Visualizando dados sobre a Pandemia da Covid-19 - Geovanna Ferreira.ipynb

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    "id": "50641a8a"
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   "source": [
    "# <font color=white|cyan>Visualizando dados sobre a Pandemia da Covid-19</font> \n",
    "\n",
    "Neste artigo apresentarei várias formas de visualização de dados acerca da Pandemia da Covid-19 no Brasil. Utilizarei algumas bibliotecas diferentes e ensinarei a vocês como utilizá-las."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bab9c72",
   "metadata": {
    "id": "8bab9c72"
   },
   "source": [
    "# Importando os dados, bibliotecas, etc.\n",
    "\n",
    "Antes de tudo precisamos importar as bibliotecas e os dados que vamos usar. Mas o que são bibliotecas? Dados? Bom, podemos entender bibliotecas como conjuntos de módulos e funções - já prontas - que nos auxiliam na construção do nosso código. Imagine que complicado seria se a cada linha do nosso código tivessémos que criar funções para realizar cada tarefa? Trabalhoso demais, né? É ai que as bibliotecas entram para nos auxiliar, elas nos apresentam uma gama de funções para que nosso trabalho seja mais rápido. É claro que você pode criar novas funções que achar interessante, as vezes queremos fazer algo muito específico e criamos nossas próprias funções, mas se fossemos fazer isso a cada linha de código, além dele ficar gigante demais, levaria muito mais tempo para realizar uma tarefa que pode ser muito mais rápida com o uso das bibliotecas.\n",
    "Já os dados representam um conjunto de informações sobre algo, por exemplo, pense em uma planilha com todos os nomes dos funcionários públicos do Estado de São Paulo, com informações como salário, idade, data de nascimento e endereço. Isso é um conjunto de dados. \n",
    "É por meio das bibliotecas que conseguimos fazer o tratamento dos dados (como os dos funcionários do Estado de São Paulo) para trabalhar com a informação do jeito que quisermos. Seja fazendo uma visualização dos funcionários por meio de gráfico, que nos possibilitaria saber qual a proporção de funcionários em cada bairro, qual a proporção de idades, quais funcionários estão perto de se aposetar, ou seja, uma análise geral do seu perfil, por exemplo.\n",
    "Dito tudo isso, vamos importar as bibliotecas e os dados que usaremos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "baaf80d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importando as bibliotecas:\n",
    "import matplotlib.pyplot as plt # biblioteca utilizada para a visualização dos dados e também para a elaboração de gráficos.\n",
    "import seaborn as sns # biblioteca usada para a plotagem dos mais variados tipos de gráficos. Ela é muito utilizada na visualização de séries temporais.\n",
    "import plotly.express as px # faz parte da biblioteca Plotly e é utilizada para plotagem de figuras e gráficos.\n",
    "import pandas as pd # biblioteca utilizada para manipulação e análise de dados.\n",
    "\n",
    "# Nomeando os dados sobre o número de óbitos:\n",
    "obitos = pd.read_csv('obito_cartorio.csv', na_values ='n/a', usecols = [0,1,3,10]) # aqui utilizei essa função do pandas que lê um arquivo csv e tranforma em DataFrame para ser utilizado no código. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5957a830",
   "metadata": {},
   "source": [
    "A base de dados foi retirada do site Brasi.io. Pode ser encontrado no seguinte link: https://brasil.io/dataset/covid19/files/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "a6f92398",
   "metadata": {},
   "outputs": [
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       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9880</th>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9881</th>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9882 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            date state  epidemiological_week_2020  deaths_covid19\n",
       "0     2020-01-01    AC                          1               0\n",
       "1     2020-01-02    AC                          1               0\n",
       "2     2020-01-03    AC                          1               0\n",
       "3     2020-01-04    AC                          1               0\n",
       "4     2020-01-05    AC                          2               0\n",
       "...          ...   ...                        ...             ...\n",
       "9877  2020-12-27    TO                         53             864\n",
       "9878  2020-12-28    TO                         53             865\n",
       "9879  2020-12-29    TO                         53             865\n",
       "9880  2020-12-30    TO                         53             865\n",
       "9881  2020-12-31    TO                         53             865\n",
       "\n",
       "[9882 rows x 4 columns]"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Vamos visualizar o DataFrame para ver quais informações temos nele\n",
    "obitos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "c293d7ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "        ...  \n",
       "9877    False\n",
       "9878    False\n",
       "9879    False\n",
       "9880    False\n",
       "9881    False\n",
       "Length: 9882, dtype: bool"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Agora vamos ver se há dados duplicados, por exemplo se há algum dia que está repetido:\n",
    "\n",
    "duplicados_obitos = obitos.duplicated()\n",
    "duplicados_obitos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e532451e",
   "metadata": {},
   "source": [
    "Como não apareceu \"True\" em nenhuma linha, podemos dizer que não há dados duplicados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "06a559f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 9882 entries, 0 to 9881\n",
      "Data columns (total 4 columns):\n",
