norma_hunspell_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "mounted-despite",
   "metadata": {},
   "source": [
    "- Notebook based on \"hunspell_analysis_public.ipynb\", copied and modified\n",
    "- _Key messages not adjusted yet_\n",
    "\n",
    "# Analysis: Norma's spelling correction (or **normalization**) on litkey data set\n",
    "Preface: This notebook is going to analyse the results of the evaluation of Norma on the litkey data set. Therefore, the evaluation results, created in _postprocessing_run_complete_default_config_ notebook, are loaded into this notebook at first (see section 1). Afterwards, the evaluation results are going to be explored (see section 2-4).\n",
    "\n",
    "\n",
    "## Outline\n",
    "0. Preparation\n",
    "    - Imports\n",
    "    - Configuration\n",
    "1. Load data sets\n",
    "    - Types & token, case insensitive & case sensitive\n",
    "    - Explanantion of (new) variables\n",
    "2. [Types & Tokens Stats](#2)\n",
    "    - Upper bound value\n",
    "    - Bar charts\n",
    "    - Ratio\n",
    "3. [Distribution (token base):](#3)\n",
    "\n",
    "    - [Per language_tool suggestions](#5)\n",
    "    \n",
    "4. [Relationships:](#4) \n",
    "\n",
    "    - Suggestions index on test point\n",
    "        - Percent stacked bar plot\n",
    "        - [Percent stacked bar plot, 3 categories](#6)\n",
    "    - Suggestions index on Levenshtein distance\n",
    "        - [Percent stacked bar plot](#7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "still-professional",
   "metadata": {},
   "source": [
    "<a id='0'></a><br>\n",
    "## 0 - Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "chief-mapping",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Change summarys of plot to language_tool data\n",
    "# IMPORTS\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "# Sets backend to the 'inline' backend; Helps with plotting\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import PercentFormatter\n",
    "\n",
    "import sys \n",
    "sys.path.insert(0, './Lisa/Experiment_hunspell')\n",
    "\n",
    "import helpers_hunspell_analysis as helpers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "scheduled-vietnam",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuration for plots\n",
    "# Set figure size for sns plot\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "mpl.rc('figure', figsize=(8, 6), dpi=100)\n",
    "sns.set()\n",
    "#sns.set_style('darkgrid')\n",
    "\n",
    "# Do not truncate rows of DataFrame\n",
    "pd.set_option('display.max_rows', None)\n",
    "# Do not truncate column width\n",
    "pd.set_option('display.max_colwidth', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "affecting-industry",
   "metadata": {},
   "source": [
    "<a id='1'></a> <br>\n",
    "## 1 - Load data sets\n",
    "Four versions of the data set are reloaded from pickles. The evaluation has been already run in _postprocessing_run_complete_default_config_ notebook.\n",
    "- type and token based case insensitive (no special ending in df name, i. e. _default_)\n",
    "- type and token based case sensitive (_cs ending_ in df name) \n",
    "\n",
    "\n",
    "### Explanation of (new) variables\n",
    "- Whether the target word is among the suggested words by Language Tool (= _**'in_sugg'**_).\n",
    "    - At which index it is among the suggested words by Language Tool (= _**'sugg_index'**_).\n",
    "- Whether the target word is ranked at index 0 by Language Tool (= _**'idx0'**_)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "female-broadcasting",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load df from pickle\n",
    "#data_error_token = pd.read_pickle('./pickles/reranking_data_error_token_boyd_evaluation_lc_2c.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "adolescent-prison",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data_error_token_cs = pd.read_pickle('./pickles/reranking_data_error_token_boyd_evaluation_cs_2c.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8c56cd6a-9736-4d8c-b513-76a9baa506e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load df from pickle\n",
    "data_error_token = pd.read_pickle('./Lisa/Experiment_norma/data_error_token_norma_hunspell_evaluation_lc_new.pkl')\n",
    "data_error_types = pd.read_pickle('./Lisa/Experiment_norma/data_error_types_norma_hunspell_evaluation_lc_new.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2f893c3b-df92-47b4-b399-c780d665390b",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_error_token_cs = pd.read_pickle('./Lisa/Experiment_norma/data_error_token_norma_hunspell_evaluation_cs_new.pkl')\n",
    "data_error_types_cs = pd.read_pickle('./Lisa/Experiment_norma/data_error_types_norma_hunspell_evaluation_cs_new.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "filled-magnet",
   "metadata": {},
   "outputs": [],
   "source": [
    "#display(data_error_token_cs.tail(100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "legendary-forty",
   "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>original</th>\n",
       "      <th>corrected</th>\n",
       "      <th>filename</th>\n",
       "      <th>freq_ori</th>\n",
       "      <th>freq_cor</th>\n",
       "      <th>freq_tup</th>\n",
       "      <th>suggestions</th>\n",
       "      <th>in_sugg</th>\n",
       "      <th>sugg_idx</th>\n",
       "      <th>idx0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-005-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-338-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-355-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>02-220-2-IV-Weg.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>02-443-2-IV-Weg.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  original corrected              filename  freq_ori  freq_cor  freq_tup  \\\n",
       "0     belt     bellt  01-005-2-III-Eis.csv        91       138        91   \n",
