scripts/tema1/06-Functions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Funciones en Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def suma(x, y):\n",
    "    return x+y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Operaciones(object):\n",
    "    def suma(self, x, y):\n",
    "        self.resultado = x+y\n",
    "        return self.resultado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "operInstance = Operaciones()\n",
    "operInstance.suma(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def saludar():\n",
    "    name = str(input(\"Introduce tu nombre: \"))\n",
    "    if name:\n",
    "        print(\"Hola \"+name)\n",
    "    else:\n",
    "        print(\"Hola, estoy programando!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Introduce tu nombre: Juan Gabriel\n",
      "Hola Juan Gabriel\n"
     ]
    }
   ],
   "source": [
    "saludar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(2,3)*5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def buscaPares():\n",
    "    for x in range(10):\n",
    "        if x % 2 == 0:\n",
    "            return\n",
    "    print(\"Fin de la ejecución\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "buscaPares()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sumaresta(x,y=0):\n",
    "    suma = x+y\n",
    "    resta = x-y\n",
    "    return (suma, resta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, -1)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sumaresta(x=2,y=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 5)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sumaresta(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def suma(*args):\n",
    "    return sum(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(1,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(1,2,3,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(1,2,3,4,5,6,7,8,9,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sumacuadrados(*datos):\n",
    "    total = 0\n",
    "    for d in datos:\n",
    "        total += d**2\n",
    "    return total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sumacuadrados(1,2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "262.9489"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sumacuadrados(2.5, 3.6, 8.9, -2, 12.67)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sumacuadrados2(1,2,3,4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Funciones anónimas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "doble = lambda x: x*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doble(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "cuadrado = lambda x: x**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cuadrado(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "suma = lambda x, y: x+y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "suma(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [1,2,3,4,5,6,7,8,9,10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_data = list(filter(lambda x: (x*2>8), data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[5, 6, 7, 8, 9, 10]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapped_data = list(map(lambda x: x*2, data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 4, 6, 8, 10, 12, 14, 16, 18, 20]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mapped_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "reduced_data = reduce(lambda x, y: x+y, data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reduced_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"../../data/bodyfat.txt\", delimiter=\" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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>Density</th>\n",
       "      <th>Fat</th>\n",
       "      <th>Age</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Height</th>\n",
       "      <th>Neck</th>\n",
       "      <th>Chest</th>\n",
       "      <th>Abdomen</th>\n",
       "      <th>Hip</th>\n",
       "      <th>Thigh</th>\n",
       "      <th>Knee</th>\n",
       "      <th>Ankle</th>\n",
       "      <th>Biceps</th>\n",
       "      <th>Forearm</th>\n",
       "      <th>Wrist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0708</td>\n",
       "      <td>12.3</td>\n",
       "      <td>23</td>\n",
       "      <td>154.25</td>\n",
       "      <td>67.75</td>\n",
       "      <td>36.2</td>\n",
       "      <td>93.1</td>\n",
       "      <td>85.2</td>\n",
       "      <td>94.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>37.3</td>\n",
       "      <td>21.9</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.4</td>\n",
       "      <td>17.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0853</td>\n",
       "      <td>6.1</td>\n",
       "      <td>22</td>\n",
       "      <td>173.25</td>\n",
       "      <td>72.25</td>\n",
       "      <td>38.5</td>\n",
       "      <td>93.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>98.7</td>\n",
       "      <td>58.7</td>\n",
       "      <td>37.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>30.5</td>\n",
       "      <td>28.9</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0414</td>\n",
       "      <td>25.3</td>\n",
       "      <td>22</td>\n",
       "      <td>154.00</td>\n",
       "      <td>66.25</td>\n",
       "      <td>34.0</td>\n",
       "      <td>95.8</td>\n",
       "      <td>87.9</td>\n",
       "      <td>99.2</td>\n",
       "      <td>59.6</td>\n",
       "      <td>38.9</td>\n",
       "      <td>24.0</td>\n",
       "      <td>28.8</td>\n",
       "      <td>25.2</td>\n",
       "      <td>16.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0751</td>\n",
