date_trunc in Python Pandas

date_trunc is the date function used to truncate a date or datetime value to the start of a given unit of duration. The function helps in truncating the date column to year, decade, century, quarter, month, week, day, hour, minute, second, or millisecond. In this article, we will truncate the date column using python pandas.

TL;DR #

use dt.floor('<trunc-param>') or dt.to_period(<trunc-param>)

date_trunc In Pandas #

for applying dt functions, we must make sure the column type is timestamp.

Convert column to datetime #

We can convert the pandas column to datetime using, pd.to_datetime() function.

Example:

data['order_dt'] = pd.to_datetime(data['order_time'])

Apply Truncate Operation #

Once we have pandas datetime column, we can apply truncate operation on datetime column using dt.floor('<trunc-param>') or dt.to_period(<trunc-param>)

Example:

data['order_hour'] = data['order_dt'].floor('h')

Truncate By Hour #

Use h or H as param.

Example:

data['order_hour'] = data['order_dt'].floor('H')

Truncate By Month #

Use M as param.

Example:

data['order_hour'] = data['order_dt'].floor('M')

Truncate By Minute #

Use m as param.

Example:

data['order_hour'] = data['order_dt'].floor('m')