Loop to grab 1% of each csv.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b705c4db",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a6cf9c0",
   "metadata": {},
   "source": [
    "# GENERATING SAMPLE SETS FOR EACH MONTH (JULY 2021-JUNE 2022)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "327e50d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "monthyear=[\"202107\",\"202108\",\"202109\",\"202110\",\"202111\",\"202112\",\"202201\",\"202202\",\"202203\",\"202204\",\"202205\",\"202206\"]\n",
    "sample_df = pd.DataFrame()\n",
    "for month in monthyear:\n",
    "    pathwaytofile=f\"files_for_analysis/{month}-citibike-tripdata.csv\"\n",
    "    df=pd.read_csv(pathwaytofile,low_memory=False)\n",
    "    df = df.sample(frac=0.010, random_state=42)\n",
    "    sample_df=sample_df.append(df)\n",
    "\n",
    "sample_df = sample_df.reset_index(drop=True)\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f5b5b43",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_df.to_csv(\"July21-June22_citibike_rides_sample.csv\", index=False)"
   ]
  }
 ],
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