assignment02_habr_visual_analysis.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>\n",
    "<img src=\"../../img/ods_stickers.jpg\">\n",
    "## Открытый курс по машинному обучению\n",
    "<center>\n",
    "Автор материала: Екатерина Демидова, Data Scientist @ Segmento <br>\n",
    "\n",
    "\n",
    "Материал распространяется на условиях лицензии [Creative Commons CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). Можно использовать в любых целях (редактировать, поправлять и брать за основу), кроме коммерческих, но с обязательным упоминанием автора материала.\n",
    "Автор материала: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center>Домашнее задание № 2 (демо). <br> Визуальный анализ данных о публикациях на Хабрахабре</center>\n",
    "\n",
    "**Заполните код в клетках и ответьте на вопросы в [веб-форме](https://docs.google.com/forms/d/1y8qj5iYpaVhczjWnZuHd5NRR_sdCGy3eTF5n-qPKknQ).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Загрузка и знакомство с данными\n",
    "\n",
    "Для работы вам понадобятся предобработанные данные нашего учебного конкурса на kaggle [«Прогноз популярности статьи на Хабре»](https://www.kaggle.com/c/howpop-habrahabr-favs)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../../data/howpop_train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(134137, 17)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>votes_minus</th>\n",
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       "      <th>dayofweek</th>\n",
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       "      <th>0</th>\n",
       "      <td>https://habrahabr.ru/post/18284/</td>\n",
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       "    <tr>\n",
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       "      <td>https://habrahabr.ru/post/18285/</td>\n",
       "      <td>habrahabr.ru</td>\n",
       "      <td>18285</td>\n",
       "      <td>2008-01-01 18:30:00</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>353</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>https://habrahabr.ru/post/18286/</td>\n",
       "      <td>habrahabr.ru</td>\n",
       "      <td>18286</td>\n",
       "      <td>2008-01-01 18:34:00</td>\n",
       "      <td>@DezmASter</td>\n",
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       "      <td>8431</td>\n",
       "      <td>Сумасшедшие яйца, или сервис для отслеживания ...</td>\n",
       "      <td>47</td>\n",
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       "      <td>1200</td>\n",
       "      <td>45.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>https://habrahabr.ru/post/18291/</td>\n",
       "      <td>habrahabr.ru</td>\n",
       "      <td>18291</td>\n",
       "      <td>2008-01-02 01:32:00</td>\n",
       "      <td>@Taoorus</td>\n",
       "      <td>design</td>\n",
       "      <td>False</td>\n",
       "      <td>5662</td>\n",
       "      <td>Сглаживание шрифтов, и субпиксельная отрисовка</td>\n",
       "      <td>102</td>\n",
       "      <td>36</td>\n",
       "      <td>5700</td>\n",
       "      <td>72.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>https://geektimes.ru/post/18294/</td>\n",
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       "      <td>18294</td>\n",
       "      <td>2008-01-02 14:34:00</td>\n",
       "      <td>@dennydo</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>3706</td>\n",
       "      <td>Почему мне не нравится iPhone</td>\n",
       "      <td>230</td>\n",
       "      <td>6</td>\n",
       "      <td>1400</td>\n",
       "      <td>73.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
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      "text/plain": [
       "                                url        domain  post_id  \\\n",
