu/sWSe6d5H3zRgKA6SmelkBV3aaqXpnkrUk+lGT/7n7JvKkAAFhwUXefnWRLVW3p7mOTHDR3KACYmrva7cKq6oAkz0hy+yR/mOQx3X3JvKkAANiGr1TVtZMcl+TIqjozyQUzZwKAyVnjaRdWVZck+VyS/5fkOwqn7v6NDQ8FAMB3qKprJrkww9qcj0pynSRHdvc5swYDgIkpnnZhVfWL2zve3a/aqCwAAHynqjo/w81fvm33+PXCJJ9K8ozufueGBgOADaJ4AgCAGVTV1iQHZBj5dMDceQBgChYXBwCAGXT3Jd19UhI3hQFgaRnxBAAAAMAkjHjaxVXV1qr6zblzAAAAAKyneNrFdfclSR4xdw4AAACA9Uy1WwJV9SdJrpbkqCQXrO3v7hNnCwUAAACsPMXTEqiqY7exu7v7xzY8DAAAAMBI8QQAAADAJKzxtASq6oZVdURVvXXc3r+qHjN3LgAAAGC1KZ6WwyuT/EuSm4zbn0zypNnSAAAAAETxtCxu0N1HJ7k0Sbr74iSXzBsJAAAAWHWKp+VwQVV9T5JOkqq6R5KvzhsJAAAAWHW7zR2AneLJSd6U5FZVdXySvZM8bN5IAAAAwKpzV7slUFXXyDC17nZJKsknkmzp7m/OGgwAAABYaYqnJVBVJ3b3XXa0DwAAAGAjmWq3C6uqGyW5aZI9qurADKOdkuQ6Sa45WzAAAACAKJ52dT+R5NFJvjfJYQv7z0vy9DkCAQAAAKwx1W4JVNVDu/v1c+cAAAAAWKR4WgJV9ekkr0/yiu4+be48AAAAAEmyZe4A7BR3SvLJJEdU1fuq6vFVdZ25QwEAAACrzYinJVNV90ryd0mum+R1SX6/u8+YNxUAAACwiox4WgJVtbWqHlRVb0zy4iQvSnLLJP+U5C2zhgMAAABWlrvaLYfTkxyb5I+6+98W9r+uqg6eKRMAAACw4ky1WwJVde3u/trcOQAAAAAWmWq3HPapqn+qqrOq6syq+sequuXcoQAAAIDVpnhaDn+X5OgkN0pykyTHJPn7WRMBAAAAK89UuyVQVSd39x3X7Tupu+80VyYAAAAAxdMSqKoXJjk3yWuTdJKfTXK9JH+UJN19znzpAAAAgFWleFoCVfWZ7Rzu7rbeEwAAALDhFE8AAAAATGK3uQNw1VXVL2xrf3e/eqOzAAAAAKxRPC2Huy483z3JvZOcmETxBAAAAMzGVLslVFXXTfLa7r7f3FkAAACA1bVl7gBM4oIkt5g7BAAAALDaTLVbAlX1T0nWhq5tTbJ/kqPnSwQAAABgqt1SqKp75bLi6eIkn+3uL8wYCQAAAEDxtCurqvMzFE617lAn+WaSTyV5Rne/c6OzAQAAACiellRVbU1yQJIju/uAufMAAAAAq8fi4kuquy/p7pOSvGTuLAAAAMBqMuIJAAAAgEkY8QQAAADAJBRPAAAAAExC8QQALLWqenRVdVXdeu4sAACrRvEEAAAAwCQUTwAAAABMQvEEAKy0qrprVb2uqj5fVd+oqk9U1fOrao915/1rVb23qu5TVSdW1der6qNV9ZBtvOYjqurjVXVhVZ1SVQ8av/9fF85ZmwJ483Xf+6yq6nX7nlhV/15V51TVV6rqfVX1U9t431tW1VvGbGdW1Yuq6vGX8z6Pr6qTxoxnVdURVXX9deccWlWnjf9dzq2qE7b15wUAuDy7zR0AAGBm+yX5SJJXJjk/ye2T/F6SWyb5uXXn3irJnyZ5QZKzkjwlyTFV9X3dfUaSVNV9kxyZ5E1Jnpxk7yQvTrJ7kk9eyYw3T/LXSf4jw+9vD0zy5qq6f3f/8/i+V0/y9iTXSPKrSb6c5LFJDln/YlX1B2P2P0vy20lumuS5SQ6oqh/q7kuq6pFJXpTkOUmOS7JHkjsmuf761wMAuDyKJwBgpXX369eeV1UlOT7JeUleXVVP6O6zF06/QZKDu/v08fwTk3wxycOTPH8859lJPpbkId3d43kfTXJCrmTx1N2/tZBxS5J3JrlthoLpn8dDj85Qlt29uz8wnvvWDKXafgvff