      " #   Column                     Non-Null Count  Dtype \n",
      "---  ------                     --------------  ----- \n",
      " 0   date                       9882 non-null   object\n",
      " 1   state                      9882 non-null   object\n",
      " 2   epidemiological_week_2020  9882 non-null   int64 \n",
      " 3   deaths_covid19             9882 non-null   int64 \n",
      "dtypes: int64(2), object(2)\n",
      "memory usage: 308.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# Vamos visualizar as informações do DataFrame:\n",
    "\n",
    "obitos.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f5f7311",
   "metadata": {},
   "source": [
    "Pudemos ver que há 4 colunas (date, state, epidemiological_week_2020 e deaths_covid19) 9882 linhas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "ecc32eb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame._add_numeric_operations.<locals>.sum of        date  state  epidemiological_week_2020  deaths_covid19\n",
       "0     False  False                      False           False\n",
       "1     False  False                      False           False\n",
       "2     False  False                      False           False\n",
       "3     False  False                      False           False\n",
       "4     False  False                      False           False\n",
       "...     ...    ...                        ...             ...\n",
       "9877  False  False                      False           False\n",
       "9878  False  False                      False           False\n",
       "9879  False  False                      False           False\n",
       "9880  False  False                      False           False\n",
       "9881  False  False                      False           False\n",
       "\n",
       "[9882 rows x 4 columns]>"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Vamos ver se há dados nulos (valor desconhecido ou ausente) no DataFrame e, caso tenha, vamos excluir:\n",
    "obitos.isna().sum"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f90ef84c",
   "metadata": {
    "id": "f90ef84c"
   },
   "source": [
    "Como pudemos ver, não aparece \"True\" nas linhas, isso que dizer que não há valores nulos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "223a744b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Para melhor visualização e para o nosso DataFrame ficar mais apresentável vou renomear o noem das colunas:\n",
    "obitos = obitos.rename(columns={'date':'Data', 'state':'UF', 'epidemiological_week_2020':'Semana Epdemiológica', 'deaths_covid19':'Mortes por Covid-19'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "0c5f15d8",
   "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>Data</th>\n",
       "      <th>UF</th>\n",
       "      <th>Semana Epdemiológica</th>\n",
       "      <th>Mortes por Covid-19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>AC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>AC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>AC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>AC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>AC</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9877</th>\n",
       "      <td>2020-12-27</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9878</th>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9879</th>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9880</th>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9881</th>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>TO</td>\n",
       "      <td>53</td>\n",
       "      <td>865</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9882 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Data  UF  Semana Epdemiológica  Mortes por Covid-19\n",
       "0     2020-01-01  AC                     1                    0\n",
       "1     2020-01-02  AC                     1                    0\n",
       "2     2020-01-03  AC                     1                    0\n",
       "3     2020-01-04  AC                     1                    0\n",
       "4     2020-01-05  AC                     2                    0\n",
       "...          ...  ..                   ...                  ...\n",
       "9877  2020-12-27  TO                    53                  864\n",
       "9878  2020-12-28  TO                    53                  865\n",
       "9879  2020-12-29  TO                    53                  865\n",
       "9880  2020-12-30  TO                    53                  865\n",
       "9881  2020-12-31  TO                    53                  865\n",
       "\n",
       "[9882 rows x 4 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Vamos visualizar a mudança:\n",
    "obitos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e5134a3",
   "metadata": {},
   "source": [
    "# Começando a visualização dos dados"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0afee72d",
   "metadata": {},
   "source": [
    "Vamos começar criando um gráfico que mostre as mortes por Covid-19 do nosso conjunto de dados, para termos uma ideia de como foi o seu crescimento ao longo dos meses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "2d973a7a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criando uma figura, axes e alterando o tamanho:\n",
    "fig, ax = plt.subplots(figsize=(12,8))\n",
    "\n",
    "# Criando o gráfico de linha:\n",
    "obitos.groupby('Data')['Mortes por Covid-19'].sum().sort_values(ascending=True).plot(kind='line')\n",
    "\n",
    "# Adicionando título:\n",
    "ax.set_title('Mortes de Covid-19 por UF', fontdict={'fontsize':20})\n",
    "\n",
    "# Mudando e nome e tamanho dos dados do eixo x:\n",
    "ax.set_xlabel('Data', fontdict={'fontsize':15})\n",
    "\n",
    "# Vamos remover as legendas e os valores do eixo y:\n",
    "ax.tick_params(axis='y', labelleft=False, left=None)    \n",
    "\n",
