This method is best if you have numerical data only-otherwise, it’ll lead to complicated data type conversions which are not recommended. You can convert a list of lists to a CSV file by using NumPy’s savetext() function and passing the NumPy array as an argument that arises from the conversion of the list of lists. Even Pandas uses NumPy arrays to implement critical functionality. NumPy is at the core of Python’s data science and machine learning functionality. Related article: Pandas Cheat Sheets to Pin to Your Wall Method 3: NumPy savetext() Check out this article for a comprehensive list of all arguments. If you want to customize the CSV output, you’ve got a lot of special arguments to play with. You don’t want them to appear in the CSV file so you set the arguments to False. You set the index and header arguments of the to_csv() method to False because Pandas, per default, adds integer row and column indices 0, 1, 2, ….Īgain, think of them as the row and column indices in your Excel spreadsheet. 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. Python: Use a pure Python implementation that doesn’t require any library by using the Python file I/O functionality.NumPy: Import the NumPy library, create a NumPy array, and write the output to a CSV file using the numpy.savetxt('file.csv', array, delimiter=',') method.Pandas: Import the pandas library, create a Pandas DataFrame, and write the DataFrame to a file using the DataFrame method DataFrame.to_csv('file.csv').CSV: Import the csv module in Python, create a csv writer object, and write the list of lists to the file in using the writerows() method on the writer object.Solution: There are four simple ways to convert a list of lists to a CSV file in Python. Your out file should look like this: # file.csv Your goal is to write the content of the list of lists into a comma-separated-values (CSV) file format. Problem: How to convert a list of lists to a csv file?Įxample: Given is a list of list-for example salary data of employees in a given company: salary = ,
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