Mod04 -Tarefa01-aula 01 e 02.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tarefa 01\n",
    "\n",
    "- Leia os enunciados com atenção\n",
    "- Saiba que pode haver mais de uma resposta correta\n",
    "- Insira novas células de código sempre que achar necessário\n",
    "- Em caso de dúvidas, procure os tutores\n",
    "- Divirta-se :)\n",
    "\n",
    "#### 1)  crie uma série do pandas a partir de uma lista com os dados abaixo:\n",
    "\n",
    "Em um estudo sobre alteração na tempreatura global, A NASA disponibiliza dados de diferenças de de temperatura média da superfície terrestre relativos às médias de temperatura entre 1951 e 1980. Os dados originais podem ser vistos no site da NASA/GISS, e estão dispostos a cada década na tabela abaixo.\n",
    "\n",
    "|ano|anomalia termica|\n",
    "|:-:|:----:|\n",
    "| 1900 | -0.08 |\n",
    "| 1920 | -0.27 |\n",
    "| 1940 | 0.12 |\n",
    "| 1960 | -0.03 |\n",
    "| 1980 | 0.26 |\n",
    "| 2000 | 0.40 |\n",
    "| 2020 | 1.02 |\n",
    "\n",
    "Crie uma séries do Pandas a partir de uma lista com esses dados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   -0.08\n",
       "1   -0.27\n",
       "2    0.12\n",
       "3   -0.03\n",
       "4    0.26\n",
       "5    0.40\n",
       "6    1.02\n",
       "dtype: float64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Seu código aqui\n",
    "\n",
    "dados = [-0.08,-0.27,0.12,-0.03,0.26,0.40,1.02]\n",
    "columns='anomalia térmica'\n",
    "temperaturaGlobal = pd.Series(dados)\n",
    "temperaturaGlobal "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2) Coloque os anos nos índices conforme a tabela."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1900   -0.08\n",
       "1920   -0.27\n",
       "1940    0.12\n",
       "1960   -0.03\n",
       "1980    0.26\n",
       "2000    0.40\n",
       "2020    1.02\n",
       "dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# seu código aqui\n",
    "\n",
    "indice = [1900, 1920, 1940, 1960, 1980, 2000, 2020]\n",
    "dados = [-0.08,-0.27,0.12,-0.03,0.26,0.40,1.02]\n",
    "temperaturaGlobal = pd.Series (data=dados, index = indice)\n",
    "temperaturaGlobal "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3) A partir do dicionário abaixo, crie uma séries do Pandas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1900   -0.08\n",
       "1920   -0.27\n",
       "1940    0.12\n",
       "1960   -0.03\n",
       "1980    0.26\n",
       "2000    0.40\n",
       "2020    1.02\n",
       "dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dic_temperaturas = {1900: -.08, 1920: -.27, 1940: .12, 1960: -.03, 1980: .26, 2000: .40, 2020: 1.02}\n",
    "\n",
    "# seu código aqui\n",
    "\n",
    "temperaturaGlobalSeries = pd.Series(dic_temperaturas)\n",
    "temperaturaGlobalSeries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4) Transforme o ndarray abaixo em um dataframe. \n",
    "O numpy é capaz de gerar arrays n-dimensionais com números pseudo-aleatórios de acordo com uma variedade de distribuições, como no exemplo abaixo. Transforme esse nd-array em um DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>85.250230</td>\n",
       "      <td>109.524504</td>\n",
       "      <td>113.778774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>106.939064</td>\n",
       "      <td>95.048094</td>\n",
       "      <td>100.199961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>105.501996</td>\n",
       "      <td>89.897138</td>\n",
       "      <td>107.070937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>101.645899</td>\n",
       "      <td>106.384923</td>\n",
       "      <td>100.886626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86.976298</td>\n",
       "      <td>108.113172</td>\n",
       "      <td>104.515186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>110.520117</td>\n",
       "      <td>103.452792</td>\n",
       "      <td>97.267406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>105.924574</td>\n",
       "      <td>93.971206</td>\n",
       "      <td>101.528361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>94.206421</td>\n",
       "      <td>98.919000</td>\n",
       "      <td>106.041272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>102.384251</td>\n",
       "      <td>101.274094</td>\n",
       "      <td>100.516668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>99.303498</td>\n",
       "      <td>85.752176</td>\n",
       "      <td>91.853465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>102.769253</td>\n",
       "      <td>93.703727</td>\n",
       "      <td>80.207873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>107.173786</td>\n",