       "0  https://habrahabr.ru/post/18284/  habrahabr.ru    18284   \n",
       "1  https://habrahabr.ru/post/18285/  habrahabr.ru    18285   \n",
       "2  https://habrahabr.ru/post/18286/  habrahabr.ru    18286   \n",
       "3  https://habrahabr.ru/post/18291/  habrahabr.ru    18291   \n",
       "4  https://geektimes.ru/post/18294/  geektimes.ru    18294   \n",
       "\n",
       "            published      author     flow  polling  content_len  \\\n",
       "0 2008-01-01 18:19:00      @Tapac  develop    False         4305   \n",
       "1 2008-01-01 18:30:00  @DezmASter   design    False         7344   \n",
       "2 2008-01-01 18:34:00  @DezmASter   design    False         8431   \n",
       "3 2008-01-02 01:32:00    @Taoorus   design    False         5662   \n",
       "4 2008-01-02 14:34:00    @dennydo      NaN    False         3706   \n",
       "\n",
       "                                               title  comments  favs  views  \\\n",
       "0     Новогодний подарок блоггерам — WordPress 2.3.2         0     0    236   \n",
       "1  Сумасшедшие яйца, или сервис для отслеживания ...         1     1    353   \n",
       "2  Сумасшедшие яйца, или сервис для отслеживания ...        47    72   1200   \n",
       "3     Сглаживание шрифтов, и субпиксельная отрисовка       102    36   5700   \n",
       "4                      Почему мне не нравится iPhone       230     6   1400   \n",
       "\n",
       "   votes_plus  votes_minus  year  month  dayofweek  hour  \n",
       "0         0.0          0.0  2008      1          2    18  \n",
       "1         1.0          0.0  2008      1          2    18  \n",
       "2        45.0          5.0  2008      1          2    18  \n",
       "3        72.0          3.0  2008      1          3     1  \n",
       "4        73.0         15.0  2008      1          3    14  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df.head(5)"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Избавимся сразу от переменных, названия которых заканчиваются на `_lognorm` (нужны для соревнования на Kaggle). Выберем их с помощью `filter()` и удалим `drop`-ом:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(filter(lambda c: c.endswith('_lognorm'), df.columns), \n",
    "        axis = 1,       # axis = 1: столбцы \n",
    "        inplace = True) # избавляет от необходимости сохранять датасет"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <td>134137.0</td>\n",
       "      <td>39.625994</td>\n",
       "      <td>62.398958</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>2266.0</td>\n",
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       "    <tr>\n",
       "      <th>favs</th>\n",
       "      <td>134137.0</td>\n",
       "      <td>71.999866</td>\n",
       "      <td>145.854135</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>8718.0</td>\n",
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       "    <tr>\n",
       "      <th>views</th>\n",
       "      <td>134137.0</td>\n",
       "      <td>16631.013084</td>\n",
       "      <td>31479.819691</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2100.0</td>\n",
       "      <td>7600.0</td>\n",
       "      <td>18700.0</td>\n",
       "      <td>1730000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>votes_plus</th>\n",
       "      <td>133566.0</td>\n",
       "      <td>35.536888</td>\n",
       "      <td>42.461073</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1466.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>votes_minus</th>\n",
       "      <td>133566.0</td>\n",
       "      <td>8.050035</td>\n",
       "      <td>11.398282</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>445.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count           mean           std      min       25%  \\\n",
