Pivot unique values from Column B to a new column after grouping Column A
up vote
1
down vote
favorite
I have the following dataframe:
COL_A COL_B
1 a
1 b
2 a
2 b
3 a
3 b
4 c
4 d
5 c
5 d
and I'm attempting to group the values in COL_A and pivot the unique values in COL_B to a new column
COL_A COL_B COL_C
1 a b
2 a b
3 a b
4 c d
5 c d
I've tried a bunch of different techniques with df.groupby and df.pivot but I can't seem to get my desired results.
python pandas
edited Nov 11 at 2:36
eyllanesc
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
add a comment |
up vote
1
down vote
favorite
I have the following dataframe:
COL_A COL_B
1 a
1 b
2 a
2 b
3 a
3 b
4 c
4 d
5 c
5 d
and I'm attempting to group the values in COL_A and pivot the unique values in COL_B to a new column
COL_A COL_B COL_C
1 a b
2 a b
3 a b
4 c d
5 c d
I've tried a bunch of different techniques with df.groupby and df.pivot but I can't seem to get my desired results.
python pandas
edited Nov 11 at 2:36
eyllanesc
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
Does each uniqueCOL_Avalue always occur exactly twice?
– jpp
Nov 11 at 2:29
In this case yes
– jbrd435
Nov 11 at 2:32
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I have the following dataframe:
COL_A COL_B
1 a
1 b
2 a
2 b
3 a
3 b
4 c
4 d
5 c
5 d
and I'm attempting to group the values in COL_A and pivot the unique values in COL_B to a new column
COL_A COL_B COL_C
1 a b
2 a b
3 a b
4 c d
5 c d
I've tried a bunch of different techniques with df.groupby and df.pivot but I can't seem to get my desired results.
python pandas
edited Nov 11 at 2:36
eyllanesc
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
I have the following dataframe:
COL_A COL_B
1 a
1 b
2 a
2 b
3 a
3 b
4 c
4 d
5 c
5 d
and I'm attempting to group the values in COL_A and pivot the unique values in COL_B to a new column
COL_A COL_B COL_C
1 a b
2 a b
3 a b
4 c d
5 c d
I've tried a bunch of different techniques with df.groupby and df.pivot but I can't seem to get my desired results.
python pandas
python pandas
edited Nov 11 at 2:36
eyllanesc
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
edited Nov 11 at 2:36
eyllanesc
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
edited Nov 11 at 2:36
eyllanesc
69.6k93052
edited Nov 11 at 2:36
eyllanesc
69.6k93052
edited Nov 11 at 2:36
eyllanesc
69.6k93052
69.6k93052
asked Nov 11 at 2:27
jbrd435
175
asked Nov 11 at 2:27
jbrd435
175
asked Nov 11 at 2:27
jbrd435
175
175
Does each uniqueCOL_Avalue always occur exactly twice?
– jpp
Nov 11 at 2:29
In this case yes
– jbrd435
Nov 11 at 2:32
add a comment |
Does each uniqueCOL_Avalue always occur exactly twice?
– jpp
Nov 11 at 2:29
In this case yes
– jbrd435
Nov 11 at 2:32
Does each unique
COL_A value always occur exactly twice?– jpp
Nov 11 at 2:29
Does each unique
COL_A value always occur exactly twice?– jpp
Nov 11 at 2:29
In this case yes
– jbrd435
Nov 11 at 2:32
In this case yes
– jbrd435
Nov 11 at 2:32
add a comment |
1 Answer
1
active
oldest
votes
up vote
1
down vote
accepted
Since each unique COL_A value always occurs exactly twice, you can reshape your series and feed to the pd.DataFrame constructor:
df = df.sort_values('COL_A')
arr = df['COL_B'].values.reshape(-1, 2)
res = pd.DataFrame({'COL_A': df['COL_A'].unique(),
'COL_B': arr[:, 0],
'COL_C': arr[:, 1]})
print(res)
COL_A COL_B COL_C
0 1 a b
1 2 a b
2 3 a b
3 4 c d
4 5 c d
answered Nov 11 at 2:33
jpp
85.4k194897
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
1
down vote
accepted
Since each unique COL_A value always occurs exactly twice, you can reshape your series and feed to the pd.DataFrame constructor:
df = df.sort_values('COL_A')
arr = df['COL_B'].values.reshape(-1, 2)
res = pd.DataFrame({'COL_A': df['COL_A'].unique(),
'COL_B': arr[:, 0],
'COL_C': arr[:, 1]})
print(res)
COL_A COL_B COL_C
0 1 a b
1 2 a b
2 3 a b
3 4 c d
4 5 c d
answered Nov 11 at 2:33
jpp
85.4k194897
add a comment |
up vote
1
down vote
accepted
Since each unique COL_A value always occurs exactly twice, you can reshape your series and feed to the pd.DataFrame constructor:
df = df.sort_values('COL_A')
arr = df['COL_B'].values.reshape(-1, 2)
res = pd.DataFrame({'COL_A': df['COL_A'].unique(),
'COL_B': arr[:, 0],
'COL_C': arr[:, 1]})
print(res)
COL_A COL_B COL_C
0 1 a b
1 2 a b
2 3 a b
3 4 c d
4 5 c d
answered Nov 11 at 2:33
jpp
85.4k194897
add a comment |
up vote
1
down vote
accepted
up vote
1
down vote
accepted
Since each unique COL_A value always occurs exactly twice, you can reshape your series and feed to the pd.DataFrame constructor:
df = df.sort_values('COL_A')
arr = df['COL_B'].values.reshape(-1, 2)
res = pd.DataFrame({'COL_A': df['COL_A'].unique(),
'COL_B': arr[:, 0],
'COL_C': arr[:, 1]})
print(res)
COL_A COL_B COL_C
0 1 a b
1 2 a b
2 3 a b
3 4 c d
4 5 c d
answered Nov 11 at 2:33
jpp
85.4k194897
Since each unique COL_A value always occurs exactly twice, you can reshape your series and feed to the pd.DataFrame constructor:
df = df.sort_values('COL_A')
arr = df['COL_B'].values.reshape(-1, 2)
res = pd.DataFrame({'COL_A': df['COL_A'].unique(),
'COL_B': arr[:, 0],
'COL_C': arr[:, 1]})
print(res)
COL_A COL_B COL_C
0 1 a b
1 2 a b
2 3 a b
3 4 c d
4 5 c d
answered Nov 11 at 2:33
jpp
85.4k194897
answered Nov 11 at 2:33
jpp
85.4k194897
answered Nov 11 at 2:33
jpp
85.4k194897
answered Nov 11 at 2:33
jpp
85.4k194897
85.4k194897
add a comment |
add a comment |
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Does each unique
COL_Avalue always occur exactly twice?– jpp
Nov 11 at 2:29
In this case yes
– jbrd435
Nov 11 at 2:32