{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-TM003HVDmy9"
      },
      "source": [
        "# Statistics"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fpPtZgqIvuXz"
      },
      "source": [
        "Sources and inspiration:\n",
        "\n",
        "\n",
        "*   https://www.kaggle.com/code/tirendazacademy/penguin-dataset-data-visualization-with-seaborn#Penguin-Dataset:-Data-Visualization-with-Seaborn\n",
        "*   https://seaborn.pydata.org/tutorial/categorical.html\n",
        "* https://pandas.pydata.org/docs/user_guide/visualization.html\n",
        "* https://levelup.gitconnected.com/statistics-on-seaborn-plots-with-statannotations-2bfce0394c00\n",
        "\n",
        "If running this from Google Colab, uncomment the cell below and run it. Otherwise, just skip it."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5saSBc40voZF",
        "outputId": "45269e9d-53b9-48e7-f432-5887fbb0888d"
      },
      "outputs": [],
      "source": [
        "# !pip install seaborn\n",
        "# !pip scikit_posthocs\n",
        "# !pip install watermark"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "cgfXd-tzqFqA",
        "pycharm": {
          "name": "#%%\n"
        }
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "from scipy.stats import mannwhitneyu, normaltest"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y2Wl1yTAY1dp"
      },
      "source": [
        "## Introduction"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mKQgwkRfRA-q"
      },
      "source": [
        "Many libraries are available in Python to clean, analyze, and plot data.\n",
        "Python also has robust statistical packages which are used by thousands of other projects.*text kurzívou*\n",
        "\n",
        "We will work with the penguins dataset from seaborn."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "A6Gi_GYV-8Dm"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>species</th>\n",
              "      <th>island</th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
              "      <th>sex</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.1</td>\n",
              "      <td>18.7</td>\n",
              "      <td>181.0</td>\n",
              "      <td>3750.0</td>\n",
              "      <td>Male</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.5</td>\n",
              "      <td>17.4</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3800.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>40.3</td>\n",
              "      <td>18.0</td>\n",
              "      <td>195.0</td>\n",
              "      <td>3250.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>36.7</td>\n",
              "      <td>19.3</td>\n",
              "      <td>193.0</td>\n",
              "      <td>3450.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.3</td>\n",
              "      <td>20.6</td>\n",
              "      <td>190.0</td>\n",
              "      <td>3650.0</td>\n",
              "      <td>Male</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
              "\n",
              "   body_mass_g     sex  \n",
              "0       3750.0    Male  \n",
              "1       3800.0  Female  \n",
              "2       3250.0  Female  \n",
              "4       3450.0  Female  \n",
              "5       3650.0    Male  "
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "penguins = sns.load_dataset(\"penguins\")\n",
        "penguins_cleaned = penguins.dropna()\n",
        "penguins_cleaned.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1nof0GrHSlKH"
      },
      "source": [
        "### Exploring the Data\n",
        "\n",
        "We already prepared the penguin dataset with `penguins_cleaned = penguins.dropna()`, but we should double check."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t1uqIFnqsLe-",
        "outputId": "4019d541-af4d-4095-bcd0-a953a4df6425"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "species              0\n",
              "island               0\n",
              "bill_length_mm       0\n",
              "bill_depth_mm        0\n",
              "flipper_length_mm    0\n",
              "body_mass_g          0\n",
              "sex                  0\n",
              "dtype: int64"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "penguins_cleaned.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "fGN_N1SwTLTQ",
        "outputId": "70640773-5854-43cd-d097-46de28371b4c"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>species</th>\n",
              "      <th>island</th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
              "      <th>sex</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.1</td>\n",
              "      <td>18.7</td>\n",
              "      <td>181.0</td>\n",
              "      <td>3750.0</td>\n",
              "      <td>Male</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.5</td>\n",
              "      <td>17.4</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3800.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>40.3</td>\n",