       "post_id      134137.0  181307.054265  81766.350702  18284.0  115565.0   \n",
       "content_len  134137.0    7516.929699   8724.771640      1.0    2179.0   \n",
       "comments     134137.0      39.625994     62.398958      0.0       7.0   \n",
       "favs         134137.0      71.999866    145.854135      0.0       8.0   \n",
       "views        134137.0   16631.013084  31479.819691      3.0    2100.0   \n",
       "votes_plus   133566.0      35.536888     42.461073      0.0      11.0   \n",
       "votes_minus  133566.0       8.050035     11.398282      0.0       2.0   \n",
       "\n",
       "                  50%       75%        max  \n",
       "post_id      182666.0  257401.0   314088.0  \n",
       "content_len    4949.0    9858.0   352471.0  \n",
       "comments         19.0      48.0     2266.0  \n",
       "favs             27.0      78.0     8718.0  \n",
       "views          7600.0   18700.0  1730000.0  \n",
       "votes_plus       22.0      45.0     1466.0  \n",
       "votes_minus       5.0      10.0      445.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>97657</td>\n",
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       "      <td>53318</td>\n",
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       "    <tr>\n",
       "      <th>polling</th>\n",
       "      <td>134137</td>\n",
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       "      <th>title</th>\n",
       "      <td>134137</td>\n",
       "      <td>133628</td>\n",
       "      <td>Интересные события, произошедшие в выходные</td>\n",
       "      <td>56</td>\n",
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      ],
      "text/plain": [
       "            count  unique                                          top    freq\n",
       "url        134137  134137            https://habrahabr.ru/post/208568/       1\n",
       "domain     134137       2                                 habrahabr.ru   97048\n",
       "published  134137  130291                          2011-06-14 15:52:00      39\n",
       "author      97657   22077                                      @alizar    5292\n",
       "flow        97048       6                                      develop   53318\n",
       "polling    134137       2                                        False  129412\n",
       "title      134137  133628  Интересные события, произошедшие в выходные      56"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include = ['object', 'bool'] # бинарные и категориальные переменные\n",
    "           ).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# настройка внешнего вида графиков в seaborn\n",
    "sns.set_style(\"dark\")\n",
    "sns.set_palette(\"RdBu\")\n",
    "sns.set_context(\"notebook\", font_scale = 1.5, \n",
    "                rc = { \"figure.figsize\" : (15, 5), \"axes.titlesize\" : 18 })"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Столбец **`published`** (время публикации) содержит строки. Чтобы мы могли работать с этими данными как с датой/временем публикации, приведём их к типу `datetime`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "object\n",
      "datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "print(df.published.dtype)\n",
    "df['published'] = pd.to_datetime(df.published, yearfirst = True)\n",
    "print(df.published.dtype)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Создадим несколько столбцов на основе данных о времени публикации:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['year'] = [d.year for d in df.published]\n",
    "df['month'] = [d.month for d in df.published]\n",
    "\n",
    "df['dayofweek'] = [d.isoweekday() for d in df.published]\n",
    "df['hour'] = [d.hour for d in df.published]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----\n",
