Python Pandas - Extract the microseconds from the DateTimeIndex with specific time series frequency

To extract the microseconds from a DateTimeIndex with specific time series frequency, use the DateTimeIndex.microsecond property. This property returns an Index containing the microsecond component of each datetime.

Creating DateTimeIndex with Microsecond Frequency

First, let's create a DateTimeIndex with microsecond frequency ?

import pandas as pd

# Create DatetimeIndex with period 6 and frequency as 'us' (microseconds)
# The timezone is Australia/Sydney
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='us')

print("DateTimeIndex...")
print(datetimeindex)

DateTimeIndex...
DatetimeIndex(['2021-10-20 02:30:50+11:00',
               '2021-10-20 02:30:50.000001+11:00',
               '2021-10-20 02:30:50.000002+11:00',
               '2021-10-20 02:30:50.000003+11:00',
               '2021-10-20 02:30:50.000004+11:00',
               '2021-10-20 02:30:50.000005+11:00'],
              dtype='datetime64[ns, Australia/Sydney]', freq='U')

Extracting Microseconds

Now let's extract the microsecond component from each datetime ?

import pandas as pd

datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='us')

# Display frequency information
print("DateTimeIndex frequency:")
print(datetimeindex.freq)

# Extract microseconds using the microsecond property
microseconds = datetimeindex.microsecond
print("\nMicroseconds extracted:")
print(microseconds)
print(f"\nType: {type(microseconds)}")

DateTimeIndex frequency:
<Micro>

Microseconds extracted:
Index([0, 1, 2, 3, 4, 5], dtype='int64')

Type: <class 'pandas.core.indexes.base.Index'>

Understanding the Results

The microsecond property returns values from 0 to 999999, representing the microsecond component of each datetime. In our example, the DateTimeIndex starts at exactly 02:30:50 (0 microseconds) and increments by 1 microsecond for each subsequent datetime.

import pandas as pd

# Example with larger microsecond values
datetimeindex = pd.date_range('2021-10-20 02:30:50.123456', periods=4, freq='100us')

print("DateTimeIndex with larger microsecond values:")
print(datetimeindex)

print("\nExtracted microseconds:")
print(datetimeindex.microsecond)

DateTimeIndex with larger microsecond values:
DatetimeIndex(['2021-10-20 02:30:50.123456',
               '2021-10-20 02:30:50.123556',
               '2021-10-20 02:30:50.123656',
               '2021-10-20 02:30:50.123756'],
              dtype='datetime64[ns]', freq='100U')

Extracted microseconds:
Index([123456, 123556, 123656, 123756], dtype='int64')

Conclusion

The DateTimeIndex.microsecond property efficiently extracts microsecond components from datetime objects. It returns an Index with integer values ranging from 0 to 999999, making it useful for time-based analysis and filtering operations.