Extracting Path from URLs in DataFrame-CodePudding

I'm sure the answer to this is simple - I just can't it for some reason.

I'd like to extract the URL Path from a DataFrame of URLs without using a for loop - as i'll be running this against 1M rows and loops are too slow.

from urllib.parse import urlparse
d = {'urls': ['https://www.example.com/ex/1','https://www.example.com/1/ex']}
df = pd.DataFrame(data=d)
df
df['urls'].apply(urlparse)

Above is where i'm at, which returns an object of all parts of the URL returned by urllib

The desired end result is a DataFrame like the below:

d = {'urls': ['https://www.example.com/ex/1','https://www.example.com/1/ex'], 'url_path': ['/ex/1', '/1/ex']}

If anyone knows how to solve this - i'd appreciate the help!

Thanks!

CodePudding user response：

The docstring of urlparse clearly says that its result is a named 6-tuple with such fields: <scheme>://<netloc>/<path>;<params>?<query>#<fragment>

So (1) get the tuple at index 2, and then convert to dict with orient='list':

df['paths'] = df['urls'].apply(lambda x: urlparse(x)[2])
df.to_dict(orient='list')
> {'urls': ['https://www.example.com/ex/1', 'https://www.example.com/1/ex'],
 'paths': ['/ex/1', '/1/ex']}