Python Pandas - Return a new Timedelta with minutely ceiling resolution

The timedelta.ceil() method returns a new Timedelta object ceiled to a specified resolution. For minutely ceiling resolution, use the frequency parameter freq='T' to round up to the nearest minute.

Syntax

The syntax for the ceil() method is ?

timedelta.ceil(freq)

Parameters

freq ? The frequency string representing the ceiling resolution. Use 'T' for minutes, 'H' for hours, 'D' for days, etc.

Creating a Timedelta Object

First, let's create a Timedelta object with various time components ?

import pandas as pd

# Create a Timedelta object
timedelta = pd.Timedelta('2 days 10 hours 45 min 20 s')

# Display the original Timedelta
print("Original Timedelta:", timedelta)

Original Timedelta: 2 days 10:45:20

Applying Minutely Ceiling

Use ceil(freq='T') to round up to the nearest minute ?

import pandas as pd

# Create a Timedelta object
timedelta = pd.Timedelta('2 days 10 hours 45 min 20 s')

# Apply minutely ceiling resolution
ceiled_timedelta = timedelta.ceil(freq='T')

print("Original Timedelta:", timedelta)
print("Minutely Ceiled:", ceiled_timedelta)

Original Timedelta: 2 days 10:45:20
Minutely Ceiled: 2 days 10:46:00

How It Works

The ceil() method rounds up the time components. Since our original Timedelta has 20 seconds, it gets rounded up to the next minute (10:46:00). If there were no seconds, the time would remain unchanged.

Different Frequency Examples

Compare minutely ceiling with other frequency resolutions ?

import pandas as pd

# Create a Timedelta with precise time
timedelta = pd.Timedelta('1 day 5 hours 23 min 45 s')

print("Original:", timedelta)
print("Minutely ceiling (T):", timedelta.ceil(freq='T'))
print("Hourly ceiling (H):", timedelta.ceil(freq='H'))
print("Daily ceiling (D):", timedelta.ceil(freq='D'))

Original: 1 days 05:23:45
Minutely ceiling (T): 1 days 05:24:00
Hourly ceiling (H): 1 days 06:00:00
Daily ceiling (D): 2 days 00:00:00

Conclusion

The timedelta.ceil(freq='T') method rounds up time to the nearest minute, removing seconds and microseconds. This is useful for time-based data analysis where you need consistent minute-level precision.