Upload date-conversion.ipynb
Browse files- date-conversion.ipynb +54 -0
date-conversion.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "b42faeb2",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"\n",
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"df = pd.read_csv('data/distilbert-usa.csv', low_memory=False)\n",
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"\n",
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"df['Created At'] = pd.to_datetime(df['Created At'], errors='coerce')\n",
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"# remove rows where 'Created At' is NaT\n",
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"df = df.dropna(subset=['Created At'])\n",
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"\n",
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"df['Month_Year'] = df['Created At'].dt.strftime('%m/%Y')\n",
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"df.head()\n",
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"\n",
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"df.to_csv('data/distilbert-usa.csv', index=False)"
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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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"id": "829d418b",
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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 (ipykernel)",
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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": "3.11.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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