I have a multindex DataFrame, df:
我有一个多索引DataFrame,df:
arrays = [['bar', 'bar', 'baz', 'baz', 'baz', 'baz', 'foo', 'foo'],
['one', 'two', 'one', 'two', 'three', 'four', 'one', 'two']]
df = pd.DataFrame(np.ones([8, 4]), index=arrays)
which looks like:
看起来像:
0 1 2 3
bar one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
baz one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
three 1.0 1.0 1.0 1.0
four 1.0 1.0 1.0 1.0
foo one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
I now need to sort the 'baz' sub-level into a new order, to create something that looks like df_end:
我现在需要将'baz'子级别排序为新的顺序,以创建看起来像df_end的东西:
arrays_end = [['bar', 'bar', 'baz', 'baz', 'baz', 'baz', 'foo', 'foo'],
['one', 'two', 'two', 'four', 'three', 'one', 'one', 'two']]
df_end = pd.DataFrame(np.ones([8, 4]), index=arrays_end)
which looks like:
看起来像:
0 1 2 3
bar one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
baz two 1.0 1.0 1.0 1.0
four 1.0 1.0 1.0 1.0
three 1.0 1.0 1.0 1.0
one 1.0 1.0 1.0 1.0
foo one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
I thought that I might be able to reindex the baz row:
我以为我可以重新索引baz行:
new_index = ['two','four','three','one']
df.loc['baz'].reindex(new_index)
Which gives:
0 1 2 3
two 1.0 1.0 1.0 1.0
four 1.0 1.0 1.0 1.0
three 1.0 1.0 1.0 1.0
one 1.0 1.0 1.0 1.0
...and insert these values back into the original DataFrame:
...并将这些值插回到原始DataFrame中:
df.loc['baz'] = df.loc['baz'].reindex(new_index)
But the result is:
但结果是:
0 1 2 3
bar one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
baz one NaN NaN NaN NaN
two NaN NaN NaN NaN
three NaN NaN NaN NaN
four NaN NaN NaN NaN
foo one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
Which is not what I'm looking for! So my question is how I can use new_index to reorder the rows in the baz index. Any advice would be greatly appreciated.
这不是我想要的!所以我的问题是如何使用new_index重新排序baz索引中的行。任何建议将不胜感激。
2 个解决方案
#1
2
Edit: (to fit the desired layout)
编辑:(以适合所需的布局)
arrays = [['bar', 'bar', 'baz', 'baz', 'baz', 'baz', 'foo', 'foo'],
['one', 'two', 'one', 'two', 'three', 'four', 'one', 'two']]
df = pd.DataFrame(np.arange(32).reshape([8, 4]), index=arrays)
new_baz_index = [('baz', i) for i in ['two','four','three','one']]
index = df.index.values.copy()
index[df.index.get_loc('baz')] = new_baz_index
df.reindex(index)
df.index.get_loc('baz') will get the location of the baz part as a slice object and we replace the part there only.
df.index.get_loc('baz')将获取baz零件的位置作为切片对象,我们只替换那里的零件。
#2
1
Update :-)
pd.concat([df[df.index.get_level_values(level=0)!='baz'],df.reindex(list(zip(['baz']*4,['two','four','three','one'])))])
Out[1156]:
0 1 2 3
bar one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
foo one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
baz two 1.0 1.0 1.0 1.0
four 1.0 1.0 1.0 1.0
three 1.0 1.0 1.0 1.0
one 1.0 1.0 1.0 1.0
#1
2
Edit: (to fit the desired layout)
编辑:(以适合所需的布局)
arrays = [['bar', 'bar', 'baz', 'baz', 'baz', 'baz', 'foo', 'foo'],
['one', 'two', 'one', 'two', 'three', 'four', 'one', 'two']]
df = pd.DataFrame(np.arange(32).reshape([8, 4]), index=arrays)
new_baz_index = [('baz', i) for i in ['two','four','three','one']]
index = df.index.values.copy()
index[df.index.get_loc('baz')] = new_baz_index
df.reindex(index)
df.index.get_loc('baz') will get the location of the baz part as a slice object and we replace the part there only.
df.index.get_loc('baz')将获取baz零件的位置作为切片对象,我们只替换那里的零件。
#2
1
Update :-)
pd.concat([df[df.index.get_level_values(level=0)!='baz'],df.reindex(list(zip(['baz']*4,['two','four','three','one'])))])
Out[1156]:
0 1 2 3
bar one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
foo one 1.0 1.0 1.0 1.0
two 1.0 1.0 1.0 1.0
baz two 1.0 1.0 1.0 1.0
four 1.0 1.0 1.0 1.0
three 1.0 1.0 1.0 1.0
one 1.0 1.0 1.0 1.0