              "      <td>18.0</td>\n",
              "      <td>195.0</td>\n",
              "      <td>3250.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>36.7</td>\n",
              "      <td>19.3</td>\n",
              "      <td>193.0</td>\n",
              "      <td>3450.0</td>\n",
              "      <td>Female</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.3</td>\n",
              "      <td>20.6</td>\n",
              "      <td>190.0</td>\n",
              "      <td>3650.0</td>\n",
              "      <td>Male</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
              "\n",
              "   body_mass_g     sex  \n",
              "0       3750.0    Male  \n",
              "1       3800.0  Female  \n",
              "2       3250.0  Female  \n",
              "4       3450.0  Female  \n",
              "5       3650.0    Male  "
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "penguins_cleaned.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "There are 3 species of penquins. We can access their names by applying the `.unique` method on the 'species' column. It returns the unique values in that column."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s7OjfV-oTt94",
        "outputId": "02661aa4-c893-45e8-d537-22c2b090572e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array(['Adelie', 'Chinstrap', 'Gentoo'], dtype=object)"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "penguins_cleaned['species'].unique()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vdc1o_nRTcdd"
      },
      "source": [
        "We can get average measurements of a property split by categories with the `.pivot_table`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "I8JtXQ6cT_2g",
        "outputId": "674fa87d-408f-49ca-8315-ebf40cc2b6bf"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>species</th>\n",
              "      <th>Adelie</th>\n",
              "      <th>Chinstrap</th>\n",
              "      <th>Gentoo</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sex</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>37.257534</td>\n",
              "      <td>46.573529</td>\n",
              "      <td>45.563793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>40.390411</td>\n",
              "      <td>51.094118</td>\n",
              "      <td>49.473770</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "species     Adelie  Chinstrap     Gentoo\n",
              "sex                                     \n",
              "Female   37.257534  46.573529  45.563793\n",
              "Male     40.390411  51.094118  49.473770"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "penguins_cleaned.pivot_table('bill_length_mm', index='sex', columns='species', aggfunc='mean')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7bOz4KTfjf6R"
      },
      "source": [
        "### Splitting data into sub-groups\n",
        "\n",
        "Furhtermore, we can also prepare subsets for each penguin species by feeding a different binary mask to the dataframe."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "jKu-kNKvVEOd"
      },
      "outputs": [],
      "source": [
        "Adelie_values =  penguins_cleaned[penguins_cleaned['species']=='Adelie']\n",
        "Chinstrap_values = penguins_cleaned[penguins_cleaned['species']=='Chinstrap']\n",
        "Gentoo_values = penguins_cleaned[penguins_cleaned['species']=='Gentoo']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O9vw7B9hlYke"
      },
      "source": [
        "Lets explore values of each species."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "D7-b8W3YVZ4F",
        "outputId": "fbb4ae50-dc60-4531-d117-0d85fcb7a397"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>146.000000</td>\n",
              "      <td>146.000000</td>\n",
              "      <td>146.000000</td>\n",
              "      <td>146.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>38.823973</td>\n",
              "      <td>18.347260</td>\n",
              "      <td>190.102740</td>\n",
              "      <td>3706.164384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>2.662597</td>\n",
              "      <td>1.219338</td>\n",
              "      <td>6.521825</td>\n",
              "      <td>458.620135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>32.100000</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>172.000000</td>\n",
              "      <td>2850.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>36.725000</td>\n",
              "      <td>17.500000</td>\n",
              "      <td>186.000000</td>\n",
              "      <td>3362.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>38.850000</td>\n",
              "      <td>18.400000</td>\n",
              "      <td>190.000000</td>\n",
              "      <td>3700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>40.775000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>4000.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>46.000000</td>\n",
              "      <td>21.500000</td>\n",
              "      <td>210.000000</td>\n",
