Joining two dataframes

Question

I have a dataframe that looks like this:

RIC | base
AAPL| AA
IBM |
AMD | 

and another table with same fields but different values:

RIC | base
AAPL | AA
IBM | 
AMD | AM

I would like to join the two tables to get this resultant table:

RIC | base
AAPL | AA
IBM | 
AMD | AM

How can I do that?

Answer 1

Do you notice that your desired result is the same as your second dataframe?

I think you meant something like this:

Consider the two dataframes d1 and d2

d1 = pd.DataFrame(dict(RIC=['AAPL', 'IBM', 'AMD'], base=['AA', None, None]))
d2 = pd.DataFrame(dict(RIC=['AAPL', 'IBM', 'AMD'], base=['aa', 'IB', 'AM']))

print(d1)
print()
print(d2)

    RIC  base
0  AAPL    AA
1   IBM  None
2   AMD  None

    RIC base
0  AAPL   aa
1   IBM   IB
2   AMD   AM

We'll use set_index and combine_first

d1.set_index('RIC').combine_first(d2.set_index('RIC')).reset_index()

    RIC base
0  AAPL   AA
1   IBM   IB
2   AMD   AM

This approach takes the values from the first dataframe when it exists. Otherwise, it takes the value from the second dataframe.

Answer 2

you try : pd.concat([df1, df2], axis=1)