[Python] How to fill blanks in dataframe1 with values from dataframe2 (with pandas)?

After some process, I got two dataframes, df1 is main frame which has some blanks in it, df2 has values that df1 missing. I used the code bellow, it should be able to fill all the blanks, but it doesn't fill any blank.

df4.update(postcode_match)


some blanks in df4:


values in postcode_match:


Values of last two columns in df2 should be fill in df1 last two columns. Why didn't it behave as expected?

I have tried .combine_first, it filled blanks and merged rows of those two dataframes.

I also tried:

for col in ['Latitude', 'Longitude']:
df4.loc[postcode_match.index, col] = postcode_match[col]


'Latitude' and 'Longitude' are indexes of the last columns, it also don't work.

This can achieve results I expected, but I want to use pandas' function to solve it. Is there any way can achieve it?

Latitude_dict = postcode_match.set_index('Postcode')['Latitude'].to_dict()
Longitude_dict = postcode_match.set_index('Postcode')['Longitude'].to_dict()

df4['Latitude'] = df4['Latitude'].fillna(df4['Postcode'].map(Latitude_dict))
df4['Longitude'] = df4['Longitude'].fillna(df4['Postcode'].map(Longitude_dict))

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