    "Теперь Ваша очередь. В каждом пункте предлагается построить картинку и с ее помощью ответить на вопрос в [форме](https://docs.google.com/forms/d/e/1FAIpQLSf3b5OG8zX_nLQBQ-t20c6M5Auz-VUL-yxj8Fm9_o_XWDBTrg/viewform?c=0&w=1). Конечно, можно попытаться ответить на все вопросы только с Pandas, без картинок, но мы советуем Вам потренироваться строить (красивые) визуализации.   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1\\. В каком месяце (и какого года) было больше всего публикаций?\n",
    "\n",
    "* март 2016\n",
    "* март 2015\n",
    "* апрель 2015\n",
    "* апрель 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25548765ef0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='year', hue='month', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2\\. Проанализируйте публикации в месяце из предыдущего вопроса\n",
    "\n",
    "Выберите один или несколько вариантов:\n",
    "\n",
    "* Один или несколько дней сильно выделяются из общей картины\n",
    "* На хабре _всегда_ больше статей, чем на гиктаймсе\n",
    "* По субботам на гиктаймс и на хабрахабр публикуют примерно одинаковое число статей\n",
    "\n",
    "Подсказки: постройте график зависимости числа публикаций от дня; используйте параметр `hue`; не заморачивайтесь сильно с ответами и не ищите скрытого смысла :)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25548b7de10>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='dayofweek', hue='domain', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3\\. Когда лучше всего публиковать статью?\n",
    "\n",
    "* Больше всего просмотров набирают статьи, опубликованные в 12 часов дня\n",
    "* У опубликованных в 10 утра постов больше всего комментариев\n",
    "* Больше всего просмотров набирают статьи, опубликованные в 6 часов утра\n",
    "* Максимальное число комментариев на гиктаймсе набрала статья, опубликованная в 9 часов вечера\n",
    "* На хабре дневные статьи комментируют чаще, чем вечерние"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002554C5D4F60>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002554C9A0BA8>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3UNov34oVK4iLi8NgMODl5cXChQuxsbFR43Nzc3n33XeJiYkhLy8PZ2dnXn/9dTp16qTGGAwGNmzYwJ49e8jMzKRXr14sWLCAJ598ssb7RBLN/dEYzxO1TTTSMZhotC5eTGH+/GCKi4uNyr/9NobFi1/jz39+gaCgv5CRcY0tWzYxe/Zf+PDDj9TeLc6dO4ePjw8BAQFG85cliOr2yxccHExiYiLz589Hp9OxYcMGJkyYQFRUlPpEZmhoKHv27GHu3Lk8/vjjREZGEhAQwD//+U86dOhg2h0lxD2SRCMaHYPBwJdf7mHTpg0VdsL68cfb6N/fnXnzXlPLOnbsxNSpARw5chhPz0EUFxdz4cJ5Xn75Rfr06VPh91SnX76EhARiY2P58MMP8fT0BMDZ2ZmhQ4eyc+dOgoKCSE9P59NPP+WNN95gzJgxQOlDMcOHD2fLli0sXbr0fu8iIe4rGY9GNDonT/7CBx+s4+WXxzF9+kyjaYqi4OzsysiRzxuV29l1AuD339MBuHgxlYKCArV7popUp1+++Ph4dDod7u7uaoy1tTUuLi4cOnQIgCNHjlBcXMzw4cPVGK1Wy6BBg9QYIeozSTSi0enUyZ7PPvsnkyYFodFojKaZmZnx6quzGThwkFH5Dz98D4C9fWcAkpJ+A2Dv3r14eHjQu3dvxo4dy8mTJ9V5qtMvX3JyMnZ2duXW486Yli1bYm1tbRRjZ2fHpUuXyM/Pr+EeEOLBkltnotGxtm5do/jff0/n/ffX0q3bn3B1fQqApKRzQGnfe++++y5ZWVmEh4czYcIEPvvsM7p161atfvlycnKq7N+vshgofZjAwqL6/cTd7yflGnNfco1522tCEo0QlUhNTSE4eAYajYa3316pPs4/YsRz9O3bDz+//97Oeuqpp3jmmWcIDw9n9erVQNX98lX20GdVMZX1IViZuz11VluN7cmrMvLUWQ3mM8G6CPFQOH48gWnTSt8FW7cunHbt2qvT2rfvQP/+7kbxLVq0oG/fvpw9exaoXr98er2e3NzcWseUTReiPpNEI0QFvv02hpCQmbRt25bw8Ej1YYAysbHfcfhwXLn5CgoK1IH7qtMvn729PWlpaeWuWlJTU9WYzp07k5mZyc2bN8vFtG/f3mgwQSHqI0k0Qtzh6NF/89Zbb9Cr1xNs3LgFG5vyPU5ER3/FypXLjBri//jjD44fP6723Vedfvk8PDzIysri8OHDasz169dJSEhQY8r+u2/fPjWmsLCQ2NhY6d9PNAjSRiPEbQoLC1m58m2aN38Ef/9J5UZttbW1xcamLRMmTGbGjECmT59OQEAA2dnZrF+/nlatWjFx4kSgev3yubi44Orqypw5c5g7dy6tWrVi/fr1WFpaqu/MtGvXjueff55ly5aRl5eHnZ0dkZGR3Lx5k8DAwAe7g4SoBUk0Qtzm119PcfXqfwAIDn613PTAwGkEBATSq1dv1q3bxLZtm5kzZw7m5uZ4eHgwb948tc1Eq9USGRlJaGgoixYtMuqX7/YXRTds2MDKlSsJCwujpKSEfv36sXbtWlq2bKnGvPXWW7Ro0YLNmzeTl5dHr169iIyMVIdMF6I+k77OpK