              "      <td>4775.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       bill_length_mm  bill_depth_mm  flipper_length_mm  body_mass_g\n",
              "count      146.000000     146.000000         146.000000   146.000000\n",
              "mean        38.823973      18.347260         190.102740  3706.164384\n",
              "std          2.662597       1.219338           6.521825   458.620135\n",
              "min         32.100000      15.500000         172.000000  2850.000000\n",
              "25%         36.725000      17.500000         186.000000  3362.500000\n",
              "50%         38.850000      18.400000         190.000000  3700.000000\n",
              "75%         40.775000      19.000000         195.000000  4000.000000\n",
              "max         46.000000      21.500000         210.000000  4775.000000"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Adelie_values.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "It7rckCZVbme",
        "outputId": "ecdc4b09-8b23-48ff-fdce-09e29ae3b4b4"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>68.000000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>68.000000</td>\n",
              "      <td>68.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>48.833824</td>\n",
              "      <td>18.420588</td>\n",
              "      <td>195.823529</td>\n",
              "      <td>3733.088235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.339256</td>\n",
              "      <td>1.135395</td>\n",
              "      <td>7.131894</td>\n",
              "      <td>384.335081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>40.900000</td>\n",
              "      <td>16.400000</td>\n",
              "      <td>178.000000</td>\n",
              "      <td>2700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>46.350000</td>\n",
              "      <td>17.500000</td>\n",
              "      <td>191.000000</td>\n",
              "      <td>3487.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>49.550000</td>\n",
              "      <td>18.450000</td>\n",
              "      <td>196.000000</td>\n",
              "      <td>3700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>51.075000</td>\n",
              "      <td>19.400000</td>\n",
              "      <td>201.000000</td>\n",
              "      <td>3950.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>58.000000</td>\n",
              "      <td>20.800000</td>\n",
              "      <td>212.000000</td>\n",
              "      <td>4800.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       bill_length_mm  bill_depth_mm  flipper_length_mm  body_mass_g\n",
              "count       68.000000      68.000000          68.000000    68.000000\n",
              "mean        48.833824      18.420588         195.823529  3733.088235\n",
              "std          3.339256       1.135395           7.131894   384.335081\n",
              "min         40.900000      16.400000         178.000000  2700.000000\n",
              "25%         46.350000      17.500000         191.000000  3487.500000\n",
              "50%         49.550000      18.450000         196.000000  3700.000000\n",
              "75%         51.075000      19.400000         201.000000  3950.000000\n",
              "max         58.000000      20.800000         212.000000  4800.000000"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Chinstrap_values.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "6q-3KASyVdcF",
        "outputId": "1864d1fb-e1f2-4fe9-8782-86d56f07a6c8"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>119.000000</td>\n",
              "      <td>119.000000</td>\n",
              "      <td>119.000000</td>\n",
              "      <td>119.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>47.568067</td>\n",
              "      <td>14.996639</td>\n",
              "      <td>217.235294</td>\n",
              "      <td>5092.436975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.106116</td>\n",
              "      <td>0.985998</td>\n",
              "      <td>6.585431</td>\n",
              "      <td>501.476154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>40.900000</td>\n",
              "      <td>13.100000</td>\n",
              "      <td>203.000000</td>\n",
              "      <td>3950.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>45.350000</td>\n",
              "      <td>14.200000</td>\n",
              "      <td>212.000000</td>\n",
              "      <td>4700.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>47.400000</td>\n",
              "      <td>15.000000</td>\n",
              "      <td>216.000000</td>\n",
              "      <td>5050.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>49.600000</td>\n",
              "      <td>15.750000</td>\n",
              "      <td>221.500000</td>\n",
              "      <td>5500.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>59.600000</td>\n",
              "      <td>17.300000</td>\n",
              "      <td>231.000000</td>\n",
