hw01-2.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Задание 1\n",
        "Импортируйте библиотеку Pandas и дайте ей псевдоним pd.\n",
        "Создайте датафрейм authors со столбцами author_id и author_name,\n",
        "в которых соответственно содержатся данные:\n",
        "[1, 2, 3] и ['Тургенев', 'Чехов', 'Островский'].\n",
        "\n",
        "Затем создайте датафрейм book cо столбцами author_id, book_title и price,\n",
        "в которых соответственно содержатся данные:\n",
        "[1, 1, 1, 2, 2, 3, 3],\n",
        "['Отцы и дети', 'Рудин', 'Дворянское гнездо', 'Толстый и тонкий', 'Дама с собачкой', 'Гроза', 'Таланты и поклонники'],\n",
        "[450, 300, 350, 500, 450, 370, 290]."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "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>author_id</th>\n",
              "      <th>author_name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   author_id author_name\n",
              "0          1    Тургенев\n",
              "1          2       Чехов\n",
              "2          3  Островский"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "authors = pd.DataFrame({'author_id': [1, 2, 3], \n",
        "                        'author_name': ['Тургенев', 'Чехов', 'Островский']})\n",
        "authors"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>author_id</th>\n",
              "      <th>book_title</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Отцы и дети</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Рудин</td>\n",
              "      <td>300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Дворянское гнездо</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>Толстый и тонкий</td>\n",
              "      <td>500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Дама с собачкой</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3</td>\n",
              "      <td>Гроза</td>\n",
              "      <td>370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>3</td>\n",
              "      <td>Таланты и поклонники</td>\n",
              "      <td>290</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   author_id            book_title  price\n",
              "0          1           Отцы и дети    450\n",
              "1          1                 Рудин    300\n",
              "2          1     Дворянское гнездо    350\n",
              "3          2      Толстый и тонкий    500\n",
              "4          2       Дама с собачкой    450\n",
              "5          3                 Гроза    370\n",
              "6          3  Таланты и поклонники    290"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "book = pd.DataFrame({'author_id': [1, 1, 1, 2, 2, 3, 3], \n",
        "                     'book_title': ['Отцы и дети', 'Рудин', 'Дворянское гнездо',\n",
        "                                    'Толстый и тонкий', 'Дама с собачкой',\n",
        "                                    'Гроза', 'Таланты и поклонники'], \n",
        "                     'price': [450, 300, 350, 500, 450, 370, 290]})\n",
        "book"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Задание 2\n",
        "Получите датафрейм authors_price, соединив датафреймы authors и books по полю author_id."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "data": {
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              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\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>author_id</th>\n",
              "      <th>author_name</th>\n",
              "      <th>book_title</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Отцы и дети</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Рудин</td>\n",
              "      <td>300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Дворянское гнездо</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Толстый и тонкий</td>\n",
              "      <td>500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Дама с собачкой</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "      <td>Гроза</td>\n",
              "      <td>370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "      <td>Таланты и поклонники</td>\n",
              "      <td>290</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   author_id author_name            book_title  price\n",
              "0          1    Тургенев           Отцы и дети    450\n",
              "1          1    Тургенев                 Рудин    300\n",
              "2          1    Тургенев     Дворянское гнездо    350\n",
              "3          2       Чехов      Толстый и тонкий    500\n",
              "4          2       Чехов       Дама с собачкой    450\n",
              "5          3  Островский                 Гроза    370\n",
              "6          3  Островский  Таланты и поклонники    290"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "authors_price = pd.merge(authors, book, on='author_id', how='inner')\n",
        "authors_price"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Задание 3\n",
        "Создайте датафрейм top5, в котором содержатся строки из authors_price\n",
        "с пятью самыми дорогими книгами."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\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>index</th>\n",
              "      <th>author_id</th>\n",
              "      <th>author_name</th>\n",
              "      <th>book_title</th>\n",
              "      <th>price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Толстый и тонкий</td>\n",
              "      <td>500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Отцы и дети</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Дама с собачкой</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "      <td>Гроза</td>\n",
              "      <td>370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Дворянское гнездо</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  author_id author_name         book_title  price\n",
              "0      3          2       Чехов   Толстый и тонкий    500\n",
              "1      0          1    Тургенев        Отцы и дети    450\n",
              "2      4          2       Чехов    Дама с собачкой    450\n",
              "3      5          3  Островский              Гроза    370\n",
              "4      2          1    Тургенев  Дворянское гнездо    350"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "top5 = authors_price.sort_values('price', ascending=False).head()\n",
        "top5.reset_index(inplace=True)\n",
        "top5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Задание 4\n",
        "Создайте датафрейм authors_stat на основе информации из authors_price.\n",
        "В датафрейме authors_stat должны быть четыре столбца:\n",
        "author_name, min_price, max_price и mean_price,\n",
        "в которых должны содержаться соответственно имя автора,\n",
        "минимальная, максимальная и средняя цена на книги этого автора."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>author_name</th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
              "      <th>mean</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Островский</td>\n",
              "      <td>290</td>\n",
              "      <td>370</td>\n",
              "      <td>330.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Тургенев</td>\n",
              "      <td>300</td>\n",
              "      <td>450</td>\n",
              "      <td>366.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Чехов</td>\n",
              "      <td>450</td>\n",
              "      <td>500</td>\n",
              "      <td>475.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  author_name  min  max        mean\n",
              "0  Островский  290  370  330.000000\n",
              "1    Тургенев  300  450  366.666667\n",
              "2       Чехов  450  500  475.000000"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "authors_stat = authors_price.groupby('author_name')['price'].agg(['min',\n",
        "                                                                  'max',\n",
        "                                                                  'mean'])\n",
        "\n",
        "authors_stat.reset_index(inplace=True)\n",
        "authors_stat"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Задание 5*\n",
        "Создайте новый столбец в датафрейме authors_price под названием cover,\n",
        "в нем будут располагаться данные о том, какая обложка у данной книги - твердая или мягкая.\n",
        "В этот столбец поместите данные из следующего списка:\n",
        "['твердая', 'мягкая', 'мягкая', 'твердая', 'твердая', 'мягкая', 'мягкая'].\n",
        "Просмотрите документацию по функции pd.pivot_table\n",
        "с помощью вопросительного знака.\n",
        "\n",
        "Для каждого автора посчитайте суммарную стоимость книг в твердой и мягкой обложке.\n",
        "Используйте для этого функцию pd.pivot_table.\n",
        "При этом столбцы должны называться \"твердая\" и \"мягкая\",\n",
        "а индексами должны быть фамилии авторов. Пропущенные значения стоимостей заполните нулями,\n",
        "при необходимости загрузите библиотеку Numpy.\n",
        "\n",
        "Назовите полученный датасет book_info и сохраните его в формат pickle под названием \"book_info.pkl\".\n",
        "Затем загрузите из этого файла датафрейм и назовите его book_info2.\n",
        "Удостоверьтесь, что датафреймы book_info и book_info2 идентичны."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>author_id</th>\n",
              "      <th>author_name</th>\n",
              "      <th>book_title</th>\n",
              "      <th>price</th>\n",
              "      <th>cover</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Отцы и дети</td>\n",
              "      <td>450</td>\n",
              "      <td>твердая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Рудин</td>\n",
              "      <td>300</td>\n",
              "      <td>мягкая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>Тургенев</td>\n",
              "      <td>Дворянское гнездо</td>\n",
              "      <td>350</td>\n",
              "      <td>мягкая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Толстый и тонкий</td>\n",
              "      <td>500</td>\n",
              "      <td>твердая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2</td>\n",
              "      <td>Чехов</td>\n",
              "      <td>Дама с собачкой</td>\n",
              "      <td>450</td>\n",
              "      <td>твердая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "      <td>Гроза</td>\n",
              "      <td>370</td>\n",
              "      <td>мягкая</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>3</td>\n",
              "      <td>Островский</td>\n",
              "      <td>Таланты и поклонники</td>\n",
              "      <td>290</td>\n",
              "      <td>мягкая</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   author_id author_name            book_title  price    cover\n",
              "0          1    Тургенев           Отцы и дети    450  твердая\n",
              "1          1    Тургенев                 Рудин    300   мягкая\n",
              "2          1    Тургенев     Дворянское гнездо    350   мягкая\n",
              "3          2       Чехов      Толстый и тонкий    500  твердая\n",
              "4          2       Чехов       Дама с собачкой    450  твердая\n",
              "5          3  Островский                 Гроза    370   мягкая\n",
              "6          3  Островский  Таланты и поклонники    290   мягкая"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "cover = pd.DataFrame({'cover': ['твердая', 'мягкая', 'мягкая', 'твердая', \n",
        "                                'твердая', 'мягкая', 'мягкая']})\n",
        "\n",
        "authors_price = pd.concat([authors_price, cover], axis=1)\n",
        "authors_price"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<function pandas.core.reshape.pivot.pivot_table(data: 'DataFrame', values=None, index=None, columns=None, aggfunc: 'AggFuncType' = 'mean', fill_value=None, margins: 'bool' = False, dropna: 'bool' = True, margins_name: 'str' = 'All', observed: 'bool' = False, sort: 'bool' = True) -> 'DataFrame'>"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "pd.pivot_table"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "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>cover</th>\n",
              "      <th>мягкая</th>\n",
              "      <th>твердая</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>author_name</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Островский</th>\n",
              "      <td>660</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Тургенев</th>\n",
              "      <td>650</td>\n",
              "      <td>450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Чехов</th>\n",
              "      <td>0</td>\n",
              "      <td>950</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "cover        мягкая  твердая\n",
              "author_name                 \n",
              "Островский      660        0\n",
              "Тургенев        650      450\n",
              "Чехов             0      950"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "book_info = pd.pivot_table(authors_price, values='price', index='author_name', \n",
        "                           columns='cover', fill_value=0, aggfunc=sum)\n",
        "book_info"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [],
      "source": [
        "book_info.to_pickle('BookInfo.PKL')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [],
      "source": [
        "book_info2 = pd.read_pickle('BookInfo.PKL')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "book_info2.equals(book_info)"
      ]
    }
  ],
  "metadata": {
    "kernel_info": {
      "name": "python3"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
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      "pygments_lexer": "ipython3",
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