Criação_de_Visualizações_com_Matplotlib_e_Seaborn.ipynb

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        "Nosso cérebro está conectado de uma forma que facilita a extração de padrões ou tendências de dados visuais em comparação com a extração de detalhes com base na leitura ou outros meios.\n",
        "Este foi escrito por sharan e é extremamente interessante!\n",
        "\n",
        "# Como criar visualizações impressionantes usando python do zero\n",
        "\n",
        "##Um guia passo a passo usando as bibliotecas Matplotlib e Seaborn\n",
        "\n",
        "#Sharan Kumar Ravindran\n",
        "\n",
        "Imagem para postagem\n",
        "\n",
        "Foto de Luke Chesser no Unsplash\n",
        "\n",
        "A visualização é um conjunto importante de habilidades para um cientista de dados. Uma boa visualização pode ajudar a comunicar com clareza os insights identificados na análise também é uma boa técnica para entender melhor o conjunto de dados. Nosso cérebro está conectado de uma forma que facilita a extração de padrões ou tendências de dados visuais em comparação com a extração de detalhes com base na leitura ou outros meios.\n",
        "\n",
        "Neste artigo, estarei cobrindo o conceito de visualização desde o básico usando Python. Abaixo estão as etapas para aprender a visualização do básico,\n",
        "\n",
        "Etapa 1: Importar dados\n",
        "Etapa 2: Visualização básica usando Matplotlib\n",
        "Etapa 3: visualizações mais avançadas, ainda usando Matplotlib\n",
        "Etapa 4: construir visualizações rápidas para análise de dados usando Seaborn\n",
        "Etapa 5: construir gráficos interativos\n",
        "\n",
        "Ao final desta jornada, você estará equipado com tudo o que é necessário para construir uma visualização. Embora não iremos cobrir todas as visualizações que podem ser construídas, você aprenderá os conceitos por trás da construção de um gráfico e, portanto, seria fácil para você construir qualquer gráfico novo que não seja abordado neste artigo.\n",
        "\n",
        "Os scripts e os dados usados ​​neste artigo também podem ser encontrados no repositório git [aqui](https://github.com/rsharankumar/Learn_Data_Science_in_100Days). Todos os dados usados ​​neste artigo podem ser encontrados na pasta \"Data\" dentro do repositório git mencionado e os scripts estão disponíveis nas pastas ‘Dia23, Dia 24 e Dia25’.\n",
        "\n",
        "#Importando Dados\n",
        "\n",
        "A primeira etapa é ler os conjuntos de dados necessários. Podemos usar pandas para ler os dados. Abaixo está um comando simples que pode ser usado para ler dados de um arquivo CSV\n",
        "\n",
        "https://gist.github.com/rsharankumar/f99da3bd4ea2f44280a820d31f13ebd2/raw/f06284d2fd479fdf1da71a9a6dd122ca2756454c/art01_read_data\n",
        "\n",
        "*#import pandas library and provide alias name as pd\n",
        "import pandas as pd\n",
        "# Data from: https://www.kaggle.com/shivamb/netflix-shows\n",
        "netflix_data = pd.read_csv('../Data/netflix_titles.csv')\n",
        "netflix_data.head()*\n",
        "\n"
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        "#import pandas library and provide alias name as pd\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "sns.set_theme(style=\"darkgrid\")\n",
        "\n",
        "# Data from: https://www.kaggle.com/shivamb/netflix-shows\n",
        "netflix_data = pd.read_csv('https://raw.githubusercontent.com/rsharankumar/Learn_Data_Science_in_100Days/master/Data/netflix_titles.csv')\n",
        "netflix_data.head()"
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      "source": [
        "Ao ler o conjunto de dados, é importante transformá-lo e torná-lo adequado para a visualização que aplicaremos. Por exemplo, digamos que temos detalhes de vendas no nível do cliente e se quisermos construir um gráfico que mostra a tendência de vendas do dia, então é necessário agrupar os dados e agregá-los no nível do dia e, em seguida, usar uma tendência gráfico.\n",
        "\n",
        "#Visualização básica usando Matplotlib\n",
        "\n",
        "Vamos começar com algumas visualizações básicas. É melhor usar o código *'fig, ax = plt.subplots ()'*, onde *'plt.subplots ()'* é uma função que retornará uma tupla com objetos de figura e eixos e atribuída às variáveis *​​'fig'* e *' ax '* respectivamente. Sem usar isso também, você pode imprimir um gráfico, mas usando isso você será capaz de fazer alterações na figura como se fosse capaz de redimensionar os gráficos dependendo de sua aparência e também salvar o gráfico. Da mesma forma, a variável *'ax'* aqui pode ser usada para fornecer rótulos aos eixos. Abaixo está um exemplo simples onde passei os dados como um array e os imprimi diretamente como um gráfico\n",
        "\n",
