Creating a column identifier based on another column

February 17, 2022

I have a df below as

    NAME 
German Rural
 1990 german
Mexican 1998
Mexican City

How can i create a new column based on the values of these columns ( if the column has the term %German% or % german% regardless of capital or lower case or case insensitive?

Desired output

NAME         | Identifier
German Rural    Euro
1990 german     Euro
Mexican 1998 South American 
Mexican City South American

>Solution :

You could do that with something like the following.

df["Identifier"] = (df["NAME"].str.lower().replace(
                     to_replace = ['german', 'mexican'], 
                     value = ['Euro', 'South American']
                   ))

print(df)
      NAME      Identifier
0   German            Euro
1   german            Euro
2  Mexican  South American
3  mexican  South American

Or, the following will match cells that contain additional characters.

conditions = [df["NAME"].str.lower().str.contains("german"), 
               df["NAME"].str.lower().str.contains("mexican")]

values = [ "Euro", 'South American']
    
df["identifiter"] = np.select(conditions, values, default=np.nan)

print(df)
      NAME      Identifier
0   German            Euro
1   german            Euro
2  Mexican  South American
3  mexican  South American