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Lesson PreviewLesson 3 of 8 in this unit

2. 3. Working with CSV, JSON, and Excel files

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In data science, files like CSV, JSON, and Excel are commonly used to store and exchange data.

CSV files store tabular data in plain text, with values separated by commas. They are lightweight and widely used in spreadsheets and databases but lack advanced features like formulas or formatting.

JSON, on the other hand, stores structured data as key-value pairs and supports nested structures, making it ideal for APIs and web applications. Unlike CSV, JSON is more versatile for handling complex data but requires parsing before use.

Excel files (.xlsx or .xls) are common in business and data analysis, offering advanced features like formulas and pivot tables. They can be processed programmatically using pandas or openpyxl, making them useful for structured data storage. However, Excel is less efficient than CSV or JSON for large-scale automated processing.

In this unit

8 lessons

  1. 2.1Types Data CleaningPreview lesson
  2. 2.2Collecting types of data from APIs, web scraping, and databasesPreview lesson
  3. 2.3Working with CSV, JSON, and Excel filesThis lesson
  4. 2.4Types of SQL Basics for Querying DatabasesPreview lesson
  5. 2.5Handling Missing DataPreview lesson
  6. 2.6Data Duplicates and Inconsistent DataPreview lesson
  7. 2.7Data transformation and feature scalingPreview lesson
  8. 2.8Convecting data typesPreview lesson

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