Can't change empty index name in DataFrame

Question

I have over 100 csv files, all contain a table with the same indexes and indentical length. I am able to concat them into a single dataframe and save as csv.

print(df)

         a   b   c   d
0    1   5   1   7   7
1    2   3   1   7   7
2    3   2   2   8   7
3    1   6   1   7   6

I want to add a name to the now blank 'initial index' but every solution I find doesn't work... I've tried:

df.rename(columns={'': 'initial'}, inplace=True)
df1 = df.rename(columns={'': 'initial'})
df1 = df.set_index('initial')
df1 = df.rename_axis("initial")

Header printout as is:

print([*df])
[' a b c d']

I am using Python 3.7.3

Edit

Thanks for the feedback. Both Joe Ferndz and icecity96 solutions work. They didn't initially only because .csv file columns were seperated with spaces not comma's, therefore the DataFrame has seen only one column. Problem gone away after adding delim_whitespace=True

pd.read_csv(file, delim_whitespace=True)

Output before:

print(*df)
[' a b c d']

Output after:

print([*df])
['a', 'b', 'c', 'd']

That doesn't seem like the output you'd get from print([*df]), unless somehow you have a single column with the label ' a b c d' and everything happened to pretty print perfectly. What is df.index? — ALollz
– ALollz, Commented Aug 28, 2020 at 5:45
How many columns do you have in your original dataframe. I think 5 or is it 1? — Joe Ferndz
– Joe Ferndz, Commented Aug 28, 2020 at 6:53
can you do print (list(df)) and tell me what it shows? Does it print ['','a','b','c','d'] ? — Joe Ferndz
– Joe Ferndz, Commented Aug 28, 2020 at 6:55

icecity96 · Accepted Answer · 2020-08-28 05:54:00Z

1

Try:

df.rename({df.columns[0]: 'initial'}, axis='columns', inplace=True)

Output:

>>> print([*df])
['', 'a', 'b']
>>> df.rename({df.columns[0]: 'initial'}, axis='columns', inplace=True)
>>> print([*df])
['initial', 'a', 'b']

answered Aug 28, 2020 at 5:54

icecity96

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Joe Ferndz · Accepted Answer · 2020-08-28 07:01:02Z

0

If you want to rename the columns, can't you just do something as simple as this please?

import pandas as pd

df = pd.DataFrame({'' :[1,2,3,4],
                   'A':['A','B','C','D'],
                   'Z':[True, False, False, True]})
print(df)

df.columns = ['New','A','B']

print(df)

Here the first column got renamed as 'New' and also renamed column Z as B

Output is:

Before:

      A      Z
0  1  A   True
1  2  B  False
2  3  C  False
3  4  D   True

After:

   New  A      B
0    1  A   True
1    2  B  False
2    3  C  False
3    4  D   True

edited Aug 28, 2020 at 7:01

answered Aug 28, 2020 at 5:54

Joe Ferndz

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