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pythonpandastimestampperiod

Check if a pandas.Timestamp is in a pandas.Period

# pseudo code: 
myPeriod.contains(myTimestamp)

I found the lack of such function in pandas quite surprising. Am I missing something here?

Solution

  • You can try isin if you have multiple values:

    print df.index
PeriodIndex(['2015-11'], dtype='int64', name=u'', freq='M')

d = "2015-09-01"
d1 = "2015-10-01"
print df.index.isin([pd.to_datetime(d).to_period('M'), pd.to_datetime(d1).to_period('M')])
[False]

d = "2015-11-01"
d1 = "2015-11-01"   
print df.index.isin([pd.to_datetime(d).to_period('M'), pd.to_datetime(d1).to_period('M')])
[ True]

    If you want compare only one datetime, easier is use (thanks maxymoo):

    d = "2015-09-01"    
print df.index == pd.to_datetime(d).to_period('M')  
[False]

d = "2015-11-01"    
print df.index == pd.to_datetime(d).to_period('M')  
[True]

    Or with Series:

    print df.a
0   2015-11
Name: a, dtype: object

d = "2015-09-01"
d1 = "2015-10-01"   
print df.a.isin([pd.to_datetime(d).to_period('M'), pd.to_datetime(d1).to_period('M')]).values
[False]

d = "2015-11-01"
d1 = "2015-11-01"
print df.a.isin([pd.to_datetime(d).to_period('M'), pd.to_datetime(d1).to_period('M')]).values
[ True]