Pandas: How to fill null values with mean of a groupby?

Question

I have a dataset will some missing data that looks like this:

id    category     value
1     A            NaN
2     B            NaN
3     A            10.5
         


        

Answer 1

I think you can use groupby and apply fillna with mean. Then get NaN if some category has only NaN values, so use mean of all values of column for filling NaN:

df.value = df.groupby('category')['value'].apply(lambda x: x.fillna(x.mean()))
df.value = df.value.fillna(df.value.mean())
print (df)
   id category  value
0   1        A   6.25
1   2        B   1.00
2   3        A  10.50
3   4        C   4.15
4   5        A   2.00
5   6        B   1.00