gabrielle_oficina1_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Oficina 1.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Aluna: Gabrielle Fernandes de Campos"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O consumo excessivo de álcool é um problema grave de saúde pública, você não acha? Imagine que você é um cientista de dados trabalhando em uma equipe da Organização Mundial da Saúde (OMS), cujo objetivo é desenvolver relatórios sobre o consumo de álcool no mundo. Tudo certo até aqui? Então, vamos continuar!\n",
    "\n",
    "Foram coletados dados de diferentes países, indicando o consumo de cerveja (beer), licor (spirit) e vinho (wine), e o consumo de litros de álcool por pessoa do país no ano de 2010. Seu trabalho, então, é responder a algumas perguntas sobre os dados que irão ajudar a compor o relatório. Vamos lá?\n",
    "\n",
    "Qual a média e desvio padrão do consumo de cerveja, licor, vinho e total de álcool?\n",
    "Qual o consumo de licor na França?\n",
    "Quais os 5 países nos quais se consome mais vinho?\n",
    "Quais os países nos quais o consumo de cerveja está acima da média?\n",
    "Quais países nos quais o consumo total de álcool está acima do Brasil, em ordem do menor para o maior?\n",
    "Para responder a essas questões, você deve usar os dados disponibilizados nesta página:\n",
    "\n",
    "dados.\n",
    "\n",
    "Baixe o conjunto de dados, selecionando o link e clicando com o botão direito do mouse ou usando a tecla Aplicação. Então, escolha a opção “Salvar como…”, e salve o arquivo com o nome drinks.txt. Na mesma pasta em que você salvou os dados, crie um Jupyter Notebook, importe a biblioteca pandas e carregue os dados com os comandos:\n",
    "\n",
    "Para responder a essas questões, você deve usar os dados disponibilizados nesta página: dados. Baixe o conjunto de dados, selecionando o link e clicando com o botão direito do mouse ou usando a tecla Aplicação. Então, escolha a opção “Salvar como…”, e salve o arquivo com o nome drinks.txt. Na mesma pasta em que você salvou os dados, crie um Jupyter Notebook, importe a biblioteca pandas e carregue os dados com os comandos:\n",
    "\n",
    "\n",
    "01 import pandas as pd\n",
    "02 df = pd.read_csv('drinks.txt')\n",
    "A partir daí, você deverá responder a cada pergunta em uma célula diferente. Note que existem várias formas diferentes de chegar ao resultado da resposta. Além disso, você pode fazer comentários sobre conclusões a respeito dos dados para enriquecer as suas respostas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Respostas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('drinks.txt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Qual a média e desvio padrão do consumo de cerveja, licor, vinho e total de álcool?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_servings                   106.160622\n",
       "spirit_servings                  80.994819\n",
       "wine_servings                    49.450777\n",
       "total_litres_of_pure_alcohol      4.717098\n",
       "dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# media\n",
    "df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_servings                   101.143103\n",
       "spirit_servings                  88.284312\n",
       "wine_servings                    79.697598\n",
       "total_litres_of_pure_alcohol      3.773298\n",
       "dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# desvio padrão\n",
    "df.std()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Qual o consumo de licor na França?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>beer_servings</th>\n",
       "      <th>spirit_servings</th>\n",
       "      <th>wine_servings</th>\n",
       "      <th>total_litres_of_pure_alcohol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>France</td>\n",
       "      <td>127</td>\n",
       "      <td>151</td>\n",
       "      <td>370</td>\n",
       "      <td>11.8</td>\n",
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      ],
      "text/plain": [
       "   country  beer_servings  spirit_servings  wine_servings  \\\n",
       "61  France            127              151            370   \n",
       "\n",
       "    total_litres_of_pure_alcohol  \n",
       "61                          11.8  "
      ]
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     "execution_count": 13,
     "metadata": {},
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   "source": [
    "df[df['country'] == 'France']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ## Quais os 5 países nos quais se consome mais vinho?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>beer_servings</th>\n",
       "      <th>spirit_servings</th>\n",
       "      <th>wine_servings</th>\n",
       "      <th>total_litres_of_pure_alcohol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>France</td>\n",
       "      <td>127</td>\n",
       "      <td>151</td>\n",
       "      <td>370</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>194</td>\n",
       "      <td>67</td>\n",
       "      <td>339</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>245</td>\n",
       "      <td>138</td>\n",
       "      <td>312</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>185</td>\n",
       "      <td>100</td>\n",
       "      <td>280</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>224</td>\n",
       "      <td>81</td>\n",
       "      <td>278</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "         country  beer_servings  spirit_servings  wine_servings  \\\n",
       "61        France            127              151            370   \n",
       "136     Portugal            194               67            339   \n",
       "3        Andorra            245              138            312   \n",
       "166  Switzerland            185              100            280   \n",
       "48       Denmark            224               81            278   \n",
       "\n",
       "     total_litres_of_pure_alcohol  \n",
       "61                           11.8  \n",