        "https://gist.github.com/rsharankumar/61a9142b4906ad0c75da8bf537a16357/raw/37d3f9e041858ad65c369c6a4d3b4c6483fa93a7/VisualizationArticle_01.ipynb\n",
        "\n",
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        "fig, ax = plt.subplots()  \n",
        "# Creating some  dummy data\n",
        "ax.plot([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [3, 2, 4, 5, 8, 2, 5, 7, 4, 6])"
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "22bkFTFcZxvX",
        "outputId": "3b4bac0e-c73c-48e4-829a-9f96c2e5efa2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        }
      },
      "source": [
        "#  Declare a chart with one Axis\n",
        "fig, ax = plt.subplots()  \n",
        "# Creating some  dummy data\n",
        "ax.plot([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [3, 2, 4, 5, 8, 2, 5, 7, 4, 6], label = 'data1')\n",
        "ax.plot([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [1, 2, 3, 2, 3, 1, 2, 3, 1, 4], label = 'data2') \n",
        "ax.set_xlabel('x axis') \n",
        "ax.set_ylabel('y axis')\n",
        "ax.set_title(\"Sample Chart\")\n",
        "#ax.legend()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Sample Chart')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AkiJVuFTaGc9"
      },
      "source": [
        "No código acima, primeiro, as bibliotecas necessárias são importadas e, em seguida, a função *'plt.subplots ()'* é usada para gerar a figura e os objetos de eixos e, em seguida, os dados são passados ​​diretamente como uma matriz para o objeto de eixos para imprimir o gráfico. No segundo gráfico, a variável de eixos *'ax'* tomou entradas para rótulos específicos para o eixo x, eixo y e o título.\n",
        "\n",
        "#Gráficos de tendência\n",
        "\n",
        "Agora, vamos começar a usar alguns dados reais e aprender como construir gráficos interessantes e personalizá-los para torná-los mais intuitivos. Conforme explicado, na maioria dos casos de uso da vida real, os dados exigiriam alguma transformação para torná-los utilizáveis ​​para os gráficos. Abaixo está um exemplo em que usei os dados do Netflix, mas transformei os dados para consolidar o número de filmes e programas de TV por ano. E então eu usei a função *‘plt.subplots ()’*, mas também adicionei alguns detalhes adicionais para tornar o gráfico mais intuitivo e autoexplicativo.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "22lT5T0ja2zJ",
        "outputId": "12700df7-f7af-4c3d-ca89-2101138d5195",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        }
      },
      "source": [
        "\n",
        "n_data = netflix_data.groupby(['release_year', 'type'], as_index=False).show_id.count()\n",
        "n_data.columns = ['release_year', 'type', 'count']\n",
        "n_data_pivot = n_data.pivot(index='release_year', columns='type', values='count').reset_index()\n",
        "n_data_pivot.fillna(0, inplace = True)\n",
        "n_data_pivot.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>type</th>\n",
              "      <th>release_year</th>\n",
              "      <th>Movie</th>\n",
              "      <th>TV Show</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1925</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1942</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1943</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1944</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1945</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "type  release_year  Movie  TV Show\n",
              "0             1925    0.0      1.0\n",
              "1             1942    2.0      0.0\n",
              "2             1943    3.0      0.0\n",
              "3             1944    3.0      0.0\n",
              "4             1945    3.0      0.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A8nDcpy1bSdW",
        "outputId": "2ebab49c-c985-43cc-d922-afd74a522e0b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 665
        }
      },
      "source": [
        "#  Declare a chart with one Axis\n",
        "fig, ax = plt.subplots()  \n",
        "\n",
        "# Creating some  dummy data\n",
        "ax.plot(n_data_pivot.release_year, n_data_pivot.Movie, label = 'Movies')\n",
        "ax.plot(n_data_pivot.release_year, n_data_pivot['TV Show'], label = 'Tv Shows') \n",
        "ax.set_ylabel('Number of Movies/TV Shows') \n",
        "ax.set_xlabel('Year of Release')\n",
        "ax.set_title(\"Trend Chart\")\n",
        "plt.text(x=1970, y=400, s=r'Majority Movies are released after 2000 and Tv Shows mostly after 2010')#, fontsize = 12)\n",
        "fig.set_size_inches(18.5, 10.5)\n",
        "plt.grid()\n",
        "ax.legend()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7fea5af05128>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1332x756 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-DaKAnhUa3PB"
      },
      "source": [
        "\n",
        "\n",
