How rakib313/pandas_exercises works
Pandas Exercises is a self-guided collection of notebook exercises and accompanying solutions, organized by pandas topic and example dataset. A learner selects a topic, works through its exercise instructions, and can consult answer-only solutions before using commented code solutions. The README documents this learning flow and the topic catalog; notebook internals were not sampled, so the graph represents the repository’s documented organization rather than notebook execution details.
Main entry points: 01_Getting_&_Knowing_Your_Data Getting Data · 02_Filtering_&_Sorting Filtering Sorting · 03_Grouping Grouping · 04_Apply Apply
Components 15
Explore Data
- Getting Data
01_Getting_&_Knowing_Your_Data - Filtering Sorting
02_Filtering_&_Sorting - Grouping
03_Grouping
Analyze Results
- Statistics
06_Stats - Visualization
07_Visualization
Special Topics
- Series DataFrames
08_Creating_Series_and_DataFrames - Time Series
09_Time_Series - Indexing
11_Indexing - Exercise Instructions
- Answer Solutions
- Code Solutions
Other components
- Learner
Connections 14
- Learner → Getting Data: chooses topic
README.md - Learner → Filtering Sorting: chooses topic
README.md - Learner → Grouping: chooses topic
README.md - Learner → Apply: chooses topic
README.md - Learner → Merge: chooses topic
README.md - Learner → Statistics: chooses topic
README.md - Learner → Visualization: chooses topic
README.md - Learner → Series DataFrames: chooses topic
README.md - Learner → Time Series: chooses topic
README.md - Learner → Deleting: chooses topic
README.md - Learner → Indexing: chooses topic
README.md - Learner → Exercise Instructions: works through
README.md - Learner → Answer Solutions: checks answers
README.md - Learner → Code Solutions: consults code
README.md