Python | Pandas Series.dt.microsecond
Last Updated :
20 Mar, 2019
Series.dt
can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.microsecond
attribute return a numpy array containing the microsecond of the datetime in the underlying data of the given series object.
Syntax: Series.dt.microsecond
Parameter : None
Returns : numpy array
Example #1: Use Series.dt.microsecond
attribute to return the microsecond of the datetime in the underlying data of the given Series object.
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-12 12:12' ,
periods = 5 , freq = '5U' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use Series.dt.microsecond
attribute to return the microsecond of the datetime in the underlying data of the given Series object.
result = sr.dt.microsecond
print (result)
|
Output :
As we can see in the output, the Series.dt.microsecond
attribute has successfully accessed and returned the microsecond of the datetime in the underlying data of the given series object.
Example #2 : Use Series.dt.microsecond
attribute to return the microsecond of the datetime in the underlying data of the given Series object.
import pandas as pd
sr = pd.Series(pd.date_range( '2008-2-9 08:20:21' ,
periods = 5 , freq = '9U' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use Series.dt.microsecond
attribute to return the microsecond of the datetime in the underlying data of the given Series object.
result = sr.dt.microsecond
print (result)
|
Output :
As we can see in the output, the Series.dt.microsecond
attribute has successfully accessed and returned the microsecond of the datetime in the underlying data of the given series object.
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