Let’s read the budget.xlsx file into a DataFrame:

import pandas as pd

data = pd.read_excel("budget.xlsx", parse_dates=["Opening Date"])

data

Output:

Let;s return the data type of each column using dtypes:

data.dtypes

Output:

The Opening Date column contains datetime objects.

We can extract various parts from the date - year, month, date & quarter - using Pandas dt, which is the accessor object to the datetime properties of a Pandas Series.

Note that the dt accessor object works only with datetime data types.

data["Opening Date"].dt.year

Output:

data["Opening Date"].dt.month

Output:

data["Opening Date"].dt.day

Output:

data["Opening Date"].dt.quarter

Output: