Data analysis typically starts with getting data into your analytical environment. While previous chapters demonstrated creating Series and DataFrames from scratch, real-world applications often involve loading data stored in external files. Similarly, after processing and analysis, you'll frequently need to save your results.

This chapter concentrates on Pandas's input/output (IO) capabilities. You will learn how to:

• Read data from common file formats, primarily Comma Separated Value (CSV) files, using functions like pd.read_csv().
• Load data from Microsoft Excel spreadsheets (.xls or .xlsx) using pd.read_excel().
• Briefly touch upon reading other potential data sources.
• Write the contents of your DataFrames back into CSV files using the .to_csv() method.
• Save DataFrames to Excel files using the .to_excel() method.

By the end of this chapter, you will be equipped to handle the fundamental tasks of reading data into Pandas DataFrames for analysis and exporting your processed data.