       "136                          11.0  \n",
       "3                            12.4  \n",
       "166                          10.2  \n",
       "48                           10.4  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='wine_servings', ascending = False). head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quais os países nos quais o consumo de cerveja está acima da média?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>beer_servings</th>\n",
       "      <th>spirit_servings</th>\n",
       "      <th>wine_servings</th>\n",
       "      <th>total_litres_of_pure_alcohol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>245</td>\n",
       "      <td>138</td>\n",
       "      <td>312</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>217</td>\n",
       "      <td>57</td>\n",
       "      <td>45</td>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>193</td>\n",
       "      <td>25</td>\n",
       "      <td>221</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Australia</td>\n",
       "      <td>261</td>\n",
       "      <td>72</td>\n",
       "      <td>212</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Austria</td>\n",
       "      <td>279</td>\n",
       "      <td>75</td>\n",
       "      <td>191</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>219</td>\n",
       "      <td>126</td>\n",
       "      <td>195</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>USA</td>\n",
       "      <td>249</td>\n",
       "      <td>158</td>\n",
       "      <td>84</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>Uruguay</td>\n",
       "      <td>115</td>\n",
       "      <td>35</td>\n",
       "      <td>220</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>Venezuela</td>\n",
       "      <td>333</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>Vietnam</td>\n",
       "      <td>111</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>77 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            country  beer_servings  spirit_servings  wine_servings  \\\n",
       "3           Andorra            245              138            312   \n",
       "4            Angola            217               57             45   \n",
       "6         Argentina            193               25            221   \n",
       "8         Australia            261               72            212   \n",
       "9           Austria            279               75            191   \n",
       "..              ...            ...              ...            ...   \n",
       "182  United Kingdom            219              126            195   \n",
       "184             USA            249              158             84   \n",
       "185         Uruguay            115               35            220   \n",
       "188       Venezuela            333              100              3   \n",
       "189         Vietnam            111                2              1   \n",
       "\n",
       "     total_litres_of_pure_alcohol  \n",
       "3                            12.4  \n",
       "4                             5.9  \n",
       "6                             8.3  \n",
       "8                            10.4  \n",
       "9                             9.7  \n",
       "..                            ...  \n",
       "182                          10.4  \n",
       "184                           8.7  \n",
       "185                           6.6  \n",
       "188                           7.7  \n",
       "189                           2.0  \n",
       "\n",
       "[77 rows x 5 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# considenrando que a média de consumo de cerveja é 106 conforme verificado acima.\n",
    "df[df['beer_servings'] >= 106]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quais países nos quais o consumo total de álcool está acima do Brasil, em ordem do menor para o maior?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "beer_servings                   245.0\n",
       "spirit_servings                 145.0\n",
       "wine_servings                    16.0\n",
       "total_litres_of_pure_alcohol      7.2\n",
       "dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# identificando qual o consumo total de álcool do BR\n",
    "\n",
    "df[df['country'] == 'Brazil']. mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# isolo os países na variavel pb\n",
    "\n",
    "pb = df[df['total_litres_of_pure_alcohol'] > 7.2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>country</th>\n",
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       "      <th>132</th>\n",
       "      <td>Paraguay</td>\n",
       "      <td>213</td>\n",
       "      <td>117</td>\n",
       "      <td>74</td>\n",
       "      <td>7.3</td>\n",
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       "      <th>35</th>\n",
       "      <td>Chile</td>\n",
       "      <td>130</td>\n",
       "      <td>124</td>\n",
       "      <td>172</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>Venezuela</td>\n",
       "      <td>333</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>St. Kitts &amp; Nevis</td>\n",
       "      <td>194</td>\n",
       "      <td>205</td>\n",
       "      <td>32</td>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>225</td>\n",
       "      <td>76</td>\n",
       "      <td>81</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Canada</td>\n",
       "      <td>240</td>\n",
       "      <td>122</td>\n",
       "      <td>100</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Cyprus</td>\n",
       "      <td>192</td>\n",
       "      <td>154</td>\n",
       "      <td>113</td>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>193</td>\n",
       "      <td>25</td>\n",
       "      <td>221</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>Uganda</td>\n",
       "      <td>45</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Greece</td>\n",
       "      <td>133</td>\n",
       "      <td>112</td>\n",
       "      <td>218</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>USA</td>\n",
