CODEWITHSUNDEEP
pythonpandasfunctionurl-parsing
user18274957
user18274957

Reputation:

How to change column values with function?

I have a 'leads' dataset, which has 'ref_url' column. This column includes links, which I want to parse and get only a particular part of them. I need to replace old values with parsed values.

This is how old values look like:

https://regalia-deyaar.sales-centre.properties/?utm_source=email&utm_medium=mailerlite&utm_campaign=regalia&utm_id=regalia

This is how I want them to look like:

https://regalia-deyaar.sales-centre.properties/

Here is what I did:

from urllib.parse import urlparse
def parsing_url(Series):
    for rows in Series:
        parsed_url = urlparse(rows)
        parsed=(f"{parsed_url.scheme}://{parsed_url.netloc}{parsed_url.path}")
        rows=parsed
leads['ref_url'].apply(parsing_url)

However, this didn't work. It returned only NaN values. Can you help me, please?

Upvotes: 0

Views: 186

Answers (1)

d_frEak
d_frEak

Reputation: 470

I assume you are using pandas, you can use lambda and split string by "?"

df = pd.DataFrame({
'url': ["https://regalia-deyaar.sales-centre.properties/?utm_source=email&utm_medium=mailerlite&utm_campaign=regalia&utm_id=regalia"
      , "https://regalia-deyaar.sales-centre.properties/?utm_source=email&utm_medium=mailerlite&utm_campaign=regalia&utm_id=regalia"
      , "https://regalia-deyaar.sales-centre.properties/?utm_source=email&utm_medium=mailerlite&utm_campaign=regalia&utm_id=regalia"]
})

# split string by "?" and get the first, assume main url will not contains "?"
df['url']=df['url'].apply(lambda x: x.split("?",1)[0])

Upvotes: 0

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