Manually set the keys in Pandas DataFrame built with read_csv

Question

I have a .tsv file dataset, and I transformed it into a DataFrame using Pandas. Imagine that my_tsv_file was something like:

A Apple
B Orange
C Pear

To build the DataFrame I used:

df = pandas.read_csv(my_tsv_file, sep='\t')

Now, the first row of my_tsv_file was originally a row part of the data, but it has been transformed to the "key row" in the new DataFrame. So now the Dataframe is something like:

      A Apple
   0  B Orange
   1  C Pear

As "A" and "Apple" were keys, when they actually are not. I would like to add the correct "key row", in order to obtain something like:

      ID Fruit
   0  A  Apple
   1  B  Orange
   2  C  Pear

How can I achieve this? I can't modify the original .tsv file. Please remind that I am at the very beginning with Python and Pandas.

Does this answer your question? How to add header row to a pandas DataFrame — Chris
– Chris, Commented Jan 10, 2020 at 17:20

Kenan · Accepted Answer · 2020-01-10 17:20:26Z

1

have you tried

df = pandas.read_csv(my_tsv_file, sep='\t', names=['ID', 'Fruit'])

answered Jan 10, 2020 at 17:20

Kenan

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2 Comments

Kenan Over a year ago

I don't think you need to do that, by supplying names pandas will understand there is no header

albero123 Over a year ago

Thanks! I didn't know this option, is exactly what I was looking for

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