       "1     belt     bellt  01-338-2-III-Eis.csv        91       138        91   \n",
       "2     belt     bellt  01-355-2-III-Eis.csv        91       138        91   \n",
       "3     belt     bellt   02-220-2-IV-Weg.csv        91       138        91   \n",
       "4     belt     bellt   02-443-2-IV-Weg.csv        91       138        91   \n",
       "\n",
       "  suggestions in_sugg  sugg_idx   idx0  \n",
       "0        bild   False       NaN  False  \n",
       "1        bild   False       NaN  False  \n",
       "2        bild   False       NaN  False  \n",
       "3        bild   False       NaN  False  \n",
       "4        bild   False       NaN  False  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data_error_token.head(5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "canadian-junction",
   "metadata": {},
   "source": [
    "<a id='2'></a><br>\n",
    "## 2 - Types & Tokens Stats"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fantastic-status",
   "metadata": {},
   "source": [
    "### Get upper bound information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "seeing-terrorism",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Values copied from language_tool_upper_bound notebook\n",
    "# TODO: Do not hardcode\n",
    "ub_types = 0.0\n",
    "ub_token = 0.0\n",
    "\n",
    "#  TODO: Change values\n",
    "ub_types_ci = 0.0\n",
    "ub_token_ci = 0.0\n",
    "\n",
    "df_list = [data_error_types, data_error_token]\n",
    "#df_list = [data_error_token]\n",
    "\n",
    "def get_ub(df, ub):\n",
    "    ub_pct = round(ub*100, 2)\n",
    "    ub_ttl = int(df.shape[0]*ub)\n",
    "    return [ub, ub_pct, ub_ttl]\n",
    "\n",
    "ub_types_list = get_ub(data_error_types, ub_types)\n",
    "ub_token_list = get_ub(data_error_token, ub_token)\n",
    "\n",
    "ub_types_ci_list = get_ub(data_error_types, ub_types_ci)\n",
    "ub_token_ci_list = get_ub(data_error_token, ub_token_ci)\n",
    "\n",
    "#for i in range(len(ub_types_list)):\n",
    "#    print(ub_types_list[i])\n",
    "#print('*'*20)\n",
    "#for i in range(len(ub_token_list)):\n",
    "#    print(ub_token_list[i])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "extra-automation",
   "metadata": {},
   "source": [
    "### Get values for bar chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "mathematical-namibia",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Types case insensitive\n",
      "9484\n",
      "4613\n",
      "4613\n",
      "********************\n",
      "Token case insensitive\n",
      "24601\n",
      "14137\n",
      "14137\n",
      "********************\n",
      "Types CASE SENSITIVE\n",
      "9484\n",
      "4274\n",
      "4274\n",
      "********************\n",
      "Token CASE SENSITIVE\n",
      "24601\n",
      "12862\n",
      "12862\n"
     ]
    }
   ],
   "source": [
    "# Get values for y axis\n",
    "def get_values_bars(df):\n",
    "    total = df.shape[0]\n",
    "    in_sugg = df[df.in_sugg].shape[0]\n",
    "    idx0 = df[df.idx0].shape[0]\n",
    "    return [total, in_sugg, idx0]\n",
    "\n",
    "values_types = get_values_bars(data_error_types)\n",
    "values_token = get_values_bars(data_error_token)\n",
    "\n",
    "values_types_cs = get_values_bars(data_error_types_cs)\n",
    "values_token_cs = get_values_bars(data_error_token_cs) \n",
    "\n",
    "print('Types case insensitive')\n",
    "for i in range(len(values_types)):\n",
    "    print(values_types[i])\n",
    "print('*'*20)\n",
    "\n",
    "print('Token case insensitive')\n",
    "for i in range(len(values_token)):\n",
    "    print(values_token[i])\n",
    "print('*'*20)\n",
    "\n",
    "print('Types CASE SENSITIVE')\n",
    "for i in range(len(values_types_cs)):\n",
    "    print(values_types_cs[i])\n",
    "print('*'*20)\n",
    "\n",
    "print('Token CASE SENSITIVE')\n",
    "for i in range(len(values_token_cs)):\n",
    "    print(values_token_cs[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "trying-effects",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Put everything together in lists\n",
    "# define x axis POSITIONS\n",
    "x_pos = [[0,1,2], [0,1,2], [0,1,2], [0,1,2]] #plot 0, plot 1, plot 3, plot 4\n",
    "#x_pos = [[0,1,2], [0,1,2]]\n",
    "\n",
    "# put y axis VALUES together, see above\n",
    "y_val = [values_types, values_token, values_types_cs, values_token_cs] #plot 0, plot 1, plot 3, plot 4\n",
    "#y_val = [values_token, values_token_cs]\n",
    "\n",
    "# put upper bound values together, see above\n",
    "ub_list = [ub_types_ci_list, ub_token_ci_list, ub_types_list, ub_token_list]\n",
    "#ub_list = [ub_token_ci_list, ub_token_list]\n",
    "\n",
    "x_y_plots = zip(x_pos, y_val)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "complex-brass",
   "metadata": {},
   "source": [
    "### Bar charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "human-crowd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Outsource\n",
    "\n",
    "def loop_plot(plots, ub_list):\n",
    "    \n",
    "        # Plot everythin in one figure\n",
    "        fig = plt.figure(figsize=(8,8))\n",
    "        \n",
    "        # Use dict to have more control\n",
    "        axs = {}\n",
    "        # Counter for position of subplot, third argument\n",
    "        e = 1\n",
    "        \n",
    "        # loop over 'plots', i. e. 1 list containing 4 tuples (idx 0,1,2,3);\n",
    "        # each tuple containing 2 lists (x and y values)\n",
    "        \n",
    "        # control overall plot via 'idx', set axes\n",
    "            # idx is no. of plot\n",
    "        # control content of plot via 'value'\n",
    "        \n",
    "        for idx, value in enumerate(plots):\n",
    "        #for idx, (x, y) in enumerate(zip(x_pos, y_vals)):\n",
    "            \n",
    "            # Add axes subplot\n",
