Pandas for Data Science

Data manipulation and analysis with Python’s Pandas library

Topics Covered

• DataFrames and Series - Core data structures and creation
• Data Loading - Reading CSV, Excel, JSON, and databases
• Data Cleaning - Handling missing values and duplicates
• Data Selection - Indexing, filtering, and querying data
• Data Transformation - Grouping, aggregation, and pivot tables
• Time Series - Working with dates and time-based data
• Data Visualization - Basic plotting with Pandas
• Performance Tips - Optimizing operations for large datasets

Learning Path

1. Start with basic DataFrame operations
2. Learn data loading and inspection techniques
3. Master data cleaning and preprocessing
4. Explore advanced transformations and analysis
5. Practice with real-world datasets

---

Available Notebooks