Pandas | College Workshops - 5 Days
Pandas is a powerful open-source data manipulation and analysis library for Python. It provides high-performance, easy-to-use data structures and tools for working with structured data. Pandas is particularly well-suited for handling and analyzing real-world data with its powerful DataFrame object, which allows for efficient data manipulation, cleaning, and analysis.
Features of Pandas
Pandas offers numerous features that make it an essential tool for data analysis and manipulation. Here are some key features:
- DataFrame Structure: Provides a two-dimensional labeled data structure with integrated indexing.
- Data Manipulation: Powerful tools for reshaping, merging, sorting, and manipulating large datasets.
- Missing Data Handling: Flexible handling of missing data and NA values.
- Data Import/Export: Support for various file formats including CSV, Excel, SQL databases, and JSON.
- Time Series Functionality: Extensive capabilities for working with date, time, and time-series data.
- Data Alignment: Automatic and explicit data alignment with integrated handling of missing data.
- Grouping and Aggregating: Powerful group by functionality for split-apply-combine operations.
- Data Visualization: Integration with plotting libraries for data visualization.
- Performance Optimization: High performance with optimized C code behind the scenes.
- Statistical Functions: Built-in statistical tools for data analysis.
Topics in Pandas Workshop
- Introduction to Pandas and Data Structures
- DataFrame and Series Operations
- Data Import and Export
- Data Cleaning and Preprocessing
- Data Manipulation and Transformation
- Indexing and Selection
- Grouping and Aggregation
- Merging and Joining DataFrames
- Time Series Analysis
- Data Visualization with Pandas
- Practical Applications and Case Studies