How do I transpose dataframe in pandas without index?

Pretty sure this is very simple.

I am reading a csv file and have the dataframe:

Attribute    A   B   C
a            1   4   7
b            2   5   8
c            3   6   9

I want to do a transpose to get

Attribute    a   b   c
A            1   2   3
B            4   5   6
C            7   8   9

However, when I do df.T, it results in

             0   1   2 
Attribute    a   b   c
A            1   2   3
B            4   5   6
C            7   8   9`

How do I get rid of the indexes on top?

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Answers:

Method 1

Method 2

Method 3

Answers:

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Method 1

You can set the index to your first column (or in general, the column you want to use as as index) in your dataframe first, then transpose the dataframe. For example if the column you want to use as index is 'Attribute', you can do:

df.set_index('Attribute',inplace=True)
df.transpose()

df.set_index('Attribute').T

Method 2

It works for me:

>>> data = {'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]}
>>> df = pd.DataFrame(data, index=['a', 'b', 'c'])
>>> df.T
   a  b  c
A  1  2  3
B  4  5  6
C  7  8  9

Method 3

If your index column ‘Attribute’ is really set to index before the transpose, then the top row after the transpose is not the first row, but a title row. if you don’t like it, I would first drop the index, then rename them as columns after the transpose.

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0

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