Pandas: how to add row values by index value

Question

I'm having trouble working out how to add the index value of a pandas dataframe to each value at that index. For example, if I have a dataframe of zeroes, the row with index 1 should have a value of 1 for all columns. The row at index 2 should have values of 2 for each column, and so on.

Can someone enlighten me please?

Can you provide an example of code you have tried so far with example data and the output you expect? — vielkind
– vielkind, Commented Jun 20, 2018 at 12:40
If you have a dataframe of zeroes and you try to multiply that by index value the dataframe will stay the same. Do you mean addition instead of multiplication? An example with expected output would help as stated above. — Menno Van Dijk
– Menno Van Dijk, Commented Jun 20, 2018 at 12:48

jpp · Accepted Answer · 2018-06-20 12:39:43Z

1

You can use pd.DataFrame.add with axis=0. Just remember, as below, to convert your index to a series first.

df = pd.DataFrame(np.random.randint(0, 10, (5, 5)))

print(df)

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

df = df.add(df.index.to_series(), axis=0)

print(df)

    0   1  2   3   4
0   3   4  2   2   2
1  10   7  2   9   1
2   4  11  2   7   5
3   6   4  4  10   3
4   6  10  7  10  10

answered Jun 20, 2018 at 12:39

jpp

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2 Comments

Menno Van Dijk Over a year ago

This seems like an addition while the question is asking for multiplication?

jpp Over a year ago

@MennoVanDijk, OP has now corrected the title to match the description.

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