Business Days with Custom Holidays.ipynb

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   "source": [
    "import pandas as pd"
   ]
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   "source": [
    "start_date = ['2019-06-03', '2019-06-13', '2019-10-01', '2019-09-01']\n",
    "end_date =  ['2019-08-31', '2019-06-21', '2019-10-25', '2019-12-25']\n",
    "data = pd.DataFrame(list(zip(start_date,end_date)), columns = ['Start Date', 'End Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Start Date</th>\n",
       "      <th>End Date</th>\n",
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       "      <th>0</th>\n",
       "      <td>2019-06-03</td>\n",
       "      <td>2019-08-31</td>\n",
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       "      <th>1</th>\n",
       "      <td>2019-06-13</td>\n",
       "      <td>2019-06-21</td>\n",
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       "      <th>2</th>\n",
       "      <td>2019-10-01</td>\n",
       "      <td>2019-10-25</td>\n",
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       "      <th>3</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>2019-12-25</td>\n",
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      "text/plain": [
       "   Start Date    End Date\n",
       "0  2019-06-03  2019-08-31\n",
       "1  2019-06-13  2019-06-21\n",
       "2  2019-10-01  2019-10-25\n",
       "3  2019-09-01  2019-12-25"
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    "data"
   ]
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  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "holiday_dates = [pd.datetime(2019, 8, 15), \n",
    "            pd.datetime(2019, 10, 2),\n",
    "            pd.datetime(2019, 10, 8),\n",
    "            pd.datetime(2019, 10, 28),\n",
    "            pd.datetime(2019, 12, 25)]"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2019-08-01', '2019-08-02', '2019-08-05', '2019-08-06',\n",
       "               '2019-08-07', '2019-08-08', '2019-08-09', '2019-08-12',\n",
       "               '2019-08-13', '2019-08-14', '2019-08-16', '2019-08-19',\n",
       "               '2019-08-20', '2019-08-21', '2019-08-22', '2019-08-23',\n",
       "               '2019-08-26', '2019-08-27', '2019-08-28', '2019-08-29',\n",
       "               '2019-08-30'],\n",
       "              dtype='datetime64[ns]', freq='C')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "# Exclude weekends and custome holidays\n",
    "pd.bdate_range(pd.datetime(2019, 8, 1), pd.datetime(2019, 8, 31),  holidays=holiday_dates, freq='C', weekmask = None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Business Days'] = data.apply(lambda x: len(pd.bdate_range(x['Start Date'], \n",
    "                                                                x['End Date'], \n",
    "                                                                holidays=holiday_dates,\n",
    "                                                                freq='C', \n",
    "                                                                weekmask = None)), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Start Date</th>\n",
       "      <th>End Date</th>\n",
       "      <th>Business Days</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-06-03</td>\n",
       "      <td>2019-08-31</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-06-13</td>\n",
       "      <td>2019-06-21</td>\n",
       "      <td>7</td>\n",
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       "      <th>2</th>\n",
       "      <td>2019-10-01</td>\n",
       "      <td>2019-10-25</td>\n",
       "      <td>17</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>2019-12-25</td>\n",
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       "   Start Date    End Date  Business Days\n",
       "0  2019-06-03  2019-08-31             64\n",
       "1  2019-06-13  2019-06-21              7\n",
       "2  2019-10-01  2019-10-25             17\n",
       "3  2019-09-01  2019-12-25             79"
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