How to use if statements to assign values to new column in python?

Question

I have two columns in a dataframe and I need to create a new one based on them. For example:

df = pd.DataFrame(data={'a':[1.0,1.0,2.0], 'b':[3.0,3.0,3.0]})

df.iloc[1,0]=np.nan

 a    b
0  1.0  3.0
1  NaN  3.0
2  2.0  3.0

I need to add a column c which takes value from a when it is not null and otherwise from b. like:

a    b    c
0  1.0  3.0  1.0
1  NaN  3.0  3.0
2  2.0  3.0  2.0

Here is what I have tried:

def dist(df):
    if df['a']:
        return df.a
    else:
        return df.b
df['c']=df.apply(dist,axis=1)

but the result is not what I expected. Can anyone suggest what I should do? Thx!

Neapolitan · Accepted Answer · 2016-05-20 01:51:04Z

1

>>> d['c'] = df.a.where(~np.isnan(df.a), df.b)
>>> df
    a  b  c
0   1  3  1
1 NaN  3  3
2   2  3  2

It is tempting to write the more compact:

df['c'] = df.a.where(df.a, df.b)

but this won't do the right thing for df.a[k] == 0 (which is also interpreted as False).

Instead of isnan, you can use the property of NaN in that it is the only value not equal to itself, so the following also works:

df['c'] = df.a.where(df.a==df.a, df.b)

answered May 19, 2016 at 3:28

Neapolitan

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1 Comment

I tried the where phrase and it worked nicely with my data. thx!