apply function to rows pandas dataframe with different parameters depending on values of another column

Question

I have a dataframe df

import pandas
df = pandas.DataFrame(data=[[1,True],[2,False]],columns=['A','decide'])

to which rows I want to apply a function fun depending on the value of the decide column

def fun(case,var):
   case = case + var
   return case


df=df.apply(lambda x: fun(x,1) if x['decide'] else fun(x,2))

of course doesn't work :) any idea why and how to make it working?

BENY · Accepted Answer · 2019-02-21 16:32:06Z

4

Try to fix your code , PS : You forget to add axis=1

df.apply(lambda x: fun(x['A'],1) if x['decide'] else fun(x['A'],2),axis=1)
Out[560]: 
0    2
1    4
dtype: int64

Also When you using np.where you still can pass your own defined functions

np.where(df.decide,fun(df.A,1),fun(df.A,2))

If you logic is as simple as you show to us in your sample function

df.A+2-df.decide
Out[563]: 
0    2
1    4
dtype: int64

answered Feb 21, 2019 at 16:25

BENY

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Comments

yatu · Accepted Answer · 2019-02-21 16:24:27Z

4

IIUC you can use np.where:

df['A'] = np.where(df.decide, df.A+1, df.A+2)

   A  decide
0  2    True
1  4   False

answered Feb 21, 2019 at 16:24

yatu

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