              "      <td>6300.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       bill_length_mm  bill_depth_mm  flipper_length_mm  body_mass_g\n",
              "count      119.000000     119.000000         119.000000   119.000000\n",
              "mean        47.568067      14.996639         217.235294  5092.436975\n",
              "std          3.106116       0.985998           6.585431   501.476154\n",
              "min         40.900000      13.100000         203.000000  3950.000000\n",
              "25%         45.350000      14.200000         212.000000  4700.000000\n",
              "50%         47.400000      15.000000         216.000000  5050.000000\n",
              "75%         49.600000      15.750000         221.500000  5500.000000\n",
              "max         59.600000      17.300000         231.000000  6300.000000"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Gentoo_values.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Applying Statistics tests"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "di_UCUwdXKDb"
      },
      "source": [
        "### Normality Test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PVcy5evnYtSL"
      },
      "source": [
        "`normaltest()` test whether a sample differs from a normal distribution.\n",
        "\n",
        "This function tests the null hypothesis that a sample comes from a normal distribution."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WaIMJYl_ZqAp"
      },
      "source": [
        "The p-value range is between 0 and 1,"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UO0yB80vqFqO",
        "outputId": "a54f5a1a-d8f6-4d66-ad84-09b81a301301",
        "pycharm": {
          "name": "#%%\n"
        }
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Adelie:  0.7046667395852243\n",
            "Chinstrap:  0.9143668075479967\n",
            "Gentoo:  0.002785628232779262\n"
          ]
        }
      ],
      "source": [
        "from scipy.stats import normaltest\n",
        "print(\"Adelie: \", normaltest(Adelie_values['bill_length_mm']).pvalue)\n",
        "print(\"Chinstrap: \", normaltest(Chinstrap_values['bill_length_mm']).pvalue)\n",
        "print(\"Gentoo: \", normaltest(Gentoo_values['bill_length_mm']).pvalue)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jR6_9Nn3abKY"
      },
      "source": [
        "Traditionally, in statistics, we need a p-value of less than 0.05 to\n",
        "reject the null hypothesis.  In this case, the 2 out of 3 species have p-value > 0.05.  Because our p value is greater than 0.05, we cannot reject the null hypothesis.  Therefore, we have not proven that the 2 data sets are different from normality.\n",
        "\n",
        "But what about the last?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "liLKelkYa2Sw"
      },
      "source": [
        "Aren't we forgeting something? Do we know enough about the data?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XndEb8ycnU2h"
      },
      "source": [
        "![penguins_species_bill-length_PNG.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "NTJlvbMybCEo"
      },
      "outputs": [],
      "source": [
        "# import matplotlib.pyplot as plt\n",
        "# # Set up the matplotlib figure\n",
        "# f, ax = plt.subplots(figsize=(10, 5))\n",
        "\n",
        "# sns.histplot(x = \"bill_length_mm\", data = penguins_cleaned, binwidth=1, hue=\"species\", kde=True)\n",
        "# # plt.title(\"Bill Length\", size=20, color=\"red\") # would look wierd\n",
        "# ax.set(title=\"Bill Length\")\n",
        "\n",
        "# sns.move_legend(\n",
        "#     ax, \"upper center\",\n",
        "#     bbox_to_anchor=(.5, 1), ncol=3, title=None, frameon=False,\n",
        "# )\n",
        "\n",
        "# f.savefig('penguins_species_bill-length_PNG.png', dpi=300)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iolWcFn0bgLo"
      },
      "source": [
        "A normal distribution is symmetric about the mean.  \n",
        "A normal distribution also has a specific width for a given height.\n",
        "\n",
        "If you double the height, the width scales proportionally.  However,\n",
        "you could imagine stretching a bell curve out in weird ways without\n",
        "changing its symmetry.  You could have a sharp, pointy distribution,\n",
        "or a fat, boxy one."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mKuk_-LFnjCE"
      },
      "source": [
        "![penguins_gentoo_bill-length_PNG.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "JhH952mmbqPn"
      },
      "outputs": [],
      "source": [
        "# import matplotlib.pyplot as plt\n",
        "\n",
        "# # Set up the matplotlib figure\n",
        "# f, ax = plt.subplots(figsize=(10, 5))\n",
        "\n",
        "# sns.histplot(x = \"bill_length_mm\", data = Gentoo_values, binwidth=1, hue=\"sex\", kde=True)\n",
        "# # plt.title(\"Bill Length\", size=20, color=\"red\") # would look wierd\n",
        "# ax.set(title=\"Bill Length of Gentoo\")\n",
        "\n",