        "Existem mais algumas personalizações que podem ser feitas no gráfico acima, como a criação de um eixo duplo. No caso acima, não há muita diferença entre o número de filmes e programas de TV, portanto, os dados parecem OK, se houver uma grande diferença entre eles, o gráfico não será muito claro, nesses casos podemos fazer uso eixo duplo para que o atributo com valores menores também seja escalado em linha com o outro.\n",
        "\n",
        "#Gráficos de dispersão\n",
        "\n",
        "Também podemos usar o gráfico de dispersão, para revelar qualquer relação entre as variáveis ​​que estamos traçando. Este gráfico ajuda a trazer a correlação entre variáveis ​​como o que acontece com um atributo quando o outro atributo está aumentando / diminuindo.\n",
        "\n",
        "#Mais visualizações avançadas, ainda usando Matplotlib\n",
        "\n",
        "Assim que estiver confortável com os gráficos de tendência simples que cobrimos até agora, você estará pronto para passar para gráficos e funcionalidades um pouco mais avançados para personalizar melhor sua visualização\n",
        "\n",
        "#Gráficos de barra\n",
        "\n",
        "Os gráficos de barras nos ajudam a comparar vários valores ao mesmo tempo, plotando-os lado a lado. Existem diferentes tipos de gráficos de barras,\n",
        "\n",
        "  - Gráfico de Barras Verticais\n",
        "\n",
        "  - Gráfico de Barras Horizontais\n",
        "\n",
        "  - Gráfico de Barras Empilhadas\n",
        "\n",
        "\n",
        "Abaixo está um exemplo de um gráfico de barras, há uma série de personalizações adicionadas a este gráfico. Eles são,\n",
        "\n",
        "  - Rótulos de eixo e títulos são adicionados\n",
        "  - O tamanho da fonte foi fornecido\n",
        "  - O tamanho da figura também é fornecido (o gráfico padrão pareceria muito menor e desordenado)\n",
        "  - Uma função é usada para gerar e adicionar valores ao topo de cada uma das barras para ajudar os visualizadores a obter os detalhes reais\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DIEhQHRocnH5",
        "outputId": "4a9bdbad-6582-484b-c626-ec4a61385d9d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        }
      },
      "source": [
        "# Data from: https://www.kaggle.com/shivamb/netflix-shows\n",
        "# With transformations\n",
        "\n",
        "netflix_data['year_added'] = netflix_data['date_added'].str.slice(start=-4)\n",
        "n_data_added = netflix_data.groupby(['year_added', 'type'], as_index=False).show_id.count()\n",
        "n_data_added.columns = ['year_added', 'type', 'count']\n",
        "n_data_added = n_data_added.pivot(index='year_added', columns='type', values='count').reset_index()\n",
        "n_data_added.fillna(0, inplace = True)\n",
        "n_data_added.head()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>type</th>\n",
              "      <th>year_added</th>\n",
              "      <th>Movie</th>\n",
              "      <th>TV Show</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2008</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2009</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2010</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2011</td>\n",
              "      <td>13.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2012</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "type year_added  Movie  TV Show\n",
              "0          2008    1.0      1.0\n",
              "1          2009    2.0      0.0\n",
              "2          2010    1.0      0.0\n",
              "3          2011   13.0      0.0\n",
              "4          2012    4.0      3.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SH9Uw_mxc0ts",
        "outputId": "da32b369-02eb-4649-f50e-1cb91a130915",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 754
        }
      },
      "source": [
        "\n",
        "labels = n_data_added['year_added']\n",
        "\n",
        "x = np.arange(len(labels))  # the label locations\n",
        "width = 0.35  # the width of the bars\n",
        "\n",
        "fig, ax = plt.subplots()\n",
        "Movies_rects = ax.bar(x - width/2, n_data_added['Movie'], width, label='Movies') # Add color here\n",
        "TVshows_rects = ax.bar(x + width/2, n_data_added['TV Show'], width, label='TV Show')\n",
        "\n",
        "# Add some text for labels, title, configure chart size\n",
        "ax.set_xlabel('Year added on Netflex')\n",
        "ax.set_ylabel('Count of Number of Movies/TV Shows')\n",
        "ax.set_title('Number of movies and TV Shows by year they got added')\n",
        "ax.set_xticks(x)\n",
        "ax.set_xticklabels(labels)\n",
        "fig.set_size_inches(18.5, 10.5)\n",
        "plt.rcParams.update({'font.size': 15})\n",
        "ax.legend()\n",
        "\n",
        " #Function to generate labels on top of the bars\n",
        "def gen_label(rects):\n",
