计算日期值是否出现在两个不同的时间之间python pandas [英] calculate if date value occurs between two different times python pandas

问题描述

我正在尝试创建一个新列，以确定行值是否在营业时间之间".为此，我尝试使用时间间隔功能. 如果有更简单的方法，我不需要使用它.

I am trying to create a new column to determine if a row value is "between business hours". To do this I am trying to use the between time function. I dont need to use it if there is an easier way.

我有一个数据框，其中包含日期" ，开始时间" ，结束时间" 的列.

I have a dataframe with columns for 'Date', 'StartHour', 'End Hour'.

问题:

如果"日期"列中的时间在"开始时间"和""之间，我想给出"True"或"False"结束时间的时间.

I would like to give a 'True' or 'False' if the time in the 'Date' column is between the 'StartHour' and 'EndHour' time.

import pandas as pd
import numpy as np

#create dataframe with dates
d = {'Date': ['2016-11-17 05:01:45','2011-01-04 16:34:00','2011-01-05 09:25:45',
              '2011-01-10 12:00:45','2011-01-14 07:05:45','2011-01-15 10:19:00',
              '2011-01-17 13:59:45','2011-01-19 18:39:45','2011-01-22 06:19:45'], 
     'StartHour': ['16:00','16:00','16:00','16:00','16:00','16:00','16:00','16:00','16:00'],
     'EndHour': ['10:00','10:00','10:00','10:00','10:00','10:00','10:00','10:00','10:00'],
     'Station_ID': ['A','A','A','A','B','B','B','B','B']}
df = pd.DataFrame(data=d)
#convert date column to datetime
df['Date'] = df['Date'].values.astype('datetime64[ns]')


#************************
# set index to Date (need for 'between_time')
df = df.set_index('Date')

# run calculation for between time
df['between_business_hours'] = df.index.isin(df.between_time('16:00', '10:00', include_start=True, include_end=True).index)


df

我已经使用between_time函数计算了一个列，但这仅允许我将硬编码值用于开始时间和结束时间.我想使用"StartTime"和"EndTime"列中的值.通过使用ween_time函数，我可能会比需要做的更加困难.

I have calculated a column using the between_time function but this only lets me use hard coded values for the start and end time. I would like to use the values in the 'StartTime' and 'EndTime' columns. I am probably making this more difficult than it needs to be by using the between_time function.

我希望输出看起来像这样.

I would like the output to looks something like this.

                    EndHour StartHour   Station_ID  between_business_hours
Date                
2016-11-17 05:01:45  10:00   16:00       A            True
2011-01-04 16:34:00  10:00   16:00       A            True
2011-01-05 09:25:45  10:00   16:00       A            True
2011-01-10 12:00:45  10:00   16:00       A            False
2011-01-14 07:05:45  10:00   16:00       B            True
2011-01-15 10:19:00  10:00   16:00       B            False
2011-01-17 13:59:45  10:00   16:00       B            False
2011-01-19 18:39:45  10:00   16:00       B            True
2011-01-22 06:19:45  10:00   16:00       B            True

感谢您的帮助

推荐答案

您不需要设置index

df.Date.dt.strftime('%H:%M').between(df.StartHour,df.EndHour)
Out[297]: 
0    False
1     True
2     True
3     True
4    False
5     True
6     True
7     True
8    False
dtype: bool

更新

l=[df.loc[[y],:].index.indexer_between_time(df.loc[y,'StartHour'],df.loc[y,'EndHour'])==0 for y in df.index]
df['New']=l
df.New=df.New.str[0].fillna(False)
df
                    EndHour StartHour Station_ID    New
Date                                                   
2016-11-17 05:01:45   10:00     16:00          A   True
2011-01-04 16:34:00   10:00     16:00          A   True
2011-01-05 09:25:45   10:00     16:00          A   True
2011-01-10 12:00:45   10:00     16:00          A  False
2011-01-14 07:05:45   10:00     16:00          B   True
2011-01-15 10:19:00   10:00     16:00          B  False
2011-01-17 13:59:45   10:00     16:00          B  False
2011-01-19 18:39:45   10:00     16:00          B   True
2011-01-22 06:19:45   10:00     16:00          B   True

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