{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from util import load_user_data\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "245 valid participants\n",
      "{'control': 61, 'dashboard': 61, 'chatxai': 62, 'chatxaiboost': 61, 'chatxaiAuto': 0}\n",
      "91 participants blindly rely on AI advice\n",
      "{'control': 8, 'dashboard': 27, 'chatxai': 32, 'chatxaiboost': 24, 'chatxaiAuto': 0}\n",
      "61 valid participants\n",
      "{'control': 0, 'dashboard': 0, 'chatxai': 0, 'chatxaiboost': 0, 'chatxaiAuto': 61}\n",
      "25 participants blindly rely on AI advice\n",
      "{'control': 0, 'dashboard': 0, 'chatxai': 0, 'chatxaiboost': 0, 'chatxaiAuto': 25}\n",
      "(306, 7)\n"
     ]
    }
   ],
   "source": [
    "valid_users, tp_data, _ = load_user_data(filename=\"../data/xailabdata_all.csv\")\n",
    "valid_users_2, tp_data_2, _ = load_user_data(filename=\"../data/xailabdata_llm_agent.csv\")\n",
    "\n",
    "valid_users = valid_users | valid_users_2\n",
    "tp_data.update(tp_data_2)\n",
    "variable_dict = {}\n",
    "variable_dict[\"condition\"] = []\n",
    "dimensions = [\"accuracy\", \"agreement_fraction\", \"switch_fraction\", \"accuracy-wid\", \"RAIR\", \"RSR\"]\n",
    "all_conditions = [\"Control\", \"Dashboard\", \"CXAI\", \"ECXAI\", \"LLM Agent\"]\n",
    "for dimension in dimensions:\n",
    "    variable_dict[dimension] = []\n",
    "\n",
    "for user in valid_users:\n",
    "    tp_condition = tp_data[user][\"condition\"]\n",
    "    variable_dict[\"condition\"].append(tp_condition)\n",
    "    reliance_measures = tp_data[user][\"reliance_measures\"]\n",
    "    for dimension in dimensions:\n",
    "        variable_dict[dimension].append(reliance_measures[dimension])\n",
    "\n",
    "df = pd.DataFrame(variable_dict)\n",
    "print(df.shape)\n",
    "\n",
    "condition_name_map = {\n",
    "    \"control\": \"Control\",\n",
    "    \"dashboard\": \"Dashboard\",\n",
    "    \"chatxai\": \"CXAI\",\n",
    "    \"chatxaiboost\": \"ECXAI\",\n",
    "    \"chatxaiAuto\": \"LLM Agent\"\n",
    "}\n",
    "\n",
    "df['condition'] = df['condition'].map(condition_name_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "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>condition</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>agreement_fraction</th>\n",
       "      <th>switch_fraction</th>\n",
       "      <th>accuracy-wid</th>\n",
       "      <th>RAIR</th>\n",
       "      <th>RSR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ECXAI</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CXAI</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Control</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ECXAI</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Control</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  condition  accuracy  agreement_fraction  switch_fraction  accuracy-wid  \\\n",
       "0     ECXAI       0.7                 1.0         1.000000      0.500000   \n",
       "1      CXAI       0.7                 1.0         1.000000      0.500000   \n",
       "2   Control       0.8                 0.9         0.750000      0.750000   \n",
       "3     ECXAI       0.5                 0.6         0.333333      0.166667   \n",
       "4   Control       0.7                 1.0         1.000000      0.500000   \n",
       "\n",
       "   RAIR       RSR  \n",
       "0   1.0  0.000000  \n",
       "1   1.0  0.000000  \n",
       "2   1.0  0.500000  \n",
       "3   0.0  0.333333  \n",
       "4   1.0  0.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dabest\n",
    "# df[\"condition\"].unique()\n",
    "\n",
    "four_groups_unpaired = {}\n",
    "for reliance_measure in dimensions:\n",
    "    four_groups_unpaired[reliance_measure] = dabest.load(df, x=\"condition\", idx=all_conditions, y=reliance_measure, resamples=5000, ci=95, x1_level=all_conditions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DABEST v2023.02.14\n",
       "==================\n",
       "                  \n",
       "Good afternoon!\n",
       "The current time is Mon Sep 30 15:52:55 2024.\n",
       "\n",
       "The unpaired mean difference between Control and Dashboard is 0.157 [95%CI 0.00367, 0.304].\n",
       "The p-value of the two-sided permutation t-test is 0.0446, calculated for legacy purposes only. \n",
       "\n",
       "The unpaired mean difference between Control and CXAI is 0.254 [95%CI 0.0999, 0.397].\n",
       "The p-value of the two-sided permutation t-test is 0.0012, calculated for legacy purposes only. \n",
       "\n",
       "The unpaired mean difference between Control and ECXAI is 0.17 [95%CI 0.0175, 0.314].\n",
       "The p-value of the two-sided permutation t-test is 0.0264, calculated for legacy purposes only. \n",
       "\n",
       "The unpaired mean difference between Control and LLM Agent is 0.132 [95%CI -0.0232, 0.277].\n",
       "The p-value of the two-sided permutation t-test is 0.0834, calculated for legacy purposes only. \n",
       "\n",
       "5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated.\n",
       "Any p-value reported is the probability of observing theeffect size (or greater),\n",
       "assuming the null hypothesis ofzero difference is true.\n",
       "For each p-value, 5000 reshuffles of the control and test labels were performed.\n",
       "\n",
       "To get the results of all valid statistical tests, use `.mean_diff.statistical_tests`"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "four_groups_unpaired[\"RAIR\"].mean_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 13.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 27.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 45.2% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 34.4% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 31.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 23.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 30.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 18.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 26.2% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 19.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 23.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 32.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 21.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 8.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 11.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 16.4% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 27.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 32.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 40.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 31.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 36.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:473: FutureWarning: Passing `palette` without assigning `hue` is deprecated.\n",
      "  rawdata_plot = sns.swarmplot(data=plot_data, x=xvar, y=yvar,\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 44.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 52.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 53.2% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 47.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 63.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/dabest/plotter.py:563: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  rawdata_axes.set_xticklabels(ticks_with_counts)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 19.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 34.4% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 50.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 41.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 39.3% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 63888 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 8.2% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 29.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 33.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 24.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 36.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 73856 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 23.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 38.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 27.9% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 76400 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 9.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 17.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 80956 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 31.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 46.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 37.7% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 42.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 65748 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 50.8% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 59.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 58.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 54.1% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/Users/ghe/opt/anaconda3/envs/agreement_phi/lib/python3.8/site-packages/seaborn/categorical.py:3544: UserWarning: 67.2% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 55728 characters]",
      "text/plain": [
       "<Figure size 750x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for reliance_measure in dimensions:\n",
    "    four_groups_unpaired[reliance_measure].mean_diff.plot();"
   ]
  }
 ],
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