        "    \"\"\"Attach a text label above each bar in *rects*, displaying its height.\"\"\"\n",
        "    for rect in rects:\n",
        "        height = rect.get_height()\n",
        "        ax.annotate('{}'.format(height),\n",
        "                    xy=(rect.get_x() + rect.get_width() / 2, height),\n",
        "                    xytext=(0, 3),  # 3 points vertical offset\n",
        "                    textcoords=\"offset points\",\n",
        "                    ha='center', va='bottom')\n",
        "\n",
        "\n",
        "gen_label(Movies_rects)\n",
        "gen_label(TVshows_rects)\n",
        "\n",
        "fig.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1332x756 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HtdoCaP2cnhS"
      },
      "source": [
        "#Gráfico de barras horizontais e empilhadas\n",
        "\n",
        "Os gráficos de barras verticais são mais comuns, mas também podemos fazer uso dos gráficos de barras horizontais, especialmente quando as etiquetas de dados têm um nome longo e é muito difícil imprimi-los abaixo de uma barra vertical. No caso do gráfico de barras empilhadas, as barras serão empilhadas umas sobre as outras dentro de uma categoria. abaixo está o exemplo de implementação dos gráficos de barras horizontais e empilhadas. O código abaixo também inclui personalização para a cor do gráfico.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IKSYlusNdMty",
        "outputId": "016f0165-c192-41ce-8737-8d45d7792a18",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 635
        }
      },
      "source": [
        "\n",
        "data = pd.DataFrame(dict(Year = n_data_added['year_added'],\n",
        "                       Movie = n_data_added['Movie'], TVshow=n_data_added['TV Show'])) \n",
        "\n",
        "ind = np.arange(len(data))\n",
        "width = 0.4\n",
        "\n",
        "fig1, ax1 = plt.subplots()\n",
        "ax1.barh(ind, data.Movie, width, color='red', label='Movies')\n",
        "ax1.barh(ind + width, data.TVshow, width, color='green', label='TV Shows')\n",
        "\n",
        "ax1.set(yticks=ind + width, yticklabels=data.Year, ylim=[2*width - 1, len(data)])\n",
        "\n",
        "ax1.set_ylabel('Year added on Netflex')\n",
        "ax1.set_xlabel('Count of Number of Movies/TV Shows')\n",
        "ax1.set_title('Number of movies and TV Shows by year they got added')\n",
        "\n",
        "ax1.legend()\n",
        "fig1.set_size_inches(10, 10)\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gr5NUoHadNDw"
      },
      "source": [
        "#Gráfico de pizza e donut\n",
        "\n",
        "Os gráficos de pizza são úteis para mostrar a proporção de diferentes categorias nos dados e esses gráficos de pizza podem ser facilmente modificados para um gráfico de rosca cobrindo a parte central do gráfico de pizza com um círculo e realinhando o texto / valores para se adequar à rosca gráfico. Abaixo está um exemplo simples onde implementei o gráfico de pizza e, posteriormente, o modifiquei em um gráfico de rosca\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YcKIsQyldf7S",
        "outputId": "c9cad674-5b83-4165-ae82-3455f9ad74ea",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 167
        }
      },
      "source": [
        "# Small modification to data to suit for the Pie Chart\n",
        "n_data_added['Total'] = n_data_added['Movie'] + n_data_added['TV Show']\n",
        "# To select last few rows only\n",
        "n_data_added_flt = n_data_added[-4:]\n",
        "n_data_added_flt = n_data_added_flt.reset_index(drop=True) # For resetting index\n",
        "n_data_added_flt.head()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>type</th>\n",
              "      <th>year_added</th>\n",
              "      <th>Movie</th>\n",
              "      <th>TV Show</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2017</td>\n",
              "      <td>913.0</td>\n",
              "      <td>387.0</td>\n",
              "      <td>1300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2018</td>\n",
              "      <td>1290.0</td>\n",
              "      <td>492.0</td>\n",
              "      <td>1782.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2019</td>\n",
              "      <td>1546.0</td>\n",
              "      <td>803.0</td>\n",
              "      <td>2349.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020</td>\n",
              "      <td>147.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>184.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "type year_added   Movie  TV Show   Total\n",
              "0          2017   913.0    387.0  1300.0\n",
              "1          2018  1290.0    492.0  1782.0\n",
              "2          2019  1546.0    803.0  2349.0\n",
              "3          2020   147.0     37.0   184.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6liVFNeKdlrz",
