readability scoring

text_analysis/020125_CONTRIBUTING_readability.csv

@@ -0,0 +1,716 @@
+filename,flesch_reading_ease,flesch_kincaid_grade,linsear_write_formula,dale_chall_readability_score,mcalpine_eflaw,reading_time,char_count,word_count
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import math"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "contributing_readability = pd.read_csv(\"020125_CONTRIBUTING_readability.csv\")\n",
+    "readme_readability = pd.read_csv(\"020125_README_readability.csv\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "      <th>4</th>\n",
+       "      <td>mypaint_libmypaint_hullabaloo_CONTRIBUTING.md</td>\n",
+       "      <td>51.04</td>\n",
+       "      <td>9.1</td>\n",
+       "      <td>6.5625</td>\n",
+       "      <td>9.93</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>8.68</td>\n",
+       "      <td>591</td>\n",
+       "      <td>94</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                            filename  flesch_reading_ease  \\\n",
+       "0  pytest-dev_pytest-bdd.git_hullabaloo_CONTRIBUT...                40.95   \n",
+       "1      lxqt_qterminal.git_hullabaloo_CONTRIBUTING.md                51.14   \n",
+       "2    rbenv_ruby-build.git_hullabaloo_CONTRIBUTING.md                71.14   \n",
+       "3    muse-sequencer_muse.git_hullabaloo_CONTRIBUTING               -68.97   \n",
+       "4      mypaint_libmypaint_hullabaloo_CONTRIBUTING.md                51.04   \n",
+       "\n",
+       "   flesch_kincaid_grade  linsear_write_formula  dale_chall_readability_score  \\\n",
+       "0                  10.9                10.6000                         11.61   \n",
+       "1                   9.0                 8.0000                          9.63   \n",
+       "2                   7.6                 9.0000                         10.05   \n",
+       "3                  24.1                 3.5000                         25.99   \n",
+       "4                   9.1                 6.5625                          9.93   \n",
+       "\n",
+       "   mcalpine_eflaw  reading_time  char_count  word_count  \n",
+       "0            18.2          6.58         448          67  \n",
+       "1            15.3         10.44         711         105  \n",
+       "2            27.0          1.16          79          17  \n",
+       "3             6.0          1.09          74           5  \n",
+       "4            16.8          8.68         591          94  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contributing_readability.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "214.0"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contributing_readability['word_count'].median()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9.1"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "readme_readability['flesch_kincaid_grade'].median()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "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": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

text_analysis/readability.ipynb

@@ -0,0 +1,104 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os \n",
+    "import textstat\n",
+    "import csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "contributing_directory = \"/data/users/mgaughan/kkex/012825_cam_revision_main/final_data/first_version_documents/contributing/\"\n",
+    "readme_directory = \"/data/users/mgaughan/kkex/012825_cam_revision_main/final_data/first_version_documents/readme/\"\n",
+    "\n",
+    "csv_fieldnames = [ 'filename', 'flesch_reading_ease', 'flesch_kincaid_grade', 'linsear_write_formula', 'dale_chall_readability_score', 'mcalpine_eflaw', 'reading_time', 'char_count', 'word_count']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_file(output_csv, wdirectory):\n",
+    "    with open(output_csv, 'w') as csvfile: \n",
+    "        writer = csv.DictWriter(csvfile, fieldnames = csv_fieldnames) \n",
+    "        writer.writeheader() \n",
+    "        files = os.listdir(wdirectory)\n",
+    "        for file in files:\n",
+    "            file_dict = {\"filename\": file}\n",
+    "            full_address = wdirectory + file\n",
+    "            file_dict = get_readibility(full_address, file_dict)\n",
+    "            writer.writerow(file_dict)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_readibility(file_address, file_dict):\n",
+    "    file = open(file_address, \"r\", encoding='utf-8', errors=\"ignore\")\n",
+    "    document = file.read()\n",
+    "    file_dict['flesch_reading_ease'] = textstat.flesch_reading_ease(document)\n",
+    "    file_dict['flesch_kincaid_grade'] = textstat.flesch_kincaid_grade(document)\n",
+    "    file_dict['linsear_write_formula'] = textstat.linsear_write_formula(document)\n",
+    "    file_dict['dale_chall_readability_score'] = textstat.dale_chall_readability_score(document)\n",
+    "    file_dict['mcalpine_eflaw'] = textstat.mcalpine_eflaw(document)\n",
+    "    file_dict['reading_time']  = textstat.reading_time(document, ms_per_char=14.69)\n",
+    "    file_dict['char_count'] = textstat.char_count(document, ignore_spaces=True)\n",
+    "    file_dict['word_count'] = textstat.lexicon_count(document, removepunct=True)\n",
+    "    return file_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generate_file('020125_CONTRIBUTING_readability.csv', contributing_directory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generate_file('020125_README_readability.csv', readme_directory)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "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": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}