How to fill Nan values for multiple columns at once?

Question

df
   Fruits  Veg       Non_veg
 1 Apple   Broccoli  Chicken
 2 Banana   Nan       Nan
 3  Nan    Tomato     Nan

In the above sample data frame, I have Nan values and I need to fill it with forward filling all at once and the code I used is :

df[['Fruits','Veg','Non_veg']].fillna(method='ffill',inplace=True)

Is this way of coding is correct ? also if the forward filling cell has another Nan value like in the above data frame how to overcome?

The Expected output for ffill is:

df
       Fruits  Veg       Non_veg
     1 Apple   Broccoli  Chicken
     2 Banana  Broccoli  Chicken
     3 Banana  Tomato    Chicken

please show your expected output – ansev Nov 23 '19 at 19:29 — ansev, Nov 23 '19 at 19:29

ansev · Answer 1 · 2019-11-23T21:45:15.973

1

Use: DataFrame.ffill.Here you can se how use inplace : How to use inplace=True

#df.replace('Nan',np.nan) #if NaN is string
cols=['Fruits','Veg','Non_veg']
df[cols]=df[cols].ffill()

edited Nov 23 '19 at 21:45

answered Nov 23 '19 at 19:39

ansev

score 0 · Answer 2 · answered Nov 23 '19 at 19:39

0

Don't use inplace on slicing object. Do assigment

df.loc[:, ['Fruits','Veg','Non_veg']] = df.loc[:, ['Fruits','Veg','Non_veg']].ffill()

answered Nov 23 '19 at 19:39

Andy L.

score 0 · Answer 3 · answered Nov 23 '19 at 19:40

0

You should remove inplace=True
df['Fruits','Veg','Non_veg'] = df['Fruits','Veg','Non_veg'].fillna(method= 'ffill')

answered Nov 23 '19 at 19:40

rishabh.malhotra

3 Answers3