vander_plus_2_NumPy_3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "84c7719f",
   "metadata": {},
   "source": [
    "# Агрегирование: мин, макс и всё, что посередине"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "96b9f138",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "922753c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "L = np.random.random(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "745a8c87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.04 µs ± 56.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit sum(L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "de34d35a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.43 µs ± 36.5 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.sum(L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bfb9e837",
   "metadata": {},
   "outputs": [],
   "source": [
    "M = np.arange(1,10).reshape(3,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a6605ebb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 2, 3],\n",
       "       [4, 5, 6],\n",
       "       [7, 8, 9]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3145194c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(M)  # работает с многомерными массивами"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b7b30e35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([12, 15, 18])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(M)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a1929ecf",
   "metadata": {},
   "outputs": [],
   "source": [
    "big_array = np.random.rand(1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5c208208",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "44.9 ms ± 444 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit min(big_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c88d1f1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "378 µs ± 3.29 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.min(big_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e7f8f54b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "376 µs ± 2.32 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit big_array.min()  # min/max и т.д. как методы самого объекта массива"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "619ab598",
   "metadata": {},
   "source": [
    "### Многомерные агрегации (сводные показатели)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "48c1ba32",
   "metadata": {},
   "outputs": [],
   "source": [
    "M = np.random.random((5,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9835c292",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.59238255, 0.83315097, 0.23869727, 0.3965887 , 0.93358045],\n",
       "       [0.16620457, 0.1750463 , 0.33304747, 0.80604594, 0.13160616],\n",
       "       [0.97403574, 0.61134909, 0.10303118, 0.49714999, 0.45892873],\n",
       "       [0.45489607, 0.90780246, 0.75874638, 0.45928825, 0.48667763],\n",
       "       [0.10544564, 0.2988811 , 0.13790194, 0.68791736, 0.36727934]])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e314b3ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11.915681290121553"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "3184b628",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.29296456, 2.82622992, 1.57142424, 2.84699024, 2.37807232])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.sum(axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3525ae16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.99439994, 1.61195045, 2.64449474, 3.06741079, 1.59742538])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.sum(axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "71916516",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.10544564, 0.1750463 , 0.10303118, 0.3965887 , 0.13160616])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.min(axis = 0)  # по столбцам, axis - означает ось которая будет схлопнута"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fcb05cba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.23869727, 0.13160616, 0.10303118, 0.45489607, 0.10544564])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M.min(axis = 1)  # по строкам"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "744ad039",
   "metadata": {},
   "source": [
    "#### Существуют NaN безопасные эквиваленты агрегирующих ф-ий, игнорирующие эл-ты с пустыми значениями np.nansum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "23be0b07",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\"head\" не является внутренней или внешней\n",
      "командой, исполняемой программой или пакетным файлом.\n"
     ]
    }
   ],
   "source": [
    "!head -4 president_heights.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "77cdd0e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "26943ab2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('data/president_heights.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ac11bddc",
   "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>order</th>\n",
       "      <th>name</th>\n",
       "      <th>height(cm)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>George Washington</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>John Adams</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Thomas Jefferson</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>James Madison</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>James Monroe</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>John Quincy Adams</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Andrew Jackson</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Martin Van Buren</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>William Henry Harrison</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>John Tyler</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>James K. Polk</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Zachary Taylor</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Millard Fillmore</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Franklin Pierce</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>James Buchanan</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Abraham Lincoln</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Andrew Johnson</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Ulysses S. Grant</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Rutherford B. Hayes</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>James A. Garfield</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Chester A. Arthur</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>23</td>\n",
       "      <td>Benjamin Harrison</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>25</td>\n",
       "      <td>William McKinley</td>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>26</td>\n",
       "      <td>Theodore Roosevelt</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>27</td>\n",
       "      <td>William Howard Taft</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>28</td>\n",
       "      <td>Woodrow Wilson</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>29</td>\n",
       "      <td>Warren G. Harding</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>30</td>\n",
       "      <td>Calvin Coolidge</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>31</td>\n",
       "      <td>Herbert Hoover</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>32</td>\n",
       "      <td>Franklin D. Roosevelt</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>33</td>\n",
       "      <td>Harry S. Truman</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>34</td>\n",
       "      <td>Dwight D. Eisenhower</td>\n",
       "      <td>179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>35</td>\n",
       "      <td>John F. Kennedy</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>36</td>\n",
       "      <td>Lyndon B. Johnson</td>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>37</td>\n",
       "      <td>Richard Nixon</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>38</td>\n",
       "      <td>Gerald Ford</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>39</td>\n",
       "      <td>Jimmy Carter</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>40</td>\n",
       "      <td>Ronald Reagan</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>41</td>\n",
       "      <td>George H. W. Bush</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>42</td>\n",
       "      <td>Bill Clinton</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>43</td>\n",
       "      <td>George W. Bush</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>44</td>\n",
       "      <td>Barack Obama</td>\n",
       "      <td>185</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    order                    name  height(cm)\n",
       "0       1       George Washington         189\n",
       "1       2              John Adams         170\n",
       "2       3        Thomas Jefferson         189\n",
       "3       4           James Madison         163\n",
       "4       5            James Monroe         183\n",
       "5       6       John Quincy Adams         171\n",
       "6       7          Andrew Jackson         185\n",
       "7       8        Martin Van Buren         168\n",
       "8       9  William Henry Harrison         173\n",
       "9      10              John Tyler         183\n",
       "10     11           James K. Polk         173\n",
       "11     12          Zachary Taylor         173\n",
       "12     13        Millard Fillmore         175\n",
       "13     14         Franklin Pierce         178\n",
       "14     15          James Buchanan         183\n",
       "15     16         Abraham Lincoln         193\n",
       "16     17          Andrew Johnson         178\n",
       "17     18        Ulysses S. Grant         173\n",
       "18     19     Rutherford B. Hayes         174\n",
       "19     20       James A. Garfield         183\n",
       "20     21       Chester A. Arthur         183\n",
       "21     23       Benjamin Harrison         168\n",
       "22     25        William McKinley         170\n",
       "23     26      Theodore Roosevelt         178\n",
       "24     27     William Howard Taft         182\n",
       "25     28          Woodrow Wilson         180\n",
       "26     29       Warren G. Harding         183\n",
       "27     30         Calvin Coolidge         178\n",
       "28     31          Herbert Hoover         182\n",
       "29     32   Franklin D. Roosevelt         188\n",
       "30     33         Harry S. Truman         175\n",
       "31     34    Dwight D. Eisenhower         179\n",
       "32     35         John F. Kennedy         183\n",
       "33     36       Lyndon B. Johnson         193\n",
       "34     37           Richard Nixon         182\n",
       "35     38             Gerald Ford         183\n",
       "36     39            Jimmy Carter         177\n",
       "37     40           Ronald Reagan         185\n",
       "38     41       George H. W. Bush         188\n",
       "39     42            Bill Clinton         188\n",
       "40     43          George W. Bush         182\n",
       "41     44            Barack Obama         185"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4c5e7a2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "heights = np.array(data['height(cm)'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ded8406f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([189, 170, 189, 163, 183, 171, 185, 168, 173, 183, 173, 173, 175,\n",
       "       178, 183, 193, 178, 173, 174, 183, 183, 168, 170, 178, 182, 180,\n",
       "       183, 178, 182, 188, 175, 179, 183, 193, 182, 183, 177, 185, 188,\n",
       "       188, 182, 185], dtype=int64)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c90c69f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "179.73809523809524"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "6b41bd92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.931843442745892"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "2cb6619f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "193"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "9942eecd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "163"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heights.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c020b16a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "174.25\n",
      "182.0\n",
      "183.0\n"
     ]
    }
   ],
   "source": [
    "print(np.percentile(heights, 25))\n",
    "print(np.median(heights))\n",
    "print(np.percentile(heights, 75))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "16c29d5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn\n",
    "seaborn.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "90889fdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'number')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(heights)\n",
    "plt.title('Рост президентов')\n",
    "plt.xlabel('height(cm)')\n",
    "plt.ylabel('number')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed760027",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}