python-根据列中的值重复行x次 [英] python - Duplicate rows x number of times based on a value in a column

问题描述

我在旅馆预订时有一个熊猫数据框.每行都是一个预订，像这样:

I have a pandas dataframe of bookings at a hotel. Each row is a booking, like this:

Name             Arrival       Departure     RoomNights
Trent Cotchin    29/10/2017    2/11/2017     4
Dustin Martin    1/11/2017     4/11/2017     3
Alex Rance       2/11/2017     3/11/2017     1

我想使用python进行转换，以便每一行成为一个roomnight.输出看起来像这样:

I want to use python to convert so that each row becomes a roomnight. The output would look like this:

Name             Arrival       Departure     RoomNights   RoomNight Date
Trent Cotchin    29/10/2017    2/11/2017     4            29/10/2017
Trent Cotchin    29/10/2017    2/11/2017     4            30/10/2017
Trent Cotchin    29/10/2017    2/11/2017     4            31/10/2017
Trent Cotchin    29/10/2017    2/11/2017     4            1/11/2017
Dustin Martin    1/11/2017     4/11/2017     3            1/11/2017
Dustin Martin    1/11/2017     4/11/2017     3            2/11/2017
Dustin Martin    1/11/2017     4/11/2017     3            3/11/2017
Alex Rance       2/11/2017     3/11/2017     1            2/11/2017

这使我可以轻松求和任何给定日期/月份的房晚总数.

This allows me to easily sum the total number of roomnights for any given day/month.

推荐答案

使用:

#convert columns to datetime
df['Arrival'] = pd.to_datetime(df['Arrival'])
df['Departure'] = pd.to_datetime(df['Departure'])

#repeat rows
df = df.loc[df.index.repeat(df['RoomNights'])]
#group by index with transform for date ranges
df['RoomNight Date'] =(df.groupby(level=0)['Arrival']
                         .transform(lambda x: pd.date_range(start=x.iat[0], periods=len(x))))
#unique default index
df = df.reset_index(drop=True)
print (df)
            Name    Arrival  Departure  RoomNights RoomNight Date
0  Trent Cotchin 2017-10-29 2017-11-02           4     2017-10-29
1  Trent Cotchin 2017-10-29 2017-11-02           4     2017-10-30
2  Trent Cotchin 2017-10-29 2017-11-02           4     2017-10-31
3  Trent Cotchin 2017-10-29 2017-11-02           4     2017-11-01
4  Dustin Martin 2017-11-01 2017-11-04           3     2017-11-01
5  Dustin Martin 2017-11-01 2017-11-04           3     2017-11-02
6  Dustin Martin 2017-11-01 2017-11-04           3     2017-11-03
7     Alex Rance 2017-11-02 2017-11-03           1     2017-11-02

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