Python Pandas - Snap time stamps in DateTimeIndex to nearest occurring frequency\\n\\n

To snap time stamps in DateTimeIndex to nearest occurring frequency, use the DateTimeIndex.snap() method. Set the frequency using the freq parameter.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 6 and frequency as D i.e. day −

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

Display DateTimeIndex −

print("DateTimeIndex...\n", datetimeindex)

Snap time stamps to nearest occurring i.e. Month end here −

print("\nSnap time stamps to nearest occurring frequency...\n",
datetimeindex.snap(freq='M'))

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 6 and frequency as D i.e. day
# The timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Adelaide', freq='D')

# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)

# display DateTimeIndex frequency
print("\nDateTimeIndex frequency...\n", datetimeindex.freq)

# Snap time stamps to nearest occurring i.e. Month end here
print("\nSnap time stamps to nearest occurring frequency...\n",
datetimeindex.snap(freq='M'))

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex(['2021-10-20 02:30:50+10:30', '2021-10-21 02:30:50+10:30',
'2021-10-22 02:30:50+10:30', '2021-10-23 02:30:50+10:30',
'2021-10-24 02:30:50+10:30', '2021-10-25 02:30:50+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='D')
DateTimeIndex frequency...
<Day>

Snap time stamps to nearest occurring frequency...
DatetimeIndex(['2021-10-31 02:30:50+10:30', '2021-10-31 02:30:50+10:30',
'2021-10-31 02:30:50+10:30', '2021-10-31 02:30:50+10:30',
'2021-10-31 02:30:50+10:30', '2021-10-31 02:30:50+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq=None)