Pandas fill missing values in dataframe from another dataframe

Question

I cannot find a pandas function (which I had seen before) to substitute the NaN\'s in a dataframe with values from another dataframe (assuming a common index which can be sp

Answer 1

A dedicated method for this is DataFrame.update:

Quoted from the documentation:

Modify in place using non-NA values from another DataFrame.
Aligns on indices. There is no return value.

Important to note is that this method will modify your data inplace. So it will overwrite your updated dataframe.

Example:

print(df1)
       A    B     C
aaa  NaN  1.0   NaN
bbb  NaN  NaN  10.0
ccc  3.0  NaN   6.0
ffffd  NaN  NaN   NaN
eee  NaN  NaN   NaN

print(df2)
         A    B     C
index                
aaa    1.0  1.0   NaN
bbb    NaN  NaN  10.0
eee    NaN  1.0   NaN

# update df1 NaN where there are values in df2
df1.update(df2)
print(df1)
       A    B     C
aaa  1.0  1.0   NaN
bbb  NaN  NaN  10.0
ccc  3.0  NaN   6.0
ffffd  NaN  NaN   NaN
eee  NaN  1.0   NaN

Notice the updated NaN values at intersect aaa, A and eee, B