CODEWITHSUNDEEP
pythonpandasapply
Joseph Noirre
Joseph Noirre

Reputation: 387

pandas dataframe apply function over column creating multiple columns

I have the pandas df below, with a few columns, one of which is ip_addresses

    df.head()
           my_id   someother_id  created_at        ip_address     state
308074     309115   2859690   2014-09-26 22:55:20   67.000.000.000  rejected
308757     309798   2859690   2014-09-30 04:16:56   173.000.000.000  approved
309576     310619   2859690   2014-10-02 20:13:12   173.000.000.000  approved
310347     311390   2859690   2014-10-05 04:16:01   173.000.000.000 approved
311784     312827   2859690   2014-10-10 06:38:39   69.000.000.000  approved

For each ip_address I'm trying to return the description, city, country

I wrote a function below and tried to apply it

from ipwhois import IPWhois


def returnIP(ip) :
    obj = IPWhois(str(ip))
    result = obj.lookup_whois()

    description = result["nets"][len(result["nets"]) - 1 ]["description"]
    city = result["nets"][len(result["nets"]) - 1 ]["city"]
    country = result["nets"][len(result["nets"]) - 1 ]["country"]

    return [description, city, country]

# --- 

suspect['ipwhois'] = suspect['ip_address'].apply(returnIP)

My problem is that this returns a list, I want three separate columns.

Any help is greatly appreciated. I'm new to Pandas/Python so if there's a better way to write the function and use Pandas would be very helpful.

Upvotes: 0

Views: 171

Answers (2)

Joseph Noirre
Joseph Noirre

Reputation: 387

I was able to solve it with another stackoverflow solution

for n,col in enumerate(cols):
    suspect[col] = suspect['ipwhois'].apply(lambda ipwhois: ipwhois[n])

If there's a more elegant way to solve this, please share!

Upvotes: 0

AidanGawronski
AidanGawronski

Reputation: 2085

from ipwhois import IPWhois

def returnIP(ip) :
    obj = IPWhois(str(ip))
    result = obj.lookup_whois()

    description = result["nets"][len(result["nets"]) - 1 ]["description"]
    city = result["nets"][len(result["nets"]) - 1 ]["city"]
    country = result["nets"][len(result["nets"]) - 1 ]["country"]

    return (description, city, country)


suspect['description'], suspect['city'], suspect['country'] = \
suspect['ip_address'].apply(returnIP)

Upvotes: 2

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