       "      <td>97.262336</td>\n",
       "      <td>92.311088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>93.959338</td>\n",
       "      <td>99.643146</td>\n",
       "      <td>120.517834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>84.787405</td>\n",
       "      <td>94.879431</td>\n",
       "      <td>98.347855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>93.304242</td>\n",
       "      <td>119.127488</td>\n",
       "      <td>90.347645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>98.847023</td>\n",
       "      <td>85.479123</td>\n",
       "      <td>86.722485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>114.917643</td>\n",
       "      <td>93.347495</td>\n",
       "      <td>102.485155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>98.966160</td>\n",
       "      <td>87.271155</td>\n",
       "      <td>94.295147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>77.629620</td>\n",
       "      <td>109.506714</td>\n",
       "      <td>95.026917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>96.693774</td>\n",
       "      <td>107.312292</td>\n",
       "      <td>103.896810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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      "text/plain": [
       "             0           1           2\n",
       "0    85.250230  109.524504  113.778774\n",
       "1   106.939064   95.048094  100.199961\n",
       "2   105.501996   89.897138  107.070937\n",
       "3   101.645899  106.384923  100.886626\n",
       "4    86.976298  108.113172  104.515186\n",
       "5   110.520117  103.452792   97.267406\n",
       "6   105.924574   93.971206  101.528361\n",
       "7    94.206421   98.919000  106.041272\n",
       "8   102.384251  101.274094  100.516668\n",
       "9    99.303498   85.752176   91.853465\n",
       "10  102.769253   93.703727   80.207873\n",
       "11  107.173786   97.262336   92.311088\n",
       "12   93.959338   99.643146  120.517834\n",
       "13   84.787405   94.879431   98.347855\n",
       "14   93.304242  119.127488   90.347645\n",
       "15   98.847023   85.479123   86.722485\n",
       "16  114.917643   93.347495  102.485155\n",
       "17   98.966160   87.271155   94.295147\n",
       "18   77.629620  109.506714   95.026917\n",
       "19   96.693774  107.312292  103.896810"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr = np.random.normal(100, 10, (20,3))\n",
    "\n",
    "# seu código aqui\n",
    "\n",
    "df = pd.DataFrame(arr)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5) Nomeie os índices das linhas com inteiros de 1 a 20, e as colunas com os nomes \"x1\", \"x2\", e \"x3\" respectivamente."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
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       "      <th>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85.250230</td>\n",
       "      <td>109.524504</td>\n",
       "      <td>113.778774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>106.939064</td>\n",
       "      <td>95.048094</td>\n",
       "      <td>100.199961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>105.501996</td>\n",
       "      <td>89.897138</td>\n",
       "      <td>107.070937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>101.645899</td>\n",
       "      <td>106.384923</td>\n",
       "      <td>100.886626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86.976298</td>\n",
       "      <td>108.113172</td>\n",
       "      <td>104.515186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>110.520117</td>\n",
       "      <td>103.452792</td>\n",
       "      <td>97.267406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>105.924574</td>\n",
       "      <td>93.971206</td>\n",
       "      <td>101.528361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>94.206421</td>\n",
       "      <td>98.919000</td>\n",
       "      <td>106.041272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>102.384251</td>\n",
       "      <td>101.274094</td>\n",
       "      <td>100.516668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>99.303498</td>\n",
       "      <td>85.752176</td>\n",
       "      <td>91.853465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>102.769253</td>\n",
       "      <td>93.703727</td>\n",
       "      <td>80.207873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>107.173786</td>\n",
       "      <td>97.262336</td>\n",
       "      <td>92.311088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>93.959338</td>\n",
       "      <td>99.643146</td>\n",
       "      <td>120.517834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>84.787405</td>\n",
       "      <td>94.879431</td>\n",
       "      <td>98.347855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>93.304242</td>\n",
       "      <td>119.127488</td>\n",
       "      <td>90.347645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>98.847023</td>\n",
       "      <td>85.479123</td>\n",
       "      <td>86.722485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>114.917643</td>\n",
       "      <td>93.347495</td>\n",
       "      <td>102.485155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>98.966160</td>\n",
       "      <td>87.271155</td>\n",
       "      <td>94.295147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>77.629620</td>\n",
       "      <td>109.506714</td>\n",
       "      <td>95.026917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>96.693774</td>\n",
       "      <td>107.312292</td>\n",
       "      <td>103.896810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            x1          x2          x3\n",
       "1    85.250230  109.524504  113.778774\n",
       "2   106.939064   95.048094  100.199961\n",
       "3   105.501996   89.897138  107.070937\n",
       "4   101.645899  106.384923  100.886626\n",
       "5    86.976298  108.113172  104.515186\n",
       "6   110.520117  103.452792   97.267406\n",
       "7   105.924574   93.971206  101.528361\n",
       "8    94.206421   98.919000  106.041272\n",
       "9   102.384251  101.274094  100.516668\n",
       "10   99.303498   85.752176   91.853465\n",
       "11  102.769253   93.703727   80.207873\n",
       "12  107.173786   97.262336   92.311088\n",
       "13   93.959338   99.643146  120.517834\n",
       "14   84.787405   94.879431   98.347855\n",
       "15   93.304242  119.127488   90.347645\n",
       "16   98.847023   85.479123   86.722485\n",
       "17  114.917643   93.347495  102.485155\n",
       "18   98.966160   87.271155   94.295147\n",
       "19   77.629620  109.506714   95.026917\n",
       "20   96.693774  107.312292  103.896810"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#seu código aqui\n",
    "\n",
    "df = pd.DataFrame(arr, columns=['x1','x2','x3'], index=(list(range(1, 21, 1))))\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6) No DataFrame do exercício 5, crie uma nova coluna como sendo a média das três colunas, e dê a ela o nome de \"media\" (não recomendo colocar acentos em nomes de variáveis)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
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       "      <th>media</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85.250230</td>\n",
       "      <td>109.524504</td>\n",
       "      <td>113.778774</td>\n",
       "      <td>102.851169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>106.939064</td>\n",
       "      <td>95.048094</td>\n",
       "      <td>100.199961</td>\n",
       "      <td>100.729040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>105.501996</td>\n",
       "      <td>89.897138</td>\n",
       "      <td>107.070937</td>\n",
       "      <td>100.823357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>101.645899</td>\n",
       "      <td>106.384923</td>\n",
       "      <td>100.886626</td>\n",
       "      <td>102.972483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86.976298</td>\n",
       "      <td>108.113172</td>\n",
       "      <td>104.515186</td>\n",
       "      <td>99.868219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>110.520117</td>\n",
       "      <td>103.452792</td>\n",
       "      <td>97.267406</td>\n",
       "      <td>103.746772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>105.924574</td>\n",
       "      <td>93.971206</td>\n",
       "      <td>101.528361</td>\n",
       "      <td>100.474714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>94.206421</td>\n",
       "      <td>98.919000</td>\n",
       "      <td>106.041272</td>\n",
       "      <td>99.722231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>102.384251</td>\n",
       "      <td>101.274094</td>\n",
       "      <td>100.516668</td>\n",
       "      <td>101.391671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>99.303498</td>\n",
       "      <td>85.752176</td>\n",
       "      <td>91.853465</td>\n",
       "      <td>92.303046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>102.769253</td>\n",
       "      <td>93.703727</td>\n",
       "      <td>80.207873</td>\n",
       "      <td>92.226951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>107.173786</td>\n",
       "      <td>97.262336</td>\n",
