Python append dataframe such that only columns remain the same

Question

I have the following dataframes in python pandas:

A:

      1   2   3   4   5   6   7   8   9  10
0 1   1   1   1   1   1   1   0   0   1   1

B:

      1   2   3   4   5   6   7   8   9  10
1 0   1   1   1   1   1   1   0   0   1   0

C:

      1   2   3   4   5   6   7   8   9  10
2 0   1   1   1   0   0   0   0   0   1   0

I want to concatenate them together such that the column titles remain the same while row index and values get appended so the new dataframe is:

df:

      1   2   3   4   5   6   7   8   9  10
0 1   1   1   1   1   1   1   0   0   1   1
1 0   1   1   1   1   1   1   0   0   1   0
2 0   1   1   1   0   0   0   0   0   1   0

I have tried using append and concat but none seem to be fulfilling the output I am trying to achieve. Any suggestions?

Here is what I tried:

df = pd.concat([df,pd.concat([A,B,C], ignore_index=True)], axis=1)

Ah yes @piRSquared Thats right! Answer it so I can mark as correct. The more complicated approaches didn't work, it did! — sshussain270
– sshussain270, Commented Feb 16, 2018 at 0:35

piRSquared · Accepted Answer · 2018-02-16 00:36:32Z

3

This is a plain vanilla concat

pd.concat([A, B, C])

     1  2  3  4  5  6  7  8  9  10
0 1  1  1  1  1  1  1  0  0  1   1
1 0  1  1  1  1  1  1  0  0  1   0
2 0  1  1  1  0  0  0  0  0  1   0

answered Feb 16, 2018 at 0:36

piRSquared

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Comments

Yilun Zhang · Accepted Answer · 2018-02-16 00:30:59Z

2

Simple pd.concat will just do the work, you over complicated the task a little bit:

pd.concat([A,B,C], axis=0, ignore_index=True)

answered Feb 16, 2018 at 0:30

Yilun Zhang

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2 Comments

cs95 Over a year ago

For this problem, the last 2 params are redundant, but props for being explicit :)

Yilun Zhang Over a year ago

If B and C do have the correct index, then it is redundant, but I always want it to be clear when I'm joining. :)

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