        "# sns.move_legend(\n",
        "#     ax, \"upper center\",\n",
        "#     bbox_to_anchor=(.5, 1), ncol=3, title=None, frameon=False,\n",
        "# )\n",
        "\n",
        "# f.savefig('penguins_gentoo_bill-length_PNG.png', dpi=300)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BsPrjqZFcBBv",
        "outputId": "91b6c933-f0f1-475a-bea2-41614680fe7d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Gentoo male:  0.0005453287292381343\n",
            "Gentoo female:  0.9029679515828937\n"
          ]
        }
      ],
      "source": [
        "Gentoo_values_male=Gentoo_values[Gentoo_values.sex=='Male']\n",
        "Gentoo_values_female=Gentoo_values[Gentoo_values.sex=='Female']\n",
        "\n",
        "print(\"Gentoo male: \", normaltest(Gentoo_values_male['bill_length_mm']).pvalue)\n",
        "print(\"Gentoo female: \", normaltest(Gentoo_values_female['bill_length_mm']).pvalue)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Esjlxz45c49X"
      },
      "source": [
        "Luckily we are able to test and compare sets of values, even if they do not come from Normal Distribution"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Comparing 2 groups"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uwN3p34bcsDF"
      },
      "source": [
        "#### Parametric Tests\n",
        "\n",
        "##### T-Test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6BUomQcSfbkl"
      },
      "source": [
        "`ttest_ind()` calculates the T-test for the means of two independent samples of scores.\n",
        "\n",
        "This is a test for the null hypothesis that 2 independent samples have identical average (expected) values. This test assumes that the populations have identical variances by default.\n",
        "\n",
        "There is a catch! We need to have either same number of samples, or same variance. `ttest_ind()` can perform a standard independent 2 sample test that assumes equal population variances. If False, perform Welch’s t-test, which does not assume equal population variance.\n",
        "\n",
        "---\n",
        "**Note**\n",
        "*Using Student's original definition of the t-test, the two populations being compared should have the same variance. If the sample sizes in the two groups being compared are equal, Student's original t-test is highly robust to the presence of unequal variances. Welch's t-test is insensitive to equality of the variances regardless of whether the sample sizes are similar.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "na3ztua1gqrP"
      },
      "source": [
        "Perform Levene test for equal variances.\n",
        "\n",
        "The Levene test tests the null hypothesis that all input samples are from populations with equal variances."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "pBrWKB1dgUuk"
      },
      "outputs": [],
      "source": [
        "from scipy.stats import ttest_ind, levene"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N8Qy-aPUdJw2",
        "outputId": "4d224e1e-38bb-4edc-b2f9-c7cbad1e748c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Adelie vs Chinstrap, variance:  LeveneResult(statistic=4.529733833453024, pvalue=0.03446512682844295)\n"
          ]
        }
      ],
      "source": [
        "# pvalues with scipy:\n",
        "stat_results = [levene(Adelie_values['bill_length_mm'], Chinstrap_values['bill_length_mm'])]\n",
        "\n",
        "print(\"Adelie vs Chinstrap, variance: \", stat_results[0])\n",
        "\n",
        "pvalues = [result.pvalue for result in stat_results]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6azzEtg3iLB6"
      },
      "source": [
        "With p-value < 0.05 , we reject the null hypothesis that all input samples are from populations with equal variances. So we need Welch’s t-test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "foRasXqAjkAp"
      },
      "source": [
        "---\n",
        "Null hypothesis is that 2 independent samples have identical average (expected) values."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o1vYC0PniQi7",
        "outputId": "69bcb07e-0031-47ed-8aaf-bc81a920e8f6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Adelie vs Chinstrap, mean:  TtestResult(statistic=-21.712498056635937, pvalue=3.1490764303457434e-41, df=108.17221912082128)\n"
          ]
        }
      ],
      "source": [
        "# pvalues with scipy:\n",
        "stat_results_ACh = [ttest_ind(Adelie_values['bill_length_mm'], Chinstrap_values['bill_length_mm'], equal_var=False)]\n",
        "\n",
        "print(\"Adelie vs Chinstrap, mean: \", stat_results_ACh[0])\n",
        "\n",
        "pvalues = [result.pvalue for result in stat_results_ACh]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hVwFdAUWjtzI"
      },
      "source": [
        "With p-value < 0.05 , we reject the null hypothesis. Now how we can plot this?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TthTHYeKcuaP"
      },
      "source": [
        "#### Non-parametric\n",
        "\n",
        "##### Mann-Whitney U Test"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P1AR8Gd2dcpO",
