# import necessary libraries
import pandas as pd

# define two series
ser1 = pd.Series(['a', 'b', 'c', 'd', 'e'])
ser2 = pd.Series(['b', 'd', 'f', 'a', 'g'])

# make boolean mask of values of ser1 which are in ser2
mask = ser1.isin(ser2)

# find the index positions using mask & drop NaN values
positions = mask.where(mask).dropna().index

# print the result in the form of a dictionary
print(ser2[positions].to_dict())