Skip NA in Mean function within Pandas agg function
NaN values are skipped automatically. For example if we have the following table:
  store  reviewScore
0     a          4.0
1     b          3.0
2     a          3.0
3     a          NaN
4     b          5.0

groupby and find mean for each group:
df.groupby('store', as_index = False).agg({'reviewScore': 'mean'})

what is equivalent to:
df.groupby('store', as_index = False).mean()

Output:
  store  reviewScore
0     a          3.5
1     b          4.0

To use arguments in aggregation functions you can utilize a lambda function:
df.groupby('store', as_index = False).agg({'reviewScore': lambda x: x.mean(skipna=True)})

or
df.groupby('store', as_index = False).agg(lambda x: x.mean(skipna=True))

The result should be the same.