[英]Allocating the timeframe based on the datetime using pandas
I need to find the timeframe from the master based on the input time.我需要根据输入时间从主人那里找到时间范围。 cust_id starttime 0 1 2000-01-01 09:00:03 1 2 2000-01-01 18:01:03
cust_id 开始时间 0 1 2000-01-01 09:00:03 1 2 2000-01-01 18:01:03
output i needed is cust_id starttime timeframe 0 1 2000-01-01 09:00:03 morning 1 2 2000-01-01 18:01:03 evening我需要的输出是 cust_id starttime timeframe 0 1 2000-01-01 09:00:03 早上 1 2 2000-01-01 18:01:03 晚上
Code for creating master timeframe details mastdf={'timeframe':['morning','latemorning','midnoon','evening'],'start_time':['8:00:00','11:00:00','13:00:00','17:00:00'],'end_time':['10:59:59','13:59:59','16:59:59','7:59:59']}enter code here用于创建主时间框架详细信息的代码 mastdf={'timeframe':['morning','latemorning','midnoon','evening'],'start_time':['8:00:00','11:00:00 ','13:00:00','17:00:00'],'end_time':['10:59:59','13:59:59','16:59:59','7 :59:59']}在此处输入代码
Code for creating input dataframe inputdf={'cust_id':[1,2],'starttime':['2000-01-01 09:00:03', '2000-01-01 18:01:03']}创建输入数据帧的代码 inputdf={'cust_id':[1,2],'starttime':['2000-01-01 09:00:03', '2000-01-01 18:01:03']}
Use cut
for binning but first convert values to timedeltas by to_timedelta
, create bins with add endpoint 24H
and for timeframe between 00:00:00
to 8:00:00
is used fillna
by last value of column timeframe
:使用
cut
的分级,但首先将值转换为通过timedeltas to_timedelta
,创建附加端点箱24H
和之间的时间框架00:00:00
至8:00:00
用于fillna
通过列的最后一个值timeframe
:
mastdf={'timeframe':['morning','latemorning','midnoon','evening'],
'start_time':['8:00:00','11:00:00','13:00:00','17:00:00'],
'end_time':['10:59:59','13:59:59','16:59:59','7:59:59']}
mastdf = pd.DataFrame(mastdf)
print (mastdf)
timeframe start_time end_time
0 morning 8:00:00 10:59:59
1 latemorning 11:00:00 13:59:59
2 midnoon 13:00:00 16:59:59
3 evening 17:00:00 7:59:59
inputdf={'cust_id':[1,2],'starttime':['2000-01-01 09:00:03', '2000-01-01 18:01:03']}
inputdf = pd.DataFrame(inputdf)
inputdf['starttime'] = pd.to_datetime(inputdf['starttime'])
start = pd.to_timedelta(mastdf['start_time']).tolist() + [pd.Timedelta(24, unit='h')]
s = pd.to_timedelta(inputdf['starttime'].dt.strftime('%H:%M:%S'))
last = mastdf['timeframe'].iat[-1]
inputdf['timeframe'] = pd.cut(s,
bins=start,
labels=mastdf['timeframe'], right=False).fillna(last)
print (inputdf)
cust_id starttime timeframe
0 1 2000-01-01 09:00:03 morning
1 2 2000-01-01 18:01:03 evening
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