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).