Mixing
Removing elements from Pandas Series of lists
-1
I've been searching for solutions and hints from the site, but couldn't find issue directly related with my case.
I have scraped text data from various sites and have split the text by using str.split('n'). The text contains a lot of 'n' and splitting this way made it pretty desirable. (Please let me know if this approach is too bad.)
df['scrape']
0 nWebsite:nnnnVisitnn nWhite paper:nn...
1 nWebsite:nnnnVisitnn nWhite paper:nn...
2 nWebsite:nnnnVisitnn nWhite paper:nn...
3 nWebsite:nnnnVisitnn nWhite paper:nn...
4 nWebsite:nnnnVisitnn nWhite paper:nn...
5 nWebsite:nnnnVisitnn nWhite paper:nn...
The result was a Pandas Series of lists – all elements are list of strings.
df['split'] = df['scrape'].str.split('n')
0 [, Website:, , , , Visit, , , White paper:, ,...
1 [, Website:, , , , Visit, , , White paper:, ,...
2 [, Website:, , , , Visit, , , White paper:, ,...
3 [, Website:, , , , Visit, , , White paper:, ,...
4 [, Website:, , , , Visit, , , White paper:, ,...
5 [, Website:, , , , Visit, , , White paper:, ,...
6 [, Website:, , , , Visit, , , White paper:, ,...
I want to get rid of None element (‘’ and ‘ ‘) on each list.
I tried looping:
for i in series:
While ‘’ in i:
i.remove(‘’)
Above code works with some arbitrary example I made, but with my real data it produces an error.
for i in df['split']:
... while '' in i:
... i.remove('')
...
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
TypeError: argument of type 'float' is not iterable
I'm not sure why I am getting an error with my data. Could get get some advice on this? Thanks!
python string pandas list series
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
add a comment |
-1
I've been searching for solutions and hints from the site, but couldn't find issue directly related with my case.
I have scraped text data from various sites and have split the text by using str.split('n'). The text contains a lot of 'n' and splitting this way made it pretty desirable. (Please let me know if this approach is too bad.)
df['scrape']
0 nWebsite:nnnnVisitnn nWhite paper:nn...
1 nWebsite:nnnnVisitnn nWhite paper:nn...
2 nWebsite:nnnnVisitnn nWhite paper:nn...
3 nWebsite:nnnnVisitnn nWhite paper:nn...
4 nWebsite:nnnnVisitnn nWhite paper:nn...
5 nWebsite:nnnnVisitnn nWhite paper:nn...
The result was a Pandas Series of lists – all elements are list of strings.
df['split'] = df['scrape'].str.split('n')
0 [, Website:, , , , Visit, , , White paper:, ,...
1 [, Website:, , , , Visit, , , White paper:, ,...
2 [, Website:, , , , Visit, , , White paper:, ,...
3 [, Website:, , , , Visit, , , White paper:, ,...
4 [, Website:, , , , Visit, , , White paper:, ,...
5 [, Website:, , , , Visit, , , White paper:, ,...
6 [, Website:, , , , Visit, , , White paper:, ,...
I want to get rid of None element (‘’ and ‘ ‘) on each list.
I tried looping:
for i in series:
While ‘’ in i:
i.remove(‘’)
Above code works with some arbitrary example I made, but with my real data it produces an error.
for i in df['split']:
... while '' in i:
... i.remove('')
...
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
TypeError: argument of type 'float' is not iterable
I'm not sure why I am getting an error with my data. Could get get some advice on this? Thanks!
python string pandas list series
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
1
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00
add a comment |
-1
-1
-1
I've been searching for solutions and hints from the site, but couldn't find issue directly related with my case.
I have scraped text data from various sites and have split the text by using str.split('n'). The text contains a lot of 'n' and splitting this way made it pretty desirable. (Please let me know if this approach is too bad.)
df['scrape']
0 nWebsite:nnnnVisitnn nWhite paper:nn...
1 nWebsite:nnnnVisitnn nWhite paper:nn...
2 nWebsite:nnnnVisitnn nWhite paper:nn...
3 nWebsite:nnnnVisitnn nWhite paper:nn...
4 nWebsite:nnnnVisitnn nWhite paper:nn...
5 nWebsite:nnnnVisitnn nWhite paper:nn...
The result was a Pandas Series of lists – all elements are list of strings.
df['split'] = df['scrape'].str.split('n')
0 [, Website:, , , , Visit, , , White paper:, ,...
1 [, Website:, , , , Visit, , , White paper:, ,...
2 [, Website:, , , , Visit, , , White paper:, ,...
3 [, Website:, , , , Visit, , , White paper:, ,...
4 [, Website:, , , , Visit, , , White paper:, ,...
5 [, Website:, , , , Visit, , , White paper:, ,...
6 [, Website:, , , , Visit, , , White paper:, ,...
I want to get rid of None element (‘’ and ‘ ‘) on each list.
I tried looping:
for i in series:
While ‘’ in i:
i.remove(‘’)
Above code works with some arbitrary example I made, but with my real data it produces an error.
for i in df['split']:
... while '' in i:
... i.remove('')
...
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
TypeError: argument of type 'float' is not iterable
I'm not sure why I am getting an error with my data. Could get get some advice on this? Thanks!
python string pandas list series
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
I've been searching for solutions and hints from the site, but couldn't find issue directly related with my case.