        "outputId": "ea7b7591-3640-4d0b-c731-5109fafaa9a5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Gentoo male vs Gentoo female, bill_length_mm:  MannwhitneyuResult(statistic=3125.5, pvalue=5.58594267834405e-13)\n"
          ]
        }
      ],
      "source": [
        "from scipy.stats import mannwhitneyu\n",
        "\n",
        "# pvalues with scipy:\n",
        "stat_results_GFM = [mannwhitneyu(Gentoo_values_male['bill_length_mm'], Gentoo_values_female['bill_length_mm'], alternative=\"two-sided\"),]\n",
        "\n",
        "print(\"Gentoo male vs Gentoo female, bill_length_mm: \", stat_results_GFM[0])\n",
        "\n",
        "pvalues = [result.pvalue for result in stat_results_GFM]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fyK-kOiXj6Ze"
      },
      "source": [
        "### Comparing more than 2 groups"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AN5wIjCTvFWa"
      },
      "source": [
        "#### Analysis of Variance\n",
        "\n",
        "Now we have three samples, so a t-test is actually not appropriate. If we state the 0-Hypothesis that there is no difference between samples, we should apply a one-way ANOVA."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Y9HoWv_wfN2"
      },
      "source": [
        "Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the \"variation\" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. **In other words, the ANOVA is used to test the difference between two or more means.**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "7aBgPsKdvE9a"
      },
      "outputs": [],
      "source": [
        "from scipy.stats import f_oneway\n",
        "\n",
        "stat_results_f_oneway = f_oneway(Adelie_values['bill_length_mm'], Chinstrap_values['bill_length_mm'], Gentoo_values['bill_length_mm'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wgVCvkZWwUYx",
        "outputId": "2a827ba3-8980-4a77-a3bd-d55cf6419d62"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "F_onewayResult(statistic=397.29943741282835, pvalue=1.3809842053150027e-88)"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "stat_results_f_oneway"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xXJQhqC-wufJ"
      },
      "source": [
        "#### Kruskal–Wallis test\n",
        "The Kruskal–Wallis test is a **non-parametric** method for testing whether samples originate from the same distribution. It is used for comparing two or more independent samples of equal or different sample sizes. It extends the Mann–Whitney U test, which is used for comparing only two groups."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "lIiCDHqMxa0g"
      },
      "outputs": [],
      "source": [
        "from scipy.stats import kruskal\n",
        "\n",
        "stat_results_kruskal = kruskal(Adelie_values['bill_length_mm'], Chinstrap_values['bill_length_mm'], Gentoo_values['bill_length_mm'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kteu-hZSxhZ8",
        "outputId": "9457db2f-608b-45b8-e751-cd35950930a7"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "KruskalResult(statistic=236.8992355590763, pvalue=3.6139705965512625e-52)"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "stat_results_kruskal"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Zasv4RyxsLS"
      },
      "source": [
        "We are looking at all comparisons at the same time. But we usually want to know which one makes the difference! **But here we need to include Multiple testing correction!**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZQhI3SxUx1Av"
      },
      "source": [
        "#### Multiple testing correction\n",
        "\n",
        "For ANOVA there is Tukey. For non-parametric tests, there is Dunn’s test."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V9eYOcgA6UEw"
      },
      "source": [
        "##### Tukey\n",
        "\n",
        " This test uses pairwise post-hoc testing for **ANOVA** to determine whether there is a difference between the mean of all possible pairs using a studentized range distribution. This method tests every possible pair of all groups."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "81cffTajx6aY"
      },
      "outputs": [],
      "source": [
        "from statsmodels.stats.multicomp import pairwise_tukeyhsd\n",
        "\n",
        "# For Tukey the dataframe needs to be melted\n",
        "\n",
        "data = penguins_cleaned[['species','bill_length_mm']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "aB4XYCB2zoab"
      },
      "outputs": [],
      "source": [
        "# perform multiple pairwise comparison (Tukey HSD)\n",
        "stat_results_pairwise_tukeyhsd = pairwise_tukeyhsd(endog=data['bill_length_mm'], groups=data['species'], alpha=0.05)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UV43AXiny-F_",
        "outputId": "c1da7cee-8dc6-47ab-f597-491f505b84f2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "   Multiple Comparison of Means - Tukey HSD, FWER=0.05    \n",
            "==========================================================\n",
