Working with JSON & CSV
Master data formats. Learn to parse and generate JSON, work with CSV files, and handle data serialization.
Master data formats. Learn to parse and generate JSON, work with CSV files, and handle data serialization. This hands-on tutorial focuses on practical implementation of working with json & csv concepts.
Working with JSON & CSV
JSON and CSV are the most common data formats for exchanging information between systems.
JSON (JavaScript Object Notation) 📋
JSON is a lightweight data format that's easy for humans to read and machines to parse.
JSON vs Python
| JSON | Python |
|---|---|
{} object | dict |
[] array | list |
"string" | str |
123 number | int/float |
true/false | True/False |
null | None |
Parsing JSON: json.loads()
Generating JSON: json.dumps()
Working with Nested JSON
CSV (Comma-Separated Values) 📊
CSV is a simple format for tabular data.
Reading CSV
Writing CSV
JSON vs CSV Comparison
| Feature | JSON | CSV |
|---|---|---|
| Structure | Hierarchical (nested) | Flat (tabular) |
| Data Types | Strings, numbers, booleans, null | All strings (need parsing) |
| Human Readable | ✅ Yes | ✅ Yes |
| File Size | Larger | Smaller |
| Use Case | APIs, configs | Spreadsheets, data export |
Coding Challenge: Data Converter 🔄
Handling JSON Errors
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Quiz
Quiz
Question 1 of 5Which function converts Python dict to JSON string?
Key Takeaways
✅ JSON is for structured, hierarchical data.
✅ json.loads() parses JSON strings to Python.
✅ json.dumps() converts Python to JSON strings.
✅ CSV is for simple tabular data.
✅ Use csv.DictReader and csv.DictWriter for easy CSV handling.
What's Next?
In the next lesson, we'll learn about Regular Expressions - powerful pattern matching for text processing.
Keep coding! 🚀