        "outputId": "90107878-b673-414a-ecfb-326ab9a2b68c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        }
      },
      "source": [
        "\n",
        "# Pie chart\n",
        "labels = n_data_added_flt['year_added']\n",
        "sizes = n_data_added_flt['Total']\n",
        "explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice \n",
        "\n",
        "fig2, ax2 = plt.subplots()\n",
        "ax2.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
        "        shadow=True, startangle=90)\n",
        "ax2.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "77mwAAPZdgeG"
      },
      "source": [
        "#Por que é importante aprender Matplotlib?\n",
        "\n",
        "Matplotlib é uma biblioteca de visualização muito importante em python porque muitas outras bibliotecas de visualização em python são dependentes de matplotlib. Algumas das vantagens / benefícios de aprender matplotib são,\n",
        "  - É fácil de aprender\n",
        "  - É eficiente\n",
        "  - Permite muitas personalizações, portanto, é possível construir quase qualquer tipo de visual\n",
        "  - Bibliotecas como a Seaborn são construídas em cima do Matpotlib\n",
        "\n",
        "Eu cobri apenas a visualização mais essencial no Matplotlib, mas o fator importante é, praticando esses gráficos, você teá adquirido o conhecimento para construir muito mais visualizações. Matplotlib suporta uma série de visualizações [aqui](https://matplotlib.org/3.1.0/gallery/index.html) está o link para a galeria de todos os gráficos suportados.\n",
        "\n",
        "#Criação de visualizações rápidas para análise de dados usando Seaborn\n",
        "\n",
        "Cobrimos uma variedade de visualização usando a biblioteca Matplotlib. Não tenho certeza se você percebeu, embora o matplotlib ofereça alta personalização, ele envolve muita codificação e, portanto, pode ser demorado, especialmente quando você está trabalhando em análises exploratórias e gostaria de fazer alguns gráficos rápidos para entender melhor os dados e tome as decisões mais rapidamente. Isso é exatamente o que é oferecido pela biblioteca Seaborn, aqui estão alguns benefícios de usar a biblioteca Seaborn:\n",
        "\n",
        "  - Temas padrão ainda são atraentes\n",
        "  - Simples e rápido de construir visualizações, especialmente para análise de dados\n",
        "  - Sua API declarativa nos permite focar apenas nos elementos-chave dos gráficos\n",
        "\n",
        "Também existem algumas desvantagens, pois não oferece muita personalização e pode levar a problemas de memória, especialmente quando trabalhamos com grandes conjuntos de dados. Mesmo assim, o benefício supera as desvantagens.\n",
        "\n",
        "#Visualizações com apenas um código de linha\n",
        "\n",
        "Abaixo estão algumas visualizações simples que são implementadas com apenas um único código usando a biblioteca seaborn.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kJqzL1GWfJ3L",
        "outputId": "812fb624-b74f-48f7-a885-fc9966886d93",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        }
      },
      "source": [
        "# Data from: https://www.kaggle.com/andrewmvd/heart-failure-clinical-data\n",
        "heart_failure_data = pd.read_csv('https://raw.githubusercontent.com/rsharankumar/Learn_Data_Science_in_100Days/master/Data/heart_failure_clinical_records_dataset.csv')\n",
        "heart_failure_data.head()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>age</th>\n",
              "      <th>anaemia</th>\n",
              "      <th>creatinine_phosphokinase</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>ejection_fraction</th>\n",
              "      <th>high_blood_pressure</th>\n",
              "      <th>platelets</th>\n",
              "      <th>serum_creatinine</th>\n",
              "      <th>serum_sodium</th>\n",
              "      <th>sex</th>\n",
              "      <th>smoking</th>\n",
              "      <th>time</th>\n",
              "      <th>DEATH_EVENT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>75</td>\n",
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              "      <td>263358.03</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>65</td>\n",
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              "      <td>146</td>\n",
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              "      <td>20</td>\n",
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              "      <td>162000.00</td>\n",
              "      <td>1.3</td>\n",
              "      <td>129</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>111</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>210000.00</td>\n",
              "      <td>1.9</td>\n",
              "      <td>137</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>160</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>327000.00</td>\n",
