检查 pandas 系列中的每一行是否包含使用 apply 的列表中的字符串？

Question

I'm trying to add a column to the DF, depending on whether other column's value contains any of the strings in a list.

The list is:

services = [
        "TELECOM",
        "AYSA",
        "PERSONAL"
]

And so far I've tried:

payments["category"] = "services" if payments["concept"].contains(service for service in services) else ""

And this:

payments["category"] = payments["concept"].apply(lambda x: "services" if x.contains(service) for service in services) else ""

Among some other variations... I've seen other questions but they're mostly related to the opposite problem (checking whether a column's value is contained by a string in a list)

I could use your help! Thanks!!

Answer 1

You can use np.where and str.contains :

payments['category'] = np.where(payments['concept'].str.contains('|'.join(services)),
                                'services', '')

Output:

        concept  category
0       TELECOM  services
1          AYSA  services
2      PERSONAL  services
3  other things          

Answer 2

i think you can use isin

payments['category'] = np.where(
    payments['concept'].isin(services),
    'services', '')

import pandas
import numpy

dic = {"concept": ["TELECOM", "NULL"]}

payments = pandas.DataFrame.from_dict(dic)

payments["category"] = numpy.where(payments["concept"].isin(["TELECOM", "AYSA", "PERSONAL"]), "services", "")

print(payments)