Python - dataframe url parsing issue - python-3.x

Question

I am trying to get domain names from the url from a column into another column. Its working on a string like object, when I apply to dataframe it doesn't work. How to do I apply this to a data frame?
Tried:
from urllib.parse import urlparse
import pandas as pd
id1 = [1,2,3]
ls = ['https://google.com/tensoflow','https://math.com/some/website',np.NaN]
df = pd.DataFrame({'id':id1,'url':ls})
df
# urlparse(df['url']) # ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
# df['url'].map(urlparse) # AttributeError: 'float' object has no attribute 'decode'
working on string:
string = 'https://google.com/tensoflow'
parsed_uri = urlparse(string)
result = '{uri.scheme}://{uri.netloc}/'.format(uri=parsed_uri)
result
looking for a column:
col3
https://google.com/
https://math.com/
nan
Errror

Answer 1

You can try something like this.
Here I have used pandas.Series.apply() to solve.
» Initialization and imports
>>> from urllib.parse import urlparse
>>> import pandas as pd
>>> id1 = [1,2,3]
>>> import numpy as np
>>> ls = ['https://google.com/tensoflow','https://math.com/some/website',np.NaN]
>>> ls
['https://google.com/tensoflow', 'https://math.com/some/website', nan]
>>>
» Inspect the newly created DataFrame.
>>> df = pd.DataFrame({'id':id1,'url':ls})
>>> df
id url
0 1 https://google.com/tensoflow
1 2 https://math.com/some/website
2 3 NaN
>>>
>>> df["url"]
0 https://google.com/tensoflow
1 https://math.com/some/website
2 NaN
Name: url, dtype: object
>>>
» Applying a function using pandas.Series.apply(func) on url column..
>>> df["url"].apply(lambda url: "{uri.scheme}://{uri.netloc}/".format(uri=urlparse(url)) if not pd.isna(url) else np.nan)
0 https://google.com/
1 https://math.com/
2 NaN
Name: url, dtype: object
>>>
>>> df["url"].apply(lambda url: "{uri.scheme}://{uri.netloc}/".format(uri=urlparse(url)) if not pd.isna(url) else str(np.nan))
0 https://google.com/
1 https://math.com/
2 nan
Name: url, dtype: object
>>>
>>>
» Store the above result in a variable (not mandatory, just to simply).
>>> s = df["url"].apply(lambda url: "{uri.scheme}://{uri.netloc}/".format(uri=urlparse(url)) if not pd.isna(url) else str(np.nan))
>>> s
0 https://google.com/
1 https://math.com/
2 nan
Name: url, dtype: object
>>>
» Finally
>>> df2 = pd.DataFrame({"col3": s})
>>> df2
col3
0 https://google.com/
1 https://math.com/
2 nan
>>>
» To make sure, what is s and what is df2, check types (again, not mandatory).
>>> type(s)
<class 'pandas.core.series.Series'>
>>>
>>>
>>> type(df2)
<class 'pandas.core.frame.DataFrame'>
>>>
Reference links:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.apply.html
https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.isnull.html