    "# Otimizando o espaço da figura:\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b378fc6b",
   "metadata": {},
   "source": [
    "Agora vamos criar um gráifoc de barras que nos mostre como se deu a distribuição de mortes pelos estados."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "4779db75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criando uma figura, axes e alterando o tamanho:\n",
    "fig, ax = plt.subplots(figsize=(12,8))\n",
    "\n",
    "# Criando o gráfico de barras:\n",
    "obitos.groupby('UF')['Mortes por Covid-19'].sum().sort_values(ascending=False).plot(kind='bar')\n",
    "\n",
    "# Adicionando título:\n",
    "ax.set_title(\"Mortes de Covid-19 por UF\", fontdict={'fontsize':20})\n",
    "\n",
    "# Mudando e nome e tamanho dos dados do eixo x:\n",
    "ax.set_xlabel('UF', fontdict={'fontsize':20})\n",
    "\n",
    "# Vamos remover as legendas e os valores do eixo y:\n",
    "ax.tick_params(axis='y', labelleft=False, left=None)                  \n",
    "\n",
    "# Otimizando o espaço da figura:\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8beea98",
   "metadata": {},
   "source": [
    "Ao olhar o DataFrame lá no começo, pudemos ver que há uma coluna com a a indicação da semana epdemiológica. Vamos criar um gráfico de barras que nos mostre isso."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "5ea891a5",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criando uma figura, axes e alterando o tamanho:\n",
    "fig, ax = plt.subplots(figsize=(12,8))\n",
    "\n",
    "# Criando o gráfico de barras:\n",
    "obitos.groupby('Semana Epdemiológica')['Mortes por Covid-19'].sum().sort_values(ascending=True).plot(kind='bar')\n",
    "\n",
    "# Adicionando título:\n",
    "ax.set_title('Mortes de Covid-19 por UF', fontdict={'fontsize':20})\n",
    "\n",
    "# Mudando e nome e tamanho dos dados do eixo x:\n",
    "ax.set_xlabel('Semana Epdemiológica', fontdict={'fontsize':15})\n",
    "\n",
    "# Vamos remover as legendas e os valores do eixo y:\n",
    "ax.tick_params(axis='y', labelleft=False, left=None)                  \n",
    "\n",
    "# Otimizando o espaço da figura:\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd8b9a17",
   "metadata": {},
   "source": [
    "Agora já conseguimos ter uma visualização geral de como as mortes se deram em cada estado, no Brasil inteiro e por semana epdemiológica. Mas e se quiséssemos tr uma noção maior da proporção de cada estado no número de mortes, como faríamos? Podemos criar um gráfico de pizza que represente isso."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "9c035edb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vamos agrupar os números de óbitos por estado\n",
    "obitos_pizza = obitos.groupby('UF')['Mortes por Covid-19'].sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "909746af",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Vamos resetar index para que a coluna UF não seja index.\n",
    "obitos_pizza = obitos_pizza.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "5ac2d15a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x3600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Criando um gráfico de pizza\n",
    "fig = plt.figure(figsize=(20,50))\n",
    "plt.pie(obitos_pizza['Mortes por Covid-19'], labels=obitos_pizza['UF'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25124d27",
   "metadata": {},
   "source": [
    "Bom, o gráfico acima nos mostreou a distribuição por estado, mas qual a porcetagem de cada estado? É possível ter uma visualização assim? Sim, é póssível. Veremos abaixo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "d265d31b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "domain": {
          "x": [
           0,
           1
          ],
          "y": [
           0,
           1
          ]
         },
         "hovertemplate": "label=%{label}<br>value=%{value}<extra></extra>",
         "labels": [
          "SP",
          "RJ",
          "CE",
          "MG",
          "BA",
          "PE",
          "PR",
          "PA",
          "RS",
          "GO",
          "ES",
          "DF",
          "SC",
          "MA",
          "AM",
          "PB",
          "AL",
          "MT",
          "RN",
          "SE",
          "MS",
          "PI",
          "RO",
          "AP",
          "AC",
          "RR",
          "TO"
         ],
         "legendgroup": "",
         "name": "",
         "showlegend": true,
         "type": "pie",
         "values": [
          7608909,
          4145484,
          1840282,
          1607090,
          1225750,
          1198557,
          1046258,
          1029211,
          946479,
          935456,
          719106,
          540671,
          529451,
          507554,
          499497,
          468824,
          409503,
          403138,
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   ],
   "source": [
    "fig = px.pie(names = obitos_pizza['UF'], values = obitos_pizza['Mortes por Covid-19'], width = 1000, height = 800)\n",
    "fig.show()"
   ]
  },
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   "source": [
    "## Conclusão\n",
    "Bom, foram poucos gráficos, mas tenho certeza que com a visualização deles ficou muito mais fácil de você entender e perceber como se deu as mortes por Covid-19 no Brasil. Qual estado teve mais mortes, qual teve menos, qual data ou semana epdemiológica teve mais mortes, etc. Enfim, com a visualização gráfica conseguimos ter uma noção maior e fazer diversas inferências, além de criar hipóteses sobre os dados. Por isso, as bibliotecas que nos auxiliam com a visualização de dados são tão importantes. A nossa interpretação somente com DataFrames acaba sendo muito limitada, pois ele não é tão intuitivo quanto os gráficos e figuras, conseguimos compreender os dados de maneira muito mais rápida com imagens."
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