pandas Code Challenges

Test your pandas knowledge with this edition of Code Challenges.

Introduction

• Stretch and test your knowledge with pandas code challenges
• What you should know

1. Reading and Initial Exploration of Data

• Read data from CSV and Excel files
• Check DataFrame information and identify types of columns
• The summary statistics of numerical and categorical features
• Add new columns to a DataFrame

2. Indexing and Slicing

• Select specific columns in a DataFrame
• Subset the data from labels using .loc[] method
• Subset the data from indexing using .iloc[] method

3. Data Cleaning

• Check for missing values
• Correct the data type of a column
• Parse dates in time series data

4. Filtering Data

• Write conditional statements to filter rows
• Chain multiple conditionals to narrow down the search
• Using bitwise operators to filter rows
• Filtering to find target demography

5. Grouping and Aggregation

• Apply the three-step process to group and aggregate data
• Group and aggregate multiple columns
• Apply a custom aggregate function
• Calculate stock returns for every year since 2003