Python

Working with JSON & CSV

Master data formats. Learn to parse and generate JSON, work with CSV files, and handle data serialization.

By TechCoder TeamLast updated: 2026-06-02
In a Nutshell

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

JSONPython
{} objectdict
[] arraylist
"string"str
123 numberint/float
true/falseTrue/False
nullNone

Parsing JSON: json.loads()

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Generating JSON: json.dumps()

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Working with Nested JSON

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CSV (Comma-Separated Values) 📊

CSV is a simple format for tabular data.

Reading CSV

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Writing CSV

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JSON vs CSV Comparison

FeatureJSONCSV
StructureHierarchical (nested)Flat (tabular)
Data TypesStrings, numbers, booleans, nullAll strings (need parsing)
Human Readable✅ Yes✅ Yes
File SizeLargerSmaller
Use CaseAPIs, configsSpreadsheets, data export

Coding Challenge: Data Converter 🔄

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Handling JSON Errors

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AI Mentor

Confused about "Python JSON CSV data formats parsing"? Ask our AI mentor for a simplified explanation.

Quiz

Quiz

Question 1 of 5

Which function converts Python dict to JSON string?

json.loads()
json.dumps()
json.parse()
json.stringify()

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! 🚀