Функции и модули в Python - решение.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Модули и функции в python\n",
    "\n",
    "На втором занятии мы познакомимся еще с двумя базовыми конструкциями языка Python - модулями и функциями. Они потребуются нам завтра, когда мы будем обсуждать использование языка Python для решения задач машинного обучения."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Функции\n",
    "\n",
    "Функция задает алгоритм (последовательность шагов, операций с переменными), который можно повторять много раз для разных входных данных.\n",
    "\n",
    "Определение функции:\n",
    "* def NAME - задаем функцию с названием NAME.\n",
    "* def NAME(OP1, OP2) - входные данные функции, называемые аргументами функции; их может быть несколько, а может совсем не быть. На место этих переменных будут подставляться другие переменные.\n",
    "* def NAME(OP1, OP2, OP3=0) - аргумент OP3 по умолчанию равен 0 (можно использовать любые значения по умолчанию). Если при вызове (использовании) функции этот аргумент не задается, то используется значение по умолчанию, если задается - то значение, которое задано.\n",
    "\n",
    "Пример:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def repeat(s):\n",
    "    print(s*10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Эта функция печатает строку s, повторенную 10 раз. Пока что мы только определили функцию (задали ее логику). Чтобы выполнить эту логику, нужно вызвать функцию. Для этого надо написать имя функции и передать аргументы в круглых скобках:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!\n"
     ]
    }
   ],
   "source": [
    "repeat(\"Срочно!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Строка \"Срочно!\" подставилась в коде функции в переменную s. \n",
    "\n",
    "Добавим необязательный аргумент, отвечающий за число повторов:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def repeat(s, count=10):\n",
    "    print(s*count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Вызовем функцию, не указывая count, в этом случае функция работает так же, как раньше:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!\n"
     ]
    }
   ],
   "source": [
    "repeat(\"Срочно!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "А можно указать, сколько раз повторять:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!Срочно!\n"
     ]
    }
   ],
   "source": [
    "repeat(\"Срочно!\", 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "При вызове функции можно подставлять переменные в том же порядке, что в определении функции, а можно указывать их по именам - работает одинаково. Во втором случае можно менять порядок указывания аргументов:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Срочно!Срочно!Срочно!\n",
      "Срочно!Срочно!Срочно!\n"
     ]
    }
   ],
   "source": [
    "repeat(s=\"Срочно!\", count=3)\n",
    "repeat(count=3, s=\"Срочно!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Мы уже встречали функции: print() - это тоже функция, в которую можно передавать много аргументов для печати, \" \".join() - тоже функция."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Задачи\n",
    "\n",
    "#### Задача 1. Создание функции\n",
    "\n",
    "Напишите функцию, которая принимает число и печатает два числа: результат умножения входного числа на 10 и результат прибавления к входному числу 1. \n",
    "\n",
    "Например, для входа 5 получится 50, 6. \n",
    "\n",
    "Обратите внимание, что на данном этапе ячейка ничего печатать не должна."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def transform(x):\n",
    "    ### напишите Ваш код\n",
    "    print(x*10, x+1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Задача 2. Тестирование функции\n",
    "\n",
    "Вызовите функцию для входа, равного 5. Она должна печатать 50, 6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50 6\n"
     ]
    }
   ],
   "source": [
    "### напишите Ваш код\n",
    "transform(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Задача 3. Опциональные аргументы\n",
    "\n",
    "Добавьте два необязательных аргумента: на какое число умножать и какое число прибавлять. Теперь вместо двух 10 и 1 в функции будут присутствовать переменные a и b."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def transform(x, a=10, b=1):\n",
    "    ### напишите Ваш код\n",
    "    print(x*a, x+b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Задача 4. Тестирование функции с опциональными аргументами\n",
    "\n",
    "Вызовите функцию для входа, равного 10, чтобы она умножала его на 100 и прибавляла 5. Вам понадобится указать значения a и b.\n",
    "\n",
    "В итоге функция должна напечатать 1000, 15."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 15\n"
     ]
    }
   ],
   "source": [
    "### напишите Ваш код\n",
    "transform(10, a=100, b=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Задача 5. Функция, обрабатывающая список\n",
    "\n",
    "Напишите еще одну фнукцию, которая принимает на вход список чисел и обрабатывает его следующим образом: все числа больше 5 пропускаются, все остальные числа возводятся в квадрат и печатаются. Например, для входного списка [4, 1, 12, 14, 3] напечатается 16, 1, 9."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def strange_fun(xs):\n",
    "    ### напишите Ваш код\n",
    "    for x in xs:\n",
    "        if x <= 5:\n",
    "            print(x**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Протестируйте функцию:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16\n",
      "1\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "### your code here\n",
    "strange_fun([4, 1, 12, 14, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Модули\n",
    "\n",
    "Для языка python написано много готовых функций, которые реализуют различные алгоритмы. Эти функции хранятся в модулях. Команда импортирования (подключения) модуля:\n",
    "\n",
    "import MODULE\n",
    "\n",
    "Например, импортируем модуль для работы с математикой:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!pip install numpy\n",
    "import numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Мы можем вызывать его функции через точку: numpy.FUNCTION. Например, функция логарифм числа:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.log10(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Или квадратный корень:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.sqrt(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Функция случайного перемешивания списка:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 4, 3, 5, 1])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.random.permutation([1, 2, 3, 4, 5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Внутри функции задана процедура перемешивания, аналогично тому, как вы реализовали функции в заданиях выше."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Модули бывают для разных операций. Для примера рассмотрим модули рисования графиков и считывания данных в формате Excel."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Модуль Matplotlib для рисования графиков"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!pip install matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "# as plt - переименование модуля, чтобы использовать более короткое название\n",
    "%matplotlib inline\n",
    "# служебная команда, чтобы графики могли рисоваться в системе jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plt.plot - функция рисования графиков. В нее можно передать список значений для рисования:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x114947e10>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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sCNvEy3EJZSwxf2zMrIGZzTOzReXj+K8jbBPZ/HL3mPkD1Aa+AboA9YBFQK/D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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f52f4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1, 4, 9, 16])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "То же самое с заданием имени переменной:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x114a50390>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sCNvEy3EJZSwxf2zMrIGZzTOzReXj+K8jbBPZ/HL3mPkD1Aa+AboA9YBFQK/D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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11499d7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "values = [1, 4, 9, 16]\n",
    "plt.plot(values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Можно вызвать дополнительные функции для подписывания осей:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'квадрат x')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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C5K/eQoN6xmlHdmRMbjYn9s7QsE8RSQpBnBEcD1wFzDezLyP3/crdXw2glhpz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1149ce320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1, 4, 9, 16])\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"квадрат x\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Можно менять абсциссу:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'|x|')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Fe+bjbH5atZ0xQ3rTtVk9v+NIiNFgkJCVckZbBvdtyfOfLePr5Xl+x6kyPlq4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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114a97860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([-1, 0, 1], [1, 0, 1])\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"|x|\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "То же самое с переменными:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'|x|')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Fe+bjbH5atZ0xQ3rTtVk9v+NIiNFgkJCVckZbBvdtyfOfLePr5Xl+x6kyPlq4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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114bede48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = [-1, 0, 1]\n",
    "ys = [1, 0, 1]\n",
    "plt.plot(xs, ys)\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"|x|\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Задача 6. Построение графика\n",
    "\n",
    "Нарисуйте график функции $y=x^2$ для точек от -10 до 10 с шагом 1. \n",
    "\n",
    "Совет: воспользуйтесь циклом! Переберите x из range(-10, 11). Возведение в квадрат задается операцией **\n",
    "\n",
    "Задать пустой список: xs = [ ], добавить элемент в список: xs.append(10)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x114d12898>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JxhY97VJBXVML817Opqq+mRfmZtE3Uk+j9DQOFb2IBGIr+UXGmHfsd5eKSKL9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\nWCX2OQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114cb99b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### напишите Ваш код\n",
    "xs = []\n",
    "ys = []\n",
    "for x in range(-10, 11):\n",
    "    xs.append(x)\n",
    "    ys.append(x**2)\n",
    "plt.plot(xs, ys)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Модуль считывания данных в разных форматах"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!pip install pandas\n",
    "!pip install xlrd\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Функция считывания данных в формате Excel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = pd.read_excel(\"scoring.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Выведем первые 10 строк таблицы:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account</th>\n",
       "      <th>duration</th>\n",
       "      <th>credit_history</th>\n",
       "      <th>amount</th>\n",
       "      <th>savings</th>\n",
       "      <th>employment</th>\n",
       "      <th>guarantors</th>\n",
       "      <th>residence</th>\n",
       "      <th>age</th>\n",
       "      <th>credits_number</th>\n",
       "      <th>...</th>\n",
       "      <th>maintenance_people</th>\n",
       "      <th>telephone</th>\n",
       "      <th>foreign</th>\n",
       "      <th>real_estate</th>\n",
       "      <th>life_insurance</th>\n",
       "      <th>car</th>\n",
       "      <th>housing_rent</th>\n",
       "      <th>sex</th>\n",
       "      <th>purpose</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.18</td>\n",
       "      <td>2</td>\n",
       "      <td>0.13110</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "      <td>4</td>\n",
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       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>business</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.15520</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>business</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1</td>\n",
       "      <td>0.12</td>\n",
       "      <td>2</td>\n",
       "      <td>0.04510</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0.21</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>retraining</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0</td>\n",
       "      <td>0.40360</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.25</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>business</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>2</td>\n",
       "      <td>0.09095</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>education</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>3</td>\n",
       "      <td>0.10320</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.34</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>furniture</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>0.09</td>\n",
       "      <td>4</td>\n",
       "      <td>0.07505</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0.34</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>education</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-1</td>\n",
       "      <td>0.12</td>\n",
       "      <td>2</td>\n",
       "      <td>0.04500</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>car_new</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>0.36</td>\n",
       "      <td>3</td>\n",
       "      <td>0.40430</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0.42</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>car_new</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-1</td>\n",
       "      <td>0.42</td>\n",
       "      <td>3</td>\n",
       "      <td>0.21850</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>television</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   account  duration  credit_history   amount  savings  employment  \\\n",
       "0        1      0.18               2  0.13110        2           2   \n",
       "1       -1      0.18               0  0.15520        1           3   \n",
       "2       -1      0.12               2  0.04510        1           3   \n",
       "3       -1      0.30               0  0.40360        0           1   \n",
       "4        0      0.36               2  0.09095        1           2   \n",
       "5        1      0.24               3  0.10320        1           0   \n",
       "6        1      0.09               4  0.07505        1           4   \n",
       "7       -1      0.12               2  0.04500        0           2   \n",
       "8        1      0.36               3  0.40430        2           4   \n",
       "9       -1      0.42               3  0.21850        1           3   \n",
       "\n",
       "   guarantors  residence   age  credits_number  ...    maintenance_people  \\\n",
       "0           1          4  0.34               1  ...                     1   \n",
       "1           1          1  0.31               1  ...                     1   \n",
       "2           1          4  0.21               1  ...                     1   \n",
       "3           1          3  0.25               3  ...                     1   \n",
       "4           1          4  0.37               1  ...                     1   \n",
       "5           1          2  0.34               1  ...                     1   \n",
       "6           1          3  0.34               2  ...                     1   \n",
       "7           1          2  0.23               1  ...                     1   \n",
       "8           1          4  0.42               4  ...                     1   \n",
       "9           1          2  0.26               2  ...                     2   \n",
       "\n",
       "   telephone  foreign  real_estate  life_insurance  car  housing_rent  sex  \\\n",
       "0          0        1            0               0    1             0    1   \n",
       "1          1        1            0               1    0             0    1   \n",
       "2          0        1            0               1    0             1    1   \n",
       "3          0        1            0               0    1             0    1   \n",
       "4          1        1            0               0    0             0    1   \n",
       "5          1        1            0               1    0             0    0   \n",
       "6          1        1            0               0    1             0    0   \n",
       "7          0        1            0               0    1             0    1   \n",
       "8          1        1            0               0    1             0    1   \n",
       "9          1        1            0               1    0             0    1   \n",
       "\n",
       "      purpose target  \n",
       "0    business      1  \n",
       "1    business      1  \n",
       "2  retraining      0  \n",
       "3    business      1  \n",
       "4   education      0  \n",
       "5   furniture      0  \n",
       "6   education      0  \n",
       "7     car_new      0  \n",
       "8     car_new      0  \n",
       "9  television      0  \n",
       "\n",
       "[10 rows x 21 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В Pandas можно и создавать Excel-файлы. Сначала создадим таблицу. Для этого нам понадобятся списки, а также еще одна структура данных - словарь. Он задается в фигурных скобках, и в нем могут храниться данные с ключами-именами:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "my_table_data = {\"index\":[1, 2, 3, 4, 5], \\\n",
    "            \"name\":[\"Maria\", \"Fedor\", \"Yulia\", \"Petr\", \"Ruslan\"],\\\n",
    "           \"age\":[10, 7, 8, 11, 4]}\n",
    "my_table = pd.DataFrame(my_table_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>index</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>Maria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>Fedor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>Yulia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11</td>\n",
       "      <td>4</td>\n",
       "      <td>Petr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Ruslan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age  index    name\n",
       "0   10      1   Maria\n",
       "1    7      2   Fedor\n",
       "2    8      3   Yulia\n",
       "3   11      4    Petr\n",
       "4    4      5  Ruslan"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Сохраним в Excel:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "my_table.to_excel(\"Таблица Дети.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Задание: создайте таблицу с колонками \"x\" и \"x2\". В первой колонке хранятся числа от -10 до 10, во второй - их квадраты. Сохраните таблицу в Excel. Используйте переменные, которые вы создали в задании по Matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### напишите Ваш код\n",
    "my_table_data = {\"x\":xs, \"x2\":ys}\n",
    "my_table = pd.DataFrame(my_table_data)\n",
    "my_table.to_excel(\"Таблица квадратов.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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