Single Condition

Let’s read an Excel file into a DataFrame:

import pandas as pd

budget = pd.read_excel("budget.xlsx").fillna(value = 0)

budget

Output:

Let’s say we want to extract the stores that are located in New Delhi.

We can filter the DataFrame in 2 steps:

• Step-1: Write the filter condition.

condition = budget["City"] == "New Delhi"

condition

The result is a new boolean Series.

Output:

• Step-2: Pass the condition in square brackets that follow the name of the DataFrame

budget[condition]

Output:

Multiple conditions

Let’s say we want to extract the stores that are flagged as LTL and have July’19 budget numbers greater than 10.

We can achieve this using the & logical operator in Pandas.

condition1 = budget["LTL Flag"] == "LTL"

condition2 = budget["July'19 Budget"] > 10

budget[condition1 & condition2]

Output:

Next, let’s say we want to extract stores that are located either in Mumbai or Bangalore.

We can achieve this using the | (vertical pipe) logical operator in Pandas.

condition1 = budget["City"] == "Mumbai"

condition2 = budget["City"] == "Bangalore"

budget[condition1 | condition2]

Output: