Change order of pandas.MultiIndex
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1
My DataFrame has the following MultiIndex:
MultiIndex(levels=[[False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True]],
labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1], [0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1]],
names=['M016105', 'M743110', 'N237000', 'N239000', 'N241000', 'P010014', 'Z050001', 'Z050002', 'Z050005'])
The HTML rendering looks like this:
The list of labels in the header (names) has automatically been sorted alphabetically. However, I would like to determine the order in which they are displayed by passing a list. How can this be done?
I assume that just assigning a different list to names breaks the data as the table values are not automatically ordered differently.
python pandas dataframe indexing
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
add a comment |
1
My DataFrame has the following MultiIndex:
MultiIndex(levels=[[False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True]],
labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1], [0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1]],
names=['M016105', 'M743110', 'N237000', 'N239000', 'N241000', 'P010014', 'Z050001', 'Z050002', 'Z050005'])
The HTML rendering looks like this:
The list of labels in the header (names) has automatically been sorted alphabetically. However, I would like to determine the order in which they are displayed by passing a list. How can this be done?
I assume that just assigning a different list to names breaks the data as the table values are not automatically ordered differently.
python pandas dataframe indexing
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
add a comment |
1
1
1
1
My DataFrame has the following MultiIndex:
MultiIndex(levels=[[False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True]],
labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1], [0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1]],
names=['M016105', 'M743110', 'N237000', 'N239000', 'N241000', 'P010014', 'Z050001', 'Z050002', 'Z050005'])
The HTML rendering looks like this:
The list of labels in the header (names) has automatically been sorted alphabetically. However, I would like to determine the order in which they are displayed by passing a list. How can this be done?
I assume that just assigning a different list to names breaks the data as the table values are not automatically ordered differently.
python pandas dataframe indexing
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
My DataFrame has the following MultiIndex:
MultiIndex(levels=[[False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True], [False, True]],
labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0], [0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1], [0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1]],
names=['M016105', 'M743110', 'N237000', 'N239000', 'N241000', 'P010014', 'Z050001', 'Z050002', 'Z050005'])
The HTML rendering looks like this:
The list of labels in the header (names) has automatically been sorted alphabetically. However, I would like to determine the order in which they are displayed by passing a list. How can this be done?
I assume that just assigning a different list to names breaks the data as the table values are not automatically ordered differently.
python pandas dataframe indexing
python pandas dataframe indexing
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
edited Jan 4 at 14:54
clstaudt
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
asked Jan 4 at 14:32
clstaudtclstaudt
6,3092395167
6,3092395167
add a comment |
add a comment |
1 Answer
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oldest
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Use DataFrame.reorder_levels:
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
}).set_index(['A','B','C','D'])
df = df.reorder_levels(['B','C','A','D']).sort_index()
print (df)
E F
B C A D
4 3 f 0 4 b
7 a 1 5 a
9 c 5 6 a
5 2 e 1 2 b
4 d 7 9 b
8 b 3 3 a
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.reorder_levelskeeps the order of rows, but I don't care about the order of rows.
– clstaudt
Jan 4 at 14:56
@clstaudt - So needdf = df.reorder_levels(['B','C','A','D']).sort_index()?
– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
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
2
Use DataFrame.reorder_levels:
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
}).set_index(['A','B','C','D'])
df = df.reorder_levels(['B','C','A','D']).sort_index()
print (df)
E F
B C A D
4 3 f 0 4 b
7 a 1 5 a
9 c 5 6 a
5 2 e 1 2 b
4 d 7 9 b
8 b 3 3 a
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.reorder_levelskeeps the order of rows, but I don't care about the order of rows.
– clstaudt
Jan 4 at 14:56
@clstaudt - So needdf = df.reorder_levels(['B','C','A','D']).sort_index()?
– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
add a comment |
2
Use DataFrame.reorder_levels:
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
}).set_index(['A','B','C','D'])
df = df.reorder_levels(['B','C','A','D']).sort_index()
print (df)
E F
B C A D
4 3 f 0 4 b
7 a 1 5 a
9 c 5 6 a
5 2 e 1 2 b
4 d 7 9 b
8 b 3 3 a
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.reorder_levelskeeps the order of rows, but I don't care about the order of rows.
– clstaudt
Jan 4 at 14:56
@clstaudt - So needdf = df.reorder_levels(['B','C','A','D']).sort_index()?
– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
add a comment |
2
2
2
Use DataFrame.reorder_levels:
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
}).set_index(['A','B','C','D'])
df = df.reorder_levels(['B','C','A','D']).sort_index()
print (df)
E F
B C A D
4 3 f 0 4 b
7 a 1 5 a
9 c 5 6 a
5 2 e 1 2 b
4 d 7 9 b
8 b 3 3 a
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
Use DataFrame.reorder_levels:
df = pd.DataFrame({
'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,3],
'D':[1,3,5,7,1,0],
'E':[5,3,6,9,2,4],
'F':list('aaabbb')
}).set_index(['A','B','C','D'])
df = df.reorder_levels(['B','C','A','D']).sort_index()
print (df)
E F
B C A D
4 3 f 0 4 b
7 a 1 5 a
9 c 5 6 a
5 2 e 1 2 b
4 d 7 9 b
8 b 3 3 a
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
edited Jan 4 at 15:01
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
answered Jan 4 at 14:36
jezraeljezrael
360k26327407
360k26327407
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.reorder_levelskeeps the order of rows, but I don't care about the order of rows.
– clstaudt
Jan 4 at 14:56
@clstaudt - So needdf = df.reorder_levels(['B','C','A','D']).sort_index()?
– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
add a comment |
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.reorder_levelskeeps the order of rows, but I don't care about the order of rows.
– clstaudt
Jan 4 at 14:56
@clstaudt - So needdf = df.reorder_levels(['B','C','A','D']).sort_index()?
– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.
reorder_levels keeps the order of rows, but I don't care about the order of rows.– clstaudt
Jan 4 at 14:56
Thanks, that does what I asked, but I forgot to add one requirement: I want the True/False entries in the MultiIndex to remain sorted hierarchically - as shown in the screenshot above.
reorder_levels keeps the order of rows, but I don't care about the order of rows.– clstaudt
Jan 4 at 14:56
@clstaudt - So need
df = df.reorder_levels(['B','C','A','D']).sort_index() ?– jezrael
Jan 4 at 14:57
@clstaudt - So need
df = df.reorder_levels(['B','C','A','D']).sort_index() ?– jezrael
Jan 4 at 14:57
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
Sure, MultiIndex is of course a normal index in most ways.
– clstaudt
Jan 4 at 14:59
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
@clstaudt - Thank you for edit, also add sorted output to answer.
– jezrael
Jan 4 at 15:01
add a comment |
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