Creating a new column by mapping a dictionary to a data frame with partial string matching-CodePudding

I'm trying to create a new column in a pandas dataframe based if a column contains a partial string.

I have a simple dataframe

    Food    Price
0   apple   1.00
1   banana  2.99
2   carrot  3.50

and I would like to append a column to it like so

        Food     Price  Sale Status
0   apple    1.00   on sale
1   banana   2.99   not on sale
2   carrot   3.50   on sale next week

This work if my keys are exact matches to the values in the Food column

my_dict={'apple':'on sale', 'banana':'not on sale', 'carrot':'on sale next week'}

df['Sale Status']= df['Food'].map(my_dict)

My problem is that my dataframe looks like this

    Food                Price
0   some other words apple  1.00
1   other banana text   2.99
2   blah blah carrot    3.50

Is there a way to match the dictionary values if the sting in Food contains the key name?

CodePudding user response：

There are several solutions. You can iterate over 'Food' and map the key to its value if found, like

df['Sale Status'] = df['Food'].apply(lambda x: [v for k, v in my_dict.items() if k in x][0])

Or you can use str.extract()

df['Sale Status'] = df['Food'].str.extract('(' '|'.join(my_dict.keys()) ')', expand=False).map(my_dict)