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