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