Python - function similar to VLOOKUP (Excel)

Question

i am trying to join two data frames but cannot get my head around the possibilities Python has to offer.

First dataframe:

ID MODEL   REQUESTS ORDERS
1  G         


        

Answer 1

I always found merge to be an easy way to do this:

df1.merge(df2[['MODEL', 'MAKE']], how = 'left')

However, I must admit it would not be as short and nice if you wanted to call the new column something else than 'MAKE'.

Answer 2

I think you can use insert with map by Series created with df2 (if some value in column MODEL in df2 is missing get NaN):

df1.insert(2, 'MAKE', df1['MODEL'].map(df2.set_index('MODEL')['MAKE']))
print (df1)
   ID    MODEL        MAKE  REQUESTS  ORDERS
0   1     Golf  Volkswagen       123       4
1   2   Passat         NaN        34       5
2   3  Model 3       Tesla       500       8
3   4       M3         BMW         5       0

Answer 3

The join method acts very similarly to a VLOOKUP. It joins a column in the first dataframe with the index of the second dataframe so you must set MODEL as the index in the second dataframe and only grab the MAKE column.

df.join(df1.set_index('MODEL')['MAKE'], on='MODEL')

Take a look at the documentation for join as it actually uses the word VLOOKUP.

Answer 4

Although not in this case, but there might be scenarios where df2 has more than two columns and you would just want to add one out of those to df1 based on a specific column as key. Here is a generic code that you may find useful.

df = pd.merge(df1, df2[['MODEL', 'MAKE']], on = 'MODEL', how = 'left')