Python Pandas - Detect the frequency of the given DatetimeIndex object

PythonServer Side ProgrammingProgramming

To detect the frequency of the given DatetimeIndex object, use the DateTimeIndex.inferred_freq property.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 5 and frequency as Y i.e. years. The timezone is Australia/Adelaide −

datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=5, tz='Australia/Adelaide', freq='3Y')

Display DateTimeIndex −

print("DateTimeIndex...\n", datetimeindex)

Display DateTimeIndex frequency −

print("\nDateTimeIndex frequency...\n", datetimeindex.freq)

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 5 and frequency as Y i.e. years
# The timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=5, tz='Australia/Adelaide', freq='3Y')

# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)

# display DateTimeIndex frequency
print("\nDateTimeIndex frequency...\n", datetimeindex.freq)

# detect the frequency
print("\nInferred DateTimeIndex frequency...\n", datetimeindex.inferred_freq)

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex(['2021-12-31 02:30:50+10:30', '2024-12-31 02:30:50+10:30',
'2027-12-31 02:30:50+10:30', '2030-12-31 02:30:50+10:30',
'2033-12-31 02:30:50+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='3A-DEC')
DateTimeIndex frequency...
<3 * YearEnds: month=12>

Inferred DateTimeIndex frequency...
3A-DEC
raja
Updated on 18-Oct-2021 12:56:45

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