This is the final chapter of the course, covering one of the most common formats for tabular data — CSV files.

CSV (Comma-Separated Values) is a simple text format where each line is a record and values are separated by a delimiter, usually a comma (but sometimes semicolons, tabs, etc.).

Python's built-in csv module makes it easy to read, write, and process CSV files without manual string handling.

Reading CSV Files

Open a CSV file and pass it to csv.reader or csv.DictReader:

• csv.reader - each row as a list, e.g. ['Alice', '30', 'New York'];
• csv.DictReader - each row as a dictionary, using the first row as headers, e.g. {'name': 'Alice', 'age': '30', 'city': 'New York'}.

DictReader is often easier since you can access values by column names instead of indexes.

Writing CSV Files

To save data into CSV, use csv.writer or csv.DictWriter:

• csv.writer - writes rows as lists with .writerow() or .writerows();
• csv.DictWriter - writes rows as dictionaries. Define fieldnames, call .writeheader(), then add rows with .writerow().

Open files with newline="" to prevent extra blank lines on some systems.

Working with CSV Data

The csv module offers options to customize how data is handled:

• Delimiter - change with delimiter=";" or "\t";
• Quoting/Escaping - control with quotechar='"' and quoting=csv.QUOTE_ALL or csv.QUOTE_MINIMAL;
• Line endings - set lineterminator="\n" or "\r\n" for consistency;
• Encoding - use encoding="utf-8" (or another) for non-English text;
• Large files - read line by line to avoid loading everything into memory.

Summary

• CSV is a universal, human-readable format for tabular data;
• Use csv.reader / csv.DictReader for reading;
• Use csv.writer / csv.DictWriter for writing;
• Configure delimiters, quoting, and encoding to match the file's structure;
• Handle large files by streaming data instead of loading it all at once.

This completes the course. Along the way, we have explored the fundamentals of Python programming.

You learned about basic data types and variables, worked with lists, tuples, sets, and dictionaries, and understood how to organize logic with loops and conditions. We also covered how to build classes and objects, and finally, how to handle files — including text files, JSON, and CSV.

These skills form a solid foundation for solving real-world programming tasks and preparing for more advanced topics. Thank you for studying this course.