{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python | Урок 2: визуализация данных"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Загрузка необходимых библиотек\n",
    "\n",
    "Для работы нам понадобятся две библиотеки:\n",
    "1. `pandas`: при помощи нее мы считаем из файла таблицу с данными\n",
    "2. `matplotlib`: библиотека для визуализации данных\n",
    "3. `seaborn`: по сути matplotlib на максималках - позволяет легко делать сложные визуализации"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Подключаем нужные библиотеки\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Для чтения данных используем метод read_csv\n",
    "table = pd.read_csv('dota2_skill_train.csv', index_col='id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Посмотрим на данные"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>skilled</th>\n",
       "      <th>player_team</th>\n",
       "      <th>winner_team</th>\n",
       "      <th>duration</th>\n",
       "      <th>pre_game_duration</th>\n",
       "      <th>first_blood_time</th>\n",
       "      <th>first_blood_claimed</th>\n",
       "      <th>hero_id</th>\n",
       "      <th>hero_pick_order</th>\n",
       "      <th>leaver_status</th>\n",
       "      <th>...</th>\n",
       "      <th>avg_deaths_x16</th>\n",
       "      <th>avg_assists_x16</th>\n",
       "      <th>avg_gpm_x16</th>\n",
       "      <th>avg_xpm_x16</th>\n",
       "      <th>best_kills_x16</th>\n",
       "      <th>best_assists_x16</th>\n",
       "      <th>best_gpm_x16</th>\n",
       "      <th>best_xpm_x16</th>\n",
       "      <th>win_streak</th>\n",
       "      <th>best_win_streak</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</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>7</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>dire</td>\n",
       "      <td>2140</td>\n",
       "      <td>90</td>\n",
       "      <td>129</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>15</td>\n",
       "      <td>352</td>\n",
       "      <td>430</td>\n",
       "      <td>10</td>\n",
       "      <td>30</td>\n",
       "      <td>551</td>\n",
       "      <td>745</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>radiant</td>\n",
       "      <td>radiant</td>\n",
       "      <td>2138</td>\n",
       "      <td>90</td>\n",
       "      <td>174</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "      <td>294</td>\n",
       "      <td>425</td>\n",
       "      <td>13</td>\n",
       "      <td>37</td>\n",
       "      <td>445</td>\n",
       "      <td>717</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>radiant</td>\n",
       "      <td>radiant</td>\n",
       "      <td>3547</td>\n",
       "      <td>90</td>\n",
       "      <td>360</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "      <td>493</td>\n",
       "      <td>543</td>\n",
       "      <td>23</td>\n",
       "      <td>18</td>\n",
       "      <td>691</td>\n",
       "      <td>762</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>radiant</td>\n",
       "      <td>1878</td>\n",
       "      <td>90</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>515</td>\n",
       "      <td>583</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>869</td>\n",
       "      <td>935</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>dire</td>\n",
       "      <td>radiant</td>\n",
       "      <td>2232</td>\n",
       "      <td>90</td>\n",
       "      <td>129</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>337</td>\n",
       "      <td>452</td>\n",
       "      <td>34</td>\n",
       "      <td>43</td>\n",
       "      <td>672</td>\n",
       "      <td>797</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    skilled player_team winner_team  duration  pre_game_duration  \\\n",
       "id                                                                 \n",
       "7         1        dire        dire      2140                 90   \n",
       "8         0     radiant     radiant      2138                 90   \n",
       "12        0     radiant     radiant      3547                 90   \n",
       "13        1        dire     radiant      1878                 90   \n",
       "14        1        dire     radiant      2232                 90   \n",
       "\n",
       "    first_blood_time  first_blood_claimed  hero_id  hero_pick_order  \\\n",
       "id                                                                    \n",
       "7                129                    0       90                9   \n",
       "8                174                    0        5                5   \n",
       "12               360                    0       81                7   \n",
       "13                28                    0       74                9   \n",
       "14               129                    0       14                6   \n",
       "\n",
       "    leaver_status       ...         avg_deaths_x16  avg_assists_x16  \\\n",
       "id                      ...                                           \n",
       "7               0       ...                      8               15   \n",
       "8               0       ...                      9               19   \n",
       "12              0       ...                      7                9   \n",
       "13              0       ...                      7               12   \n",
       "14              0       ...                     10               16   \n",
       "\n",
       "    avg_gpm_x16  avg_xpm_x16  best_kills_x16  best_assists_x16  best_gpm_x16  \\\n",
       "id                                                                             \n",
       "7           352          430              10                30           551   \n",
       "8           294          425              13                37           445   \n",
       "12          493          543              23                18           691   \n",
       "13          515          583              25                34           869   \n",
       "14          337          452              34                43           672   \n",
       "\n",
       "    best_xpm_x16  win_streak  best_win_streak  \n",
       "id                                             \n",
       "7            745           2                5  \n",
       "8            717           2               12  \n",
       "12           762           3                3  \n",
       "13           935           0                6  \n",
       "14           797           0                9  \n",
       "\n",
       "[5 rows x 57 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Очень часто важно понимать какие значения принимает признак. Для ответа на этот вопрос нам поможет [гистограмма](https://ru.wikipedia.org/wiki/%D0%93%D0%B8%D1%81%D1%82%D0%BE%D0%B3%D1%80%D0%B0%D0%BC%D0%BC%D0%B0).\n",
    "\n",
    "Гистограмма выглядит следующим образом:\n",
    "- На оси **х** располагаются значения признака\n",
