Convert Column Name from int to string in pandas

Question

I have a pandas dataframe with mixed column names:

1,2,3,4,5, 'Class'

When I save this dataframe to h5file, it says that the performance will be affected due to mixed types. How do I convert the integer to string in pandas?

Answer 1

You can simply use df.columns = df.columns.astype(str):

In [26]: df = pd.DataFrame(np.random.random((3,6)), columns=[1,2,3,4,5,'Class'])  In [27]: df Out[27]:            1         2         3         4         5     Class 0  0.773423  0.865091  0.614956  0.219458  0.837748  0.862177 1  0.544805  0.535341  0.323215  0.929041  0.042705  0.759294 2  0.215638  0.251063  0.648350  0.353999  0.986773  0.483313  In [28]: df.columns.map(type) Out[28]:  array([<class 'int'>, <class 'int'>, <class 'int'>, <class 'int'>,        <class 'int'>, <class 'str'>], dtype=object)  In [29]: df.to_hdf("out.h5", "d1") C:\Anaconda3\lib\site-packages\pandas\io\pytables.py:260: PerformanceWarning:  your performance may suffer as PyTables will pickle object types that it cannot map directly to c-types [inferred_type->mixed-integer,key->axis0] [items->None]    f(store) C:\Anaconda3\lib\site-packages\pandas\io\pytables.py:260: PerformanceWarning:  your performance may suffer as PyTables will pickle object types that it cannot map directly to c-types [inferred_type->mixed-integer,key->block0_items] [items->None]    f(store)  In [30]: df.columns = df.columns.astype(str)  In [31]: df.columns.map(type) Out[31]:  array([<class 'str'>, <class 'str'>, <class 'str'>, <class 'str'>,        <class 'str'>, <class 'str'>], dtype=object)  In [32]: df.to_hdf("out.h5", "d1")  In [33]: