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Description
Code Sample, a copy-pastable example if possible
Setup:
In [2]: df = pd.DataFrame(data=np.random.randint(5, size=(3, 4)),
...: columns=pd.UInt64Index(range(500, 504), name='foo'))
...:
In [3]: df
Out[3]:
foo 500 501 502 503
0 4 4 2 1
1 0 2 3 1
2 1 4 0 0
In [4]: df.columns
Out[4]: UInt64Index([500, 501, 502, 503], dtype='uint64', name='foo')Using .astype(dict) loses column metadata:
In [5]: df = df.astype({500: 'float64', 501: 'uint64'})
In [6]: df.columns
Out[6]: Int64Index([500, 501, 502, 503], dtype='int64')Problem description
Column metadata is lost: the name has been removed and it has been cast from UInt64Index to Int64Index.
Expected Output
I'd expect the columns post-astype to be the same as pre-astype.