    "            axs[idx] = fig.add_subplot(2,2,e)\n",
    "       \n",
    "            # Create bars\n",
    "            # value[0] is position x axis, value[1] position y axis (value count)\n",
    "            axs[idx].bar(value[0], value[1])\n",
    "\n",
    "            \n",
    "            # CONFIQ that stays same\n",
    "            \n",
    "            # Names of groups and bar width\n",
    "            names = ['all errors','in suggestions','first suggestion']\n",
    "            barWidth = 1\n",
    "\n",
    "            # Custom x axis\n",
    "            axs[idx].set_xticks(value[0])\n",
    "            axs[idx].set_xticklabels(names, rotation=20)\n",
    "            axs[idx].set_ylabel('count')\n",
    "\n",
    "            # Baseline plot\n",
    "            # Use idx of loop to control ub_list also\n",
    "            axs[idx].axhline(ub_list[idx][2], ls='-', color='r') # access total value\n",
    "            axs[idx].text(2, ub_list[idx][2]+(value[1][0]/50), str(ub_list[idx][1])+'%', color='r', weight='bold', style='italic') # x,y ; Access pct value\n",
    "            axs[idx].text(2, ub_list[idx][2]-(value[1][0]/12.5), '('+str(ub_list[idx][2])+')')\n",
    "            \n",
    "            # Text for bar plots (total, pct)\n",
    "            pct_bars = [100, round(value[1][1]/value[1][0]*100,2), round(value[1][2]/value[1][0]*100,2)] # all, in sugg, index 0\n",
    "            for idx2, value2 in enumerate(value[1]): # loop over y positions\n",
    "                # total\n",
    "                axs[idx].text(idx2-0.275, value2-(value[1][0]*0.1), '('+str(value2)+')') # x, y\n",
    "                # percent\n",
    "                axs[idx].text(idx2-0.275, value2, str(pct_bars[idx2])+'%', color='grey', weight='bold', style='italic')\n",
    "            \n",
    "            e+=1\n",
    "        \n",
    "        return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "green-seeking",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x800 with 4 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 783,
       "width": 783
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = loop_plot(x_y_plots, ub_list)\n",
    "\n",
    "# CONFIQ for each plot each\n",
    "\n",
    "axs[0].set_title(\"Type base\")\n",
    "axs[1].set_title(\"Token base\")\n",
    "\n",
    "axs[2].set_title(\"Type base, case sensitive\")\n",
    "axs[3].set_title(\"Token base, case sensitive\")\n",
    "\n",
    "#plt.set_title(\"Spelling correction by Language Tool (TYPE base)\", fontweight='bold')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "czech-invite",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "\n",
    "- There are 9484 distinct missspellings (types base) to be analyzed.\n",
    "- For 84% of types, language_tool finds any suggestions.\n",
    "- For 58% of types, the correct target word is the first suggestion made by Language Tool.\n",
    "\n",
    "- (...) The upper bound value is 94% for types and 97% for tokens."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "entire-arabic",
   "metadata": {},
   "source": [
    "### Ratios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "equal-moore",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.574651436933458"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(values_token[2]/values_token[0]) # first_sugg/all_token\n",
    "display(values_token[2]/values_token[1]) # first_sugg/in_sugg"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "broken-gender",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "\n",
    "- The ratio of tokens with index 0 towards all tokens is 57 % (see 2nd subplot).\n",
    "    - From all error token, the correct word is first suggestion for 57% of tokens.\n",
    "- The ratio of tokens with index 0 towards all tokens within suggestions is 62 %.\n",
    "    - From all tokens with any suggestion, the correct words is first suggestion for 62% of these tokens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "manual-first",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Wie viel Prozent pro Text werden auf Index 0 korrigiert? Das plotten\n",
    "# Bar chart mit dieser einen Variable, das dann im Schnitt\n",
    "# Nach oben schieben\n",
    "\n",
    "# TODO: geeignete Darstellung\n",
    "# TODO: index 0 Korrektur pro filename\n",
    "# im Schnitt der Anteil der Index0 Korrekturen (idx = 0.0, idx0=True)\n",
    "# in suggestions\n",
    "# an allen Fehlern im Text (idx0=False)\n",
    "# und dann Mittelwert: Wie oft im Schnitt pro Text richtige Korrektur?\n",
    "\n",
    "# idx 0\n",
    "# alle anderen fehler\n",
    "# pro text\n",
    "\n",
    "#sns.histplot(count_idx0, palette='Greens')\n",
    "#sns.histplot(count_not_idx0, palette='Reds')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sudden-visibility",
   "metadata": {},
   "source": [
    "<a id='3'></a><br>\n",
    "## 3 - Distributions (token base)\n",
    "- Per language_tool suggestions (indices)\n",
    "- Per testpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "considered-beijing",
   "metadata": {},
   "outputs": [],
   "source": [
    "# PREPARATION\n",
    "# How often is it not in suggestions at all? dummy index -1\n",
    "data_error_token['sugg_idx'].fillna(-1, inplace=True)\n",
    "#data_error_types['sugg_idx'].fillna(-1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "unauthorized-arrest",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 0.0    14137\n",
       "-1.0    10464\n",
       "Name: sugg_idx, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(data_error_token.sugg_idx.value_counts().sort_values(ascending=False))\n",
    "#display(data_error_types.sugg_idx.value_counts().sort_values(ascending=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "united-branch",
   "metadata": {},
   "source": [
    "<a id='5'></a><br>\n",
    "#### 1) Per language_tool suggestions (indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "separated-linux",
