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Python Pandas - Return numpy array of python datetime.date objects
To return numpy array of python datetime.date objects, use the datetimeindex.date property in Pandas.
At first, import the required libraries −
import pandas as pd
Create a DatetimeIndex with period 3 and frequency as us i.e. nanoseconds −
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns')
Display DateTimeIndex −
print("DateTimeIndex...\n", datetimeindex)Returns only the date part of Timestamps without timezone information −
print("\nThe numpy array (date part)..\n",datetimeindex.date)
Example
Following is the code −
import pandas as pd
# DatetimeIndex with period 3 and frequency as us i.e. nanoseconds
# The timezone is Australia/Sydney
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns')
# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)
# Returns only the date part of Timestamps without timezone information
print("\nThe numpy array (date part)..\n",datetimeindex.date)Output
This will produce the following code −
DateTimeIndex... DatetimeIndex([ '2021-10-20 02:30:50+11:00', '2021-10-20 02:30:50.000000001+11:00', '2021-10-20 02:30:50.000000002+11:00'], dtype='datetime64[ns, Australia/Sydney]', freq='N') The numpy array (date part).. [datetime.date(2021, 10, 20) datetime.date(2021, 10, 20) datetime.date(2021, 10, 20)]
Updated on: 18-Oct-2021
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