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Convert Text File to CSV using Python Pandas

Last Updated : 15 Mar, 2025

Converting Text File to CSV using Python Pandas refers to the process of transforming a plain text file (often with data separated by spaces, tabs, or other delimiters) into a structured CSV (Comma Separated Values) file using the Python Pandas library.

In this article we will walk you through multiple methods to convert a text file into a CSV file using Python's Pandas library.

Consider a text file named GeeksforGeeks.txt containing structured data. Python will read this data and create a DataFrame where each row corresponds to a line in the text file and each column represents a field in a single line.

import pandas as pd

df1 = pd.read_csv("GeeksforGeeks.txt")

df1.to_csv('GeeksforGeeks.csv', 
                  index = None)

Output:

The text file read is same as above. After successful run of above code a file named "GeeksforGeeks.csv" will be created in the same directory. 

If the column heading are not given and the text file looks like. In this case you need to manually define the column headers while converting to CSV:

import pandas as pd

websites = pd.read_csv("GeeksforGeeks.txt"
                       ,header = None)

websites.columns = ['Name', 'Type', 'Website']

websites.to_csv('GeeksforGeeks.csv', 
                index = None)

 Output:

Some text files use custom delimiters instead of commas. Suppose the file uses / as a separator. To handle this specify the delimiter while reading the file

import pandas as pd

account = pd.read_csv("GeeksforGeeks.txt",
                      delimiter = '/')

account.to_csv('GeeksforGeeks.csv',
               index = None)

Output:

Depending on the structure of the text file you may need to specify headers or handle custom delimiters. With these methods you can easily transform text-based data into a structured format for further analysis.

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