Closed
Description
In [8]: df = pd.DataFrame([[1., 2.], [3., 4.], [5., 6.]], columns=['a', 'b'])
In [9]: df
Out[9]:
a b
0 1.0 2.0
1 3.0 4.0
2 5.0 6.0
In [10]: df.astype('Int64')
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-10-b9d2763e69d8> in <module>()
----> 1 df.astype('Int64')
~/scipy/pandas/pandas/util/_decorators.py in wrapper(*args, **kwargs)
175 else:
176 kwargs[new_arg_name] = new_arg_value
--> 177 return func(*args, **kwargs)
178 return wrapper
179 return _deprecate_kwarg
~/scipy/pandas/pandas/core/generic.py in astype(self, dtype, copy, errors, **kwargs)
5162 # else, only a single dtype is given
5163 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 5164 **kwargs)
5165 return self._constructor(new_data).__finalize__(self)
5166
~/scipy/pandas/pandas/core/internals/managers.py in astype(self, dtype, **kwargs)
554
555 def astype(self, dtype, **kwargs):
--> 556 return self.apply('astype', dtype=dtype, **kwargs)
557
558 def convert(self, **kwargs):
~/scipy/pandas/pandas/core/internals/managers.py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
421
422 kwargs['mgr'] = self
--> 423 applied = getattr(b, f)(**kwargs)
424 result_blocks = _extend_blocks(applied, result_blocks)
425
~/scipy/pandas/pandas/core/internals/blocks.py in astype(self, dtype, copy, errors, values, **kwargs)
562 def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
563 return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 564 **kwargs)
565
566 def _astype(self, dtype, copy=False, errors='raise', values=None,
~/scipy/pandas/pandas/core/internals/blocks.py in _astype(self, dtype, copy, errors, values, klass, mgr, **kwargs)
679 "current ({newb_dtype} [{newb_size}])".format(
680 copy=copy, dtype=self.dtype.name,
--> 681 itemsize=self.itemsize, newb_dtype=newb.dtype.name,
682 newb_size=newb.itemsize))
683 return newb
AttributeError: 'FloatBlock' object has no attribute 'itemsize'
The same if the starting dataframe is of integer dtype.