[Tut] How to Convert Tab-Delimited File to CSV in Python?

How to Convert Tab-Delimited File to CSV in Python?

5/5 – (1 vote)

The easiest way to convert a tab-delimited values (TSV) file to a comma-separated values (CSV) file is to use the following three lines of code:

1. import pandas as pd
2. df = pd.read_csv('my_file.txt', sep='\t', header=None)
3. df.to_csv('my_file.csv', header=None)

We’ll explain this and other approaches in more detail next—scroll down to Method 3 for this exact method.

Problem Formulation

Given a tab-delimited file with one tab character '\t' between two values in a given column.

Input: 'my_file.tsv'

Figure: File 'my_file.tsv' with tab '\t' separated values.

Alice	DataScience	$100000

Bob	Programmer	$90000

Carl	Manager	$122000

Dave	Freelancer	$144000

How to convert the tab-delimited values (TSV) to a comma-separated values (CSV) file?

Output: 'my_file.csv'

0,Alice,DataScience,$100000

1,Bob,Programmer,$90000

2,Carl,Manager,$122000

3,Dave,Freelancer,$144000

We’ll also look at slight variations of this problem. Let’s go!

Method 1: String Replace Single Tab

The most straightforward way to convert a tab-delimited (TSV) to a comma-separated (CSV) file in Python is to replace each tabular character '\t' with a comma ',' character using the string.replace() method. This works if two values are separated by exactly one tabular character.

Here’s an example input file 'my_file.tsv':

Here’s an example of some code to convert the tab-delimited file to the CSV file:

with open('my_file.tsv') as f: # Read space-delimited file and replace all empty spaces by commas data = f.read().replace('\t', ',') # Write the CSV data in the output file print(data, file=open('my_file.csv', 'w'))

Output file 'my_file.csv':

If you have any doubts, feel free to dive into our related tutorials:

• Python String Replace Method
• Python open() Function
• Python print() to File
• Python print() Function
• Python Context Managers

Method 2: Regex Replace Arbitrary Tabs

To replace one '\t' or more tabs '\t\t\t' between two column values with a comma ',' and obtain a CSV, use the regular expressions operation re.sub('[\t]+', ',', data) on the space-separated data.

If you have any doubts, feel free to dive into our related tutorials:

• Python Regex re.sub()
• Python Regex [] Character Class
• Python Regex + Quantifier
• Python Regex Superpower

Here’s an example input file 'my_file.tsv', notice the additional tabular characters that may separate two column values:

Here’s an example of some code to convert the TSV to the CSV file:

import re with open('my_file.txt') as infile: # Read space-delimited file and replace all empty spaces by commas data = re.sub('[ ]+', ',', infile.read()) # Write the CSV data in the output file print(data, file=open('my_file.csv', 'w'))

Output file 'my_file.csv':

Method 3: Pandas read_csv() and to_csv()

To convert a tab-delimited file to a CSV, first read the file into a Pandas DataFrame using pd.read_csv(filename, sep='\t+', header=None) and then write the DataFrame to a file using df.to_csv(outfilename, header=None).

Here’s an example input file 'my_file.tsv':

Here’s an example of some code to convert the tab-delimited file to the CSV file:

import pandas as pd # Read space-delimited file

df = pd.read_csv('my_file.tsv', sep='\t+', header=None) # Write DataFrame to file

df.to_csv('my_file.csv', header=None)

Output file 'my_file.csv':

You can also use the simpler sep='\t' if you are sure that only a single tabular character separates two column values.

If you have any doubts, feel free to dive into our related tutorials:

• Pandas read_csv()
• Pandas to_csv()

Summary

We examined three great ways to convert a space-delimited to a comma-separated CSV file:

• Method 1: String Replace Single Tab
• Method 2: Regex Replace Arbitrary Tabs
• Method 3: Pandas read_csv() and to_csv()

Thanks for taking the time to read this article, my friend!

---

Regex Humor

Wait, forgot to escape a space. Wheeeeee[taptaptap]eeeeee. (source)

https://www.sickgaming.net/blog/2022/08/...in-python/