{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['created_at'] = pd.to_datetime(df['created_at'])\n",
    "df['created_at'] = df['created_at'].dt.tz_localize('UTC').dt.tz_convert('Asia/Seoul')\n",
    "df['cancelled_wait_time'] = df['cancelled_at'] - df['created_at']\n",
    "df['year'] = df['created_at'].dt.year\n",
    "df['month'] = df['created_at'].dt.month\n",
    "df['day'] = df['created_at'].dt.day\n",
    "df['date'] = df['created_at'].dt.date\n",
    "df['time'] = df['created_at'].dt.time\n",
    "df['quarter'] = df['created_at'].dt.quarter\n",
    "df['weekday'] = df['created_at'].dt.weekday\n",
    "df['hour'] = df['created_at'].dt.hour\n",
    "df['created_at'] = pd.to_datetime(df['created_at']) + pd.DateOffset(hours=9)\n",
    "df['created_at_30min'] = df['created_at'].dt.floor(\"30min\")\n",
    "df['created_at_hour'] = df['created_at'].dt.round(\"H\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 더미 데이터 생성하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-01-01 00:00:00', '2018-01-01 01:00:00',\n",
       "               '2018-01-01 02:00:00', '2018-01-01 03:00:00',\n",
       "               '2018-01-01 04:00:00', '2018-01-01 05:00:00',\n",
       "               '2018-01-01 06:00:00', '2018-01-01 07:00:00',\n",
       "               '2018-01-01 08:00:00', '2018-01-01 09:00:00',\n",
       "               ...\n",
       "               '2018-12-31 15:00:00', '2018-12-31 16:00:00',\n",
       "               '2018-12-31 17:00:00', '2018-12-31 18:00:00',\n",
       "               '2018-12-31 19:00:00', '2018-12-31 20:00:00',\n",
       "               '2018-12-31 21:00:00', '2018-12-31 22:00:00',\n",
       "               '2018-12-31 23:00:00', '2019-01-01 00:00:00'],\n",
       "              dtype='datetime64[ns]', length=8761, freq='H')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start='2018-01-01', end='2019-01-01', freq='1H')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',\n",
       "               '2018-01-05', '2018-01-06', '2018-01-07', '2018-01-08',\n",
       "               '2018-01-09', '2018-01-10',\n",
       "               ...\n",
       "               '2018-12-23', '2018-12-24', '2018-12-25', '2018-12-26',\n",
       "               '2018-12-27', '2018-12-28', '2018-12-29', '2018-12-30',\n",
       "               '2018-12-31', '2019-01-01'],\n",
       "              dtype='datetime64[ns]', length=366, freq='D')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start='2018-01-01', end='2019-01-01', freq='1D')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 맨 마지막날을 제외하고 싶으면 아래처럼"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04',\n",
       "               '2018-01-05', '2018-01-06', '2018-01-07', '2018-01-08',\n",
       "               '2018-01-09', '2018-01-10',\n",
       "               ...\n",
       "               '2018-12-22', '2018-12-23', '2018-12-24', '2018-12-25',\n",
       "               '2018-12-26', '2018-12-27', '2018-12-28', '2018-12-29',\n",
       "               '2018-12-30', '2018-12-31'],\n",
       "              dtype='datetime64[ns]', length=365, freq='D')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start='2018-01-01', end='2019-01-01', freq='1D')[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.5"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}