              "      <td>2.7</td>\n",
              "      <td>116</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  anaemia  creatinine_phosphokinase  ...  smoking  time  DEATH_EVENT\n",
              "0   75        0                       582  ...        0     4            1\n",
              "1   55        0                      7861  ...        0     6            1\n",
              "2   65        0                       146  ...        1     7            1\n",
              "3   50        1                       111  ...        0     7            1\n",
              "4   65        1                       160  ...        0     8            1\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Cm5MH4K9fm-0",
        "outputId": "bcdfbde5-98e9-4585-8f1f-e98f0e0f0a73",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        }
      },
      "source": [
        "# transforming data for visualization\n",
        "agg_data = heart_failure_data.groupby(['age', 'DEATH_EVENT'], as_index=False).ejection_fraction.count()\n",
        "agg_data.columns = ['Age', 'Death_Event', 'Count']\n",
        "agg_data.head()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Age</th>\n",
              "      <th>Death_Event</th>\n",
              "      <th>Count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>40</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>42</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>42</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>43</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Death_Event  Count\n",
              "0   40            0      7\n",
              "1   41            0      1\n",
              "2   42            0      6\n",
              "3   42            1      1\n",
              "4   43            0      1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q0hKGC83gGiU"
      },
      "source": [
        "Gráfico de tendência"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l_o5sgoAel0a",
        "outputId": "a30e2799-cc32-4480-8cff-1ecad0044c0f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382
        }
      },
      "source": [
        "sns.relplot(x=\"Age\", y=\"Count\", \n",
        "            hue=\"Death_Event\" , aspect=16/9,\n",
        "            kind=\"line\", data=agg_data);"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 725.675x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ehUqzLwngJQO"
      },
      "source": [
        "Gráfico de dispersão"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-BX22qkTf9pG",
        "outputId": "b218245f-5e91-43ff-a8f3-0c2ac4dc8f96",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382
        }
      },
      "source": [
        "\n",
        "sns.relplot(x=\"serum_creatinine\", y=\"ejection_fraction\", \n",
        "            hue=\"DEATH_EVENT\", kind=\"scatter\", # Kind is optional\n",
        "            data=heart_failure_data, aspect=16/9);"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 734.8x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "facxqBHLgXO2",
        "outputId": "383d2fc3-3ff2-4f47-8055-fe49466f341b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382
        }
      },
      "source": [
        "sns.relplot(x=\"serum_creatinine\", y=\"ejection_fraction\", \n",
        "            hue=\"DEATH_EVENT\", kind=\"scatter\", # Kind is optional\n",
        "            style=\"smoking\",\n",
        "            data=heart_failure_data, aspect=16/9);"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 743.6x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZdpJKB-OemQr"
      },
      "source": [
        "\n",
        "\n",
        "Conforme mostrado no instantâneo acima, as visualizações são criadas com apenas uma única linha de código e também parecem bastante apresentáveis. A biblioteca Seaborn é amplamente utilizada na fase de análise de dados, pois podemos construir gráficos rapidamente, com facilidade e com mínimo / nenhum efeito para torná-los apresentáveis. A visualização é fundamental na análise de dados, pois ajudam a revelar padrões nos dados e a biblioteca marítima é adequada para o propósito.\n",
        "\n",
        "#Mapas de calor\n",
        "\n",
        "Os mapas de calor são outra visualização interessante amplamente usada em dados de série temporal para revelar as sazonalidades e outros padrões no conjunto de dados. No entanto, para construir um mapa de calor, precisamos transformar os dados em um formato específico para suportar a plotagem de mapa de calor. Abaixo está um código de amostra para transformar os dados de acordo com o gráfico do mapa de calor e a biblioteca marítima usada para construir o mapa de calor\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xO7oH1-dhCjO",
        "outputId": "69547167-4483-4c2b-87e3-473d35e0c906",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        }
