SeabornHistogram (1).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "SeabornHistogram.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "dFlg9YWLogMu",
        "outputId": "a8bb11cf-4872-4580-b4a5-d36d1ad27ef3"
      },
      "source": [
        "import seaborn as sns\r\n",
        "df = sns.load_dataset('iris')\r\n",
        "df"
      ],
      "execution_count": 73,
      "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>sepal_length</th>\n",
              "      <th>sepal_width</th>\n",
              "      <th>petal_length</th>\n",
              "      <th>petal_width</th>\n",
              "      <th>species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>6.7</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.3</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>6.3</td>\n",
              "      <td>2.5</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.9</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>6.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>6.2</td>\n",
              "      <td>3.4</td>\n",
              "      <td>5.4</td>\n",
              "      <td>2.3</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>5.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>1.8</td>\n",
              "      <td>virginica</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_length  sepal_width  petal_length  petal_width    species\n",
              "0             5.1          3.5           1.4          0.2     setosa\n",
              "1             4.9          3.0           1.4          0.2     setosa\n",
              "2             4.7          3.2           1.3          0.2     setosa\n",
              "3             4.6          3.1           1.5          0.2     setosa\n",
              "4             5.0          3.6           1.4          0.2     setosa\n",
              "..            ...          ...           ...          ...        ...\n",
              "145           6.7          3.0           5.2          2.3  virginica\n",
              "146           6.3          2.5           5.0          1.9  virginica\n",
              "147           6.5          3.0           5.2          2.0  virginica\n",
              "148           6.2          3.4           5.4          2.3  virginica\n",
              "149           5.9          3.0           5.1          1.8  virginica\n",
              "\n",
              "[150 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 650
        },
        "id": "K34nOuU9d0Nx",
        "outputId": "eb858c1c-0d87-4c28-b0d2-69d70d58ef8f"
      },
      "source": [
        "# Import library and dataset\r\n",
        "\r\n",
        "sns.histplot( df[\"sepal_length\"],color=[0,0,0],fill=True,bins=20,kde=True,line_kws={'color':\"r\", \"alpha\":1, \"linewidth\": 5} )\r\n",
        "\r\n",
        " \r\n",
        "# Control the number of bins\r\n",
        "sns.displot( df[\"sepal_length\"])\r\n"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f3c88511908>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        },
        {
          "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"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "7qEAsFaAjjeL",
        "outputId": "a1687e0c-36b0-4da0-e9f8-fff43317a4a5"
      },
      "source": [
        "import seaborn as sns\r\n",
        "import matplotlib.pyplot as plt\r\n",
        " \r\n",
        "f, (ax_box, ax_hist) = plt.subplots(2,gridspec_kw={'height_ratios':[0.15,0.85]})\r\n",
        " \r\n",
        "sns.boxplot(x=df[\"sepal_length\"], ax=ax_box)\r\n",
        "sns.histplot(x=df[\"sepal_length\"],bins=20, ax=ax_hist)\r\n",
        " \r\n"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f3c876655f8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "XVEvrYYSln5u",
        "outputId": "10f5d3f8-ab78-4d8a-9c72-cff48801cdeb"
      },
      "source": [
        "import seaborn as sns\r\n",
        " \r\n",
        "a=sns.histplot( df, x=\"sepal_length\", element=\"step\")\r\n",
        "\r\n",
        "sns.histplot(  df, x=\"sepal_width\", element=\"poly\",color=[0,1,1])\r\n",
        "a.set_xlabel('Sepal_Length-Sepal Width')\r\n",
        "\r\n",
        "\r\n"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Sepal_Length-Sepal Width')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        },
        {
          "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": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "oRPmmRxan11M",
        "outputId": "863226f4-5c51-49de-8d2c-5db8ebe15582"
      },
      "source": [
        "sns.histplot(  df, x=\"sepal_width\", element=\"poly\",color=[0,1,1])\r\n",
        "a.set_xlabel('Sepal_Length-Sepal Width')\r\n",
        "\r\n",
        "\r\n",
        "sns.histplot( df,x='sepal_width', hue=\"species\",kde=True)"
      ],
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f3c876b1f28>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        },
        {
          "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"
          }
        }
      ]
    }
  ]
}