{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "############ YAAHOO QUESTION ANSWER  #################\n",
    "\n",
    "df = pd.read_json(\"hf://datasets/baohuynhbk14/yahoo-question-answers-question-answers/yahoo_answers_title_answer.jsonl\", lines=True)\n",
    "\n",
    "test = list( df.data )\n",
    "\n",
    "df =  pd.DataFrame( {\n",
    "    \"Questions\" :   [ test[index][0] for index in range( len( test ) ) ] ,\n",
    "    \"Answers\" : [ test[index][1] for index in range( len( test ) ) ]\n",
    "})\n",
    "df.to_csv(\"Question_Ans_Dataset.csv\" ,index = False )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "######## DATASET LINK : https://huggingface.co/datasets/junaid20/question_answer #############\n",
    "\n",
    "\n",
    "df = pd.read_csv(\"hf://datasets/junaid20/question_answer/dataset.csv\")\n",
    "df.drop( \"text\"  , axis = 1 , inplace = True )\n",
    "df.to_csv(\"Question_Ans_Dataset_2.csv\" , index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "########## DATASET LINK : https://huggingface.co/datasets/toughdata/quora-question-answer-dataset ###########################\n",
    "df = pd.read_json(\"hf://datasets/toughdata/quora-question-answer-dataset/Quora-QuAD.jsonl\", lines=True)\n",
    "df.to_csv(\"Question_Ans_Dataset_3.csv\" , index = False )\n",
    "\n",
    "\n",
    "#### CANNOT DONWLOAD THIS DATASET BECAUSE THIS IS TOOO LARGE #########"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ########## DATASET LINK : https://huggingface.co/datasets/formido/outfit_recomendation ##########\n",
    "\n",
    "df = pd.read_csv(\"hf://datasets/formido/outfit_recomendation/new_data.csv\")\n",
    "\n",
    "df[\"instruction\"] = df.instruction + \" \" + df.input\n",
    "\n",
    "df.drop( \"input\"  , axis = 1 , inplace = True )\n",
    "\n",
    "df.to_csv(\"Recommendation_Data.csv\"  , index = False )"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sunyenv",
   "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": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}