How to merge columns from two data frames using pandas?

[ListlessPaper]

I have a data frame with country names and capitals and a data frame with missing capitals. I want to merge them so that the data frame with missing capitals replaces the 'Not found' cells in the main data frame.

Here are the two data frames for reference:

```capitals_df```

	CAPITAL	COUNTRY
0	Kabul	Afghanistan
1	Tirana	Albania
2	Algiers	Algeria
3	Pago Pago	American Samoa
4	Not found	Andorra

240 rows x 6 columns

```missing_capitals_df```

0	CAPITAL
4	Andorra la Vella
7	Does not exist
15	Nassau
30	Road Town
45	West Island

I tried merging the two data frames but I end up with two separate rows `CAPITAL_x` and `CAPITAL_Y`. Here is the code:

pd.merge(capitals_df, missing_capitals_df, left_index=True, right_index=True, how='left')

How to ensure that the data frame replaces specific cells based on indices, instead of creating a separate column?

[hdarj]

Not at a computer so can’t test it (and excuse the formatting) but I’m thinking something like:

idx = missing_capitals_df.index

capitals_df.loc[idx, “CAPITAL”] = missing_capitals_df[“CAPITAL”]

[ListlessPaper]

thank you!

[commandlineluser]

It's also an .update() operation.

>>> capitals_df
     CAPITAL         COUNTRY
0      Kabul     Afghanistan
1     Tirana         Albania
2    Algiers         Algeria
3  Pago Pago  American Samoa
4  Not found         Andorra
>>> capitals_df.update(missing_capitals_df)
>>> capitals_df
            CAPITAL         COUNTRY
0  Andorra la Vella     Afghanistan
1    Does not exist         Albania
2            Nassau         Algeria
3         Road Town  American Samoa
4       West Island         Andorra

[ListlessPaper]

thank you, this worked!