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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a29a5a6c",
+   "metadata": {},
+   "source": [
+    "## Вычисления с помощью Numpy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5540cd2a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "989e9b52",
+   "metadata": {},
+   "source": [
+    "### Задание 1\n",
+    "Создайте массив Numpy под названием a размером 5x2, то есть состоящий из 5 строк\n",
+    "и 2 столбцов. Первый столбец должен содержать числа 1, 2, 3, 3, 1, а второй - числа 6,\n",
+    "8, 11, 10, 7. Будем считать, что каждый столбец - это признак, а строка - наблюдение.\n",
+    "Затем найдите среднее значение по каждому признаку, используя метод mean массива\n",
+    "Numpy. Результат запишите в массив mean_a, в нем должно быть 2 элемента."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5297f2b9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2.  8.4]\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = np.array([[1, 6], \n",
+    "              [2, 8], \n",
+    "              [3, 11],\n",
+    "              [3, 10],\n",
+    "              [1, 7]])\n",
+    "\n",
+    "mean_a = a.mean(axis=0)\n",
+    "\n",
+    "print(mean_a)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d1d4dec2",
+   "metadata": {},
+   "source": [
+    "### Задание 2\n",
+    "Вычислите массив a_centered, отняв от значений массива “а” средние значения\n",
+    "соответствующих признаков, содержащиеся в массиве mean_a. Вычисление должно\n",
+    "производиться в одно действие. Получившийся массив должен иметь размер 5x2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6941d9be",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[-1.  -2.4]\n",
+      " [ 0.  -0.4]\n",
+      " [ 1.   2.6]\n",
+      " [ 1.   1.6]\n",
+      " [-1.  -1.4]]\n",
+      "размер a_centered = (5, 2)\n"
+     ]
+    }
+   ],
+   "source": [
+    "a_centered = a - mean_a\n",
+    "\n",
+    "print(a_centered)\n",
+    "\n",
+    "print(f\"размер a_centered = {a_centered.shape}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da150013",
+   "metadata": {},
+   "source": [
+    "### Задание 3\n",
+    "Найдите скалярное произведение столбцов массива a_centered. В результате должна\n",
+    "получиться величина a_centered_spa. Затем поделите a_centered_sp на N-1, где N - число\n",
+    "наблюдений."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f5bf6a6d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ковариация несмещенная 2.0<=>2.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "a_centered_spa = a_centered[:, 0].dot(a_centered[:, 1])\n",
+    "a_centered_cov = a_centered_spa / (a_centered.shape[0] - 1)\n",
+    "\n",
+    "print(f\"ковариация несмещенная {a_centered_cov}<=>{np.cov(a.T)[0, 1]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0f8958b9",
+   "metadata": {},
+   "source": [
+    "## Тема “Работа с данными в Pandas”"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "df1f7fce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "121ad442",
+   "metadata": {},
+   "source": [
+    "### Задание 1\n",
+    "Импортируйте библиотеку Pandas и дайте ей псевдоним pd. Создайте датафрейм authors со\n",
+    "столбцами author_id и author_name, в которых соответственно содержатся данные: [1, 2, 3] и\n",
+    "['Тургенев', 'Чехов', 'Островский'].\n",
+    "Затем создайте датафрейм book cо столбцами author_id, book_title и price, в которых соответственно\n",
+    "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\n",
+    "поклонники']\n",
+    "Нужны prices!\n",
+    "[500, 400, 300, 350, 450, 600, 200]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "bc25aa3e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "authors = pd.DataFrame({\n",
+    "    \"author_id\": [1, 2, 3],\n",
+    "    \"author_name\": ['Тургенев', 'Чехов', 'Островский']\n",
+    "})\n",
+    "\n",
+    "books = pd.DataFrame({\n",
+    "    \"author_id\":[1, 1, 1, 2, 2, 3, 3],\n",
+    "    \"book_title\":['Отцы и дети', 'Рудин', 'Дворянское гнездо', 'Толстый и тонкий', 'Дама с собачкой', 'Гроза', \n",
+    "                  'Таланты и поклонники'],\n",
+    "    \"price\":[500, 400, 300, 350, 450, 600, 200]\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b8921adc",
+   "metadata": {},
+   "source": [
+    "### Задание 2\n",
+    "Получите датафрейм authors_price, соединив дата фреймы authors и books по полю author_id."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "055b608b",
+   "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",
+       "      <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>500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Тургенев</td>\n",
+       "      <td>Рудин</td>\n",
+       "      <td>400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Тургенев</td>\n",
+       "      <td>Дворянское гнездо</td>\n",
+       "      <td>300</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>350</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>600</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>200</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    500\n",
+       "1          1    Тургенев                 Рудин    400\n",
+       "2          1    Тургенев     Дворянское гнездо    300\n",
+       "3          2       Чехов      Толстый и тонкий    350\n",
+       "4          2       Чехов       Дама с собачкой    450\n",
+       "5          3  Островский                 Гроза    600\n",
+       "6          3  Островский  Таланты и поклонники    200"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "authors_price = pd.merge(authors, books, on='author_id', how='inner')\n",
+    "authors_price"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e5b969c6",
+   "metadata": {},
+   "source": [
+    "### Задание 3\n",
+    "Создайте датафрейм top5, в котором содержатся строки из authors_price с пятью самыми дорогими\n",
+    "книгами."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3a8c545d",
+   "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",
+       "      <th>book_title</th>\n",
+       "      <th>price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Островский</td>\n",
+       "      <td>Гроза</td>\n",
+       "      <td>600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Тургенев</td>\n",
+       "      <td>Отцы и дети</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>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Тургенев</td>\n",
+       "      <td>Рудин</td>\n",
+       "      <td>400</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>350</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   author_id author_name        book_title  price\n",
+       "5          3  Островский             Гроза    600\n",
+       "0          1    Тургенев       Отцы и дети    500\n",
+       "4          2       Чехов   Дама с собачкой    450\n",
+       "1          1    Тургенев             Рудин    400\n",
+       "3          2       Чехов  Толстый и тонкий    350"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "top5 = authors_price.sort_values(by=\"price\", ascending=False, inplace=False).head(5)\n",
+    "top5"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4665003",
+   "metadata": {},
+   "source": [
+    "### Задание 4\n",
+    "Создайте датафрейм authors_stat на основе информации из authors_price. В датафрейме authors_stat\n",
+    "должны быть четыре столбца:\n",
+    "author_name, min_price, max_price и mean_price,\n",
+    "в которых должны содержаться соответственно имя автора, минимальная, максимальная и средняя\n",
+    "цена на книги этого автора."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "865c8fb1",
+   "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 tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"3\" halign=\"left\">price</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>max</th>\n",
+       "      <th>min</th>\n",
+       "      <th>mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>author_name</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Островский</th>\n",
+       "      <td>600</td>\n",
+       "      <td>200</td>\n",
+       "      <td>400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Тургенев</th>\n",
+       "      <td>500</td>\n",
+       "      <td>300</td>\n",
+       "      <td>400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Чехов</th>\n",
+       "      <td>450</td>\n",
+       "      <td>350</td>\n",
+       "      <td>400</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            price          \n",
+       "              max  min mean\n",
+       "author_name                \n",
+       "Островский    600  200  400\n",
+       "Тургенев      500  300  400\n",
+       "Чехов         450  350  400"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "authors_stat = authors_price.groupby(\"author_name\").agg({\"price\": [\"max\", \"min\", \"mean\"]})\n",
+    "authors_stat"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea69f20e",
+   "metadata": {},
+   "source": [
+    "### Задание 5**\n",
+    "Создайте новый столбец в датафрейме authors_price под названием cover, в нем будут располагаться\n",
+    "данные о том, какая обложка у данной книги - твердая или мягкая. В этот столбец поместите данные\n",
+    "из следующего списка:\n",
+    "['твердая', 'мягкая', 'мягкая', 'твердая', 'твердая', 'мягкая', 'мягкая'].\n",
+    "Просмотрите документацию по функции pd.pivot table с помощью вопросительного знака.\n",
+    "Для каждого автора посчитайте суммарную стоимость книг в твердой и мягкой обложке. Используйте\n",
+    "для этого функцию pd.pivot_table. При этом столбцы должны называться \"твердая\" и \"мягкая\", а\n",
+    "индексами должны быть фамилии авторов. Пропущенные значения стоимостей заполните нулями,\n",
+    "при необходимости загрузите библиотеку Numpy.\n",
+    "Назовите полученный датасет book_info и сохраните его в формат pickle под названием\n",
+    "\"book_info.pkl\". Затем загрузите из этого файла датафрейм и назовите его book_info2. Удостоверьтесь,\n",
+    "что датафреймы book_info и book_info2 идентичны."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "30443e0e",
+   "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",
+       "      <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>500</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>400</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>300</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>350</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>600</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>200</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    500  твердая\n",
+       "1          1    Тургенев                 Рудин    400   мягкая\n",
+       "2          1    Тургенев     Дворянское гнездо    300   мягкая\n",
+       "3          2       Чехов      Толстый и тонкий    350  твердая\n",
+       "4          2       Чехов       Дама с собачкой    450  твердая\n",
+       "5          3  Островский                 Гроза    600   мягкая\n",
+       "6          3  Островский  Таланты и поклонники    200   мягкая"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "authors_price[\"cover\"] = ['твердая', 'мягкая', 'мягкая', 'твердая', 'твердая', 'мягкая', 'мягкая']\n",
+    "authors_price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "30648b97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "?pd.pivot_table"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "1d3cf0a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "book_info = pd.pivot_table(authors_price, values=\"price\", index=\"author_name\", columns=\"cover\", aggfunc=\"sum\")\n",
+    "book_info.fillna(0, inplace = True)\n",
+    "book_info.to_pickle(\"book_info.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "c318cc60",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "book_info2 = pd.read_pickle(\"book_info.pkl\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "d541b4d0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(cover        мягкая  твердая\n",
+       " author_name                 \n",
+       " Островский    800.0      0.0\n",
+       " Тургенев      700.0    500.0\n",
+       " Чехов           0.0    800.0,\n",
+       " cover        мягкая  твердая\n",
+       " author_name                 \n",
+       " Островский    800.0      0.0\n",
+       " Тургенев      700.0    500.0\n",
+       " Чехов           0.0    800.0)"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "book_info, book_info2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17c5d95f",
+   "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": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}