Learn more about selecting and adding columns to Pandas Dataframes in my blog post here.

Let’s first read an Excel worksheet into a Pandas Dataframe:

import pandas as pd

data = pd.read_excel("budget.xlsx")

data.columns = data.columns.str.lower().str.strip()

data

Output:

We can select both rows and columns using chaining as shown below:

data[1:5][['store code', 'revenue']]

Output:

First, we selected the store code & revenue columns for all rows and then we pulled out rows with indices 0, 1, 2, 3 & 4.

Note that column and row selection order does not matter.

data[['store code', 'revenue']][:5]

Output: