This course contains lots of challenges for Pandas, each challenge is a small Pandas project with detailed instructions and solutions. You can practice your Pandas skills by solving these challenges, improve your problem-solving skills, and learn how to write clean and efficient code.
LabEx is an interactive, hands-on learning platform dedicated to coding and technology. It combines labs, AI assistance, and virtual machines to provide a no-video, practical learning experience.
- A strict βLearn by Doingβ approach with exclusive hands-on labs and no videos.
- Interactive online environments within the browser, with automated step-by-step checks.
- A structured content organization with the Skill Tree based learning system.
- A growing learning resource of 30 Skill Trees and over 6,000 Labs.
- The AI learning assistant Labby, built on ChatGPT, providing a conversational learning experience.
Learn more about LabEx VM.
| Index | Name | Difficulty | Practice |
|---|---|---|---|
| 01 | π― DataFrame with Sales Data | β β β | Start Challenge |
| 02 | π― Filtering and Indexing with CSV | β ββ | Start Challenge |
| 03 | π― Sales Data Comparison | β ββ | Start Challenge |
| 04 | π― Handling NaN and Duplicates | β ββ | Start Challenge |
| 05 | π― Working with Series | β ββ | Start Challenge |
| 06 | π― Analyzing Sales and Discounts | β ββ | Start Challenge |
| 07 | π― DataFrame Math Operations | β ββ | Start Challenge |
| 08 | π― Pandas String Manipulation for E-commerce Data | β ββ | Start Challenge |
| 09 | π― Exploring the Where Function | β ββ | Start Challenge |
| 10 | π― The Powerful Query Method | β ββ | Start Challenge |
| 11 | π― Pandas Boolean Reductions Data Analysis | β ββ | Start Challenge |
| 12 | π― Pandas DataFrame Accessors | β ββ | Start Challenge |
| 13 | π― A Deep Dive Into Transform | β ββ | Start Challenge |
| 14 | π― Predicting Flower Types with Nearest Neighbors | β ββ | Start Challenge |
| 15 | π― Pandas IO Data Ingestion and Export | β ββ | Start Challenge |
| 16 | π― Pandas DataFrame Combination Techniques | β ββ | Start Challenge |
| 17 | π― Decision Trees | β ββ | Start Challenge |
| 18 | π― Linear Regression | β ββ | Start Challenge |
| 19 | π― Clustering and Insights | β ββ | Start Challenge |
| 20 | π― Understanding Validation Curves | β ββ | Start Challenge |
| 21 | π― Understanding Metrics and Scoring | β ββ | Start Challenge |

