Pandas “Can only compare identically-labeled DataFrame objects” error

Here’s a small example to demonstrate this (which only applied to DataFrames, not Series, until Pandas 0.19 where it applies to both):

In [1]: df1 = pd.DataFrame([[1, 2], [3, 4]])

In [2]: df2 = pd.DataFrame([[3, 4], [1, 2]], index=[1, 0])

In [3]: df1 == df2
Exception: Can only compare identically-labeled DataFrame objects

One solution is to sort the index first (Note: some functions require sorted indexes):

In [4]: df2.sort_index(inplace=True)

In [5]: df1 == df2
Out[5]: 
      0     1
0  True  True
1  True  True

Note: == is also sensitive to the order of columns, so you may have to use sort_index(axis=1):

In [11]: df1.sort_index().sort_index(axis=1) == df2.sort_index().sort_index(axis=1)
Out[11]: 
      0     1
0  True  True
1  True  True

Note: This can still raise (if the index/columns aren’t identically labelled after sorting).

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