    "- А на оси **y** - количество строк с таким значением признака"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEICAYAAAC0+DhzAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYThIkjoMB0lSh+EgSer4/w7c9X7i7JijAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1511dd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Берем колонку gold_per_min - скорость зарабатывания золота\n",
    "# Строим график используя метод hist датафрейма table\n",
    "table.hist('gold_per_min', bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Из гистограммы видно, что скорость зарабатывания золота принимает значения больше `1500` довольно редко. Сохраним в данных только те строки, где **gold_per_min** меньше `1500`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Сделаем новую таблицу, сокращенную\n",
    "table_truncated = table.query('gold_per_min < 1500')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Давайте сравним размеры нового и исходного датафреймов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер table:  (99871, 57)\n",
      "Размер table_truncated:  (99535, 57)\n"
     ]
    }
   ],
   "source": [
    "# Для этого используем метод shape - он показывает сколько строк и столбцов содержатся в датафрейме\n",
    "print(\"Размер table: \", table.shape)\n",
    "print(\"Размер table_truncated: \", table_truncated.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь гистограмма выглядит иначе"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEICAYAAABWJCMKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nT7OLVApN1AEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a15401d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Строим график методом hist нового датафрейма table_truncated\n",
    "table_truncated.hist('gold_per_min', bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Совмещение нескольких гистограмм на одном графике позволяет обнаруживать закономерности в данных.**\n",
    "\n",
    "Например, рассмотрим показатель `gold` (число золота на момент игры), зависит ли чило золота от опыта игрока? \n",
    "\n",
    "Если нарисовать гистограммы `gold` для опытных игроков (голубой цвет) и для новичков (оранжевый), можно видеть существенное отличие гистограмм друг от друга, что намекает на наличие связи между опытом и количеством золота."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAD8CAYAAACcjGjIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYxXbKEISJgYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1584ad68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Подготовим нужные выборки методом groupby\n",
    "# groupby группирует данные по значениям категориальной переменной, \n",
    "# что позволяет рисовать несколько графиков на одной картинке\n",
    "\n",
    "table_truncated.groupby('skilled')['gold'].hist(alpha=0.5, bins=50)\n",
    "plt.legend(table_truncated['skilled'].unique());"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Также метод groupby позволяет на ходу считать средние. Вот пример подсчета средних значений `gold` на разных уровнях категориальной переменной `skilled`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "skilled\n",
       "0    1947.379907\n",
       "1    1933.366405\n",
       "Name: gold, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_truncated.groupby('skilled')['gold'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сейчас вам кажется, что они почти одинаковы. И среднее количество золота у неопытных игроков даже больше - довольно странно, не правда ли?  \n",
    "\n",
    "И тут датасайентистам на помощь приходит **медиана** - это значение, расположенное посередине всей выборки. Половина всех возможных значение признака (в нашем случае gold) больше нее, а половина меньше. Это более информативный показатель, чем **среднее арифметическое** (mean). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "skilled\n",
       "0    1398\n",
       "1    1411\n",
       "Name: gold, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_truncated.groupby('skilled')['gold'].median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Как видите, у опытных игроков \"середина\" имеет большее значение, чем у неопытных - что уже совсем не противоречит здравому смыслу!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Проверим гипотезу\n",
    "\n",
    "Поскольку герои в игре развиваются с течением времени, зарабатывая золото и опыт, естественным образом возникает вопрос:   \n",
    "\"Зависит ли скорость зарабатывания золота от скорости приобретения опыта, если да, то как?\"\n",
    "\n",
    "Чтобы ответить на этот вопрос, достаточно построить график зависимости золота от опыта. В этом нам поможет [диаграмма рассеяния](https://ru.wikipedia.org/wiki/Диаграмма_рассеяния) (eng.: Scatter Plot), которая строится следующим образом:\n",
    "- Берется одна строка из таблицы данных\n",
    "- Значение показателя `xp_per_min` откладывается по оси x\n",
    "- Значение показателя `gold_per_min` откладывается по оси y\n",
    "- В результате получается точка на плоскости\n",
    "- Алгоритм повторяется для всех строк в данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY8AAAELCAYAAAAhuwopAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nm5OHmZnl5uRhZma5OXmYmVlu/wM1pPvWSKaNCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a15944198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Диаграмму можно легко построить с помощью встроенной функции plot библитеки pandas\n",
    "table_truncated.plot(kind='scatter', x='xp_per_min', y='gold_per_min');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAEyCAYAAADQqCvlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noIFCCCGEkMRBA4UQQgghieP/BzDgTzBpcK5wAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a15fc5fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Либо с помощью matplotlib:\n",
    "# - figure - создает пустой холст\n",
    "# - scatter - наносит точки на холст\n",
    "# - show - отображает картинку\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "plt.scatter(table_truncated['xp_per_min'], table_truncated['gold_per_min']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Из графика легко видеть, что между признаками **'xp_per_min'** и **'gold_per_min'** есть зависимость, причем линейная, т.е. существует формула\n",
    "$$gold = k \\cdot xp + b,$$\n",
    "где k и b - некоторые числовые константы."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Для того, чтобы посмотреть на взаимосвязь двух численных признаков в подробностях, у seaborn есть **joint plot** — это гибрид **scatter plot** и **histogram**. \n",
    "\n",
    "А если указать параметр kind = 'reg', то seaborn нарисует ту самую **линию**, которая покажет **линейную зависимость** обнаруженную нами на предыдущем графике."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAbIAAAGoCAYAAAAjPmDhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niqIoSlWjjkxRFEWpatSRKYqiKFXN/wOQetVxnIyqBQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1588d550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='xp_per_min', y='gold_per_min', data = table_truncated, kind = 'reg');"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}