{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_manifest = pd.read_csv('0203_readme_merged_manifest.csv')\n",
    "topic_distributions = pd.read_csv('020125_README_file_topic_distributions.csv')\n",
    "readability_scores = pd.read_csv('020125_README_readability.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4248"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_merge = readability_scores.merge(topic_distributions, on=['filename'],how=\"inner\")\n",
    "#primary_merge = first_merge.merge(readability_scores, )\n",
    "first_merge['fvf_filepath'] = first_merge['filename']\n",
    "second_merge = first_merge.merge(merged_manifest, on=['fvf_filepath'], how=\"inner\")\n",
    "len(second_merge)"
   ]
  }
 ],
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   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
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 "nbformat": 4,
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