06 Reading CSV, Excel, and JSON Files in Python
Learn how to read CSV, Excel, and JSON files in Python with clear, step-by-step instructions. This guide covers the basics of each file type, explains why these formats are important, and demonstrates how to work with them using both built-in modules and the powerful pandas library. You will also learn how to handle missing data, preview large files, and manage errors for a smooth data analysis workflow.
Follow along to practice creating, reading, and writing data files, including handling multiple sheets in Excel and nested data in JSON. By the end, you will be able to confidently load and process various data formats in Python for research, programming, or business projects.
00:00 Introduction and Overview
00:14 Why Learn These File Types
00:51 Checking Your Python Version
01:18 What Are CSV, Excel, and JSON
01:47 Creating a Sample CSV File
02:34 Reading CSV Files with csv Module
03:17 Using DictReader for CSV
03:49 Handling Missing Data in CSV
04:30 Reading CSV with pandas
05:03 Customizing Column Names in pandas
05:34 Selecting Columns from Large CSV Files
06:04 Saving Data to Excel with pandas
06:37 Reading Excel Files and Sheets
07:08 Working with Multiple Excel Sheets
07:45 Creating and Saving JSON Files
08:21 Loading and Using JSON Data
08:55 Reading JSON with pandas
09:25 Handling Nested JSON Data
10:22 Building a File Type Loader Program
11:18 Previewing Data with head
11:48 Handling File Errors Gracefully
12:23 Recap and Practice Tips
12:55 Conclusion and Next Steps
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