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.countplot(data_error_types.dict_index)\n",
    "#sns.countplot(data_error_types[data_error_types.possible].dict_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "crucial-surface",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 584,
       "width": 784
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "axs = fig.add_subplot(1,1,1)\n",
    "#fig, axs = plt.subplots(1,1,1)\n",
    "#ax1 = fig.add_subplot(1, 2, 1)\n",
    "#ax2 = fig.add_subplot(1, 2, 2)\n",
    "\n",
    "sns.countplot(x='sugg_idx', data=data_error_token, palette='Reds', ax=axs)\n",
    "#sns.countplot(x='sugg_idx', data=data_error_types,  palette='Reds', ax=axs[1])\n",
    "\n",
    "axs.set_title('Token base')\n",
    "#axs[1].set_title('Type base')\n",
    "\n",
    "# Labels are wrong this way; Gives back labels in the wrong order\n",
    "#axs[0].set_xticklabels(labels=list(data_error_token.sugg_idx.unique()), rotation=50)\n",
    "#axs[1].set_xticklabels(labels=list(data_error_types.sugg_idx.unique()), rotation=50)\n",
    "\n",
    "axs.set_xticklabels(axs.get_xticklabels(), rotation=50)\n",
    "#axs[1].set_xticklabels(axs[1].get_xticklabels(), rotation=50)\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pending-internship",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "- Compared to Language Tool\n",
    "    - Not any: 2000 vs 9000 token, 1500 vs 4000 types\n",
    "    - idx0: 14000 vs 8000 token, 5250 vs 3250 types\n",
    "    - idx1: 5000 vs 2250 token, 1000 vs 1000 types\n",
    "    - rest \"quite similar\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "spatial-incidence",
   "metadata": {},
   "source": [
    "<a id='4'></a><br>\n",
    "## 4 - Relationships"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "center-wealth",
   "metadata": {},
   "source": [
    "### Relationship: Suggestions index on testpoint\n",
    "- Percent stacked bar plot\n",
    "- Percent stacked bar plot, 3 categories\n",
    "\n",
    "\n",
    "*Beforehand: <br>\n",
    "Because there are so many indices of suggestions (0-14 and -1), values equal or above 5.0 are mapped to 5.0, so that there is a category \">= 5\".*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "48d9e5e7-ff5e-4f89-aae3-d93973655a7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_error_token['testpoint'] = data_error_token.filename.apply(lambda x: x.split('-')[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f2b9a702-d973-4909-b06f-43dabdae33e1",
   "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>original</th>\n",
       "      <th>corrected</th>\n",
       "      <th>filename</th>\n",
       "      <th>freq_ori</th>\n",
       "      <th>freq_cor</th>\n",
       "      <th>freq_tup</th>\n",
       "      <th>suggestions</th>\n",
       "      <th>in_sugg</th>\n",
       "      <th>sugg_idx</th>\n",
       "      <th>idx0</th>\n",
       "      <th>testpoint</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-005-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-338-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  original corrected              filename  freq_ori  freq_cor  freq_tup  \\\n",
       "0     belt     bellt  01-005-2-III-Eis.csv        91       138        91   \n",
       "1     belt     bellt  01-338-2-III-Eis.csv        91       138        91   \n",
       "\n",
       "  suggestions in_sugg  sugg_idx   idx0 testpoint  \n",
       "0        bild   False      -1.0  False        01  \n",
       "1        bild   False      -1.0  False        01  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_error_token.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "lined-cloud",
   "metadata": {},
   "outputs": [],
   "source": [
    "# JFYI: What is on suggested index 14?\n",
    "# data_error_token[data_error_token['sugg_idx'] == 14.0]\n",
    "\n",
    "# Observation: Not in_dict but in suggestions anyways?\n",
    "# Measure: New upper bound, i. e. Language Tool corrects target words, what is recognized as (not) correct? Correct is upper bound"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ambient-coverage",
   "metadata": {},
   "outputs": [],
   "source": [
    "# MAPPING\n",
    "# Summarize values; 0, 1, 2, 3, 4, 5+\n",
    "# Has to be mapped to one value, i. e. 5\n",
    "        \n",
    "def map_idx_5(x):\n",
    "    sugg_idx = x['sugg_idx']\n",
    "    if sugg_idx in [5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0]:\n",
    "        return 5.0\n",
    "    else:\n",
    "        return sugg_idx\n",
    "    \n",
    "# Map categories and create new column for result\n",
    "data_error_token['sugg_idx_5'] = data_error_token.apply(map_idx_5, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "69e22c98-9ad3-4a58-9edf-d86d3784f0ff",
   "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>original</th>\n",
       "      <th>corrected</th>\n",
       "      <th>filename</th>\n",
       "      <th>freq_ori</th>\n",
       "      <th>freq_cor</th>\n",
       "      <th>freq_tup</th>\n",
       "      <th>suggestions</th>\n",
       "      <th>in_sugg</th>\n",
       "      <th>sugg_idx</th>\n",
       "      <th>idx0</th>\n",
       "      <th>testpoint</th>\n",
       "      <th>sugg_idx_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-005-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>01</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-338-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>01</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>01-355-2-III-Eis.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>01</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>02-220-2-IV-Weg.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>02</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>02-443-2-IV-Weg.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>02</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>02-468-2-IV-Weg.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>02</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>03-291-3-I-Frosch.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>03</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>03-294-3-I-Frosch.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>03</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>03-329-3-I-Frosch.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>03</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>belt</td>\n",