       "      <td>92.311088</td>\n",
       "      <td>98.915737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>93.959338</td>\n",
       "      <td>99.643146</td>\n",
       "      <td>120.517834</td>\n",
       "      <td>104.706772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>84.787405</td>\n",
       "      <td>94.879431</td>\n",
       "      <td>98.347855</td>\n",
       "      <td>92.671563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>93.304242</td>\n",
       "      <td>119.127488</td>\n",
       "      <td>90.347645</td>\n",
       "      <td>100.926459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>98.847023</td>\n",
       "      <td>85.479123</td>\n",
       "      <td>86.722485</td>\n",
       "      <td>90.349543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>114.917643</td>\n",
       "      <td>93.347495</td>\n",
       "      <td>102.485155</td>\n",
       "      <td>103.583431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>98.966160</td>\n",
       "      <td>87.271155</td>\n",
       "      <td>94.295147</td>\n",
       "      <td>93.510821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>77.629620</td>\n",
       "      <td>109.506714</td>\n",
       "      <td>95.026917</td>\n",
       "      <td>94.054417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>96.693774</td>\n",
       "      <td>107.312292</td>\n",
       "      <td>103.896810</td>\n",
       "      <td>102.634292</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            x1          x2          x3       media\n",
       "1    85.250230  109.524504  113.778774  102.851169\n",
       "2   106.939064   95.048094  100.199961  100.729040\n",
       "3   105.501996   89.897138  107.070937  100.823357\n",
       "4   101.645899  106.384923  100.886626  102.972483\n",
       "5    86.976298  108.113172  104.515186   99.868219\n",
       "6   110.520117  103.452792   97.267406  103.746772\n",
       "7   105.924574   93.971206  101.528361  100.474714\n",
       "8    94.206421   98.919000  106.041272   99.722231\n",
       "9   102.384251  101.274094  100.516668  101.391671\n",
       "10   99.303498   85.752176   91.853465   92.303046\n",
       "11  102.769253   93.703727   80.207873   92.226951\n",
       "12  107.173786   97.262336   92.311088   98.915737\n",
       "13   93.959338   99.643146  120.517834  104.706772\n",
       "14   84.787405   94.879431   98.347855   92.671563\n",
       "15   93.304242  119.127488   90.347645  100.926459\n",
       "16   98.847023   85.479123   86.722485   90.349543\n",
       "17  114.917643   93.347495  102.485155  103.583431\n",
       "18   98.966160   87.271155   94.295147   93.510821\n",
       "19   77.629620  109.506714   95.026917   94.054417\n",
       "20   96.693774  107.312292  103.896810  102.634292"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['media'] = df.mean(axis=1)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 7) No DataFrame do exercício 6, crie uma nova coluna chamada \"log_med\", contendo o logaritmo natural da média calculada no exercício 6 <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "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>x1</th>\n",
       "      <th>x2</th>\n",
       "      <th>x3</th>\n",
       "      <th>media</th>\n",
       "      <th>log_med</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>85.250230</td>\n",
       "      <td>109.524504</td>\n",
       "      <td>113.778774</td>\n",
       "      <td>102.851169</td>\n",
       "      <td>4.633283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>106.939064</td>\n",
       "      <td>95.048094</td>\n",
       "      <td>100.199961</td>\n",
       "      <td>100.729040</td>\n",
       "      <td>4.612434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>105.501996</td>\n",
       "      <td>89.897138</td>\n",
       "      <td>107.070937</td>\n",
       "      <td>100.823357</td>\n",
       "      <td>4.613370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>101.645899</td>\n",
       "      <td>106.384923</td>\n",
       "      <td>100.886626</td>\n",
       "      <td>102.972483</td>\n",
       "      <td>4.634462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86.976298</td>\n",
       "      <td>108.113172</td>\n",
       "      <td>104.515186</td>\n",
       "      <td>99.868219</td>\n",
       "      <td>4.603852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>110.520117</td>\n",
       "      <td>103.452792</td>\n",
       "      <td>97.267406</td>\n",
       "      <td>103.746772</td>\n",
       "      <td>4.641953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>105.924574</td>\n",
       "      <td>93.971206</td>\n",
       "      <td>101.528361</td>\n",
       "      <td>100.474714</td>\n",
       "      <td>4.609906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>94.206421</td>\n",
       "      <td>98.919000</td>\n",
       "      <td>106.041272</td>\n",
       "      <td>99.722231</td>\n",
       "      <td>4.602389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>102.384251</td>\n",
       "      <td>101.274094</td>\n",
       "      <td>100.516668</td>\n",
       "      <td>101.391671</td>\n",
       "      <td>4.618991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>99.303498</td>\n",
       "      <td>85.752176</td>\n",
       "      <td>91.853465</td>\n",
       "      <td>92.303046</td>\n",
       "      <td>4.525077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>102.769253</td>\n",
       "      <td>93.703727</td>\n",
       "      <td>80.207873</td>\n",
       "      <td>92.226951</td>\n",
       "      <td>4.524252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>107.173786</td>\n",
       "      <td>97.262336</td>\n",
       "      <td>92.311088</td>\n",
       "      <td>98.915737</td>\n",
       "      <td>4.594268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>93.959338</td>\n",
       "      <td>99.643146</td>\n",
       "      <td>120.517834</td>\n",
       "      <td>104.706772</td>\n",
       "      <td>4.651164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>84.787405</td>\n",
       "      <td>94.879431</td>\n",
       "      <td>98.347855</td>\n",
       "      <td>92.671563</td>\n",
       "      <td>4.529062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>93.304242</td>\n",
       "      <td>119.127488</td>\n",
       "      <td>90.347645</td>\n",
       "      <td>100.926459</td>\n",
       "      <td>4.614392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>98.847023</td>\n",
       "      <td>85.479123</td>\n",
       "      <td>86.722485</td>\n",
       "      <td>90.349543</td>\n",
       "      <td>4.503686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>114.917643</td>\n",
       "      <td>93.347495</td>\n",
       "      <td>102.485155</td>\n",
       "      <td>103.583431</td>\n",
       "      <td>4.640377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>98.966160</td>\n",
       "      <td>87.271155</td>\n",
       "      <td>94.295147</td>\n",
       "      <td>93.510821</td>\n",
       "      <td>4.538077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>77.629620</td>\n",
       "      <td>109.506714</td>\n",
       "      <td>95.026917</td>\n",
       "      <td>94.054417</td>\n",
       "      <td>4.543874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>96.693774</td>\n",
       "      <td>107.312292</td>\n",
       "      <td>103.896810</td>\n",
       "      <td>102.634292</td>\n",
       "      <td>4.631172</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            x1          x2          x3       media   log_med\n",
       "1    85.250230  109.524504  113.778774  102.851169  4.633283\n",
       "2   106.939064   95.048094  100.199961  100.729040  4.612434\n",
       "3   105.501996   89.897138  107.070937  100.823357  4.613370\n",
       "4   101.645899  106.384923  100.886626  102.972483  4.634462\n",
       "5    86.976298  108.113172  104.515186   99.868219  4.603852\n",
       "6   110.520117  103.452792   97.267406  103.746772  4.641953\n",
       "7   105.924574   93.971206  101.528361  100.474714  4.609906\n",
       "8    94.206421   98.919000  106.041272   99.722231  4.602389\n",
       "9   102.384251  101.274094  100.516668  101.391671  4.618991\n",
       "10   99.303498   85.752176   91.853465   92.303046  4.525077\n",
       "11  102.769253   93.703727   80.207873   92.226951  4.524252\n",
       "12  107.173786   97.262336   92.311088   98.915737  4.594268\n",
       "13   93.959338   99.643146  120.517834  104.706772  4.651164\n",
       "14   84.787405   94.879431   98.347855   92.671563  4.529062\n",
       "15   93.304242  119.127488   90.347645  100.926459  4.614392\n",
       "16   98.847023   85.479123   86.722485   90.349543  4.503686\n",
       "17  114.917643   93.347495  102.485155  103.583431  4.640377\n",
       "18   98.966160   87.271155   94.295147   93.510821  4.538077\n",
       "19   77.629620  109.506714   95.026917   94.054417  4.543874\n",
       "20   96.693774  107.312292  103.896810  102.634292  4.631172"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# seu código aqui\n",
    "\n",
    "df['log_med'] = np.log(df['media'])\n",
    "df"
   ]
  }
 ],
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