How to add multiple columns to dataframe by function

Question

If I have a df such as this:

   a  b
0  1  3
1  2  4

I can use df['c'] = '' and df['d'] = -1 to add 2 columns and become this:

   a  b c  d
0  1  3   -1
1  2  4   -1

How can I make the code within a function, so I can apply that function to df and add all the columns at once, instead of adding them one by one seperately as above? Thanks

do you know all the values that correspond to the column names? I'm wondering why you may want to do this. — MattR
– MattR, Commented Dec 18, 2019 at 22:11
@MattR The values are either n/a, or with a bool value, just a default value. Because I want to create a function specifically for adding columns. But I have no idea how to do that for dataframe. — saga
– saga, Commented Dec 18, 2019 at 22:17
df = df.assign(**{'c':1,'d':2}) - or df.assign(c=1,d=2) ... pandas.pydata.org/pandas-docs/stable/reference/api/… — wwii
– wwii, Commented Dec 18, 2019 at 22:19
Sorry, I want to create a function so it can be used to add columns for different dfs. Is that a way to do that? — saga
– saga, Commented Dec 18, 2019 at 22:24
Does this answer your question? adding multiple columns to pandas simultaneously — wwii
– wwii, Commented Dec 18, 2019 at 22:25

oppressionslayer · Accepted Answer · 2019-12-18 22:32:35Z

2

Create a dictionary:

dictionary= { 'c':'', 'd':-1 }

def new_columns(df, dictionary):
    return df.assign(**dictionary)

then call it with your df:

df = new_columns(df, dictionary)

or just ( if you don't need a function call, not sure what your use case is) :

df.assign(**dictionary)

edited Dec 18, 2019 at 22:32

answered Dec 18, 2019 at 22:28

oppressionslayer

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3 Comments

BENY Over a year ago

why we need a function here ? df.assign(**dictionary)?

oppressionslayer Over a year ago

OP wants a function, so that's why i answered with one

BENY Over a year ago

assign is a function itself

Samer Ayoub · Accepted Answer · 2019-12-18 22:42:48Z

0

def update_df(a_df, new_cols_names, new_cols_vals):
  for n, v in zip(new_cols_names, new_cols_vals):
    a_df[n] = v

update_df(df, ['c', 'd', 'e'], ['', 5, 6])

answered Dec 18, 2019 at 22:42

Samer Ayoub

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