       "      <td>bellt</td>\n",
       "      <td>03-329-3-I-Frosch.csv</td>\n",
       "      <td>91</td>\n",
       "      <td>138</td>\n",
       "      <td>91</td>\n",
       "      <td>bild</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>03</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  original corrected               filename  freq_ori  freq_cor  freq_tup  \\\n",
       "0     belt     bellt   01-005-2-III-Eis.csv        91       138        91   \n",
       "1     belt     bellt   01-338-2-III-Eis.csv        91       138        91   \n",
       "2     belt     bellt   01-355-2-III-Eis.csv        91       138        91   \n",
       "3     belt     bellt    02-220-2-IV-Weg.csv        91       138        91   \n",
       "4     belt     bellt    02-443-2-IV-Weg.csv        91       138        91   \n",
       "5     belt     bellt    02-468-2-IV-Weg.csv        91       138        91   \n",
       "6     belt     bellt  03-291-3-I-Frosch.csv        91       138        91   \n",
       "7     belt     bellt  03-294-3-I-Frosch.csv        91       138        91   \n",
       "8     belt     bellt  03-329-3-I-Frosch.csv        91       138        91   \n",
       "9     belt     bellt  03-329-3-I-Frosch.csv        91       138        91   \n",
       "\n",
       "  suggestions in_sugg  sugg_idx   idx0 testpoint  sugg_idx_5  \n",
       "0        bild   False      -1.0  False        01        -1.0  \n",
       "1        bild   False      -1.0  False        01        -1.0  \n",
       "2        bild   False      -1.0  False        01        -1.0  \n",
       "3        bild   False      -1.0  False        02        -1.0  \n",
       "4        bild   False      -1.0  False        02        -1.0  \n",
       "5        bild   False      -1.0  False        02        -1.0  \n",
       "6        bild   False      -1.0  False        03        -1.0  \n",
       "7        bild   False      -1.0  False        03        -1.0  \n",
       "8        bild   False      -1.0  False        03        -1.0  \n",
       "9        bild   False      -1.0  False        03        -1.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_error_token.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "suffering-exemption",
   "metadata": {},
   "source": [
    "#### 1) Percent stacked bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "technological-bolivia",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Modularize\n",
    "\n",
    "# Get values: PERCENT STACKED BAR PLOT\n",
    "\n",
    "# 1) Get counts for hue variable sugg_idx_5\n",
    "def get_count_5(x, gb_var='testpoint'):\n",
    "    return data_error_token[data_error_token.sugg_idx_5==x].groupby(gb_var).count().reset_index()\n",
    "\n",
    "# 6\n",
    "ct_non = get_count_5(-1)\n",
    "ct_0 = get_count_5(0.0)\n",
    "ct_1 = get_count_5(1.0)\n",
    "ct_2 = get_count_5(2.0)\n",
    "ct_3 = get_count_5(3.0)\n",
    "ct_4 = get_count_5(4.0)\n",
    "ct_5 = get_count_5(5.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "059edeb8-474a-41c7-b505-5f4f5b3d2e33",
   "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>testpoint</th>\n",
       "      <th>original</th>\n",
       "      <th>corrected</th>\n",
       "      <th>filename</th>\n",
       "      <th>freq_ori</th>\n",
       "      <th>freq_cor</th>\n",
       "      <th>freq_tup</th>\n",
       "      <th>suggestions</th>\n",
       "      <th>in_sugg</th>\n",
       "      <th>sugg_idx</th>\n",
       "      <th>idx0</th>\n",
       "      <th>sugg_idx_5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [testpoint, original, corrected, filename, freq_ori, freq_cor, freq_tup, suggestions, in_sugg, sugg_idx, idx0, sugg_idx_5]\n",
       "Index: []"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Values for none, 0.0, 1.0, 2.0\n",
    "ct_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "governmental-mount",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1716, 2154, 2028, 2520, 2527, 2924, 2900, 3046, 2549, 2237]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2) Get totals, i. e. count for 100%\n",
    "#idx_5_total = [i+j+k+l+m+n+o for i,j,k,l,m,n,o in zip(ct_non['freq_ori'], ct_0['freq_ori'], ct_1['freq_ori'],\n",
    "#                                     ct_2['freq_ori'], ct_3['freq_ori'], ct_4['freq_ori'], ct_5['freq_ori'])] # list comprehension\n",
    "\n",
    "idx_5_total = [i+j for i,j in zip(ct_non['freq_ori'], ct_0['freq_ori'])]\n",
    "\n",
    "display(idx_5_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "former-somewhere",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3) Get ratio of respective bars in percent, i. e. bar \"length\"\n",
    "bars_ct_non = [i / j * 100 for i, j in zip(ct_non['freq_ori'], idx_5_total)]\n",
    "bars_ct_0 = [i / j * 100 for i, j in zip(ct_0['freq_ori'], idx_5_total)]\n",
    "#bars_ct_1 = [i / j * 100 for i, j in zip(ct_1['freq_ori'], idx_5_total)]\n",
    "#bars_ct_2 = [i / j * 100 for i, j in zip(ct_2['freq_ori'], idx_5_total)]\n",
    "#bars_ct_3 = [i / j * 100 for i, j in zip(ct_3['freq_ori'], idx_5_total)]\n",
    "#bars_ct_4 = [i / j * 100 for i, j in zip(ct_4['freq_ori'], idx_5_total)]\n",
    "#bars_ct_5 = [i / j * 100 for i, j in zip(ct_5['freq_ori'], idx_5_total)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "64c7accf-4d97-4770-b5b7-f3bf7e400c43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 541,