            "  group1    group2  meandiff p-adj   lower   upper  reject\n",
            "----------------------------------------------------------\n",
            "   Adelie Chinstrap  10.0099    0.0  8.9828 11.0369   True\n",
            "   Adelie    Gentoo   8.7441    0.0  7.8801  9.6081   True\n",
            "Chinstrap    Gentoo  -1.2658 0.0148 -2.3292 -0.2023   True\n",
            "----------------------------------------------------------\n"
          ]
        }
      ],
      "source": [
        "print(stat_results_pairwise_tukeyhsd)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nNybO7cV5bkE"
      },
      "source": [
        "##### Dunn's test\n",
        "\n",
        "If the results of a **Kruskal-Wallis** test are statistically significant, then it’s appropriate to conduct Dunn’s Test to determine exactly which groups are different."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PijgOoRT6G_4",
        "outputId": "f57cb7c1-f8b3-4c2a-972b-077ae192d4f8"
      },
      "outputs": [],
      "source": [
        "# !pip install scikit_posthocs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "PVsfEvEp5aAA"
      },
      "outputs": [],
      "source": [
        "data=[Adelie_values['bill_length_mm'].to_numpy(), Chinstrap_values['bill_length_mm'].to_numpy(), Gentoo_values['bill_length_mm'].to_numpy()]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 852
        },
        "id": "tECveDfg5nxD",
        "outputId": "eccd2fa2-2a43-4e92-b2e2-93e5bcf17bb1"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>4.623888e-36</td>\n",
              "      <td>1.030275e-37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.623888e-36</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>2.697766e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.030275e-37</td>\n",
              "      <td>2.697766e-01</td>\n",
              "      <td>1.000000e+00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              1             2             3\n",
              "1  1.000000e+00  4.623888e-36  1.030275e-37\n",
              "2  4.623888e-36  1.000000e+00  2.697766e-01\n",
              "3  1.030275e-37  2.697766e-01  1.000000e+00"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#perform Dunn's test using a Bonferonni correction for the p-values\n",
        "import scikit_posthocs as sp\n",
        "sp.posthoc_dunn(data, p_adjust = 'bonferroni', group_col='species', val_col='bill_length_mm')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OV1g1q3FqFqY"
      },
      "source": [
        "---\n",
        "# (Bonus preview) Use statannotations to apply scipy test"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tEY7A5YlqFqY"
      },
      "source": [
        "Finally, `statannotations` can take care of most of the steps required to run the test by calling `scipy.stats` directly\n",
        "and annotate the plot.\n",
        "The available options are\n",
        "\n",
        "- Mann-Whitney\n",
        "- t-test (independent and paired)\n",
        "- Welch's t-test\n",
        "- Levene test\n",
        "- Wilcoxon test\n",
        "- Kruskal-Wallis test\n",
        "\n",
        "We will cover how to use a test that is not one of those already interfaced in `statannotations`.\n",
        "If you are curious, you can also take a look at the usage\n",
        "[notebook](https://github.com/trevismd/statannotations/blob/master/usage/example.ipynb) in the project repository."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vsdfj_gM5qbt"
      },
      "source": [
        "![violin_annotated_PNG (1).png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wyUoyKXHj2UQ"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iH1jL0baGMJW",
        "outputId": "dd7307d6-eb5b-4ed0-c233-32574ddb0c40"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Last updated: 2023-08-25T10:49:29.031581+02:00\n",
            "\n",
            "Python implementation: CPython\n",
            "Python version       : 3.9.17\n",
            "IPython version      : 8.14.0\n",
            "\n",
            "Compiler    : MSC v.1929 64 bit (AMD64)\n",
            "OS          : Windows\n",
            "Release     : 10\n",
            "Machine     : AMD64\n",
            "Processor   : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel\n",
            "CPU cores   : 16\n",
            "Architecture: 64bit\n",
            "\n",
            "watermark      : 2.4.3\n",
            "numpy          : 1.23.5\n",
            "pandas         : 2.0.3\n",
            "seaborn        : 0.12.2\n",
            "matplotlib     : 3.7.2\n",
            "scipy          : 1.11.2\n",
            "statannotations: 0.4.4\n",
            "\n"
          ]
        }
      ],
      "source": [
        "from watermark import watermark\n",
        "watermark(iversions=True, globals_=globals())\n",
        "print(watermark())\n",
        "print(watermark(packages=\"watermark,numpy,pandas,seaborn,matplotlib,scipy,statannotations\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.17"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}