Ready to turn messy datasets into actionable insights? Pandas is the backbone of data science in Python, but reading documentation only gets you so far. You need to get your hands dirty! We’ve curated five beginner-friendly labs that take you from data cleaning basics to advanced boolean reductions. Whether you’re a budding data scientist or a curious analyst, these interactive challenges will sharpen your skills in a real-world playground.
Handling NaN and Duplicates
Difficulty: Beginner | Time: 20 minutes
In this challenge, you will deal with a dataset containing missing (NaN) values and duplicate entries. The main objective is to clean and preprocess the dataset by handling these NaN and duplicate values using pandas library. This challenge will test your ability …
Ready to turn messy datasets into actionable insights? Pandas is the backbone of data science in Python, but reading documentation only gets you so far. You need to get your hands dirty! We’ve curated five beginner-friendly labs that take you from data cleaning basics to advanced boolean reductions. Whether you’re a budding data scientist or a curious analyst, these interactive challenges will sharpen your skills in a real-world playground.
Handling NaN and Duplicates
Difficulty: Beginner | Time: 20 minutes
In this challenge, you will deal with a dataset containing missing (NaN) values and duplicate entries. The main objective is to clean and preprocess the dataset by handling these NaN and duplicate values using pandas library. This challenge will test your ability to work with complex data structures, manipulate and analyze data, and make decisions based on the dataset’s characteristics.
Practice on LabEx → | Tutorial →
Analyzing Sales and Discounts
Difficulty: Beginner | Time: 15 minutes
In this challenge, you will be given a dataset containing details of various products sold by a retail company. Your task is to utilize the Pandas library to perform data manipulations and transformations, specifically focusing on the iteration methods provided by Pandas.
Practice on LabEx → | Tutorial →
Pandas Basic Data Cleaning
Difficulty: Beginner | Time: 25 minutes
In this lab, you will learn the fundamental techniques for cleaning data using the Pandas library, including handling missing values, removing duplicates, and correcting data types.
Practice on LabEx → | Tutorial →
Pandas Grouping and Aggregating
Difficulty: Beginner | Time: 25 minutes
In this lab, you will learn the fundamentals of data grouping and aggregation using the Pandas library. You’ll practice using groupby() to create groups and apply various aggregation functions.
Practice on LabEx → | Tutorial →
Pandas Boolean Reductions Data Analysis
Difficulty: Beginner | Time: 20 minutes
Welcome to this Pandas programming challenge. In this challenge, you’ll utilize the power of Pandas boolean reductions to analyze complex datasets and solve real-world problems. Boolean reductions can be used to filter, summarize and understand complex data in a simple yet effective manner.
Practice on LabEx → | Tutorial →
Mastering Pandas is a journey, and these five labs are the perfect roadmap to get you started. By completing these hands-on exercises, you’re not just learning syntax—you’re building the problem-solving muscles required for a career in data. Stop watching tutorials and start coding. Your data science journey begins with a single DataFrame!