![]() ![]() One of those is the to_csv() method that allows you to write its contents into a CSV file. The DataFrame is a very powerful data structure that allows you to perform various methods. Think of it as an Excel spreadsheet within your code (with rows and columns). You create a Pandas DataFrame-which is Python’s default representation of tabular data. salary = ,ĭf.to_csv('file2.csv', index=False, header=False) ![]() ![]() This is the easiest method and it allows you to avoid importing yet another library (I use Pandas in many Python projects anyways). You can convert a list of lists to a Pandas DataFrame that provides you with powerful capabilities such as the to_csv() method. Have a look at the specification to learn about advanced modifications. You can customize the CSV writer in its constructor (e.g., by modifying the delimiter from a comma ',' to a whitespace ' ' character). You now pass a list of lists to the writerows() method of the CSV writer that takes care of converting the list of lists to a CSV format. Next, you pass this file object to the constructor of the CSV writer that implements some additional helper method-and effectively wraps the file object providing you with new CSV-specific functionality such as the writerows() method. Now, you can write content to the file object f. In the code, you first open the file using Python’s standard open() command. With open('file.csv', 'w', newline='') as f: This is the most customizable of all four methods. You can convert a list of lists to a CSV file in Python easily-by using the csv library. Simply click the “Run” button and find the generated CSV files in the “Files” tab.ĭo you want to develop the skills of a well-rounded Python professional-while getting paid in the process? Become a Python freelancer and order your book Leaving the Rat Race with Python on Amazon ( Kindle/Print)! My preference is method 2 ( Pandas) because it’s simplest to use and most robust for different input types (numerical or textual).īefore we dive into these methods in more detail, feel free to play with them in our interactive code shell.
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