Add extra columns with default values from a list in a dataframe

Question

I have a dataframe like

df = {'Name':['Tom', 'nick', 'krish', 'jack'], 'Age':[20, 21, 19, 18]}

Now i want the data frame to have additional columns from a list=['a','b','c'] with default values as 0.

so the output will be

Name  Age a b c
Tome  20  0 0 0
nick  21  0 0 0
krish 19  0 0 0
Jack  18  0 0 0

jezrael · Accepted Answer · 2020-03-19 06:49:39Z

2

Dont use variable list, because builtin (python code word).

For new columns is possible create dictionary from list and pass to DataFrame.assign:

d = {'Name':['Tom', 'nick', 'krish', 'jack'], 'Age':[20, 21, 19, 18]} 
df = pd.DataFrame(d)

L = ['a','b','c'] 

df1 = df.assign(**dict.fromkeys(L, 0))

Or create new DataFrame and use DataFrame.join:

df1 = df.join(pd.DataFrame(0, columns=L, index=df.index))

print (df1)
    Name  Age  a  b  c
0    Tom   20  0  0  0
1   nick   21  0  0  0
2  krish   19  0  0  0
3   jack   18  0  0  0

answered Mar 19, 2020 at 6:49

jezrael

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Community · Accepted Answer · 2020-06-20 09:12:55Z

2

>>> df.join(df.reindex(columns=list('abc'), fill_value=0))
    Name  Age  a  b  c
0    Tom   20  0  0  0
1   nick   21  0  0  0
2  krish   19  0  0  0
3   jack   18  0  0  0

You can also use reindex to create new df with fill_value zero. and than combine columns by using join.

edited Jun 20, 2020 at 9:12

CommunityBot

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answered Mar 19, 2020 at 7:17

Dishin Goyani

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