Adding a column in Pandas with a function [duplicate]

Question

Let's say I have a dataframe like this:

 columnA columnB 0 10 90 1 83 17 2 30 21 ...

and I have a function like this:

def my_func(a, b): value = #do some calculation return value

Now I want to get a new column columnC for my dataframe based on the calculations of the function.
Obviously, df["columnC"]= my_func(df["columnA"], df["columnB"]) does not work.

What can I do to add the column?

This also passes a pandas-series to my function. It is the same problem with the example I gave above. — Sven
– Sven, Commented Oct 3, 2020 at 10:06

yonatansc97 · Accepted Answer · 2020-10-03 11:07:40Z

2

The right way to do it is:

df['c'] = df.apply(lambda row: my_func(row['a'], row['b']), axis=1)

answered Oct 3, 2020 at 11:07

yonatansc97

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Comments

Sven · Accepted Answer · 2020-10-03 10:14:41Z

I found a workaround. It's a bit hacky though...

df["columnC"]=pd.Series([my_func(row["columnA"], row["columnB"])for index, row in df.iterrows()], index=df.index)

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