grafico_histograma.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Welcome To Colaboratory",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gilissantos/Matplotlib---Python/blob/master/grafico_histograma.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "esKNyd1LPBq0",
        "colab_type": "text"
      },
      "source": [
        "<h1 align=\"center\">Gráfico de Histograma - Python/Matplotlib</h1>\n",
        "\n",
        "<p>\n",
        "O gráfico de Histograma representa a frequência/distribuição de um conjunto de dados, por exemplo quantos alunos estão acima, abaixo ou igual a média.\n",
        "Para maiores informações sobre sobre gráfico de histograma, acesse o <a href=\"https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.hist.html\">portal oficial da biblioteca Matplotlib</a>. Vamos ao código.\n",
        "</p>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QoOmWqBuRG_8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Importando as bibliotecas Pandas, Numpy e Matplotlib:\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import random "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CoWjHnThRTr3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "cb8f150a-c231-45df-b707-67188d1b6f8b"
      },
      "source": [
        "# Criando a variável vendas com valores aleatórios com uma amostra de 100 valores:\n",
        "\n",
        "venda = np.random.randint(10, size=(100))\n",
        "venda"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 9, 5, 3, 8, 2, 2, 3, 7, 5, 4, 7, 6, 1, 9, 1, 4, 0, 6, 3, 9, 0,\n",
              "       0, 5, 2, 9, 3, 1, 1, 2, 5, 3, 0, 8, 2, 4, 4, 8, 4, 6, 3, 4, 0, 4,\n",
              "       0, 1, 8, 2, 3, 4, 5, 4, 6, 3, 8, 5, 5, 3, 2, 6, 4, 5, 5, 0, 0, 4,\n",
              "       3, 4, 6, 2, 4, 7, 7, 5, 1, 2, 8, 5, 7, 0, 1, 4, 4, 1, 6, 9, 3, 0,\n",
              "       0, 7, 6, 3, 2, 3, 8, 9, 3, 0, 0, 1])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UrWM55gESb4I",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366
        },
        "outputId": "979aac03-e718-4d41-ad89-61e8a210136c"
      },
      "source": [
        "fig = plt.figure()\n",
        "ax = fig.add_axes([0,0,1,1])\n",
        "ax.hist(venda, bins=10)\n",
        "ax.set_title(\"Gráfico de Histograma\")\n",
        "ax.set_xlabel(\"Vendas\")\n",
        "ax.set_ylabel(\"Frequência\")\n",
        "ax.set_yticks([0, 5, 10, 15, 20])\n",
        "ax.set_ylim(0, 20)\n",
        "plt.show()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "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"
          }
        }
      ]
    }
  ]
}