+z+6q+9ZklnWqWJ32d3R+N8TwhT50JIYSolyTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRiEbt3LmzeHm58Z///GFU/uOPRwgMnMDQoe6MHj2SnTu3l5v39OlfGT9+PE5OTnh4eLBmzRqKioqMYlJSUpg2bRrOzs64ubmxePFicnJyjGKuXbtGSEgIbm5u9OvXjzlz5nD16lWjmNzcXJYuXYq7uztOTk5MmTKFlJSU+7MThDCxJnW9AkLUlYsXU5g/P5ji4mKj8sTEE8yfP5uhQ58mMHAaJ0/+wsaNf0dRFMaOHQ9Aenoas2ZNo2/fvqxdu5bz58/z3nvvkZOTw5tvvgnAzZs38ff3x8bGhnfeeYeMjAxWrVrFlStXCA8PB8BgMDB58mTy8vJYsmQJBoOB1atXExgYyO7du2nSpPRPNDg4mMTERObPn49Op2PDhg1MmDCBqKgoLC0tH+BeE6LmJNGIRsdgMPDll3vYtGmDeiK/3ZYt4XTr9ifeeONtAJ56agAGg4GPPorgf/7nJbRaLdu3b0Ov17Nx40a0Wi1eXl5YWFiwbNkypk6diq2tLTt27CArK4u9e/diZWUFgK2tLUFBQZw4cQJHR0eioqI4c+YM0dHRODg4ANCjRw/8/PyIiYnB19eXhIQEYmNj+fDDD/H09ATA2dmZoUOHsnPnToKCgh7QnhOiduTWmWh0Tp78hQ8+WMfLL49j+vSZRtMKCgo4ceI4gwYNMSofPHgoOTnZnDp1Eii9tebu7olWq1VjvL29KS4uJi4uDoD4+HhcXFzUJAPg4eGBTqcjNjZWjenSpYuaZAD18+0xOp0Od3d3Ncba2hoXFxcOHTp0P3aJECYliUY0Op062fPZZ/9k0qQgNBqN0bRLl37HYDDQsaOdUXm7dh2A0ttt+fn5/Oc/f5SLsba2Rq/Xc+HCBQCSk5Oxt7c3itFoNLRv377SGICOHTsaxdjZ2ZVb19tjhKjPJNGIRsfaujVWVtYVTsvNLW2of+QRnVH5I4888n/Tc9XGfJ3OOKasrGx6dnY2er3+nmNycnKqjBGiPpM2GiFuoygKAGZmZhVONzMzB+4eoygK5ubmt8Xfe0zZOlXk9uVUV+vW5ZPWvbCxabwPIzTmba8JSTRC3EanKz0J5+bmGpXn5ZV+1uv16tXOnTGlcXnqU2B6vb7CK47c3FzatWtXZUzZVYxeryc9Pb3SmJrIyMihpMQ4ed3LCfPq1exaz9uQ2dhYNrptNzc3q9UPFbl1JsRt2rVrj0aj4fff04zK09NLP3fsaMcjjzyCjU1btaxMRkYGOTk5apuLvb09qampRjHFxcWkp6dXGgNw8eJFo5i0tLRyVzapqakVtu8IUd9IohHiNs2aNcPR0YnY2INGJ/bvv/8OvV7Pn/7UEwAXFzfi43+gsLBQjdm3bx8ajQZXV1cA3N3dOXr0KJmZmWpMXFwceXl5DBgwACh9Cu3cuXMkJyerMUlJSSQnJxvFZGVlcfjwYTXm+vXrJCQkqDFC1GeSaIS4g7//ZBITT7B48Wv8+9/xfPjhB+zc+THjx0/EwsICgHHj/Ll27RpBQUEcPHiQyMhIVqxYwYsvvsjjjz8OwNixY9FqtQQEBLB//3527drFvHnz8PT0pG/fvgD4+vpiZ2dHYGAgUVFRfP3110yZMoWuXbvi4+MDgIuLC66ursyZM4ddu3axf/9+AgICsLS0ZMyYMXWzk4SoATOlspbGh1xF96qhcd57vV9sbCw55FbzX9meRw+bZJ9XdSyjo79i+fKlfPFFFG3b2qrlsbEHiYgI5+LFVNq0acsLL4xmzJhXjOY9efIXwsPXc/r0aaysrHjuueeYOXMmTZs2VWN+++03li9fzs8//4xOp2PYsGHMnz/fqG3l8uXLhIaGEh8fj1arxd3dnQULFtC2bVs15ubNm6xcuZIDBw5QUlJCv379WLBgAZ07d67xPrlbG019Om4NQWM8T9S2jUYSjSSau7LSN6VJc4saz1efTlimPJa1/aOra5Jo7o/GeJ6obZ2Xp87EXTVpblHjk4/n0cNVBwkhGhVpoxFCCGFSkmiEEEKYlCQaIYQQJiWJRgghhElVK9GUlJSwc+dORowYgZOTE8OGDWPFihVGXWckJibKaINCCCHKqdZTZ1u2bGHt2rVMnjyZ/v37c+HCBdatW0dSUhJbt24lNTWVgIAAnJycZLRBIYQQRqpMNIqisGXLFl566SVCQkIAGDBgAFZWVgQHB3P69Gm2b9+OpaWljDYohBCinCpvneXm5jJy5Ej8/PyMysveSL548SLx8fEMHjxYRhsUQghRTpWJRq/Xs2jRIvr162dUfuDAAQAcHBy4fPlyuV5kZbRBIYQQUMunzk6cOMHmzZsZNmwYLVq0ALgvIwnKaINCCPHwqXEXNMeOHWPatGm0b9+eZcuWqd2kN8TRBivrs0dGznvwTLXP5VgKUbdqlGiio6NZsGABnTp1YsuWLVhZWamjDFZ0NVHfRxuUTjUr96BP0NKpphAPp2pfAkRGRjJnzhz69OnDjh071C7MdTodtra25UYJlNEGhRBCQDUTza5du1i5ciU+Pj5s2bKl3Lsq7u7uHDx4UEYbFEIIUU6Vt84yMjIIDQ2lXbt2jBs3jl9//dVoeseOHdXRAYOCgvD39yclJYU1a9aUG21w+/btBAQEMGPGDDIzM1m1alW50QY3bdpEYGAgISEhKIrC6tWr7zra4Ny5c2nVqhXr16+X0QaFEKKeqjLR/PDDD9y6dYvff/+dcePGlZseFhbGn//8ZyIiIggLC2PWrFlYWVkxceJEZs6cqcZZW1vz0UcfsXz5cubOnYtOp8Pb25v58+erMVqtlsjISEJDQ1m0aJHRaINlvQIAbNiwgZUrVxIWFqaONrh27Vpatmx5r/tDCCHEfSYjbMrDAHdVm1EXPY8erlcjNcrDAOXJCJv3R2M8T9S2zkvvzUIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMKkaDxMgxMPu+PEEZs2adtfpr7++BB8fP0aP/jO//16+J/F///vfWFtbA5CYmEhYWBinTp1Cp9PxwgsvMHPmTJo2barGp6SksHLlShISEtBoNHh7ezNv3jyj3sivXbvGihUriIuLw2Aw4OXlxcKFC7GxsbmPWy6EaUiiEeIO3bv/iU2bIu8oVVi58m3y8vJ46il38vLyuHTpd0JCQtSOY8uUDQaYmppKQEAATk5OrF27lvPnz/Pee++Rk5PDm2++CcDNmzfx9/fHxsaGd955h4yMDFatWsWVK1cIDw8HwGAwMHnyZPLy8liyZAkGg4HVq1cTGBjI7t27jbpnEqI+khraSFjpm9KkuUVdr0aDoNPp6d37CaOyzz7bycWLqXzwQQRWVlYkJp5AURSGDh2Kg4NDhcvZvHkzlpaWbNy4Ea1Wi5eXFxYWFixbtoypU6dia2vLjh07yMrKYu/evVhZWQFga2tLUFAQJ06cwNHRkaioKM6cOUN0dLT6XT169MDPz4+YmBh8fX1Nu0OEuEeSaBqJJs0tatVvmYDr1zPYsmUTzz03il69egNw7txvaLXN6NSp013ni4+PZ/DgwWi1WrXM29ubpUuXEhcXx6hRo4iPj8fFxUVNMlA6FIZOpyM2NhZHR0fi4+Pp0qWLUUIr+xwbGyuJRtR78jCAEFXYujUcc3Mzpkz5i1qWlPQbLVu2ZM6cOTg7O+Pk5ERwcDBXr14F4NatW1y+fLncYHzW1tbo9XouXLgAQHJycrkYjUZD+/btK42B0iE6ymKEqM8k0QhRiRs3bvDNN1GMGvWS0YB/SUnnuH49g65du7Jp0yYWLlzITz/9xIQJE8jPzyc7u7RX34qGF9fpdOqQ5dnZ2fclRoj6TG6dCVGJr77ag6KUMHq08aB6s2fPxcwMPD37A+Ds7IyDgwNjx47lyy+/xMvLCwAzM7Nyy1QUBXPz//7Gu18x1XW/hzawsbGsOugh1Zi3vSYk0QhRie+//xY3t/60atXKqLxnz96Ymxuf/Pv164elpSVnzpzh2WefBajwiiMvL0+9OtLr9RXG5Obm0q5duypjKrrSqcrdxqOprcY2JksZGY+mBvOZYF2EeChcvfoffvvtLEOGPG1UfuvWLaKivuTcud+MyhVFoaioCCsrK3Q6Hba2tqSmphrFZGRkkJOTo7a52Nvbl4spLi4mPT290hiAixcvVth2I0R9I4lGiLv49ddTADz5ZB+jcq1Wy4YNa4mI2GxU/u2335Kfn6++V+Pu7s7BgwcpLCxUY/bt24dGozGKOXr0KJmZmWpMXFwceXlyaagdAAAbg0lEQVR5DBhQ+pSgh4cH586dIzk5WY1JSkoiOTlZjRGiPpNEI8RdnD+fhIWFBY8++phRuUajwd9/ErGxB1m2bBmHDx9m27Zt/O1vf2Po0KG4ubkBEBgYyNWrVwkKCuLgwYNERkayYsUKXnzxRR5//HEAxo4di1arJSAggP3797Nr1y7mzZuHp6cnffv2BcDX1xc7OzsCAwOJiori66+/ZsqUKXTt2hUfH58Hu1OEqAVpoxHiLq5fv46lZYsKp7388itYWlqye/en7Nq1i5YtW/Lyyy8zc+ZMNcbBwYGIiAjCwsKYNWsWVlZWTJw40SjG2tqajz76iOXLlzN37lx0Oh3e3t7Mnz9fjdFqtURGRhIaGsqiRYvQarW4u7uzYMEC6RVANAhmiqIoVYc9nCpqFIWHs5HPxsayVi9sPoh5ADwOHcS8WbMazWO4lc+NnKJKY0x5LGvbMFrX7vYwQG2Om+fRww/d30p1PYzniarUts7LzyFRL5g3a1a7nguqSDRCiLonbTRCCCFMShKNEEIIk5JEI4QQwqQk0QghhDApSTRCCCFMShKNEEIIk5JEI4QQwqQk0QghhDApSTRCCCFMShKNEEIIk5JEI4QQwqSkrzPRqFjpm9KkuUWN5qlO551CiLuTRCMalSbNLaTzTiEeMLl1JoQQwqQk0QghhDApSTRCCCFMShKNEEIIk5JEI4QQwqQk0QghhDApSTRCCCFMShKNEEIIk5JEI4QQwqQk0QghhDApSTRCCCFMShKNEEIIk5JONYWoQLGiMPPmdYoAundXy5s3b87+/T8AcPTov9m6dRNJSUm0bt2aV155hUmTJhktJzExkbCwME6dOoVOp+OFF15g5syZNG3aVI1JSUlh5cqVJCQkoNFo8Pb2Zt68eej1ejXm2rVrrFixgri4OAwGA15eXixcuBAbGxuT7gch7gdJNEJU4EpJMUXAxEf0eEdu5caNPAA0mtKbAImJJ5g3bza+vr789a9/5dixY4SFhaEoCpMnTwYgNTWVgIAAnJycWLt2LefPn+e9994jJyeHN998E4CbN2/i7++PjY0N77zzDhkZGaxatYorV64QHh4OgMFgYPLkyeTl5bFkyRIMBgOrV68mMDCQ3bt306SJ/BmL+k1qqBAVSC8uxgzo11RLnz59uHo122j6li3hdO/+J1atWgWAp6cnBoOBTZs2MX78eLRaLZs3b8bS0pKNGzei1Wrx8vLCwsKCZcuWMXXqVGxtbdmxYwdZWVns3bsXKysrAGxtbQkKCuLEiRM4OjoSFRXFmTNniI6OxsHBAYAePXrg5+dHTEwMvr6+D3TfCFFT0kYjRAXSig3YmJvTzMys3LSCggJOnDjOoEFDjcqHDx9OVlYWx48fByA+Pp7Bgwej1WrVGG9vb4qLi4mLi1NjXFxc1CQD4OHhgU6nIzY2Vo3p0qWLmmQA9XNZjBD1mSQaISqQVlxMU8xYm5OFk5MT3t6DCQsLJS8vl0uXfsdgMNCxo53RPHZ2pZ8vXLjArVu3uHz5Mvb29kYx1tbW6PV6Lly4AEBycnK5GI1GQ/v27SuNAejYsaMaI0R9JrfORINVUlCAjY1llXHViblTerGBfEVhYLNmLNy8mSNHEoiI+JCLF1OZNu1VAHQ6ndE8ZZ9zcnLIzi691XZ7g/7tcTk5OQBkZ2dXK6ZLly4VxqSmptZ424R40CTRiAbLvFmz2g3LXA1BOkt0Zma01zTBxcWFTp3+hLV1a9566w1+/PEIAGYV3FYDMDc3R1GUu8YoioK5+X9vJtyvmOpq3bp8YrsXtUnkD4vGvO01IYlGiAp0b9K0XFn//h5Gn3Nzc40+l12BWFpaqlcpZWW3y8vLw9Ky9ASl1+srjMnNzaVdu3ZVxlR0NVSVjIwcSkoUo7J7OWHe+aBEY2FjY9nott3c3KxWP1SkjUaIO2SVlPBDQT5Xi4uNygsKCoDSdhaNRkN6eprR9IsXLwJgb2+PTqfD1ta23K2tjIwMcnJy1DYXe3v7cjHFxcWkp6dXGlP2fRW13QhR39Q40Zw+fZpevXpx5coVo/K4uDhGjRqFo6MjQ4YMISIioty8iYmJjB8/HicnJzw8PFizZg1FRUVGMSkpKUybNg1nZ2fc3NxYvHhxuV9z165dIyQkBDc3N/r168ecOXO4evVqTTdFiAqZAR/fyuW7wnyj8u++i0Gj0eDs7IajoxOxsd+pt8gA9u3bh6WlJb179wbA3d2dgwcPUlhYaBSj0WhwdXVVY44ePUpmZqYaExcXR15eHgMGlN4W9PDw4Ny5cyQnJ6sxSUlJJCcnqzFC1Gc1SjTJyclMnToVg8FgVH78+HGmTZtG586dWb9+PSNGjCAsLIytW7eqMWUvrzVr1oy1a9cyadIkIiMjWbFihRpT9vLatWvXeOeddwgJCSE6OpqQkBA1puzltZMnT7JkyRKWLFnC8ePHCQwMLLdeQtSGpbk5g7UWfFeQz5e38vj3v/9NZOSHfPDBel544UXat++Av/9kTp48QXBwMLGxsaxdu5atW7cydepUmjdvDkBgYCBXr14lKCiIgwcPqvX9xRdf5PHHHwdg7NixaLVaAgIC2L9/P7t27WLevHl4enrSt29fAHx9fbGzsyMwMJCoqCi+/vprpkyZQteuXfHx8amz/SREdVWrjcZgMPDpp5+yevVqo64zyqxbt46ePXvKy2vioTG6+SNYmZsTX5jPvqAg2rSxYdKkqYwbNwGAfv1cWL48jMjID5kxYwa2trbMnz/fqAsaBwcHIiIiCAsLY9asWVhZWTFx4kRmzpypxlhbW/PRRx+xfPly5s6di06nw9vbm/nz56sxWq2WyMhIQkNDWbRoEVqtFnd3dxYsWCC9AogGoVq19NixY7z77rtMnjwZW1tbFi1apE4rKCggISGB2bNnG80zfPhwtmzZwvHjx3nqqafu+vLa0qVL1dtuVb285ujoWOXLa5JoxP3QxMwMb4vmeFs0x/Po4Qobfb28hvDCCyMrXY6zszOfffZZpTHdunVj27ZtlcY89thjbNiwocr1FqI+qtatMwcHBw4cOMCrr76KRqMxmpaWlkZRUVG5Rkl5eU0IIQRUM9G0adOG1q1bVzjtbi+mmfLltapihBBC1B/3fIO3shfToH6/vFbZ8+DyIpa4ndQHIWrvnhNN2Ytnd15NNISX1yp6cQ0ezhex5ER5byqqD7V9eU2IxuaeX9js2LEjGo1GfVmtjLy8JoQQAu5DomnWrBnOzs7ExMQ8NC+vlXXWWJN/Vvryj30LIYS4T32dTZ8+nYkTJxIcHMzzzz/Pzz//zNatWwkJCTF6eS0qKoqgoCD8/f1JSUlhzZo15V5e2759OwEBAcyYMYPMzExWrVpV7uW1TZs2ERgYSEhICIqisHr16vv68lqtO2vMKao6UAghGpn70tdZ//79Wb9+PefPn2fGjBl89dVXzJ8/nylTpqgxZS+v5eXlMWvWLCIjI5k4cSKvv/66GlP28lqrVq2YO3cu7733Ht7e3rz33ntqTNnLaz179mTRokW8/fbbODk5sXXrVnl5TQgh6qEan5lfeOEFXnjhhXLlTz/9NE8//XSl88rLa0II0fjIJUADZKVvSpPmFnW9GkIIUS2SaBqgJs0tTDbglxBC3G8yHo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMClJNEIIIUxKEo0QQgiTkkQjhBDCpCTRCCGEMCkZj0aICpQoCocKC/i+IJ8bTk60amXFwIFeTJ48lUce0QEwa9Z0EhJ+LDfv559/zhNPPAFASkoKK1euJCEhAY1Gg7e3N/PmzUOv16vx165dY8WKFcTFxWEwGPDy8mLhwoXY2NioMbm5ubz77rvExMSQl5eHs7Mzr7/+Op06dTLtjhDiPpBEI0QF9hXkszc/j+HNLHjx/fdJTDzDli2buHDhAmvWrAcgKek3JkyYwLPPPms0r4ODAwA3b97E398fGxsb3nnnHTIyMli1ahVXrlwhPDwcAIPBwOTJk8nLy2PJkiUYDAZWr15NYGAgu3fvpkmT0j/R4OBgEhMTmT9/Pjqdjg0bNjBhwgSioqKwtLR8gHtGiJqTRCPEHRRF4V8Ft/DUNuOF5joGDBhA165P0LJlSxYvfo1z585iZWVNZmYmAwcOpE+fPhUuZ8eOHWRlZbF3716srKwAsLW1JSgoiBMnTuDo6EhUVBRnzpwhOjpaTVA9evTAz8+PmJgYfH19SUhIIDY2lg8//BBPT08AnJ2dGTp0KDt37iQoKOjB7BghaknaaIS4Qz4KTzVthpu2mVF5x46dAPj993TOnTsLQPfu3e+6nPj4eFxcXNQkA+Dh4YFOpyM2NlaN6dKli5pkAPXz7TE6nQ53d3c1xtraGhcXFw4dOnRvGyvEAyCJRog7NDczZ8wjOro0aWpU/sMP3wNgb+9AUtI5tFot69atw83NjSeeeIIpU6Zw4cIFNT45ORl7e3ujZWg0Gtq3b6/GVRQD0LFjR6MYOzs7NBrNXWOEqM/k1pkQ1fC//3uK7dv/HwMHDsLOrhNJSb9RWFiIhYUFGzZs4PLly7z//vuMGzeOf/7zn9jY2JCdnW3U6F9Gp9ORk5MDQHZ2Nl26dKkwJjU1FYCcnJwql1MTrVuXX9a9sLFpvG1EjXnba0ISjRBVOHbsGCEhM3n88cdZsGARAP7+k3nuuVE888xgNc7JyQkfHx+2b99OcHAwAGZmZuWWpygK5ub/vZlQVYyiKHddt9uXU10ZGTmUlBgv815OmFevZtd63obMxsay0W27ublZrX6oSKIRohI/FRbw/yZOpH37jqxevZ6WLVsB0LlzF8zNjRNEhw4dcHBw4MyZMwDo9foKrzhyc3Np165dlTFlVzF6vZ709PRKY4Soz6SNRoi7iMm/xYd5OfTp04f33/+QNm3aAP/3VNq/ovjll5/LzZOfn682/tvb26u3v8oUFxeTnp6utstUFANw8eJFo5i0tLRyVzapqakVtu8IUd9IohGiAj8U5LMrPw/nplq2bNlidOVgZmbGzp0fs27dakpKStTy//3f/+XixYu4uroC4O7uztGjR8nMzFRj4uLiyMvLY8CAAUDpU2jnzp0jOTlZjUlKSiI5OdkoJisri8OHD6sx169fJyEhQY0Roj6TRCPEHbJKSvjHrVxam5kzuJkFv/76K6dOJar/MjMzmTQpiDNnTjN37lzi4+PZtWsXU6dOpUePHvz5z38GYOzYsWi1WgICAti/fz+7du1i3rx5eHp60rdvXwB8fX2xs7MjMDCQqKgovv76a6ZMmULXrl3x8fEBwMXFBVdXV+bMmcOuXbvYv38/AQEBWFpaMmbMmDrbT0JUl7TRCHGHU4YiCoEMpYSwnCx46SWj6W+88RbDh/uycuVqduzYxquvvoqFhQVPP/00c+bMUR9Dtra25qOPPmL58uXMnTsXnU6Ht7c38+fPV5el1WqJjIwkNDSURYsWodVqcXd3Z8GCBWqvAAAbNmxg5cqVhIWFUVJSQr9+/Vi7di0tW7Z8AHtEiHsjiUaIOwzQNmPAbS9reh49XOHTRZ6eg3j+eb9Kl9WtWze2bdtWacxjjz3Ghg0bKo1p2bIlK1asYMWKFZXGCVEfya0zIYQQJiWJRgghhElJohFCCGFSkmiEEEKYlCQaIYQQJiWJRgghhElJohFCCGFSkmiEEEKYlCQaIYQQJiWJRgghhElJohFCCGFSkmiEEEKYlCQaIYQQJiW9N98nJQUFtRp33XArnxs5RSZYIyGEqB8k0dwn5s2accit5qMdeh49DJJohBAPMbl1JoQQwqQk0QghhDApSTRCCCFMStpo6lhtHyIQQoiGQhJNHavNQwSeRw+baG2EEOL+k1tnQgghTEoSjRBCCJOSRCOEEMKkJNEIIYQwKUk0QgghTEoSjRBCCJNqsInm66+/5tlnn+XJJ5/Ex8eHvXv31vUqCWFyUu9FQ9QgE80333zD3LlzcXd35/3338fV1ZW//e1v/Otf/6rrVRPCZKTei4aqQb6wuWbNGnx8fHjttdcAGDhwIDdv3uTvf/873t7edbx2QpiG1HvRUDW4K5q0tDQuXrzIM888Y1Q+fPhwkpOTSUtLq6M1E8J0pN6LhqzBXdEkJycDYG9vb1RuZ2cHwIULF+jQoUO1lmVubnbXac0ee7TG61abeR7kd9XneR7kd9VmnorqSmX15357EPW+NvulNn31GfILuJn7cIzB9CDrQH1Q2+1tcIkmOzsbAL1eb1Su0+kAyMnJqfayrKx0d53mtveLGq9bbeZ5kN9Vn+d5kN9Vm3lat9ZXHWRCD6Le1/a41VQTi2a0tmj2QL7L1Oq6XjQUDe7WmaIoAJiZmVVYbm7e4DZJiCpJvRcNWYOrnZaWpZfpd/6Cy83NNZouxMNE6r1oyBpcoim7R33x4kWj8tTUVKPpQjxMpN6LhqzBJRo7Ozvat29f7t2BmJgYOnXqxOOPP15HayaE6Ui9Fw1Zg3sYAGDGjBksXLiQli1bMmjQIL777ju++eYb3nvvvbpeNSFMRuq9aKjMlLLWxAbmH//4BxEREVy+fJkOHToQFBTEc889V9erJYRJSb0XDVGDTTRCCCEahgbXRiOEEKJhkUQjhBDCpCTR3Ea6YG94SkpK2LlzJyNGjMDJyYlhw4axYsUKo/dNEhMTGT9+PE5OTnh4eLBmzRqKih6OLlDu1cNW50+fPk2vXr24cuWKUXlcXByjRo3C0dGRIUOGEBERUW7e6tSTlJQUpk2bhrOzM25ubixevLjcu03Xrl0jJCQENzc3+vXrx5w5c7h69apRTG5uLkuXLsXd3R0nJyemTJlCSkqKUYzBYGDt2rV4eXnh6OjI2LFjOXny5D3snTqkCEVRFCU6Olrp3r27Ehoaqhw6dEh58803lW7duinffPNNXa+aqER4eLjSo0cP5d1331Xi4+OV7du3K66ursqkSZMURVGUlJQUpW/fvsrkyZOV77//Xtm6davSu3dvZenSpXW85nXvYavz58+fVwYOHKh069ZNuXz5slp+7NgxpVevXsrcuXOV2NhYZc2aNUr37t2VLVu2qDHVqSeZmZmKp6enMmrUKOXAgQPKp59+qjg7OytBQUFqTFFRkTJy5Ehl2LBhSnR0tPLll18qXl5eysiRI5WioiI1bsqUKcpTTz2lfPHFF8q+ffuUESNGKAMHDlSysrLUmCVLliiOjo7Kxx9/rHz77bfKK6+8ojg5OSkXL1401S40GUk0/2fYsGHK7Nmzjcr++te/Kt7e3nW0RqIqJSUliouLi7JkyRKj8qioKKVbt27Kr7/+qrz22muKl5eXUlBQoE7fsWOH0qNHD+XKlSsPepXrlYelzhcVFSnbt29XnJycFFdX13KJxt/fXxk9erTRPGFhYYqzs7NaL6pTT95//32lT58+yvXr19WY77//XunWrZvyyy+/KIqiKHv37lW6deumJCUlqTHnzp1TunfvrkRFRSmKoig//fST0q1bNyU2NlaNycjIUPr06aOEh4criqIoaWlpSo8ePZRPPvlEjSkoKFAGDRqkvPnmm/e2w+qA3DpDumBvqHJzcxk5ciR+fn5G5Z07dwZK36KPj49n8ODBaLVadbq3tzfFxcXExcU90PWtTx6mOn/s2DHeffddJk2axNy5c42mFRQUkJCQUOF2ZmVlcfz4cYBq1ZP4+HhcXFywsrJSYzw8PNDpdMTGxqoxXbp0wcHBQY0p+3x7jE6nw93dXY2xtrbGxcWFQ4cOAXDkyBGKi4sZPny4GqPVahk0aJAa05BIoqF6XbCL+kev17No0SL69etnVH7gwAEAHBwcuHz5crnjam1tjV6vb9TH9WGq8w4ODhw4cIBXX30VjUZjNC0tLY2ioqJKt/PWrVvVqifJycnlYjQaDe3bt680BqBjx45GMXZ2duXW9c6Yli1bYm1tXW69L126RH5+ftU7ph6RRMP97YJd1K0TJ06wefNmhg0bRosWLYDyxxVKj21jPq4PU51v06YNrVu3rnBadbbzbjFlcWX7Ijs7+77E5OTk3FMM/Lcz1YZCEg3SBfvD4tixYwQGBtK+fXuWLVt21+MKpce2MR/XxlLnK6sDULqdNakn9yNGqeQd+apiqtqe+urhqE33SLpgb/iio6OZOHEijz32GNu2bcPKykr9RVjRr/O8vLxGfVwbS52/23aWfba0tKx2PdHr9RXG5ObmqsuobkxFVyTVjSmb3pBIokG6YG/oIiMjmTNnDn369GHHjh20bdsWKL3NYGtrqx7HMhkZGeTk5DTq49pY6nzHjh3RaDTltrPss729fbXrib29fbmY4uJi0tPTK40p+77bY9LS0spdtaSmpqoxnTt3JjMzk5s3b5aLad++vdFDCw2BJBqkC/aGbNeuXaxcuRIfHx+2bNlS7pe4u7s7Bw8epLCwUC3bt28fGo0GV1fXB7269UZjqfPNmjXD2dmZmJgYoxP7vn37sLS0pHfv3kD16om7uztHjx4lMzNTjYmLiyMvL48BAwYApU+hnTt3Tn3YAiApKYnk5GSjmKysLA4fPqzGXL9+nYSEBDWm7L/79u1TYwoLC4mNjVWnNSSaJUuWLKnrlagPLC0t+eCDD7hx4wZmZmZERkayZ88eFi9eTNeuXet69UQFMjIyCAwMxNbWlpCQEDIyMrhy5Yr6T6vV0rNnTyIiIkhISKBly5Z8//33rFq1itGjRzNixIi63oQ69TDW+dOnT/Ptt98yceJE9fbSo48+yqZNmzh//jzNmzdn7969fPjhh8ycORM3Nzeg9CqjqnrSpUsX/vGPf3DgwAFat27N8ePHWbJkCW5ubkydOhUovRL55ptv2LNnD23atOG3335j4cKFPPbYYyxatAhzc3PatWvHjz/+yCeffEKrVq24dOkSr732GoqisHz5ciwsLGjRogW///47W7dupXnz5ty4cYO33nqLtLQ0wsLCaNWqVd3s4Np64G/u1GM7d+5Unn76aaV3796Kj4+PsmfPnrpeJVGJPXv2KN26dbvrv7179yqKUvqC3OjRo5XevXsrAwcOVFavXq0UFhbW8drXDw9bnd+9e3e5FzYVRVFiYmIUPz8/pVevXsqQIUOUrVu3lpu3OvXk7Nmzir+/v/Lkk08q/fv3V9544w0lOzvbKObSpUvKjBkzlD59+iiurq5KcHCw8scffxjFZGZmKgsWLFCcnZ2Vvn37KlOmTFHOnz9vFFNQUKCEhoYq/fv3VxwdHZWxY8eqL4Y2NDJMgBBCCJOSNhohhBAmJYlGCCGESUmiEUIIYVKSaIQQQpiUJBohhBAmJYlGCCGESUmiEUIIYVKSaIQQQpiUJBohhBAm9f8BfXomtU2R6QsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['hour', 'views']].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002554FCA4EB8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002554FCD73C8>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['hour', 'comments']].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2554a612780>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='hour', y='comments', data=df[df['domain'] == 'habrahabr.ru'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002554C735AC8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000025551736DA0>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['domain'] == 'habrahabr.ru'][['hour', 'comments']].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4\\. Кого из топ-20 авторов чаще всего минусуют?\n",
    "\n",
    "* @Mordatyj\n",
    "* @Mithgol\n",
    "* @alizar\n",
    "* @ilya42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x255492431d0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot( df[df['author'].isin(df['author'].value_counts().head(5).index)]['author'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5\\. Сравните субботы и понедельники\n",
    "\n",
    "Правда ли, что по субботам авторы пишут в основном днём, а по понедельникам — в основном вечером?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25551b61160>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='dayofweek', hue='hour', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}