       "      <td>10.4</td>\n",
       "      <td>26</td>\n",
       "      <td>184.75</td>\n",
       "      <td>72.25</td>\n",
       "      <td>37.4</td>\n",
       "      <td>101.8</td>\n",
       "      <td>86.4</td>\n",
       "      <td>101.2</td>\n",
       "      <td>60.1</td>\n",
       "      <td>37.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>32.4</td>\n",
       "      <td>29.4</td>\n",
       "      <td>18.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.0340</td>\n",
       "      <td>28.7</td>\n",
       "      <td>24</td>\n",
       "      <td>184.25</td>\n",
       "      <td>71.25</td>\n",
       "      <td>34.4</td>\n",
       "      <td>97.3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>101.9</td>\n",
       "      <td>63.2</td>\n",
       "      <td>42.2</td>\n",
       "      <td>24.0</td>\n",
       "      <td>32.2</td>\n",
       "      <td>27.7</td>\n",
       "      <td>17.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Density   Fat  Age  Weight  Height  Neck  Chest  Abdomen    Hip  Thigh  \\\n",
       "1   1.0708  12.3   23  154.25   67.75  36.2   93.1     85.2   94.5   59.0   \n",
       "2   1.0853   6.1   22  173.25   72.25  38.5   93.6     83.0   98.7   58.7   \n",
       "3   1.0414  25.3   22  154.00   66.25  34.0   95.8     87.9   99.2   59.6   \n",
       "4   1.0751  10.4   26  184.75   72.25  37.4  101.8     86.4  101.2   60.1   \n",
       "5   1.0340  28.7   24  184.25   71.25  34.4   97.3    100.0  101.9   63.2   \n",
       "\n",
       "   Knee  Ankle  Biceps  Forearm  Wrist  \n",
       "1  37.3   21.9    32.0     27.4   17.1  \n",
       "2  37.3   23.4    30.5     28.9   18.2  \n",
       "3  38.9   24.0    28.8     25.2   16.6  \n",
       "4  37.3   22.8    32.4     29.4   18.2  \n",
       "5  42.2   24.0    32.2     27.7   17.7  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1  2200  51.0  1128  70.9  7  0.25  54.8  1720</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>8  1450  51.4  997  73.4  7  0.10  55.2  1454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>8  1200  49.8  991  70.8  6  0.15  54.6  1475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>8  1425  50.0  928  70.8  6  0.10  53.9  1375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>8  1250  50.1  990  71.0  6  0.10  54.9  1564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>8  1500  51.7  992  70.6  7  0.15  55.1  1458</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     1  2200  51.0  1128  70.9  7  0.25  54.8  1720\n",
       "70    8  1450  51.4  997  73.4  7  0.10  55.2  1454\n",
       "71    8  1200  49.8  991  70.8  6  0.15  54.6  1475\n",
       "72    8  1425  50.0  928  70.8  6  0.10  53.9  1375\n",
       "73    8  1250  50.1  990  71.0  6  0.10  54.9  1564\n",
       "74    8  1500  51.7  992  70.6  7  0.15  55.1  1458"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Density</th>\n",
       "      <th>Fat</th>\n",
       "      <th>Age</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Height</th>\n",
       "      <th>Neck</th>\n",
       "      <th>Chest</th>\n",
       "      <th>Abdomen</th>\n",
       "      <th>Hip</th>\n",
       "      <th>Thigh</th>\n",
       "      <th>Knee</th>\n",
       "      <th>Ankle</th>\n",
       "      <th>Biceps</th>\n",
       "      <th>Forearm</th>\n",
       "      <th>Wrist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0708</td>\n",
       "      <td>12.3</td>\n",
       "      <td>23</td>\n",
       "      <td>154.25</td>\n",
       "      <td>67.75</td>\n",
       "      <td>36.2</td>\n",
       "      <td>93.1</td>\n",
       "      <td>85.2</td>\n",
       "      <td>94.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>37.3</td>\n",
       "      <td>21.9</td>\n",
       "      <td>32.0</td>\n",
       "      <td>27.4</td>\n",
       "      <td>17.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Density   Fat  Age  Weight  Height  Neck  Chest  Abdomen   Hip  Thigh  \\\n",
       "1   1.0708  12.3   23  154.25   67.75  36.2   93.1     85.2  94.5   59.0   \n",
       "\n",
       "   Knee  Ankle  Biceps  Forearm  Wrist  \n",
       "1  37.3   21.9    32.0     27.4   17.1  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
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    "data.iloc[[0]]"
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  {
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  {
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   "execution_count": 98,
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   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Density</th>\n",
       "      <th>Fat</th>\n",
       "      <th>Age</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Height</th>\n",
       "      <th>Neck</th>\n",
       "      <th>Chest</th>\n",
       "      <th>Abdomen</th>\n",
       "      <th>Hip</th>\n",
       "      <th>Thigh</th>\n",
       "      <th>Knee</th>\n",
       "      <th>Ankle</th>\n",
       "      <th>Biceps</th>\n",
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       "      <th>Wrist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>252.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.055574</td>\n",
       "      <td>19.150794</td>\n",
       "      <td>44.884921</td>\n",
       "      <td>178.924405</td>\n",
       "      <td>70.148810</td>\n",
       "      <td>37.992063</td>\n",
       "      <td>100.824206</td>\n",
       "      <td>92.555952</td>\n",
       "      <td>99.904762</td>\n",
       "      <td>59.405952</td>\n",
       "      <td>38.590476</td>\n",
       "      <td>23.102381</td>\n",
       "      <td>32.273413</td>\n",
       "      <td>28.663889</td>\n",
       "      <td>18.229762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.019031</td>\n",
       "      <td>8.368740</td>\n",
       "      <td>12.602040</td>\n",
       "      <td>29.389160</td>\n",
       "      <td>3.662856</td>\n",
       "      <td>2.430913</td>\n",
       "      <td>8.430476</td>\n",
       "      <td>10.783077</td>\n",
       "      <td>7.164058</td>\n",
       "      <td>5.249952</td>\n",
       "      <td>2.411805</td>\n",
       "      <td>1.694893</td>\n",
       "      <td>3.021274</td>\n",
       "      <td>2.020691</td>\n",
       "      <td>0.933585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.995000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>118.500000</td>\n",
       "      <td>29.500000</td>\n",
       "      <td>31.100000</td>\n",
       "      <td>79.300000</td>\n",
       "      <td>69.400000</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>47.200000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>19.100000</td>\n",
       "      <td>24.800000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>15.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.041400</td>\n",
       "      <td>12.475000</td>\n",
       "      <td>35.750000</td>\n",
       "      <td>159.000000</td>\n",
       "      <td>68.250000</td>\n",
       "      <td>36.400000</td>\n",
       "      <td>94.350000</td>\n",
       "      <td>84.575000</td>\n",
       "      <td>95.500000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>36.975000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>30.200000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>17.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.054900</td>\n",
       "      <td>19.200000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>176.500000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>99.650000</td>\n",
       "      <td>90.950000</td>\n",
       "      <td>99.300000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>38.500000</td>\n",
       "      <td>22.800000</td>\n",
       "      <td>32.050000</td>\n",
       "      <td>28.700000</td>\n",
       "      <td>18.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.070400</td>\n",
       "      <td>25.300000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>197.000000</td>\n",
       "      <td>72.250000</td>\n",
       "      <td>39.425000</td>\n",
       "      <td>105.375000</td>\n",
       "      <td>99.325000</td>\n",
       "      <td>103.525000</td>\n",
       "      <td>62.350000</td>\n",
       "      <td>39.925000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>34.325000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>18.800000</td>\n",
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       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.108900</td>\n",
       "      <td>47.500000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>363.150000</td>\n",
       "      <td>77.750000</td>\n",
       "      <td>51.200000</td>\n",
       "      <td>136.200000</td>\n",
       "      <td>148.100000</td>\n",
       "      <td>147.700000</td>\n",
       "      <td>87.300000</td>\n",
       "      <td>49.100000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>34.900000</td>\n",
       "      <td>21.400000</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "          Density         Fat         Age      Weight      Height        Neck  \\\n",
       "count  252.000000  252.000000  252.000000  252.000000  252.000000  252.000000   \n",
       "mean     1.055574   19.150794   44.884921  178.924405   70.148810   37.992063   \n",
       "std      0.019031    8.368740   12.602040   29.389160    3.662856    2.430913   \n",
       "min      0.995000    0.000000   22.000000  118.500000   29.500000   31.100000   \n",
       "25%      1.041400   12.475000   35.750000  159.000000   68.250000   36.400000   \n",
       "50%      1.054900   19.200000   43.000000  176.500000   70.000000   38.000000   \n",
       "75%      1.070400   25.300000   54.000000  197.000000   72.250000   39.425000   \n",
       "max      1.108900   47.500000   81.000000  363.150000   77.750000   51.200000   \n",
       "\n",
       "            Chest     Abdomen         Hip       Thigh        Knee       Ankle  \\\n",
       "count  252.000000  252.000000  252.000000  252.000000  252.000000  252.000000   \n",
       "mean   100.824206   92.555952   99.904762   59.405952   38.590476   23.102381   \n",
       "std      8.430476   10.783077    7.164058    5.249952    2.411805    1.694893   \n",
       "min     79.300000   69.400000   85.000000   47.200000   33.000000   19.100000   \n",
       "25%     94.350000   84.575000   95.500000   56.000000   36.975000   22.000000   \n",
       "50%     99.650000   90.950000   99.300000   59.000000   38.500000   22.800000   \n",
       "75%    105.375000   99.325000  103.525000   62.350000   39.925000   24.000000   \n",
       "max    136.200000  148.100000  147.700000   87.300000   49.100000   33.900000   \n",
       "\n",
       "           Biceps     Forearm       Wrist  \n",
       "count  252.000000  252.000000  252.000000  \n",
       "mean    32.273413   28.663889   18.229762  \n",
       "std      3.021274    2.020691    0.933585  \n",
       "min     24.800000   21.000000   15.800000  \n",
       "25%     30.200000   27.300000   17.600000  \n",
       "50%     32.050000   28.700000   18.300000  \n",
       "75%     34.325000   30.000000   18.800000  \n",
       "max     45.000000   34.900000   21.400000  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
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