Python Pandas dataframe column not update correctly on Split data fraction
I have a Python function to split data, that is formatted as a fraction: 4/5, 1/1, 1,2, etc. This function iterates thru the dataframe ok. the split() function. The print() statements shows correct split on variable s[0] and s[1], respectively. The problem is that the df_ff_reviews['NumHelpfulVotes'] = s[0] and df_ff_reviews['NumVotes'] = s[1] dataframe columnes are not updated with the split value of the s[0], s[1], respectively. When I view the dataframe (head) I see all rows for columns NumHelpfulVotes and NumVotes which are set to zero. Never matching the s[0] and s[1] split values inside the iterated loop.
def split_votes():
for idx, row in df_ff_reviews.iterrows():
value = ''
s = ''
value = str(row['helpfulness'])
s = value.split('/')
df_ff_reviews['NumHelpfulVotes'] = s[0]
df_ff_reviews['NumVotes'] = s[1]
s[0]): 0
s[1]): 1
s[0]): 19
s[1]): 19
s[0]): 13
s[1]): 13
s[0]): 9
s[1]): 9
s[0]): 3
s[1]): 3
python-3.x pandas split
asked Nov 21 '18 at 2:33
user1857373user1857373
316
add a comment |
I have a Python function to split data, that is formatted as a fraction: 4/5, 1/1, 1,2, etc. This function iterates thru the dataframe ok. the split() function. The print() statements shows correct split on variable s[0] and s[1], respectively. The problem is that the df_ff_reviews['NumHelpfulVotes'] = s[0] and df_ff_reviews['NumVotes'] = s[1] dataframe columnes are not updated with the split value of the s[0], s[1], respectively. When I view the dataframe (head) I see all rows for columns NumHelpfulVotes and NumVotes which are set to zero. Never matching the s[0] and s[1] split values inside the iterated loop.
def split_votes():
for idx, row in df_ff_reviews.iterrows():
value = ''
s = ''
value = str(row['helpfulness'])
s = value.split('/')
df_ff_reviews['NumHelpfulVotes'] = s[0]
df_ff_reviews['NumVotes'] = s[1]
s[0]): 0
s[1]): 1
s[0]): 19
s[1]): 19
s[0]): 13
s[1]): 13
s[0]): 9
s[1]): 9
s[0]): 3
s[1]): 3
python-3.x pandas split
asked Nov 21 '18 at 2:33
user1857373user1857373
316
add a comment |
I have a Python function to split data, that is formatted as a fraction: 4/5, 1/1, 1,2, etc. This function iterates thru the dataframe ok. the split() function. The print() statements shows correct split on variable s[0] and s[1], respectively. The problem is that the df_ff_reviews['NumHelpfulVotes'] = s[0] and df_ff_reviews['NumVotes'] = s[1] dataframe columnes are not updated with the split value of the s[0], s[1], respectively. When I view the dataframe (head) I see all rows for columns NumHelpfulVotes and NumVotes which are set to zero. Never matching the s[0] and s[1] split values inside the iterated loop.
def split_votes():
for idx, row in df_ff_reviews.iterrows():
value = ''
s = ''
value = str(row['helpfulness'])
s = value.split('/')
df_ff_reviews['NumHelpfulVotes'] = s[0]
df_ff_reviews['NumVotes'] = s[1]
s[0]): 0
s[1]): 1
s[0]): 19
s[1]): 19
s[0]): 13
s[1]): 13
s[0]): 9
s[1]): 9
s[0]): 3
s[1]): 3
python-3.x pandas split
asked Nov 21 '18 at 2:33
user1857373user1857373
316
I have a Python function to split data, that is formatted as a fraction: 4/5, 1/1, 1,2, etc. This function iterates thru the dataframe ok. the split() function. The print() statements shows correct split on variable s[0] and s[1], respectively. The problem is that the df_ff_reviews['NumHelpfulVotes'] = s[0] and df_ff_reviews['NumVotes'] = s[1] dataframe columnes are not updated with the split value of the s[0], s[1], respectively. When I view the dataframe (head) I see all rows for columns NumHelpfulVotes and NumVotes which are set to zero. Never matching the s[0] and s[1] split values inside the iterated loop.
def split_votes():
for idx, row in df_ff_reviews.iterrows():
value = ''
s = ''
value = str(row['helpfulness'])
s = value.split('/')
df_ff_reviews['NumHelpfulVotes'] = s[0]
df_ff_reviews['NumVotes'] = s[1]
s[0]): 0
s[1]): 1
s[0]): 19
s[1]): 19
s[0]): 13
s[1]): 13
s[0]): 9
s[1]): 9
s[0]): 3
s[1]): 3
python-3.x pandas split
python-3.x pandas split
asked Nov 21 '18 at 2:33
user1857373user1857373
316
asked Nov 21 '18 at 2:33
user1857373user1857373
316
asked Nov 21 '18 at 2:33
user1857373user1857373
316
asked Nov 21 '18 at 2:33
user1857373user1857373
316
asked Nov 21 '18 at 2:33
user1857373user1857373
316
316
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Doing like str.split with expand
df_ff_reviews[['NumHelpfulVotes','NumVotes']]=df_ff_reviews.helpfullness.str.split('/',expand=True)[[0,1]]
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
add a comment |
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1 Answer
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active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Doing like str.split with expand
df_ff_reviews[['NumHelpfulVotes','NumVotes']]=df_ff_reviews.helpfullness.str.split('/',expand=True)[[0,1]]
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
add a comment |
Doing like str.split with expand
df_ff_reviews[['NumHelpfulVotes','NumVotes']]=df_ff_reviews.helpfullness.str.split('/',expand=True)[[0,1]]
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
add a comment |
Doing like str.split with expand
df_ff_reviews[['NumHelpfulVotes','NumVotes']]=df_ff_reviews.helpfullness.str.split('/',expand=True)[[0,1]]
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
Doing like str.split with expand
df_ff_reviews[['NumHelpfulVotes','NumVotes']]=df_ff_reviews.helpfullness.str.split('/',expand=True)[[0,1]]
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
answered Nov 21 '18 at 2:58
Wen-BenWen-Ben
117k83369
117k83369
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
add a comment |
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
1
1
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
that worked perfectly.
– user1857373
Nov 21 '18 at 3:33
add a comment |
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