/MMZdOzu/s5C/s/meS9GUqtf0jyg0lOXjwnyVuuTH4AYHWZagcArLSquk5VvbCqPpXkm0kuSvKaJJXkNutOP32tdEqS7j4zyZkZi52q2prkoCSvXyudxvM+lOQzVyHjD1TVm6vqv5NcPGa8b5LbLZx2jyT/uVY6je/bSV6fb3ffDL8DHllVu609krw/w4ivg8fzPpjkzlX1knF64TWvbH4AYHUpngCAVfc3SX4lw7Sz+ya5a5InjMd2X3fuOdv4/m8unHeDJFfLUEat999XJlxV7ZthhNP1k/x6kh8aM/7zunw3voLvu8/49YwMBdbiY88k3zMef3WGEVV3T/IvSc6pqjesXysKAGB7TLUDAFZWVe2e5MFJntXdf7qw/w5X8iXPylDg7LONYzdM8p8L2xeOX6++7rzvWbd9vyR7JXl4d39+IeP6EUhfTLL/5bzvorWpgz+e5NxtnH928q3RUn+Z5C+r6nrj+S9KclSGMgoAYIeMeAIAVtk1kmzNUBYtevSVebHuviTDWk4PHdeLSjJMlUtyi3Wnf3b8esDCebtlKHgWrRVMFy2cd9sk91x33vuS7FdVd1s4r5I8dN15b09yaZL9uvuEbTy+Y0pgd5/b3UclOXoxLwDAjhjxBACsivtV1ZfW7ftqhsLmKVX1xQwjln45w13erqxnJnlbkjdW1eEZpt89K8mXMhQ+az6Y5FNJ/mhcMPybSX4tQxm26B0Z1nV6dVW9KMOUumdnGD21+CHiK5P8nyRvqKpn5LK72l1vPH5pknT3p6rqhUleWlW3S/LuDKOv9s0w1fCvu/vYMfv5Sf49wxS+2yb5+fHPBgBwhSieAIBV8ZJt7Ds1yQOS/EWSlyX5RoZRPYcmefOVeZPufntVPTJDAfXGDGspPSXJ72UoutbOu7iqHjy+7yszrB/14gyLfD9z4bxTx9d7TpI3ZSirnpphCt6PLJz3P1X14+Of8+VJvpbk78bX+4N17/30qjotw1pWT0jSST6XYS2ptcXTj0/ySxnKpr2S/FeSv13MBgCwI7VwwxUAACZQVd+boYB6Xnf//ga/95uTfH9332oj3xcAIDHiCQBgp6qqPZIclmGK3FlJbpnkd5J8PclfT/zeT84w0un0DHeoe1iSn8pwdzoAgA2neAIA2LkuSXKjJC/NcIe6C5Icl+Rh3f3Fid/7m0l+M8l+GRZN/0SSx3b3ERO/LwDANplqBwAAAMAktuz4FAAAAAD47imeAAAAAJiE4gkAAACASSieAAAAAJiE4gkAAACASfx/eSQyPjXR63kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "languages_count = pd.Series(list_of_languages).value_counts()\n",
    "\n",
    "plt.figure(figsize = (20, 12))\n",
    "sns.barplot(languages_count.index, languages_count.values)\n",
    "plt.xlabel(\"Languages\", fontsize = 16)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.ylabel(\"Repositories\", fontsize = 16)\n",
    "plt.title(\"Language distribution amongst all repositories\", fontsize = 16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I've worked on a variety of languages inclduing **HTML**, **C++** and others. However, the most is **Jupyter Notebook** which is mainly working with **Python** in my case."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}