How to create a column based on size of a set in pandas
I have a dataframe in pandas and I'm using 'set' as an aggregate function in a groupby and I create the following dataframe
A, B, C
1, 2, {nan, v}
1, 3, {nan, v,b}
In this example A and B are the columns I used in the groupby. I'd like to add another column to this dataframe which is the number of elements in column C which are not ``nan. That is I want my dataframe to look like below
A, B, C, D
1, 2, {nan, v}, 1
1, 3, {nan, v,b}, 2
How can I do that?
pandas pandas-groupby
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
add a comment |
I have a dataframe in pandas and I'm using 'set' as an aggregate function in a groupby and I create the following dataframe
A, B, C
1, 2, {nan, v}
1, 3, {nan, v,b}
In this example A and B are the columns I used in the groupby. I'd like to add another column to this dataframe which is the number of elements in column C which are not ``nan. That is I want my dataframe to look like below
A, B, C, D
1, 2, {nan, v}, 1
1, 3, {nan, v,b}, 2
How can I do that?
pandas pandas-groupby
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53
add a comment |
I have a dataframe in pandas and I'm using 'set' as an aggregate function in a groupby and I create the following dataframe
A, B, C
1, 2, {nan, v}
1, 3, {nan, v,b}
In this example A and B are the columns I used in the groupby. I'd like to add another column to this dataframe which is the number of elements in column C which are not ``nan. That is I want my dataframe to look like below
A, B, C, D
1, 2, {nan, v}, 1
1, 3, {nan, v,b}, 2
How can I do that?
pandas pandas-groupby
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
I have a dataframe in pandas and I'm using 'set' as an aggregate function in a groupby and I create the following dataframe
A, B, C
1, 2, {nan, v}
1, 3, {nan, v,b}
In this example A and B are the columns I used in the groupby. I'd like to add another column to this dataframe which is the number of elements in column C which are not ``nan. That is I want my dataframe to look like below
A, B, C, D
1, 2, {nan, v}, 1
1, 3, {nan, v,b}, 2
How can I do that?
pandas pandas-groupby
pandas pandas-groupby
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
asked Nov 15 '18 at 15:27
H.Z.H.Z.
1,83354394
1,83354394
It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53
add a comment |
It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53
It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53
It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53
add a comment |
1 Answer
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Using
df['D']=pd.DataFrame(df.C.tolist(),index=df.index).notnull().sum(axis=1)
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
add a comment |
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1 Answer
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1 Answer
1
active
oldest
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Using
df['D']=pd.DataFrame(df.C.tolist(),index=df.index).notnull().sum(axis=1)
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
add a comment |
Using
df['D']=pd.DataFrame(df.C.tolist(),index=df.index).notnull().sum(axis=1)
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
add a comment |
Using
df['D']=pd.DataFrame(df.C.tolist(),index=df.index).notnull().sum(axis=1)
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
Using
df['D']=pd.DataFrame(df.C.tolist(),index=df.index).notnull().sum(axis=1)
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
answered Nov 15 '18 at 15:39
Wen-BenWen-Ben
117k83469
117k83469
add a comment |
add a comment |
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It is better upvote and accept to close the old question before you asking a new one, I notice , you have been asking a lot question with good answer posted but none of them had been accepted
– Wen-Ben
Nov 15 '18 at 15:53