       "width": 812
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Code schöner machen?!\n",
    "# PERCENT STACKED BAR PLOT\n",
    "\n",
    "x_pos = np.arange(0,10) # position of x-ticks\n",
    "x_lab = ct_non['testpoint']\n",
    "\n",
    "fig = plt.figure()\n",
    "axs = fig.add_subplot(1,1,1)\n",
    "\n",
    "# Create bars\n",
    "axs.bar(x_pos, bars_ct_0, bottom = 0, label='0') # index 0\n",
    "#axs.bar(x_pos, bars_ct_1, bottom=bars_ct_0, label='1') # index 1\n",
    "#axs.bar(x_pos, bars_ct_2, bottom=[i+j for i, j in zip(bars_ct_0,bars_ct_1)], label='2') \n",
    "#axs.bar(x_pos, bars_ct_3, bottom=[i+j+k for i, j, k in zip(bars_ct_0,bars_ct_1, bars_ct_2)], label='3') \n",
    "#axs.bar(x_pos, bars_ct_4, bottom=[i+j+k+l for i, j, k, l in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3)], label='4')\n",
    "#axs.bar(x_pos, bars_ct_5, bottom=[i+j+k+l+m for i, j, k, l, m in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4)], label='>= 5')\n",
    "#axs.bar(x_pos, bars_ct_non, bottom=[i+j+k+l+m+n for i, j, k, l, m, n in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4, bars_ct_5)], label='not any')\n",
    "axs.bar(x_pos, bars_ct_non, bottom=bars_ct_0, label='not any', color='plum')\n",
    "\n",
    "# Costum x-axis\n",
    "axs.set_xticks(x_pos)\n",
    "axs.set_xticklabels(x_lab)\n",
    "axs.set_xlabel('testpoint')\n",
    "\n",
    "axs.set_ylabel('percentage')\n",
    "\n",
    "# Plot percentages\n",
    "\n",
    "#for idx, (ct_ttl, pct_non, pct_0, pct_1) in enumerate(zip(suggs_total, bars_sugg_non, bars_sugg_0, bars_sugg_1)):\n",
    "#    axs.text(idx, bars_sugg_0[idx]/2, str(round(pct_0,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "#    axs.text(idx, bars_sugg_0[idx]+(bars_sugg_1[idx]/2), str(round(pct_1,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "#    axs.text(idx, bars_sugg_0[idx]+bars_sugg_1[idx]+(bars_sugg_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "\n",
    "#for idx, (ct_ttl, pct_non, pct_0, pct_1, pct_2, pct_3, pct_4, pct_5) in enumerate(zip(idx_5_total, bars_ct_non, bars_ct_0, bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4, bars_ct_5)):\n",
    "for idx, (ct_ttl, pct_non, pct_0) in enumerate(zip(idx_5_total, bars_ct_non, bars_ct_0)): \n",
    "    axs.text(idx, bars_ct_0[idx]/2, str(round(pct_0,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+(bars_ct_1[idx]/2), str(round(pct_1,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+(bars_ct_2[idx]/2), str(round(pct_2,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+(bars_ct_3[idx]/2), str(round(pct_3,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    \n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+(bars_ct_4[idx]/2), str(round(pct_4,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    \n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+bars_ct_4[idx]+(bars_ct_5[idx]/2), str(round(pct_5,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+bars_ct_4[idx]+bars_ct_5[idx]+(bars_ct_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    axs.text(idx, bars_ct_0[idx]+(bars_ct_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    \n",
    "# Add a legend\n",
    "axs.legend(loc='upper left', bbox_to_anchor=(1,1), ncol=1)\n",
    "\n",
    "# Plot title\n",
    "axs.set_title('Index of suggestion by norma (hun-dict) on testpoint')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "constitutional-blackjack",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "\n",
    "For most of tokens,\n",
    "- the suggestion is on index 0 (blue proportion)\n",
    "- or suggestion is at second position (index 1, orange proportion).\n",
    "    \n",
    "    \n",
    "In the course of time, it can be observed that... <br>\n",
    "_..., see also below_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "improved-olympus",
   "metadata": {},
   "source": [
    "<a id='6'></a><br>\n",
    "#### 2) Percent stacked bar plot, 3 categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "hourly-thousand",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Per testpoint, count of error at index 0 in contrast to all other errors\n",
    "# alle anderen\n",
    "# sugg_idx nicht gefunden?! -1\n",
    "def map_idx_bin(x):\n",
    "    sugg_idx = x['sugg_idx']\n",
    "    if sugg_idx == 0.0:\n",
    "        return 0.0\n",
    "    elif sugg_idx in np.arange(1.0,15.0):\n",
    "        return 1.0\n",
    "    else:\n",
    "        return sugg_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "employed-austin",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map categories\n",
    "data_error_token['sugg_idx_three'] = data_error_token.apply(map_idx_bin, axis=1)\n",
    "#data_error_types['sugg_idx_three'] = data_error_types.apply(map_idx_bin, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "intended-baking",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Modularize\n",
    "# Count of error tokens, i. e. freq_ori, for each category (-1; 0; 1)\n",
    "suggs_non = data_error_token[data_error_token.sugg_idx_three==-1].groupby('testpoint').count().reset_index() # returns index, not testpoint as index\n",
    "#display(suggs_non)\n",
    "suggs_0 = data_error_token[data_error_token.sugg_idx_three==0].groupby('testpoint').count().reset_index()\n",
    "#display(suggs_0)\n",
    "#suggs_1 = data_error_token[data_error_token.sugg_idx_three==1].groupby('testpoint').count().reset_index()\n",
    "#display(suggs_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "lesser-dubai",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get total, i. e. count for 100%\n",
    "suggs_total = [i+j for i,j in zip(suggs_non['freq_ori'], suggs_0['freq_ori'])] # list comprehension\n",
    "#display(suggs_total)\n",
    "\n",
    "# Get ratio of respective bars in percent, i. e. bar \"length\"\n",