I have scraped text data from various sites and have split the text by using str.split('n'). The text contains a lot of 'n' and splitting this way made it pretty desirable. (Please let me know if this approach is too bad.)
df['scrape']
0 nWebsite:nnnnVisitnn nWhite paper:nn...
1 nWebsite:nnnnVisitnn nWhite paper:nn...
2 nWebsite:nnnnVisitnn nWhite paper:nn...
3 nWebsite:nnnnVisitnn nWhite paper:nn...
4 nWebsite:nnnnVisitnn nWhite paper:nn...
5 nWebsite:nnnnVisitnn nWhite paper:nn...
The result was a Pandas Series of lists – all elements are list of strings.
df['split'] = df['scrape'].str.split('n')
0 [, Website:, , , , Visit, , , White paper:, ,...
1 [, Website:, , , , Visit, , , White paper:, ,...
2 [, Website:, , , , Visit, , , White paper:, ,...
3 [, Website:, , , , Visit, , , White paper:, ,...
4 [, Website:, , , , Visit, , , White paper:, ,...
5 [, Website:, , , , Visit, , , White paper:, ,...
6 [, Website:, , , , Visit, , , White paper:, ,...
I want to get rid of None element (‘’ and ‘ ‘) on each list.
I tried looping:
for i in series:
While ‘’ in i:
i.remove(‘’)
Above code works with some arbitrary example I made, but with my real data it produces an error.
for i in df['split']:
... while '' in i:
... i.remove('')
...
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
TypeError: argument of type 'float' is not iterable
I'm not sure why I am getting an error with my data. Could get get some advice on this? Thanks!
python string pandas list series
python string pandas list series
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
edited Nov 19 '18 at 19:46
Matthew Son
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
asked Nov 19 '18 at 19:28
Matthew SonMatthew Son
33
33
1
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00
add a comment |
1
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00
1
1
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00
add a comment |
1 Answer
1
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1
You could use list comprehension:
new_series = [s for s in series if s!='' and s!=' ' and s!=None]
To apply the list comprehension to each element in a Pandas Series of lists (essentially a list of lists), you need to nest the list comprehension like this:
new_series = [[s for s in element if s!='' and s!=' ' and s!=None] for element in series]
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]
– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
|
show 4 more comments
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You could use list comprehension:
new_series = [s for s in series if s!='' and s!=' ' and s!=None]
To apply the list comprehension to each element in a Pandas Series of lists (essentially a list of lists), you need to nest the list comprehension like this:
new_series = [[s for s in element if s!='' and s!=' ' and s!=None] for element in series]
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]
– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
|
show 4 more comments
1
You could use list comprehension:
new_series = [s for s in series if s!='' and s!=' ' and s!=None]
To apply the list comprehension to each element in a Pandas Series of lists (essentially a list of lists), you need to nest the list comprehension like this:
new_series = [[s for s in element if s!='' and s!=' ' and s!=None] for element in series]
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]
– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
|
show 4 more comments
1
1
1
You could use list comprehension:
new_series = [s for s in series if s!='' and s!=' ' and s!=None]
To apply the list comprehension to each element in a Pandas Series of lists (essentially a list of lists), you need to nest the list comprehension like this:
new_series = [[s for s in element if s!='' and s!=' ' and s!=None] for element in series]
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
You could use list comprehension:
new_series = [s for s in series if s!='' and s!=' ' and s!=None]
To apply the list comprehension to each element in a Pandas Series of lists (essentially a list of lists), you need to nest the list comprehension like this:
new_series = [[s for s in element if s!='' and s!=' ' and s!=None] for element in series]
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
edited Nov 19 '18 at 20:59
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
answered Nov 19 '18 at 19:33
Toby PettyToby Petty
661412
661412
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]
– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
|
show 4 more comments
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]
– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Doesn't work. I tried series = [s for s in df['split'] if s!='' and s!=' '] and still it contains '' and ' ' values.
– Matthew Son
Nov 19 '18 at 19:51
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Do you need to add None criteria also? See my updated example
– Toby Petty
Nov 19 '18 at 20:15
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Still it doesn't work... tried converting it into list of lists too. Your suggestion yields one big list collapsed into, but I do have to keep those separate.
– Matthew Son
Nov 19 '18 at 20:40
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:
[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]– Toby Petty
Nov 19 '18 at 20:52
Ah ok I think I understand, you want to apply the list comprehension to each list in the series (essentially a list of lists). If I understand correctly this should work:
[[s for s in x if s!='' and s!=' ' and s!=None] for x in series]– Toby Petty
Nov 19 '18 at 20:52
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
Thanks for keep updating. This answer looks like what I want, but honestly don't know why it makes error still.. [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] >>> [[s for s in x if s!='' and s!=' ' and s!=None] for x in df['split']] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 1, in <listcomp> TypeError: 'float' object is not iterable
– Matthew Son
Nov 19 '18 at 21:18
|
show 4 more comments
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1
Don't store lists in a Series
– user3483203
Nov 19 '18 at 19:32
What's the suggestion for this case then, if I don't store lists in a Series?
– Matthew Son
Nov 19 '18 at 19:50
Solution Thanks to Toby's idea : def remover(list): return [s for s in list if s !='' and s != ' '] df['new'] = df['split'].apply(remover) With this method you don't need to drop NaN values.
– Matthew Son
Nov 19 '18 at 22:00