{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python для сбора и анализа данных\n",
    "\n",
    "*Алла Тамбовцева, НИУ ВШЭ*\n",
    "\n",
    "### Управление браузером с Selenium: пример Кинопоиска"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Библиотека Selenium – библиотека для управления браузером с помощью Python. Она позволяет запускать браузер и имитировать действия пользователя в нем. Зачем это может понадобиться? Во-первых, такое «встраивание» в браузер в большинстве случаев позволяет решить проблему с возникающими капчами и иными ограничениями, так как настройки сайта не распознают, что запрос к исходному коду страницы производится автоматически. Во-вторых, необходимость имитации действий в браузере неизбежно возникает при обработке динамических веб-страниц, где некоторые элементы (окна, графики, таблицы) появляются только при определенных действиях пользователя, например, при скроллинге или наведении мышкой. В-третьих, библиотека может быть полезна в случаях, если доступ к API сайта или базы данных получить довольно сложно, но при работе в браузере информация доступна (в таком случае можем залогиниться через Python как будто пользователь и потихоньку выгружать данные).\n",
    "\n",
    "Установим библиотеку:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# устанавливаем selenium\n",
    "\n",
    "!pip install selenium"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Импортируем необходимые компоненты Selenium:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# импортируем модуль wd для открытия браузера\n",
    "# By – коллекция методов для поиска элементов\n",
    "# Keys – коллекция для имитации нажатия клавиш на клавиатуре\n",
    "\n",
    "from selenium import webdriver as wd\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.common.keys import Keys"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Заодно импортируем `BeautifulSoup`, понадобится, когда дойдем до исходного кода:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bs4 import BeautifulSoup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Открываем браузер – начинаем новую сессию работы с Selenium (скачиваем драйвер для Chrome, см. [инструкцию](https://github.com/allatambov/WebScrape23/blob/main/selenium.pdf)), после запуска кода должно открыться новое окно браузера, пустое:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:1: DeprecationWarning: executable_path has been deprecated, please pass in a Service object\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "br = wd.Chrome(executable_path=\"/Users/allat/Documents/chromedriver\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Отправляем запрос – открываем главную страницу Кинопоиска в новом окне браузера:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# чудеса вышкинского вайфая – капча не вылезает\n",
    "# если вылезла – проходим ее вручную, тыкаем на галочку и вводим текст\n",
    "\n",
    "br.get(\"https://www.kinopoisk.ru/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Почти со 100% уверенностью Кинопоиск покажет капчу, мы поступим не самым спортивным, но бесплатным способом – вручную пройдем ее в открытом через Selenium окне браузера. Вообще самый надежный и универсальный способ обхода – установить специальное расширение и получить доступ к сервисам типа AntiCapcha или Antigate, а потом активировать это расширение при открытии браузера через Selenium. Но эти сервисы платные, хоть и не очень дорогие. \n",