    "bars_sugg_non = [i / j * 100 for i, j in zip(suggs_non['freq_ori'], suggs_total)]\n",
    "bars_sugg_0 = [i / j * 100 for i, j in zip(suggs_0['freq_ori'], suggs_total)]\n",
    "#bars_sugg_1 = [i / j * 100 for i, j in zip(suggs_1['freq_ori'], suggs_total)]\n",
    "#display(bars_sugg_non, bars_sugg_0, bars_sugg_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "focused-austin",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 541,
       "width": 825
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PERCENT STACKED BAR PLOT\n",
    "\n",
    "x_pos = np.arange(0,10) # position of x-ticks\n",
    "x_lab = suggs_non['testpoint']\n",
    "\n",
    "fig = plt.figure()\n",
    "axs = fig.add_subplot(1,1,1)\n",
    "# Create bars\n",
    "axs.bar(x_pos, bars_sugg_0, bottom = 0, color='orange', label='index = 0') # index 0\n",
    "#axs.bar(x_pos, bars_sugg_1, bottom=bars_sugg_0, color='green', label='index >= 1') # index 1\n",
    "axs.bar(x_pos, bars_sugg_non, bottom=bars_sugg_0, color='blue', label='not any') # noty any\n",
    "\n",
    "# Costum x-axis\n",
    "axs.set_xticks(x_pos)\n",
    "axs.set_xticklabels(x_lab)\n",
    "axs.set_xlabel('testpoint')\n",
    "\n",
    "axs.set_ylabel('percentage')\n",
    "\n",
    "# Plot percentages\n",
    "for idx, (ct_ttl, pct_non, pct_0) in enumerate(zip(suggs_total, bars_sugg_non, bars_sugg_0)):\n",
    "    axs.text(idx, bars_sugg_0[idx]/2, str(round(pct_0,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_sugg_0[idx]+(bars_sugg_1[idx]/2), str(round(pct_1,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    axs.text(idx, bars_sugg_0[idx]+(bars_sugg_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "\n",
    "# Add a legend\n",
    "axs.legend(loc='upper left', bbox_to_anchor=(1,1), ncol=1)\n",
    "\n",
    "# Plot title\n",
    "axs.set_title('Suggestion by norma (hun-dict) on testpoint')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "inner-brighton",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "55.92\n",
      "58.54\n",
      "********************\n",
      "44.08\n",
      "41.46\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "# Get averages for testpoints 1-5 and 6-10\n",
    "# Shares ordered by appereance in plot\n",
    "shares = [bars_sugg_0, bars_sugg_non]\n",
    "helpers.print_AM_half_tp(shares)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interpreted-overhead",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "\n",
    "<span style='background : yellow' > <br>\n",
    "Trends to be observed...</span> \n",
    "- Portion of index 0 gets just slightly higher over time (rougly 56,3% to 57,6; increase 1,3%)\n",
    "- Portion of indices above 0 decrease only slightly over time (from roughly 35,3% to 34,7%; decrease 0,6%)\n",
    "- Portion of noty any decrease slightly over time (from 8,5% to 7,4%; decrease 1,1%)\n",
    "\n",
    "\n",
    "Generally spoken:\n",
    "- Portion of not any holds below one tenth (about 8%).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "welsh-force",
   "metadata": {},
   "source": [
    "<a id='7'></a><br>\n",
    "### Relationship: Suggestions index on Levenshtein distance\n",
    "- Percent stacked bar plot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vital-algeria",
   "metadata": {},
   "source": [
    "#### - Percent stacked bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e2849887-5cd3-4a9f-925e-d2a1e9428892",
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.metrics.distance import edit_distance\n",
    "\n",
    "#data_error_types['edit_dst'] = 'data_error_types.apply(lambda r: edit_distance(r.original, r.corrected), axis=1)\n",
    "data_error_token['edit_dst'] = data_error_token.apply(lambda r: edit_distance(r.original, r.corrected), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0e75116e-071b-4da0-bf92-18e2b943006b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map them to edit distance 1 for plotting of Levenshtein distance stats\n",
    "data_error_token['edit_dst_0excl'] = data_error_token.edit_dst.apply(lambda x: 1 if x == 0 else x)\n",
    "#data_error_types['edit_dst_0excl'] = data_error_types.edit_dst.apply(lambda x: 1 if x == 0 else x)\n",
    "#display(data_error_token[data_error_token['edit_dst_0excl']==0])\n",
    "#display(data_error_types[data_error_types['edit_dst_0excl']==0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1a7703a1-b03b-4a73-b1f6-dc2d89c2a7c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map values above 4 to 4 to summarize categories with few counts\n",
    "data_error_token['edit_dst_4'] = data_error_token.edit_dst_0excl.apply(lambda x: 4 if x in [5,6,7,8,9] else x)\n",
    "#data_error_types['edit_dst_4'] = data_error_types.edit_dst_0excl.apply(lambda x: 4 if x in [5,6,7,8,9] else x)\n",
    "#data_error_token.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "employed-liberia",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_count_zero(x, gb_var='edit_dst_4'):\n",
    "    grouped = data_error_token[data_error_token.sugg_idx_5==x].groupby(gb_var).count()\n",
    "    # From edit-distance 2 on, there are zero values for the categories (index of suggestions) that are not counted by count\n",
    "    # Therefore zero counts have to be added manually\n",
    "    added_zero_values = grouped.reindex(data_error_token.edit_dst_4.unique()).fillna(0).astype(int)\n",
    "    return added_zero_values.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "million-gilbert",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Modularize\n",
    "# 1) Get counts for each category (-1; 0; 1; 2; 3; 4; 5)\n",
    "# Function see above\n",
    "ct_non = get_count_zero(-1, gb_var='edit_dst_4')\n",
    "ct_0 = get_count_zero(0.0, gb_var='edit_dst_4')\n",
    "#ct_1 = get_count_zero(1.0, gb_var='edit_dst_4')\n",
    "#ct_2 = get_count_zero(2.0, gb_var='edit_dst_4')\n",
    "#ct_3 = get_count_zero(3.0, gb_var='edit_dst_4')\n",
