88 lines
1.8 KiB
Text
88 lines
1.8 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import parsing_functions as pf\n",
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"import re\n",
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"import pandas as pd\n",
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"import time"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"listOfFiles = pf.getListOfFiles(\"data\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"commentaires = []\n",
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"\n",
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"for xlpath in listOfFiles:\n",
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" comments_df = []\n",
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" media, post_id = re.match(r\"data/([A-Z]+)/comments([0-9a-z\\-]+)\\.xlsx\",xlpath).groups()\n",
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" comments_df = pf.get_comments(xlpath)\n",
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" comments_df['media']=media\n",
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" comments_df['post_id']=post_id\n",
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" commentaires.append(comments_df)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"commentaires_df = pd.concat(commentaires, ignore_index=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"commentaires_df.to_csv(\"refined_data/commentaires_df.csv\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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