    "\n",
    "В нашем случае проблема с капчей не такая уж и глобальная, если мы пишем код для себя. Если мы все-таки пишем код для другого пользователя или вообще готовим какое-то приложение, тут есть о чем подумать еще помимо капчи, например, о том, как пользователям безболезненно установить все для Selenium или как разместить драйвер для Chrome (и сам Chrome) на сервере..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ищем на странице поле для поиска фильма, судя по его виду (проверить можно, открыв исходный код страницы), оно будет иметь тэг `<input>`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<selenium.webdriver.remote.webelement.WebElement (session=\"71c6e8b5f201596779921459a1a8b3c8\", element=\"688321c8-8edf-4269-ab19-8689ae504d42\")>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ищем на странице поле для поиска фильма\n",
    "# find_elements – все элементы в виде списка\n",
    "# тут такой один\n",
    "\n",
    "br.find_elements(By.TAG_NAME, \"input\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Метод `.find_elements()` возвращает все элементы, удовлетворяющие критериям поиска, в виде списка. В данном случае результат точно один, поэтому изменим метод на `.find_element()`, чтобы не извлекать элемент из списка по индексу. Метод `.find_element()` всегда возвращает один результат, если подходящих фрагментов несколько, забирается только первое совпадение."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "search = br.find_element(By.TAG_NAME, \"input\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь нам надо в это поле впечатать название фильма. Сделать это можно с помощью метода `.send_keys()`, он используется для заполнения полей (и иногда для выбора опций в выпадающем меню)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "film = \"Господин оформитель\"\n",
    "search.send_keys(film)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Если проверить, в окне браузера в строке поиска должно появиться название фильма. Чтобы активировать поиск, надо выбрать в выпадающем меню подходящее название и кликнуть на него. Но мы поступим проще – имитируем нажатие *Enter* через набор клавишей `Keys` и тот же метод `.send_keys()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "search.send_keys(Keys.ENTER)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Отлично! Результаты появились. Единственный минус – фильм не один. Найдем тот, который нам нужен, по частичному совпадению текста ссылки (ссылки на фильмы содержат сами ссылки в виде адресов и текст):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# результат не один – ищем подходящую ссылку\n",
    "# по совпадению текста ссылки с film\n",
    "\n",
    "link = br.find_element(By.PARTIAL_LINK_TEXT, film)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Объект найден, кликаем на него:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "link.click()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Страница фильма открыта. Заберем исходный код страницы, открытой в браузере в данный момент:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "html = br.page_source"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Переменная `html` хранит обычную строку с кодом HTML. Преобразуем ее в объект BeautifulSoup, чтобы далее, как обычно, выполнять поиск по тэгам."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "soup = BeautifulSoup(html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "С поиском информации по тэгам мы уже довольно много работали, поэтому давайте для примера найдем раздел с описанием фильма и на этом остановимся:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "tab = soup.find(\"div\", {\"data-test-id\" : \"encyclopedic-table\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Внутри этого раздела можно найти все подразделы с тэгом `div`, а затем из каждого извлечь текст (не очень красиво, но задача у этого практикума немного другая – сейчас перейдем к более интересным данным):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Год производства1988',\n",
       " 'Год производства',\n",
       " '1988',\n",
       " 'СтранаСССР',\n",
       " 'Страна',\n",
       " 'СССР',\n",
       " 'Жанружасы, фэнтези, драма, детективслова',\n",
       " 'Жанр',\n",
       " 'ужасы, фэнтези, драма, детективслова',\n",
       " 'ужасы, фэнтези, драма, детектив',\n",
       " 'Слоган—',\n",
       " 'Слоган',\n",
       " '—',\n",
       " '—',\n",
       " 'РежиссерОлег Тепцов',\n",
       " 'Режиссер',\n",
       " 'Олег Тепцов',\n",
       " 'СценарийЮрий Арабов, Александр Грин',\n",
       " 'Сценарий',\n",
       " 'Юрий Арабов, Александр Грин',\n",
       " 'Директор фильмаОлег Тепцов, Вениамин Кутиков',\n",
       " 'Директор фильма',\n",
       " 'Олег Тепцов, Вениамин Кутиков',\n",
       " 'ОператорАнатолий Лапшов',\n",
       " 'Оператор',\n",
       " 'Анатолий Лапшов',\n",
       " 'КомпозиторСергей Курехин',\n",
       " 'Композитор',\n",
       " 'Сергей Курехин',\n",
       " 'ХудожникНаталья Васильева, Лариса Конникова',\n",
       " 'Художник',\n",
       " 'Наталья Васильева, Лариса Конникова',\n",
       " 'МонтажИрина Гороховская',\n",
       " 'Монтаж',\n",
       " 'Ирина Гороховская',\n",
       " 'Зрители3.3 млн , ...',\n",
       " 'Зрители',\n",
       " '3.3 млн , ...',\n",
       " 'Премьера в мире18 мая 1990, ...',\n",
       " 'Премьера в мире',\n",
       " '18 мая 1990, ...',\n",
       " 'Возраст16+',\n",
       " 'Возраст',\n",
       " '16+',\n",
       " 'Время109 мин. / 01:49',\n",
       " 'Время',\n",
       " '109 мин. / 01:49',\n",
       " '109 мин. / 01:49']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# некрасиво, но пока для примера\n",
    "\n",
    "divs = tab.find_all(\"div\")\n",
    "texts = [d.text for d in divs]\n",
    "texts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Информация выгружена, при желании из `tab` элементы можно извлечь более аккуратно, уточнив атрибуты тэгов `div`, а мы перейдем к более глобальной задаче. Давайте получим данные, на основе которых на сайте строятся графики, визуализирующие распределение оценок фильмов. Для этого сначала найдем ссылку, которую ведет на страницу с оценками. Если изучить исходный код страницы, можно заметить, что эта ссылка, как и все ссылки, имеет тэг `<a>`, но отличается тем, что имеет атрибут `class` со значением `film-rating-value styles_rootLink__mm0kW`. Для разнообразия найдем ссылку с помощью XPATH:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ищем и кликаем\n",
    "\n",
    "rating = br.find_element(By.XPATH, \n",
    "                         \"//a[@class = 'film-rating-value styles_rootLink__mm0kW']\")\n",
    "rating.click()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Небольшое отступление – что такое XPATH и зачем.\n",
    "\n",
    "**XPATH** (от *XML Path Language*) – язык запросов в XML-файлу, который можно использовать и для HTML тоже.\n",
    "\n",
    "**XML** (от *eXtended MarkUp Language*) – язык разметки, только в отличие от HTML не позволяет регулировать внешний вид страницы, а просто хранит данные в виде строки с удобными тэгами.\n",
    "\n",
    "На XML-файл можно смотреть как на хранилище, откуда по запросу динамически подгружаются данные для подстановки в HTML-файл. Смысл: когда нам нужно постоянно обновлять информацию на веб-странице (каталоги товаров в магазине, данные о погоде, курсе валют), не нужно каждый раз переписывать HTML-файл, достаточно изменить XML-файл, а из него уже информация «подтянется» на страницу с помощью запроса, написанного на JavaScript.\n",
    "\n",
    "Примеры запросов с XPATH (честно взяты [отсюда](https://www.w3schools.com/xml/xpath_intro.asp), очень полезный тьюториал по XPATH, у них же есть классные материалы по XML):\n",
    "\n",
    "* `//title[@lang]`: все элементы с тэгом `<title>`, имеющие атрибут `lang`;\n",
    "* `//title[@lang='en']` : все элементы с тэгом `<title>`, имеющие атрибут `lang`, равный `'en'`;\n",
    "* `//title[@*]`: все элементы с тэгом `<title>`, имеющие хоть какие-нибудь атрибуты."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Возвращаемся к странице на Кинопоиске. В браузере открыта страница с оценками фильма. Давайте снова сгрузим исходный код HTML и найдем в нем фрагмент, содержащий ссылку на данные, на основе которых строится круговая диаграмма."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# снова забираем исходный код страницы\n",
    "# преобразуем\n",
    "\n",
    "htm = br.page_source\n",
    "sou = BeautifulSoup(htm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Если внимательно изучим исходный код страницы, заметим, что ссылка на нужные данные хранится во фрагменте кода на JavaScript. Найдем его и заберем весь текст оттуда (атрибут `.text`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\n$(function () {\\n    $('#flashcontent_2').css({\\n        marginTop: 20,\\n        width: 500,\\n        height: 330,\\n    });\\n    KPChart.create({\\n        containerId: 'flashcontent_2',\\n        chartType: 'pie',\\n        dataURI: 'https://kinopoisk-fvs.s3.yandex.net/films/44587/value-stats.json',\\n        dataType: 'json',\\n        pie: {\\n            minRadius: 110,\\n            innerRadius: 25,\\n            depth3D: 20,\\n            angle: 25,\\n            labelRadius: 30,\\n            startDuration: 0,\\n            pulledField: 'out',\\n            hideLabelsPercent: 3,\\n            descriptionField: null,\\n            colors: [\\n                '#FF0F00',\\n                '#FF6600',\\n                '#FF9E01',\\n                '#FCD202',\\n                '#F8FF01',\\n                '#B0DE09',\\n                '#04D215',\\n                '#0D8ECF',\\n                '#0D52D1',\\n                '#2A0CD0'\\n            ]\\n        },\\n        legend: {\\n            position: 'absolute',\\n            left: '10px',\\n            maxColumns: 1,\\n            borderAlpha: 0.2,\\n            borderColor: '#000000',\\n            horizontalGap: 2,\\n            markerLabelGap: 10,\\n            textClickEnabled: true,\\n            verticalGap: 7,\\n            width: 90\\n        },\\n    }, function(chart) {\\n        var chartGroupVote = chart;\\n    });\\n});\\n\""
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "code = sou.find_all(\"script\", {\"type\" : \"text/javascript\"})[12].text\n",
    "code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В переменной `code` хранится обычная строка, объект типа `string`. Так это не блок кода HTML, поиск по тэгам здесь невозможен. Воспользуемся регулярными выражениями – найдем все ссылки, который заканчиваются на `.json`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://kinopoisk-fvs.s3.yandex.net/films/44587/value-stats.json'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "\n",
    "# начало и конец ссылки известны\n",
    "\n",
    "data_link = re.findall(\"https:.+\\.json\", code)[0]\n",
    "data_link"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ура, ссылка найдена! Отправляем ее в браузер, окно которого у нас все еще открыто, благодаря Selenium, и снова забираем исходный код (уже последний раз). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "br.get(data_link)\n",
    "page = br.page_source"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В данном случае проще не преобразовывать исходный код в объект BeautifulSoup, поэтому с помощью регулярных выражений найдем фрагмент, который содержит данные в формате JSON-строки (как будто список со словарями):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[{\"value\":241,\"title\":\"1\",\"out\":null},{\"value\":140,\"title\":\"2\",\"out\":null},{\"value\":211,\"title\":\"3\",\"out\":null},{\"value\":305,\"title\":\"4\",\"out\":null},{\"value\":730,\"title\":\"5\",\"out\":null},{\"value\":1262,\"title\":\"6\",\"out\":null},{\"value\":2202,\"title\":\"7\",\"out\":\"true\"},{\"value\":2130,\"title\":\"8\",\"out\":null},{\"value\":1136,\"title\":\"9\",\"out\":null},{\"value\":1638,\"title\":\"10\",\"out\":null}]'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# как список словарей, только в тексте\n",
    "\n",
    "data_str = re.findall(\"\\[\\{.+\\}\\]\", page)[0]\n",
    "data_str"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Теперь импортируем модуль `json`, который позволит преобразовать эту JSON-строку в полноценный список словарей, принятый в Python:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В этом модуле есть две функции: `load()` загружает данные из текстового файла с расширением `.json`, а \n",
    "`loads()` загружает данные из строки в формате JSON:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'value': 241, 'title': '1', 'out': None},\n",
       " {'value': 140, 'title': '2', 'out': None},\n",
       " {'value': 211, 'title': '3', 'out': None},\n",
       " {'value': 305, 'title': '4', 'out': None},\n",
       " {'value': 730, 'title': '5', 'out': None},\n",
       " {'value': 1262, 'title': '6', 'out': None},\n",
       " {'value': 2202, 'title': '7', 'out': 'true'},\n",
       " {'value': 2130, 'title': '8', 'out': None},\n",
       " {'value': 1136, 'title': '9', 'out': None},\n",
       " {'value': 1638, 'title': '10', 'out': None}]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dict = json.loads(data_str)\n",
    "data_dict "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Полноценный список словарей получен, далее превратим его в таблицу с помощью `pandas`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>value</th>\n",
       "      <th>title</th>\n",
       "      <th>out</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>241</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>140</td>\n",
       "      <td>2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>211</td>\n",
       "      <td>3</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>305</td>\n",
       "      <td>4</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>730</td>\n",
       "      <td>5</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1262</td>\n",
       "      <td>6</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2202</td>\n",
       "      <td>7</td>\n",
       "      <td>true</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2130</td>\n",
       "      <td>8</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1136</td>\n",
       "      <td>9</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1638</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   value title   out\n",
       "0    241     1  None\n",
       "1    140     2  None\n",
       "2    211     3  None\n",
       "3    305     4  None\n",
       "4    730     5  None\n",
       "5   1262     6  None\n",
       "6   2202     7  true\n",
       "7   2130     8  None\n",
       "8   1136     9  None\n",
       "9   1638    10  None"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data_dict)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Данные есть, причем в удобном и понятном всем виде. Построим по ним столбиковую диаграмму, круговую для большого числа категорий строить не рекомендуется (и вообще *pie charts* уже не любят). Импортируем модуль `pyplot` из библиотеки `matplotlib` для графики:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Вообще график `matplotlib` состоит из двух частей:\n",
    "\n",
    "* «рамка» для картинки (обычно сохраняется в переменную `fig`);\n",
    "* поле с осями, внутри которого строится график (обычно сохраняется в переменную `ax`).\n",
    "\n",
    "Так, мы можем воспользоваться функцией `subplots()` и сообщить Python, что мы хотим получить картинку размера 16 на 9 дюймов с разрешением 300 точек на дюйм (`dpi` от *dots per inch*):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 10 artists>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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mvTpbruendveJ2zgcYG7ssuNDAIBFnJbk5t39gO5+dnf/VXd/Yjk79QGwlSd1908vtVE6Sbr7z5O8eTD89NWNBbB5dfd3M3nC/rS7ziILwBhV1T5J/npq6GVJPjWjOAAAsJgnZctG6TM0SgPMRlXtleSpg+FXzSILwAZ36KD+6lIapRe8ZVDfbRXyAMyFqqokPzUY/uOlzO3u92ey6dCN7pzk6NVJBrAxdfdl29rdeRX9XG5qlE6S03fUKL3gxYP6yVV1s9WLBbAxaZYGgJ2wTl9uADaV7r5gJ6cOd5Z+5AqjALClSwf1fjNJATBOf5jkkIV/fynJKTNLAgAAiztpUP/3maQAIEmOT7L/VH15ktNnlAVgI9tnUH9tGXO/OqhvscIsAPPk8CS3nqqvzZa7Re/IOwf18SsNBECeMKiX9KDL7j4nycenhvZJ8qjVCgWwUWmWBgAAxu6Tg3qvqjpgJkkA5tOdBvXXZ5ICYGSq6seS/OrU0EndffWs8gAAwFBV3TXJI6aGLkjyL7NJA0CSZw7q13qIO8Civjmol7ND3vDY4UODATazgwf1F7v7B8uY/9lBPdylGoBlqKqDktxvauj6JB9exinOHNSPWWkmgI1OszQAADB21y8ytse6pwCYQ1V19yQPnhrqJO+fURyA0aiqPZP8TW66Bn9ad793hpEAAGAxjxzUZ3R3zyQJwCZXVXdJ8vDB8CtnkQVgBP4tyXTz3j2raq8lzn3QIucCYOKWg/ryZc4fHn+Hqtp/BXkANrt7D+rPdPdVy5j/kUF9rxXmAdjwNEsDAABjd9dBfX23nbVcAAATHElEQVSSb88iCMA8qarbJXljkl2nht/U3RfMJhHAqJyS5B4L/74kyfNnFwUAALbpRwf1R5OkJo6tqlOr6t+r6oqquqqqLqyq91bVC6rqkHVPCzDfTkxSU/UnuvtTswoDsJF19/eSvGZq6GZJnrmjeVW1a5LnDIZPW8VoAGN37aDec5nzFzv+8J3MAsDWa+h5y5x//g7OBzB3NEsDAABjd/ygPqu7fziTJAAjVlW7VdWBVfXwqnpJknOT3HfqkC9l6xtIABioqgcm+S9TQ8/t7u/MKg/AnDppoVnvoqq6pqq+V1UXVNX7q+r/q6qHzTogwEgcMajPWWiCfm+S9yQ5Ick9k9w8yd5J7pjkmCR/mOQLVfVnVbX3eoUFmFcLzXvPGAy/ahZZAEbkBUkumKpfUlXHbuvgqto9yV8lecDU8PuSvHlN0gGM0/D3rNstc/5ix99jkTEAlma4kdBXljn/wkF9q6q6xQryAGx4u806AAAAwM6qqn2z9ROi/3EWWQDGpqr+V5JfX+Lh/5Lk6d39rTWMBDB6VbVbkr/JTdfe39ndfz/DSADz6qmDes8k+ya5U5KHJ/mdqjoryW9393vXOxzAiAxvYt47yb8lufUS5u6e5FeSHFlVP9Xd31jtcACbyHFJbj9VX53E9QSA7ejuS6vqkUlOz6QBeq8k76qqNyV5UyYPBb46k8+2RyY5KVs27P1rkuO7u9c1OMDGdu6gvn1VHdzdX1vi/CMXGdt/hZkANrMDBvWy7tvq7iur6pokN5sa3j/JZSsNBrBR2VkaAAAYsz9MctBUfXmSV84oC8A8emuSR3f3j3f3RbMOAzACL0hyv4V/X5Xkl2eYBWCzOyLJuxd2mq5ZhwHYoIY3252amxqlr0ry0iTHJjksyYOSnJjkQ4M5D0jy5oWd+gDYOScO6jd39+UzSQIwIt19QZIHJ/mlJGclqSRPTvKGJJ9J8sUkH03ystzUKP2dJL+b5KHdrUkEYEp3fzPJ5wfDT1/K3KraJ8kTF3lpv5XmAtjE9h3UV+/EOYZzrMvAXLOzNAAAMEpV9YQkzxkM/253XzqLPABz6jFJdq2qa7r7A7MOA7CRVdXhSf7r1NALF27WA2D1XJTk7Zns/nROkkuT/DDJrZI8MMlPJ3n01PGV5HcyeYD0b69rUoANrqr2TLLnYPjghf/+e5Ljuvurg9c/keTUqnp+kj+eGj8yyW8l+YO1yAowz6rqwCQ/Mxh+1SyyAIzUrgt/P0jSmVwL2JavJvm9JK/v7uvWIRvAGP1dkv82Vf9mVb1mCQ9X/29ZfBdpTXkAO2/YLH3NTpzj6iS32M45AeaKnaUBAIDRqar7JXnNYPjdSf5iBnEAxur3k9x56u/wJA9L8mtJ3rdwzO5JfirJ+6vqFVW16yyCAmx0VbVLJjcy39hs8n+S/OnsEgHMnX/NpAn6Dt39S939yu7+cHef092f7+6PdPcruvu4JP8pk52jpr2gqh637qkBNrZtfce/Ios3Sv+H7n5pkv85GP7PVeVGO4Dl+4VMrsPe6Pwk759RFoBRqaqjMnmY2l8kOSo7vif6DklOTfKVqnrWGscDGKtXZHJt4EYHJHlHVd1+WxOq6nlJnruNl3+4itkANrtepzkAo6VZGgAAGJWqumOSf86WT7i7MMnPd7cLOwBL1N2XdvcFU3/ndPeHFppMjsmkcfrCqSm/muSvZpMWYMP79SQPWfj39Ume1d03zDAPwFzp7rd397uX8r2/u8/KZE3+wuClP/LwH4CbdPf3s/gNyy/bXqP0lBdmy5unb5nkMauRDWCT+cVB/Td+7wLYsao6Jsl7kxwyNXxRkhckeUAmzX17JDkoyXFJTsvk2m2SHJjkr6vqr6pqeztRA2w63X15khMHw/dJck5VvaSqHllV96iq+1fVCVX1wSQvTXLjevq1wdzL1zgywDy7clDvtRPnGM4ZnhNgrmiWBgAARqOqbpPkPUmmn1b6zSQ/0d2XzCYVwHzq7g8leWSS70wNn2hHPoAtVdWhSf5gauhl3f2pWeUBYPJgoCRPy5ZPyz8sk8+3ANzkqkXGXrOUid19VZLTB8NHrzQQwGZSVQ9Jcq+poRuSvHo2aQDGo6oOTPK6JDebGv7fSQ7v7hd396e6+4ruvq67L+7ud3X3CZk8KHj6d69nJ/nNdQsOMBLdfXomDwqefsjafkl+I8n7kpyb5JNJTk3y0Klj/jTJGYPTaZYG2HmapQGWSbM0AAAwClV1y0yeDH33qeFvJzm2u784m1QA8627v5zk9wfDbhoBWLCw68hfJ9l7YehLSU6ZWSAA/kN3fyLJuwfDx80iC8AGNrxh+eLuvmAZ8z82qO+5sjgAm84zB/U7uvvrM0kCMC7Py2R36Budm+TJ3f3d7U3q7o8lecpg+OSFh7YDMKW7/zTJY5J8fgmHX5nkV5M8N1tugJFMNsEAYOdcMagPXPSobaiqfbN1s7SHWABzTbM0AACw4VXV/pnc4HyfqeHLMtlR+nOzSQWwabx+UD+kqg6YSRKAjefZSX58qj6pu6+eVRgAtvLOQX3fmaQA2Li+MKi/scz5w4a+W60gC8CmUlX7ZOuGvVfNIgvACD1pUL+4u69ZysTuPiPJB6eG9kry1NUKBjBPuvvdSe6V5Gcz+ax6TpJLk1yX5KIkH0ryX5Lcrbv/vLs7yWGD05y1fokB5s5wE6E7LXP+8PhLu/uyFeQB2PB2m3UAAACA7amq/TK5uflBU8PfTXJcd39qNqkANo/u/lZVXZbkFgtDuyS5c5JPzi4VwIbxoql/vz3JeVV1yA7mHDSod1tkzte7+9oVJQMgSS4Y1Mt64j7AJvC5JMdM1T9Y5vzh8TdbWRyATeVJSfabqi9O8rYZZQEYjYWHTdxlMHzGMk/z3iQPm6ofvKJQAHOsu29IcvrC33ZV1R2SHDw1dFF3X7RW2QA2gXMG9V2XOf/QQf3vK8gCMAqapQEAgA1r4YfOtyd5yNTwlUke093/OptUAJvSdYN6z5mkANh49pr6908m+fJOnOP2i8x7QBIPBgJYuasH9V6LHgWweX1mUB+wzPnD47+zgiwAm80zB/Vruvv6mSQBGJfFPrN+c5nnGB5/653MAsCWjhnUZ84iBMAcOXtQ37eq9u7u7y9x/lE7OB/A3Nll1gEAAAAWU1V7ZfIE/YdODX8/yU9190dmkwpg86mqm2Xrm0QunkUWAABYpuHn2G/PJAXAxvWOJD1VH7pwHWCp7j2ov7bySADzr6runi1//0qSV80iC8AIXb7I2D7LPMe+g/rKncwCwJaGDwR65UxSAMyJ7v5Gtnzg5W7Z+nrC9hw9qN+x0kwAG51maQAAYMNZuCHvrdnyYs01SR7b3R+YSSiAzeuYbHkN6ftJLppRFgAAWI4HD+qvzyQFwAbV3V9P8tGpod2z9S5Q23PcoP7gikMBbA4nDuoPdffnZ5IEYGS6+6ok3x0MP2CZp3nQoF7uztQADFTVQ7NlA9/nu/vMGcUBmCf/OKh/cSmTquqwbPk72VVJ3r1aoQA2Ks3SAADAhlJVeyQ5PcmxU8M/SPL47j5jNqkANqeq2iXJCwfD7+zua2eRB2Cj6e4DuruW85fkkYPTXLjIcZ+axf8PwDxZeBDbEwfDZ84gCsBGd+qgft5SJlXVw5L86NTQD5O8fbVCAcyrqto1yS8Mhu0qDbA8Zw7qX1rqxKo6KMljB8Me+gOwAlW1d5K/HAz/7iyyAMyh1ya5Yap+YlXdbQnzfmtQv6G7r1m9WAAbk2ZpAABgw6iq3ZK8IcljpoavS3J8d79rNqkAxq+qfq2qbrfMObtncpPecDe+P1u1YAAAsHZ+K8ntp+obkvzzjLIAbGSnJjlnqv7xqtpuw3RV3SZbN1m/obvPX+1wAHPoJ5NMX6v9XpI3zigLwFj9w6B+SlX9/I4mVdWeSf42yb5Tw1cmcS8CwJSF+7eWeuy+mVx3vdfU8Ju7+82rHgxgE+ruLyY5bWpojySvXnho8KKq6nFJTpgaujbJi9YkIMAGo1kaAADYEBaepP/aJI+bGr4+yVO6+22zSQUwN56Z5Pyq+ruq+pmq2m9bB1bVXlX1tCSfzJYXzpPkb7v7fWuYEwAAtlBVT6+q2y5zzrOTnDwYfnV3X7h6yQDmQ3ffkOTXM9kZ+kYvrao/qapbDI+vqmOTfDjJXaaGL0vyO2s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      "text/plain": [
       "<Figure size 4800x2700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# множественное присваивание, subplots() возвращает сразу 2 элемента\n",
    "\n",
    "fig, ax = plt.subplots(figsize = (16, 9), dpi = 300) \n",
    "ax.bar(df[\"title\"], df[\"value\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Неформально, создавая `fig` мы резервируем место под картинку соответствующего размера, а затем проводим различные манипуляции с `ax`, чтобы внутри этого поля для картинки построить график, настроить подписи, оси и прочее. Соответственно, к `ax` мы будем применять различные методы, а по завершении работы сможем выгрузить объект `fig` в файл PNG или JPEG. Вообще функция `subplots()`, как следует из ее названия, может использоваться для построения сразу нескольких графиков, но у нас пока внутри `fig` будет один."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Добавим сетку на график и зафиксируем, чтобы она не накладывалась поверх столбиков (`set_axisbelow()`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 4800x2700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize = (16, 9), dpi = 300) \n",
    "\n",
    "ax.bar(df[\"title\"], df[\"value\"])\n",
    "\n",
    "# color – цвет сетки\n",
    "# linestyle – тип линии\n",
    "# linewidth – толщина линии\n",
    "# alpha – прозрачность\n",
    "\n",
    "ax.set_axisbelow(True)\n",
    "ax.grid(b = True, color ='grey', linestyle = '-.', \n",
    "        linewidth = 0.5, alpha = 0.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Изменим цвета столбцов – создадим список, предполагая, что оценки от 1 до 3 должны быть отмечены темно-красным, оценки 4-5 – темно-оранжевым, оценки 6-7 – золотым и оценки 8-10 – темно-зеленым:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['darkred',\n",
       " 'darkred',\n",
       " 'darkred',\n",
       " 'darkorange',\n",
       " 'darkorange',\n",
       " 'gold',\n",
       " 'gold',\n",
       " 'darkcyan',\n",
       " 'darkcyan',\n",
       " 'darkcyan']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# список цветов\n",
    "\n",
    "cols = [\"darkred\"] * 3 + [\"darkorange\"] * 2 + [\"gold\"] * 2 + [\"darkcyan\"] * 3\n",
    "cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 4800x2700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize = (16, 9), dpi = 300) \n",
    "\n",
    "ax.bar(df[\"title\"], df[\"value\"], color = cols)\n",
    "ax.set_axisbelow(True)\n",
    "ax.grid(b = True, color ='grey', linestyle = '-.', \n",
    "        linewidth = 0.5, alpha = 0.4);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Цвета, конечно, пока не очень, но вдля начала неплохо :)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "График можно сохранить – выгрузить в файл:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig.savefig(\"ratings.png\")"
   ]
  }
 ],
 "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}