      },
      "source": [
        "# Data for heatmap\n",
        "agg_data2 = heart_failure_data.groupby(['age', 'ejection_fraction'], as_index=False).DEATH_EVENT.sum()\n",
        "agg_data2.columns = ['Age', 'ejection_fraction', 'Deaths']\n",
        "agg_data2_p = agg_data2.pivot(index='Age', columns='ejection_fraction', values='Deaths')\n",
        "agg_data2_p.fillna(0, inplace=True)\n",
        "agg_data2_p.head(20)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>ejection_fraction</th>\n",
              "      <th>14</th>\n",
              "      <th>15</th>\n",
              "      <th>17</th>\n",
              "      <th>20</th>\n",
              "      <th>25</th>\n",
              "      <th>30</th>\n",
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              "      <th>38</th>\n",
              "      <th>40</th>\n",
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              "      <th>50</th>\n",
              "      <th>55</th>\n",
              "      <th>60</th>\n",
              "      <th>62</th>\n",
              "      <th>65</th>\n",
              "      <th>70</th>\n",
              "      <th>80</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
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              "      <th>40</th>\n",
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              "    <tr>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>43</th>\n",
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              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "ejection_fraction   14   15   17   20   25   30  ...   55   60   62   65   70   80\n",
              "Age                                              ...                              \n",
              "40                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "41                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "42                 0.0  1.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "43                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "44                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "45                 1.0  0.0  0.0  1.0  1.0  2.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "46                 0.0  0.0  1.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "47                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "48                 0.0  0.0  0.0  0.0  0.0  1.0  ...  1.0  0.0  0.0  0.0  0.0  0.0\n",
              "49                 0.0  0.0  0.0  1.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "50                 0.0  0.0  0.0  1.0  0.0  1.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "51                 0.0  0.0  0.0  0.0  1.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "52                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "53                 0.0  0.0  0.0  1.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "54                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  1.0  0.0\n",
              "55                 0.0  0.0  0.0  1.0  1.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "56                 0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "57                 0.0  0.0  0.0  0.0  0.0  1.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "58                 0.0  0.0  0.0  0.0  1.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "59                 0.0  0.0  0.0  1.0  2.0  0.0  ...  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "\n",
              "[20 rows x 17 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tmvWeFsnhRrv"
      },
      "source": [
        "Mapa de calor"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tF8jO6UbhL-F",
        "outputId": "d7cab910-ee25-46e4-8633-4670afa1b3af",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 886
        }
      },
      "source": [
        "\n",
        "plt.subplots(figsize=(20,15))\n",
        "sns.heatmap(agg_data2_p, annot=True)\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1080 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oFql9rKQhDIL"
      },
      "source": [
        "#Pair Plot - minha funcionalidade favorita do Seaborn\n",
        "\n",
        "Considero o enredo de pares uma das melhores características da biblioteca do *seaborn*. Ajuda na comparação de cada atributo no conjunto de dados com todos os outros atributos por meio de recursos visuais e novamente em uma única linha de código. Abaixo está um exemplo de código para construir gráficos de pares. O uso de um gráfico de pares pode não ser viável quando o conjunto de dados em que estamos trabalhando tem um grande número de colunas. Nesses casos, os gráficos de pares podem ser usados ​​para analisar a relação entre um conjunto específico de atributos sozinho.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0BCS_USMhxU8",
