Creating columns dynamically. Assigning them a constant row vector

Question

Say I have some dataframe df. I would like to add to it four columns ['A', 'B', 'C, 'D'] that do not exist yet, and that will hold a constant row vector [1, 2, 3, 4].

When I try to do:

df[new_columns] = [1,2,3,4]

it fails (saying ['A', 'B', 'C, 'D'] is not in index).

How can I create multiple columns dynamically in Pandas? Do I always have to use append for something like this? I remember reading (e.g. in @Jeff's comment to this question) that in newer versions the dynamic creation of columns was supported. Am I wrong?

Jeff · Accepted Answer · 2014-09-17 17:10:52Z

4

I think this is the way to go. Pretty clear logic here.

In [19]: pd.concat([df,DataFrame([[1,2,3,4]],columns=list('ABCD'),index=df.index)],axis=1)
Out[19]: 
  label  somedata  A  B  C  D
0     b  1.462108  1  2  3  4
1     c -2.060141  1  2  3  4
2     e -0.322417  1  2  3  4
3     f -0.384054  1  2  3  4
4     c  1.133769  1  2  3  4
5     e -1.099891  1  2  3  4
6     d -0.172428  1  2  3  4
7     e -0.877858  1  2  3  4
8     c  0.042214  1  2  3  4
9     e  0.582815  1  2  3  4

Multi-assignment could work, but I don't think its a great soln because its so error prone (e.g. say some of your columns already exists, what should you do?). And the rhs is very problematic as you normally want to align, so its not obvious that you need to broadcast.

answered Sep 17, 2014 at 17:10

Jeff

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YS-L · Accepted Answer · 2014-09-17 17:09:58Z

1

You can do it column by column:

import pandas as pd
df = pd.DataFrame(index=range(5))
cols = ['A', 'B', 'C', 'D', 'E']
vals = [1, 2, 3, 4, 5]
for c, v in zip(cols, vals):
    df[c] = v
print df

Note that the last method mentioned in the other question you referred works similarly by creating each column before hand:

for a in attrlist:
    df[a] = 0

answered Sep 17, 2014 at 17:09

YS-L

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