Filtering Rows in DataFrames

Sample DataFrame

Let’s start with a sample DataFrame that we’ll use throughout this section:

Filtering Rows

Pandas provides powerful ways to filter rows based on conditions. We use boolean indexing to select rows that meet specific criteria.

Syntax

 # Basic filtering
filtered_df = df[df['column_name'] condition]
 
# Multiple conditions
filtered_df = df[(condition1) & (condition2)] 

Exercise 2.1: Basic Filtering (Numbers)

Run the code below to filter the DataFrame and show only employees who are older than 30:

Exercise 2.2: Basic Filtering (Strings)

Modify the code below to filter the DataFrame and show only employees from Chicago:

Exercise 2.3: Filtering with AND (&)

Modify the code below to filter the DataFrame and show employees from New York with a salary greater than 60000:

Exercise 2.4: Filtering with OR (|)

Modify the code below to filter the DataFrame and show employees who are either from Chicago or have a salary less than 70000:

Exercise 2.5: Complex Filtering (Combining AND and OR)

Modify the code below to filter the DataFrame and show employees who are either from New York and older than 30, or have a salary greater than 70000:

Quiz