        "outputId": "36607966-2587-4530-a710-f1fe574fff44",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        }
      },
      "source": [
        "subset = heart_failure_data.iloc[:,[0,1,2,3,4]]\n",
        "subset.head()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>age</th>\n",
              "      <th>anaemia</th>\n",
              "      <th>creatinine_phosphokinase</th>\n",
              "      <th>diabetes</th>\n",
              "      <th>ejection_fraction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>75</td>\n",
              "      <td>0</td>\n",
              "      <td>582</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>55</td>\n",
              "      <td>0</td>\n",
              "      <td>7861</td>\n",
              "      <td>0</td>\n",
              "      <td>38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>65</td>\n",
              "      <td>0</td>\n",
              "      <td>146</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>50</td>\n",
              "      <td>1</td>\n",
              "      <td>111</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>1</td>\n",
              "      <td>160</td>\n",
              "      <td>1</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   age  anaemia  creatinine_phosphokinase  diabetes  ejection_fraction\n",
              "0   75        0                       582         0                 20\n",
              "1   55        0                      7861         0                 38\n",
              "2   65        0                       146         0                 20\n",
              "3   50        1                       111         0                 20\n",
              "4   65        1                       160         1                 20"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dUN09yDwh7WJ",
        "outputId": "8d76724a-dd39-49ec-b7b8-9812155a8e65",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        }
      },
      "source": [
        "\n",
        "sns.pairplot(subset)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fea4cd662b0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 900x900 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mrxTYqRphxzI"
      },
      "source": [
        "\n",
        "\n",
        "#Criação de gráficos interativos\n",
        "\n",
        "Ao trabalhar em projetos de ciência de dados, às vezes havia a necessidade de compartilhar alguma visualização com as equipes de negócios. Ferramentas de painel são amplamente usados ​​para esse propósito, mas digamos que haja um padrão interessante que você percebeu ao realizar a análise de dados e gostaria de compartilhá-lo com o usuário empresarial. Se eles forem compartilhados como uma imagem, pode não haver muito que o usuário empresarial possa fazer, mas se forem compartilhados como um gráfico interativo, isso dá ao usuário empresarial o poder de ver os detalhes granulares aumentando ou diminuindo o zoom ou usar outra funcionalidade para interagir com o gráfico. Abaixo está um exemplo onde estamos criando um arquivo HTML como uma saída que inclui a visualização que pode ser compartilhada com qualquer outro usuário e pode ser simplesmente aberto em um navegador da web.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ynk3KjCgiXsc"
      },
      "source": [
        "\n",
        "from bokeh.plotting import figure, output_file, show\n",
        "\n",
        "p = figure(title = \"Age Vs Ejection Fraction\")\n",
        "p.xaxis.axis_label = 'Age'\n",
        "p.yaxis.axis_label = 'Ejection Fraction'\n",
        "\n",
        "p.circle(agg_data2[\"Age\"], agg_data2[\"ejection_fraction\"],\n",
        "         fill_alpha=0.2, size=10)\n",
        "\n",
        "output_file(\"test.html\", title=\"Example\")\n",
        "\n",
        "show(p)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bdo2jIXPiYOo"
      },
      "source": [
        "\n",
        "Se você estiver interessado em aprender sobre visualizações usando python, verifique minha lista de reprodução abaixo. Inclui três vídeos, com uma duração total do tutorial de pouco mais de uma hora.\n",
        "\n",
        "Sobre Sharan Kumar Ravindran\n",
        "É um profissional de Data Science com mais de 10 anos de experiência e autor de 2 livros na área de Data Science, que estão disponíveis para venda [aqui](https://www.amazon.com/Sharan-Kumar-Ravindran/e/B015SUYR2S/ref=dp_byline_cont_ebooks_1). Tem um canal no YouTube onde ensina e conversa sobre vários conceitos de ciência de dados. Se estiver interessado, inscreva-se no meu canal abaixo.\n",
        "[Ciência de dados com Sharan](https://www.youtube.com/c/DataSciencewithSharan)\n",
        "\n",
        "\n",
        "ESCRITO POR Sharan Kumar Ravindran\n",
        "Cientista de dados | Autor | youtube.com/c/DataSciencewithSharan | rsharankumar.com | @rsharankumar\n"
      ]
    }
  ]
}