Fill values based on reference table

Question

I have two df with different lenghts, one (reference/dictionary) with various types of products and brand who makes them, and another df with just the products, I have to fill brand based on the reference table

Reference df is like

Product	Brand
Shirt	Zara
Sneakers	Nike
Pants	Zara
Tennis ball	Wilson
Football ball	Adidas
Football boots	Adidas

The df to be filled is something like

Product	Brand
Shirt	NaN
Shirt	NaN
Pants	NaN
Tennis ball	NaN
Shirt	NaN
Football boots	NaN
Football boots	NaN
Football boots	NaN
Pants	NaN
Sneakers	NaN
Football ball	NaN
Football boots	NaN
(+100k rows)	NaN

I´ve tried the following code

df['Brand'] = df['Brand'].map(referencedf.set_index('Product')['Brand'])
df

Unfortunately, the output is not the desired and it always returns the same brand for all products

Product	Brand
Shirt	Zara
Shirt	Zara
Pants	Zara
Tennis ball	Zara
Shirt	Zara
Football boots	Zara
Football boots	Zara
Football boots	Zara
Pants	Zara
Sneakers	Zara
Football ball	Zara
Football boots	Zara
(+100k rows)	Zara

Any ideas on how can i get the output right?

Answer 1

Try:

df['Brand'] = df['Product'].map(reference_df.set_index('Product')['Brand'])
print(df)

Prints:

           Product   Brand
0            Shirt    Zara
1            Shirt    Zara
2            Pants    Zara
3      Tennis ball  Wilson
4            Shirt    Zara
5   Football boots  Adidas
6   Football boots  Adidas
7   Football boots  Adidas
8            Pants    Zara
9         Sneakers    Nike
10   Football ball  Adidas
11  Football boots  Adidas