Python – Combining CSV files

Learn how to efficiently merge CSV files using Python. This comprehensive guide demonstrates seamless techniques for combining CSV files in Python, ensuring smooth data integration and organization. Dive into our step-by-step tutorial for optimal CSV file management.

What is a CSV file?

A CSV (Comma-Separated Values) file is a simple file format used to store tabular data, such as a spreadsheet or database. Each line in a CSV file represents a row in the table, with individual data fields separated by commas.

Why use a CSV file?

CSV files are commonly used for their simplicity and compatibility, enabling easy data exchange between different systems. They are lightweight, human-readable, and can be manipulated using basic text editors or spreadsheet software.

Why combine a CSV file?

Combining CSV files is often necessary to integrate and consolidate data from multiple sources. It facilitates comprehensive data analysis, enhances data organization, and simplifies the process of drawing insights from disparate data sets. This process is crucial for creating a unified dataset for various analytical purposes and business operations.

Tutorial Python – Combining CSV files

Create 2 CSV files.

Install the PANDAS library.

Read the CSV files.

Combine the CSV files.

Python will merge two dataframes using the NAME column as the key. It combines the dataframes based on the values of the NAME column in both dataframes.

Write the new CSV file.

Here is the new CSV file content.

Here is the complete Python script.

Conclusion

Elevate your data management proficiency with Python’s CSV file merging capabilities. Empower your data analysis endeavors and streamline workflow efficiency. Unlock the full potential of streamlined data integration for comprehensive insights and strategic decision-making.