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

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.freq 

Parameter: None 

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.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D',
                            tz = 'US / Central'))

# Creating the index
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']

# set the index
sr.index = idx

# Print the series
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.

# find the frequency
result = sr.dt.freq

# print the result
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.