Python pandas: remove everything after a delimiter in a string

Question

I have data frames which contain e.g.:

"vendor a::ProductA" "vendor b::ProductA" "vendor a::Productb" 

I need to remove everything (and including) the two :: so that I end up with:

"vendor a" "vendor b" "vendor a" 

I tried str.trim (which seems to not exist) and str.split without success. what would be the easiest way to accomplish this?

Answer 1

You can use pandas.Series.str.split just like you would use split normally. Just split on the string '::', and index the list that's created from the split method:

>>> df = pd.DataFrame({'text': ["vendor a::ProductA", "vendor b::ProductA", "vendor a::Productb"]}) >>> df                  text 0  vendor a::ProductA 1  vendor b::ProductA 2  vendor a::Productb >>> df['text_new'] = df['text'].str.split('::').str[0] >>> df                  text  text_new 0  vendor a::ProductA  vendor a 1  vendor b::ProductA  vendor b 2  vendor a::Productb  vendor a 

Here's a non-pandas solution:

>>> df['text_new1'] = [x.split('::')[0] for x in df['text']] >>> df                  text  text_new text_new1 0  vendor a::ProductA  vendor a  vendor a 1  vendor b::ProductA  vendor b  vendor b 2  vendor a::Productb  vendor a  vendor a 

Edit: Here's the step-by-step explanation of what's happening in pandas above:

# Select the pandas.Series object you want >>> df['text'] 0    vendor a::ProductA 1    vendor b::ProductA 2    vendor a::Productb Name: text, dtype: object  # using pandas.Series.str allows us to implement "normal" string methods  # (like split) on a Series >>> df['text'].str <pandas.core.strings.StringMethods object at 0x110af4e48>  # Now we can use the split method to split on our '::' string. You'll see that # a Series of lists is returned (just like what you'd see outside of pandas) >>> df['text'].str.split('::') 0    [vendor a, ProductA] 1    [vendor b, ProductA] 2    [vendor a, Productb] Name: text, dtype: object  # using the pandas.Series.str method, again, we will be able to index through # the lists returned in the previous step >>> df['text'].str.split('::').str <pandas.core.strings.StringMethods object at 0x110b254a8>  # now we can grab the first item in each list above for our desired output >>> df['text'].str.split('::').str[0] 0    vendor a 1    vendor b 2    vendor a Name: text, dtype: object 

I would suggest checking out the pandas.Series.str docs, or, better yet, Working with Text Data in pandas.