Check if Python list elements are in a Pandas dataframe row and append to a new column-CodePudding

I have a dataframe like this:

Casa	Name
Solo Deportes	Paleta De Padel Adidas Metalbone CTRL
Solo Deportes	Zapatillas Running Under Armour Charged Stamin...
Solo Deportes	Rompeviento Con Capucha Reebok Woven Azu

and a List:

Maestro_Marcas=['Adidas', 'Reebebok','Under Armour']

How can I check each row of df['Name'], see if the row contains a value of the list, and in that case get the value of the list and put it in the new column?. The result should be something like this:

Casa	Name	Marca
Solo Deportes	Paleta De Padel Adidas Metalbone CTRL	Adidas
Solo Deportes	Zapatillas Running Under Armour Charged Stamin...	Under Armour
Solo Deportes	Rompeviento Con Capucha Reebok Woven Azu	Reebok

CodePudding user response：

you can use apply with a function such that:

Maestro_Marcas=['Adidas', 'Reebebok','Under Armour']

def is_exist(name):
    for i in Maestro_Marcas:
        if i in name:
            return i

df['Marca']  = df.apply(lambda x: is_exist(x['Name']), axis=1)

desired result:

    Casa            Name                                                 Marca   
0   Solo Deportes   Paleta De Padel Adidas Metalbone CTRL               Adidas
1   Solo Deportes   Zapatillas Running Under Armour Charged Stamin...   Under Armour
2   Solo Deportes   Rompeviento Con Capucha Reebok Woven Azu        None

I'm quite sure you should improve the function at one point for Reebebok vs Reebok adjust as you see fit.

CodePudding user response：

You can try findall

df['Marca'] = df['Name'].str.findall('|'.join(Maestro_Marcas))

Notice,it will return a list of finding, if two items found within one Name, it will return both.

To match the output you need

 df['Marca'] = df['Name'].str.findall('|'.join(Maestro_Marcas)).str[0]