How to assign values to multiple non existing columns in a pandas dataframe?

Question

So what I want to do is to add columns to a dataframe and fill them (all rows respectively) with a single value.

import pandas as pd
import numpy as np

df = pd.DataFrame(np.array([[1,2],[3,4]]), columns = ["A","B"])
arr = np.array([7,8])

# this is what I would like to do
df[["C","D"]] = arr

# and this is what I want to achieve
#    A  B  C  D
# 0  1  2  7  8
# 1  3  4  7  8
# but it yields an "KeyError" sadly
# KeyError: "['C' 'D'] not in index"

I do know about the assign-functionality and how I would tackle this issue if I only were to add one column at once. I just want to know whether there is a clean and simple way to do this with multiple new columns as I was not able to find one.

jezrael · Accepted Answer · 2018-03-01 14:41:27Z

8

For me working:

df[["C","D"]] = pd.DataFrame([arr], index=df.index)

Or join:

df = df.join(pd.DataFrame([arr], columns=['C','D'], index=df.index))

Or assign:

df = df.assign(**pd.Series(arr, index=['C','D']))

print (df)
   A  B  C  D
0  1  2  7  8
1  3  4  7  8

edited Mar 1, 2018 at 14:41

answered Mar 1, 2018 at 14:36

jezrael

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1 Comment

Dremet Over a year ago

Nice answer. My take-away message is that there is no basic functionality to do is, but one has to choose one of your workarounds to achieve that. I would prefer the last of your three options.

BENY · Accepted Answer · 2018-03-01 14:51:11Z

1

You can using assign and pass a dict in it

df.assign(**dict(zip(['C','D'],[arr.tolist()]*2)))
Out[755]: 
   A  B  C  D
0  1  2  7  7
1  3  4  8  8

answered Mar 1, 2018 at 14:51

BENY

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2 Comments

Dremet Over a year ago

The "2" should probably not be hardcoded. I do also like this answer, jezaels answer just looks like to fit better into pandas programming style.

BENY Over a year ago

@Corrumpo if so using len(['C','D']) to replace the 2 :-)

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