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JBed/AirBnB_Prob.ipynb

Created April 17, 2017 18:33
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AirBnB_Prob.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>check_in_day</th>\n",
" <th>check_out_day</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2017-01-08</td>\n",
" <td>2017-01-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2017-01-14</td>\n",
" <td>2017-01-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2017-02-20</td>\n",
" <td>2017-02-26</td>\n",
" </tr>\n",
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"</table>\n",
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],
"text/plain": [
" check_in_day check_out_day\n",
"0 2017-01-08 2017-01-12\n",
"1 2017-01-14 2017-01-18\n",
"2 2017-02-20 2017-02-26"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"stays = pd.DataFrame({'check_in_day':['Jan 08 2017','Jan 14 2017','Feb 20 2017'], \\\n",
" 'check_out_day':['Jan 12 2017','Jan 18 2017','Feb 26 2017']})\n",
"\n",
"stays['check_in_day'] = pd.to_datetime(stays['check_in_day'])\n",
"stays['check_out_day'] = pd.to_datetime(stays['check_out_day'])\n",
"\n",
"stays"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### my idea is to refactor so that the index is the day and the column is True/False is occupied that night."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>occupied_that_night</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-01-01</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-02</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-03</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-04</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-05</th>\n",
" <td>False</td>\n",
" </tr>\n",
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"</table>\n",
"</div>"
],
"text/plain": [
" occupied_that_night\n",
"2017-01-01 False\n",
"2017-01-02 False\n",
"2017-01-03 False\n",
"2017-01-04 False\n",
"2017-01-05 False"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# this is all of the days that the room could be occupied in Jan 2017\n",
"Jan_bookings = pd.DataFrame()\n",
"Jan_dateRange = pd.date_range(start='2017-01-01', end='2017-01-31')\n",
"Jan_bookings['occupied_that_night'] = [False]*len(Jan_dateRange)\n",
"Jan_bookings.index = Jan_dateRange\n",
"Jan_bookings.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# make a df for the first stay \n",
"stay_i = pd.DataFrame()\n",
"dr = pd.date_range(start=stays.iloc[0]['check_in_day'],\\\n",
" end=stays.iloc[0]['check_out_day']-pd.Timedelta('1 day')\\\n",
" ,freq='D')\n",
"stay_i['stay_1'] = ['True']*len(dr)\n",
"stay_i.index = dr"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-01-01</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-02</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-03</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-04</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-05</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-06</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-07</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-08</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-09</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-10</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-11</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-12</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-13</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-14</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-15</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-16</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-17</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-18</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-19</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-20</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-21</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-22</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-23</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-24</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-25</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-26</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-27</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-28</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-29</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-30</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-31</th>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0\n",
"2017-01-01 False\n",
"2017-01-02 False\n",
"2017-01-03 False\n",
"2017-01-04 False\n",
"2017-01-05 False\n",
"2017-01-06 False\n",
"2017-01-07 False\n",
"2017-01-08 True\n",
"2017-01-09 True\n",
"2017-01-10 True\n",
"2017-01-11 True\n",
"2017-01-12 False\n",
"2017-01-13 False\n",
"2017-01-14 False\n",
"2017-01-15 False\n",
"2017-01-16 False\n",
"2017-01-17 False\n",
"2017-01-18 False\n",
"2017-01-19 False\n",
"2017-01-20 False\n",
"2017-01-21 False\n",
"2017-01-22 False\n",
"2017-01-23 False\n",
"2017-01-24 False\n",
"2017-01-25 False\n",
"2017-01-26 False\n",
"2017-01-27 False\n",
"2017-01-28 False\n",
"2017-01-29 False\n",
"2017-01-30 False\n",
"2017-01-31 False"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# and merge... collapse wiht any...\n",
"pd.merge(Jan_bookings, stay_i, left_index=True, right_index=True,\\\n",
" how='outer').fillna(False).any(axis=1).to_frame()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# ok now we just need to loop"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"Jan_bookings = pd.DataFrame()\n",
"Jan_dateRange = pd.date_range(start='2017-01-01', end='2017-01-31')\n",
"Jan_bookings['occupied_that_night'] = [False]*len(Jan_dateRange)\n",
"Jan_bookings.index = Jan_dateRange\n",
"Jan_bookings.head()\n",
"\n",
"# now loop over the stays in Jan\n",
"for ii in range(len(stays)):\n",
" stay_i = pd.DataFrame()\n",
" dr = pd.date_range(start=stays.iloc[ii]['check_in_day'],\\\n",
" end=stays.iloc[ii]['check_out_day']-pd.Timedelta('1 day')\\\n",
" ,freq='D')\n",
" stay_i['Stay_i'] = [True]*len(dr)\n",
" stay_i.index = dr\n",
" Jan_bookings = pd.merge(Jan_bookings, stay_i, \\\n",
" left_index=True, right_index=True,\\\n",
" how='outer').fillna(False).any(axis=1).to_frame()\n",
"\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-01-01</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-02</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-03</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-04</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-05</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-06</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-07</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-08</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-09</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-10</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-11</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-12</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-13</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-14</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-15</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-16</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-17</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-18</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-19</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-20</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-21</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-22</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-23</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-24</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-25</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-26</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-27</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-28</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-29</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-30</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-01-31</th>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-20</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-21</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-22</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-23</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-24</th>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-25</th>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0\n",
"2017-01-01 False\n",
"2017-01-02 False\n",
"2017-01-03 False\n",
"2017-01-04 False\n",
"2017-01-05 False\n",
"2017-01-06 False\n",
"2017-01-07 False\n",
"2017-01-08 True\n",
"2017-01-09 True\n",
"2017-01-10 True\n",
"2017-01-11 True\n",
"2017-01-12 False\n",
"2017-01-13 False\n",
"2017-01-14 True\n",
"2017-01-15 True\n",
"2017-01-16 True\n",
"2017-01-17 True\n",
"2017-01-18 False\n",
"2017-01-19 False\n",
"2017-01-20 False\n",
"2017-01-21 False\n",
"2017-01-22 False\n",
"2017-01-23 False\n",
"2017-01-24 False\n",
"2017-01-25 False\n",
"2017-01-26 False\n",
"2017-01-27 False\n",
"2017-01-28 False\n",
"2017-01-29 False\n",
"2017-01-30 False\n",
"2017-01-31 False\n",
"2017-02-20 True\n",
"2017-02-21 True\n",
"2017-02-22 True\n",
"2017-02-23 True\n",
"2017-02-24 True\n",
"2017-02-25 True"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Jan_bookings"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>False</th>\n",
" <th>True</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"0 False True \n",
"0 3 3\n",
"1 3 3\n",
"2 3 2\n",
"3 4 1\n",
"4 4 1\n",
"5 3 2\n",
"6 3 2"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Jan_bookings.groupby(Jan_bookings.index.dayofweek)[0].value_counts().unstack()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x10c887240>"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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VfXjUOQ4lyduAtwJ7gZOAi6vqH7t1u6rq5FHmO5QkX2cm8zHAd4GNs/6i7qiqF4804ABJ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\nSWrQ/wLzIqr7r9ItEgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10c89fda0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# these would be the unoccupied nights\n",
"# Monday=0, Sunday=6\n",
"Jan_bookings.groupby(Jan_bookings.index.dayofweek)[0].value_counts()\\\n",
".unstack()[False].plot(kind='bar')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"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": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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