Pandas Series dt.freq | Retrieve Frequency of Pandas Time Series
Pandas dt.freq attribute returns the time series frequency applied on the given series object if any, else it returns None.
Examples
Python3
import pandas as pd
sr = pd.Series([ '2012-12-31' , '2019-1-1 12:30' , '2008-02-2 10:30' ,
'2010-1-1 09:25' , '2019-12-31 00:00' ])
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
sr = pd.to_datetime(sr)
result = sr.dt.freq
print (result)
|
Output
Syntax
Syntax: Series.dt.freqÂ
Parameter: NoneÂ
Returns: frequency
How to Find Frequency of Time Series Data in Pandas
To find the frequency of the time series we use dt.freq attribute of the Pandas library in Python.
Let us understand it with an example:
Example:
Use the Series.dt.freq attribute to find the frequency of the underlying DateTime based data in the given series object.
Python3
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-31 00:00' , periods = 5 , freq = 'D' ,
tz = 'US / Central' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use the dt.freq attribute to find the frequency of the DateTime based data in the given series object.
Python3
result = sr.dt.freq
print (result)
|
Output :
As we can see in the output, the dt.freq attribute has successfully returned the frequency of the underlying DateTime based data in the given Series object.
Last Updated :
08 Feb, 2024
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