CODEWITHSUNDEEP
pythonpandassortingdataframemulti-index
tomp
tomp

Reputation: 653

Custom sorting of the level 1 index of a multiindex Pandas DataFrame according to the level 0 index

I have a multindex 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:

             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:

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:

             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:

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:

df.loc['baz'] = df.loc['baz'].reindex(new_index)

But the result is:

             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.

Upvotes: 4

Views: 1194

Answers (2)

Tai
Tai

Reputation: 7994

Edit: (to fit the desired layout)

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.

enter image description here

Upvotes: 3

BENY
BENY

Reputation: 323326

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

Upvotes: 1

Related Questions