SeabornBoxplot.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "SeabornBoxplot.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "sGR_3dWyr77w",
        "outputId": "8abae644-fca0-4685-de4c-a804a7cd860a"
      },
      "source": [
        "import seaborn as sns\r\n",
        "df = sns.load_dataset('iris')\r\n",
        "df"
      ],
      "execution_count": 1,
      "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": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "bTEgIJHGsxmV",
        "outputId": "56bb2234-b075-451f-8ac7-314b408c1b3c"
      },
      "source": [
        "#fliersize is the outlier size\r\n",
        "\r\n",
        "\r\n",
        "ax = sns.boxplot(x='species', y='sepal_length', data=df,fliersize=15,)\r\n",
        "ax = sns.swarmplot(x='species', y='sepal_length', data=df, color=\"red\")\r\n"
      ],
      "execution_count": 8,
      "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"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "BEX6mb7RtUyW",
        "outputId": "aca9450f-c497-496e-e460-5e3fa1e4a3b1"
      },
      "source": [
        "from matplotlib import pyplot as plt\r\n",
        "\r\n",
        "f,ax=plt.subplots(1,2,gridspec_kw={'width_ratios':[0.2,0.8]})\r\n",
        "\r\n",
        "sns.boxplot(data=df,x='species',y=df['sepal_length'],hue='species',width=0.5,notch=True,linewidth=3)\r\n",
        "\r\n",
        "sns.boxplot(data=df,y=df['sepal_length'],hue='species',width=0.5,notch=True,linewidth=3,ax=ax[0])\r\n"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f668582a550>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "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": 279
        },
        "id": "eDKCmWhYxDk7",
        "outputId": "e5dcdb57-3269-4053-9a33-1fcbb3007a31"
      },
      "source": [
        "\r\n",
        "\r\n",
        "ax=sns.boxplot(x=df['species'],y=df['sepal_length'])\r\n",
        "\r\n",
        "for idx,dat in enumerate(df.groupby('species')['sepal_length'].median()):\r\n",
        "  ax.text(idx, dat + 0.03,str(dat) ,horizontalalignment='center', size='x-small', color='w', weight='semibold')\r\n",
        " \r\n"
      ],
      "execution_count": 63,
      "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"
          }
        }
      ]
    }
  ]
}