Create a new column based on the values of the column by ID
Please help me solve this problem. I searched online but couldn’t find the solution.
df
Id Fruit
1 Apple
1 Carrot
2 Apple
3 Carrot
list = [fruit, vegetable, both]
The question is, how to assign for each id, if id’s fruit column contains apple or carrot the list. If id contains apple then assign ID 1 fruit, if carrot only, then vegetable, if both then both.
I tried to use str.contains by row, but it doesn’t take ID column.
Result
Newdf
Id Fruit New_col
1 Apple Both
1 Carrot Both
2 Apple Fruit
3 Carrot Vegetable
Thank you a lot.
python pandas
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
add a comment |
Please help me solve this problem. I searched online but couldn’t find the solution.
df
Id Fruit
1 Apple
1 Carrot
2 Apple
3 Carrot
list = [fruit, vegetable, both]
The question is, how to assign for each id, if id’s fruit column contains apple or carrot the list. If id contains apple then assign ID 1 fruit, if carrot only, then vegetable, if both then both.
I tried to use str.contains by row, but it doesn’t take ID column.
Result
Newdf
Id Fruit New_col
1 Apple Both
1 Carrot Both
2 Apple Fruit
3 Carrot Vegetable
Thank you a lot.
python pandas
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
add a comment |
Please help me solve this problem. I searched online but couldn’t find the solution.
df
Id Fruit
1 Apple
1 Carrot
2 Apple
3 Carrot
list = [fruit, vegetable, both]
The question is, how to assign for each id, if id’s fruit column contains apple or carrot the list. If id contains apple then assign ID 1 fruit, if carrot only, then vegetable, if both then both.
I tried to use str.contains by row, but it doesn’t take ID column.
Result
Newdf
Id Fruit New_col
1 Apple Both
1 Carrot Both
2 Apple Fruit
3 Carrot Vegetable
Thank you a lot.
python pandas
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
Please help me solve this problem. I searched online but couldn’t find the solution.
df
Id Fruit
1 Apple
1 Carrot
2 Apple
3 Carrot
list = [fruit, vegetable, both]
The question is, how to assign for each id, if id’s fruit column contains apple or carrot the list. If id contains apple then assign ID 1 fruit, if carrot only, then vegetable, if both then both.
I tried to use str.contains by row, but it doesn’t take ID column.
Result
Newdf
Id Fruit New_col
1 Apple Both
1 Carrot Both
2 Apple Fruit
3 Carrot Vegetable
Thank you a lot.
python pandas
python pandas
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
asked Nov 21 '18 at 3:04
PythonistaPythonista
274
274
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Doing map first , then we just using transform nunqiue finding the the position should be 'both'
s=df.Fruit.map({'Apple':'Fruit','Carrot':'Vegetable'})
mask=s.groupby(df.Id).transform('nunique').eq(2)
s[mask]='both'
df['New']=s
df
Out[190]:
Id Fruit New
0 1 Apple both
1 1 Carrot both
2 2 Apple Fruit
3 3 Carrot Vegetable
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Doing map first , then we just using transform nunqiue finding the the position should be 'both'
s=df.Fruit.map({'Apple':'Fruit','Carrot':'Vegetable'})
mask=s.groupby(df.Id).transform('nunique').eq(2)
s[mask]='both'
df['New']=s
df
Out[190]:
Id Fruit New
0 1 Apple both
1 1 Carrot both
2 2 Apple Fruit
3 3 Carrot Vegetable
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
add a comment |
Doing map first , then we just using transform nunqiue finding the the position should be 'both'
s=df.Fruit.map({'Apple':'Fruit','Carrot':'Vegetable'})
mask=s.groupby(df.Id).transform('nunique').eq(2)
s[mask]='both'
df['New']=s
df
Out[190]:
Id Fruit New
0 1 Apple both
1 1 Carrot both
2 2 Apple Fruit
3 3 Carrot Vegetable
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
add a comment |
Doing map first , then we just using transform nunqiue finding the the position should be 'both'
s=df.Fruit.map({'Apple':'Fruit','Carrot':'Vegetable'})
mask=s.groupby(df.Id).transform('nunique').eq(2)
s[mask]='both'
df['New']=s
df
Out[190]:
Id Fruit New
0 1 Apple both
1 1 Carrot both
2 2 Apple Fruit
3 3 Carrot Vegetable
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
Doing map first , then we just using transform nunqiue finding the the position should be 'both'
s=df.Fruit.map({'Apple':'Fruit','Carrot':'Vegetable'})
mask=s.groupby(df.Id).transform('nunique').eq(2)
s[mask]='both'
df['New']=s
df
Out[190]:
Id Fruit New
0 1 Apple both
1 1 Carrot both
2 2 Apple Fruit
3 3 Carrot Vegetable
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
answered Nov 21 '18 at 3:11
W-BW-B
106k83165
106k83165
add a comment |
add a comment |
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