从MultiIndex删除级别

Question

I need to remove a level (either by position or name) from a DataFrame's index and create a new DataFrame with the new index. The problem is that I end up having a non-unique index.

I had a look at Remove a level from a pandas MultiIndex but the problem is that the use of unique(), as the answer in there suggests, reduces the index to an array, that doesn't retain the names of the levels.

Other than using unique(), and then creating a new Index by stitching the label names onto the array, is there a more elegant solution?

index = [np.array(['foo', 'foo', 'qux']), np.array(['a', 'b', 'a'])]
data = np.random.randn(3, 2)
columns = ["X", "Y"]
df = pd.DataFrame(data, index=index, columns=columns)
df.index.names = ["Level0", "Level1"]
print df

                      X         Y
Level0 Level1                    
foo    a      -0.591649  0.831599
       b       0.049961 -1.524291
qux    a      -0.100124 -1.059195

index2 = df.reset_index(level=1, drop=True).index
df2 = pd.DataFrame(index=index2)
print df2.loc[idx['foo'], :]

Empty DataFrame
Columns: []
Index: [foo, foo]

Answer 1

If I understand you correctly, you are looking for a solution to get the first level index without duplicated values. Your result should be an Ìndex object without using unique and without explicitly creating the index again.

For your example data frame, you can use the following including get_level_values and drop_duplicates :

print(df.index.get_level_values(0).drop_duplicates())
Index(['foo', 'qux'], dtype='object', name='Level0')

Edit

For a more general solution either returning an Index or MultiIndex depending on the number of levels, you may use droplevel and drop_duplicates in conjunction:

print(df.index.droplevel(-1).drop_duplicates())
Index(['foo', 'qux'], dtype='object', name='Level0')

Here is the example from the linked SO post with 3 levels which are reduced to 2 levels mutltiindex with unique values:

tuples = [(0, 100, 1000),(0, 100, 1001),(0, 100, 1002), (1, 101, 1001)]
index_3levels=pd.MultiIndex.from_tuples(tuples,names=["l1","l2","l3"])
print(index_3levels)

MultiIndex(levels=[[0, 1], [100, 101], [1000, 1001, 1002]],
           labels=[[0, 0, 0, 1], [0, 0, 0, 1], [0, 1, 2, 1]],
           names=['l1', 'l2', 'l3'])


index2level= index_3levels.droplevel(-1).drop_duplicates()
print(index2level)

MultiIndex(levels=[[0, 1], [100, 101]],
           labels=[[0, 1], [0, 1]],
           names=['l1', 'l2'])

# show unique values of new index
print(index2level)
[(0, 100) (1, 101)]