Python Pandas - Return index locations of values between particular time of day in DateTimeIndex

To return index locations of values between particular time of day in DateTimeIndex, use the DateTimeIndex.indexer_between_time() method. This method is useful for filtering time-series data based on specific time ranges.

Syntax

DateTimeIndex.indexer_between_time(start_time, end_time, include_start=True, include_end=True)

Parameters

The method accepts the following parameters:

• start_time ? The start time in 'HH:MM:SS' format
• end_time ? The end time in 'HH:MM:SS' format
• include_start ? Boolean to include start time (default: True)
• include_end ? Boolean to include end time (default: True)

Creating a DateTimeIndex

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

import pandas as pd

# Create DatetimeIndex with period 5 and frequency as 20 minutes
# The timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=5, tz='Australia/Adelaide', freq='20T')

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

DateTimeIndex...
DatetimeIndex(['2021-10-30 02:30:50+10:30', '2021-10-30 02:50:50+10:30',
               '2021-10-30 03:10:50+10:30', '2021-10-30 03:30:50+10:30',
               '2021-10-30 03:50:50+10:30'],
              dtype='datetime64[ns, Australia/Adelaide]', freq='20T')

Finding Index Locations Between Time Range

Now let's find index locations of values between specific times using indexer_between_time() ?

import pandas as pd

datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=5, tz='Australia/Adelaide', freq='20T')

# Find index locations between 02:30:50 and 03:20:50
indices = datetimeindex.indexer_between_time('02:30:50', '03:20:50')

print("Index locations between 02:30:50 and 03:20:50:")
print(indices)

# Show the actual datetime values at these indices
print("\nCorresponding datetime values:")
print(datetimeindex[indices])

Index locations between 02:30:50 and 03:20:50:
[0 1 2]

Corresponding datetime values:
DatetimeIndex(['2021-10-30 02:30:50+10:30', '2021-10-30 02:50:50+10:30',
               '2021-10-30 03:10:50+10:30'],
              dtype='datetime64[ns, Australia/Adelaide]', freq='20T')

Complete Example

Here's a comprehensive example showing different time filtering operations ?

import pandas as pd

# Create DatetimeIndex
datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=5, tz='Australia/Adelaide', freq='20T')

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

print("\nDateTimeIndex frequency...")
print(datetimeindex.freq)

# Find index at specific time
print("\nIndex locations at time 03:10:50...")
specific_time_indices = datetimeindex.indexer_at_time('03:10:50')
print(specific_time_indices)

# Find indices between time range
print("\nIndex locations between 02:30:50 and 03:20:50...")
range_indices = datetimeindex.indexer_between_time('02:30:50', '03:20:50')
print(range_indices)

DateTimeIndex...
DatetimeIndex(['2021-10-30 02:30:50+10:30', '2021-10-30 02:50:50+10:30',
               '2021-10-30 03:10:50+10:30', '2021-10-30 03:30:50+10:30',
               '2021-10-30 03:50:50+10:30'],
              dtype='datetime64[ns, Australia/Adelaide]', freq='20T')

DateTimeIndex frequency...
<20 * Minutes>

Index locations at time 03:10:50...
[2]

Index locations between 02:30:50 and 03:20:50...
[0 1 2]

Conclusion

The indexer_between_time() method efficiently returns integer indices for datetime values falling within a specified time range. This is particularly useful for time-series data analysis and filtering operations on DateTimeIndex objects.