    "#ct_4 = get_count_zero(4.0, gb_var='edit_dst_4')\n",
    "#ct_5 = get_count_zero(5.0, gb_var='edit_dst_4')\n",
    "#display(ct_non)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "special-champagne",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2) Get total, i. e. count for 100%\n",
    "#ct_total_2 = [i+j+k+l+m+n+o for i,j,k,l,m,n,o in zip(ct_non['sugg_idx_5'], ct_0['sugg_idx_5'], ct_1['sugg_idx_5'],\n",
    "#                                                   ct_2['sugg_idx_5'], ct_3['sugg_idx_5'], ct_4['sugg_idx_5'], ct_5['sugg_idx_5'])]\n",
    "ct_total_2 = [i+j for i,j in zip(ct_non['sugg_idx_5'], ct_0['sugg_idx_5'])]    \n",
    "#display(ct_total_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "5bca3005-2b25-4ae7-a627-e5ce26a1bdd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[18563, 4597, 1028, 413]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ct_total_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "military-payment",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3) Get ratio of respective bars in percent, i. e. bar \"length\"\n",
    "bars_ct_non = [i / j * 100 for i, j in zip(ct_non['sugg_idx_5'], ct_total_2)]\n",
    "bars_ct_0 = [i / j * 100 for i, j in zip(ct_0['sugg_idx_5'], ct_total_2)]\n",
    "#bars_ct_1 = [i / j * 100 for i, j in zip(ct_1['sugg_idx_5'], ct_total_2)]\n",
    "#bars_ct_2 = [i / j * 100 for i, j in zip(ct_2['sugg_idx_5'], ct_total_2)]\n",
    "#bars_ct_3 = [i / j * 100 for i, j in zip(ct_3['sugg_idx_5'], ct_total_2)]\n",
    "#bars_ct_4 = [i / j * 100 for i, j in zip(ct_4['sugg_idx_5'], ct_total_2)]\n",
    "#bars_ct_5 = [i / j * 100 for i, j in zip(ct_5['sugg_idx_5'], ct_total_2)]\n",
    "#display(bars_ct_non)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "outstanding-thomas",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 541,
       "width": 812
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PERCENT STACKED BAR PLOT\n",
    "\n",
    "x_pos = np.arange(0,4) # position of x-ticks\n",
    "#x_lab = ct_non['edit_dst_4']\n",
    "\n",
    "fig = plt.figure()\n",
    "axs = fig.add_subplot(1,1,1)\n",
    "\n",
    "# Create bars\n",
    "axs.bar(x_pos, bars_ct_0, bottom = 0, label='0') # index 0\n",
    "#axs.bar(x_pos, bars_ct_1, bottom=bars_ct_0, label='1') # index 1\n",
    "#axs.bar(x_pos, bars_ct_2, bottom=[i+j for i, j in zip(bars_ct_0,bars_ct_1)], label='2') \n",
    "#axs.bar(x_pos, bars_ct_3, bottom=[i+j+k for i, j, k in zip(bars_ct_0,bars_ct_1, bars_ct_2)], label='3') \n",
    "#axs.bar(x_pos, bars_ct_4, bottom=[i+j+k+l for i, j, k, l in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3)], label='4')\n",
    "#axs.bar(x_pos, bars_ct_5, bottom=[i+j+k+l+m for i, j, k, l, m in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4)], label='>= 5')\n",
    "\n",
    "#axs.bar(x_pos, bars_ct_non, bottom=[i+j+k+l+m+n for i, j, k, l, m, n in zip(bars_ct_0,bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4, bars_ct_5)], label='not any')\n",
    "axs.bar(x_pos, bars_ct_non, bottom=bars_ct_0, label='not any', color='plum')\n",
    "\n",
    "# Costum x-axis\n",
    "axs.set_xticks(x_pos)\n",
    "axs.set_xticklabels(['1','2','3','> 4'])\n",
    "axs.set_xlabel('edit_dst_4')\n",
    "\n",
    "axs.set_ylabel('percentage')\n",
    "\n",
    "# Plot percentages\n",
    "#for idx, (ct_ttl, pct_non, pct_0, pct_1, pct_2, pct_3, pct_4, pct_5) in enumerate(zip(ct_total_2, bars_ct_non, bars_ct_0, bars_ct_1, bars_ct_2, bars_ct_3, bars_ct_4, bars_ct_5)):\n",
    "for idx, (ct_ttl, pct_non, pct_0) in enumerate(zip(ct_total_2, bars_ct_non, bars_ct_0)):\n",
    "    axs.text(idx, bars_ct_0[idx]/2, str(round(pct_0,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+(bars_ct_1[idx]/2), str(round(pct_1,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+(bars_ct_2[idx]/2), str(round(pct_2,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+(bars_ct_3[idx]/2), str(round(pct_3,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+(bars_ct_4[idx]/2), str(round(pct_4,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+bars_ct_4[idx]+(bars_ct_5[idx]/2), str(round(pct_5,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    \n",
    "    #axs.text(idx, bars_ct_0[idx]+bars_ct_1[idx]+bars_ct_2[idx]+bars_ct_3[idx]+bars_ct_4[idx]+bars_ct_5[idx]+(bars_ct_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    axs.text(idx, bars_ct_0[idx]+(bars_ct_non[idx]/2), str(round(pct_non,1))+'%', va='center', ha='center', rotation=20, fontsize=10)\n",
    "    \n",
    "# Add a legend\n",
    "axs.legend(loc='upper left', bbox_to_anchor=(1,1), ncol=1)\n",
    "\n",
    "# Plot title\n",
    "axs.set_title('Index of suggestion by norma (hun-dict) on Levensthein distance')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "collect-recycling",
   "metadata": {},
   "source": [
    "#### <span style='background : yellow' > Key message: </span>\n",
    "\n",
    "<span style='background : yellow' >  <br>\n",
    "Trends to be observed ...</span>\n",
    "- language_tool catches 96% of tokens with edit distance of 1, 60% are on index 0 (resulting in proportion at about 62,5%)\n",
    "- language_tool catches 84% of tokens with edit distance of 2, 52% are on index 0 (resulting in proportion at about 61,9%)\n",
    "- language_tool catches at about 70% of tokens with edit distance of 3, 38% are on index 0 (resulting in proportion at about 54,3%)\n",
    "- language_tool catches about 60% of tokens with edit distance of 4, 38% are on index 0 (resulting in proportion at about 63,3%) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "respective-intention",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO: Percent stacked bar plot, 3 categories\n",
    "# with edit_dst_4 & sugg_idx_three"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "bodu-spell_Env",
   "language": "python",
   "name": "bodu-spell_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}