Python Pandas - Return numpy array of python datetime.time objects

To return numpy array of python datetime.time objects, use the datetimeindex.time property in Pandas. This property extracts only the time component from datetime objects, discarding date and timezone information.

Syntax

DatetimeIndex.time

This property returns a numpy array containing datetime.time objects.

Creating a DatetimeIndex

First, let's create a DatetimeIndex with timezone information ?

import pandas as pd

# Create DatetimeIndex with nanosecond frequency
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns')
print("DateTimeIndex...")
print(datetimeindex)

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')

Extracting Time Components

Use the .time property to extract only the time part without timezone information ?

import pandas as pd

# Create DatetimeIndex
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns')

# Extract time components
time_array = datetimeindex.time
print("Time components:")
print(time_array)
print(f"Type: {type(time_array)}")
print(f"Element type: {type(time_array[0])}")

Time components:
[datetime.time(2, 30, 50) datetime.time(2, 30, 50, 0, 1)
 datetime.time(2, 30, 50, 0, 2)]
Type: <class 'numpy.ndarray'>
Element type: <class 'datetime.time'>

Complete Example

Here's a comprehensive example showing both date and time extraction ?

import pandas as pd

# Create DatetimeIndex with timezone
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=3, tz='Australia/Sydney', freq='ns')

print("DateTimeIndex:")
print(datetimeindex)

# Extract date components
print("\nDate components:")
print(datetimeindex.date)

# Extract time components
print("\nTime components:")
print(datetimeindex.time)

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')

Date components:
[datetime.date(2021, 10, 20) datetime.date(2021, 10, 20)
 datetime.date(2021, 10, 20)]

Time components:
[datetime.time(2, 30, 50) datetime.time(2, 30, 50, 0, 1)
 datetime.time(2, 30, 50, 0, 2)]

Key Points

• The .time property returns a numpy array of datetime.time objects
• Timezone information is stripped from the result
• Microsecond and nanosecond precision is preserved when present
• Each element in the array is a standard Python datetime.time object

Conclusion

The DatetimeIndex.time property provides an efficient way to extract time components from datetime data. It returns a numpy array of Python datetime.time objects while preserving precision and removing timezone information.