Data manipulation and analysis with Pandas
Pandas is a powerful library for data manipulation and analysis. Its two primary data structures are Series (1-dimensional) and DataFrame (2-dimensional), which can handle heterogeneous data with labeled axes. Pandas provides tools for reading and writing data in various formats (CSV, Excel, SQL, etc.), data cleaning and preparation, data transformation, aggregation, and time series functionality. Key features include: handling missing data, merging and joining datasets, grouping and aggregation, pivot tables, and time series analysis. Pandas is built on NumPy and is particularly well-suited for tabular data like spreadsheets or database tables. Understanding Pandas is essential for data analysis, data cleaning, and preprocessing for machine learning. The library's expressive API allows complex data manipulations to be expressed concisely.