       "      <td>249</td>\n",
       "      <td>158</td>\n",
       "      <td>84</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Gabon</td>\n",
       "      <td>347</td>\n",
       "      <td>98</td>\n",
       "      <td>59</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>Ukraine</td>\n",
       "      <td>206</td>\n",
       "      <td>237</td>\n",
       "      <td>45</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>Nigeria</td>\n",
       "      <td>42</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>New Zealand</td>\n",
       "      <td>203</td>\n",
       "      <td>79</td>\n",
       "      <td>175</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>251</td>\n",
       "      <td>88</td>\n",
       "      <td>190</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Estonia</td>\n",
       "      <td>224</td>\n",
       "      <td>194</td>\n",
       "      <td>59</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Serbia</td>\n",
       "      <td>283</td>\n",
       "      <td>131</td>\n",
       "      <td>127</td>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Austria</td>\n",
       "      <td>279</td>\n",
       "      <td>75</td>\n",
       "      <td>191</td>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>South Korea</td>\n",
       "      <td>140</td>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Finland</td>\n",
       "      <td>263</td>\n",
       "      <td>133</td>\n",
       "      <td>97</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>Spain</td>\n",
       "      <td>284</td>\n",
       "      <td>157</td>\n",
       "      <td>112</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>St. Lucia</td>\n",
       "      <td>171</td>\n",
       "      <td>315</td>\n",
       "      <td>71</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>185</td>\n",
       "      <td>100</td>\n",
       "      <td>280</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Croatia</td>\n",
       "      <td>230</td>\n",
       "      <td>87</td>\n",
       "      <td>254</td>\n",
       "      <td>10.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Bulgaria</td>\n",
       "      <td>231</td>\n",
       "      <td>252</td>\n",
       "      <td>94</td>\n",
       "      <td>10.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Australia</td>\n",
       "      <td>261</td>\n",
       "      <td>72</td>\n",
       "      <td>212</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Romania</td>\n",
       "      <td>297</td>\n",
       "      <td>122</td>\n",
       "      <td>167</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>219</td>\n",
       "      <td>126</td>\n",
       "      <td>195</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>224</td>\n",
       "      <td>81</td>\n",
       "      <td>278</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>295</td>\n",
       "      <td>84</td>\n",
       "      <td>212</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Latvia</td>\n",
       "      <td>281</td>\n",
       "      <td>216</td>\n",
       "      <td>62</td>\n",
       "      <td>10.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>Slovenia</td>\n",
       "      <td>270</td>\n",
       "      <td>51</td>\n",
       "      <td>276</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Poland</td>\n",
       "      <td>343</td>\n",
       "      <td>215</td>\n",
       "      <td>56</td>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Portugal</td>\n",
       "      <td>194</td>\n",
       "      <td>67</td>\n",
       "      <td>339</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Hungary</td>\n",
       "      <td>234</td>\n",
       "      <td>215</td>\n",
       "      <td>185</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Germany</td>\n",
       "      <td>346</td>\n",
       "      <td>117</td>\n",
       "      <td>175</td>\n",
       "      <td>11.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Luxembourg</td>\n",
       "      <td>236</td>\n",
       "      <td>133</td>\n",
       "      <td>271</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>196</td>\n",
       "      <td>293</td>\n",
       "      <td>116</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Ireland</td>\n",
       "      <td>313</td>\n",
       "      <td>118</td>\n",
       "      <td>165</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>247</td>\n",
       "      <td>326</td>\n",
       "      <td>73</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>361</td>\n",
       "      <td>170</td>\n",
       "      <td>134</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>France</td>\n",
       "      <td>127</td>\n",
       "      <td>151</td>\n",
       "      <td>370</td>\n",
       "      <td>11.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Grenada</td>\n",
       "      <td>199</td>\n",
       "      <td>438</td>\n",
       "      <td>28</td>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>245</td>\n",
       "      <td>138</td>\n",
       "      <td>312</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Lithuania</td>\n",
       "      <td>343</td>\n",
       "      <td>244</td>\n",
       "      <td>56</td>\n",
       "      <td>12.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Belarus</td>\n",
       "      <td>142</td>\n",
       "      <td>373</td>\n",
       "      <td>42</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                country  beer_servings  spirit_servings  wine_servings  \\\n",
       "132            Paraguay            213              117             74   \n",
       "35                Chile            130              124            172   \n",
       "188           Venezuela            333              100              3   \n",
       "143   St. Kitts & Nevis            194              205             32   \n",
       "159        South Africa            225               76             81   \n",
       "32               Canada            240              122            100   \n",
       "44               Cyprus            192              154            113   \n",
       "6             Argentina            193               25            221   \n",
       "179              Uganda             45                9              0   \n",
       "67               Greece            133              112            218   \n",
       "184                 USA            249              158             84   \n",
       "62                Gabon            347               98             59   \n",
       "180             Ukraine            206              237             45   \n",
       "124             Nigeria             42                5              2   \n",
       "121         New Zealand            203               79            175   \n",
       "120         Netherlands            251               88            190   \n",
       "57              Estonia            224              194             59   \n",
       "151              Serbia            283              131            127   \n",
       "9               Austria            279               75            191   \n",
       "138         South Korea            140               16              9   \n",
       "60              Finland            263              133             97   \n",
       "160               Spain            284              157            112   \n",
       "144           St. Lucia            171              315             71   \n",
       "166         Switzerland            185              100            280   \n",
       "42              Croatia            230               87            254   \n",
       "25             Bulgaria            231              252             94   \n",
       "8             Australia            261               72            212   \n",
       "140             Romania            297              122            167   \n",
       "182      United Kingdom            219              126            195   \n",
       "48              Denmark            224               81            278   \n",
       "16              Belgium            295               84            212   \n",
       "93               Latvia            281              216             62   \n",
       "156            Slovenia            270               51            276   \n",
       "135              Poland            343              215             56   \n",
       "136            Portugal            194               67            339   \n",
       "75              Hungary            234              215            185   \n",
       "65              Germany            346              117            175   \n",
       "99           Luxembourg            236              133            271   \n",
       "155            Slovakia            196              293            116   \n",
       "81              Ireland            313              118            165   \n",
       "141  Russian Federation            247              326             73   \n",
       "45       Czech Republic            361              170            134   \n",
       "61               France            127              151            370   \n",
       "68              Grenada            199              438             28   \n",
       "3               Andorra            245              138            312   \n",
       "98            Lithuania            343              244             56   \n",
       "15              Belarus            142              373             42   \n",
       "\n",
       "     total_litres_of_pure_alcohol  \n",
       "132                           7.3  \n",
       "35                            7.6  \n",
       "188                           7.7  \n",
       "143                           7.7  \n",
       "159                           8.2  \n",
       "32                            8.2  \n",
       "44                            8.2  \n",
       "6                             8.3  \n",
       "179                           8.3  \n",
       "67                            8.3  \n",
       "184                           8.7  \n",
       "62                            8.9  \n",
       "180                           8.9  \n",
       "124                           9.1  \n",
       "121                           9.3  \n",
       "120                           9.4  \n",
       "57                            9.5  \n",
       "151                           9.6  \n",
       "9                             9.7  \n",
       "138                           9.8  \n",
       "60                           10.0  \n",
       "160                          10.0  \n",
       "144                          10.1  \n",
       "166                          10.2  \n",
       "42                           10.2  \n",
       "25                           10.3  \n",
       "8                            10.4  \n",
       "140                          10.4  \n",
       "182                          10.4  \n",
       "48                           10.4  \n",
       "16                           10.5  \n",
       "93                           10.5  \n",
       "156                          10.6  \n",
       "135                          10.9  \n",
       "136                          11.0  \n",
       "75                           11.3  \n",
       "65                           11.3  \n",
       "99                           11.4  \n",
       "155                          11.4  \n",
       "81                           11.4  \n",
       "141                          11.5  \n",
       "45                           11.8  \n",
       "61                           11.8  \n",
       "68                           11.9  \n",
       "3                            12.4  \n",
       "98                           12.9  \n",
       "15                           14.4  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# apresento os dados isolados de forma ascendente.\n",
    "\n",
    "pb.sort_values(by ='total_litres_of_pure_alcohol', ascending = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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