BUG: `Dataframe.astype(...)` Fails With `'bool' object has no attribute 'all'`

[zombie-einstein]

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Reproducible Example

import modin.pandas as pd
import numpy as np

# This will cast to a float type due to NaNs
df = pd.DataFrame({"a": [1, 2, 3, np.nan]})

# This passes
df.astype({"a": pd.Int64Dtype()})
>>    a
0     1
1     2
2     3
3  <NA>

# This fails
df.astype(pd.Int64Dtype())
>> AttributeError: 'bool' object has no attribute 'all'

Issue Description

I think this is the same error as #7276, but that issue was closed. When using astype on a Dataframe it fails at this check

File .../modin/core/dataframe/pandas/dataframe/dataframe.py:
   1736, in PandasDataframe.astype(self, col_dtypes, errors)
   1730         return df.astype(
   1731             {k: v for k, v in col_dtypes.items() if k in df}, errors=errors
   1732         )
   1734 else:
   1735     # Assume that the dtype is a scalar.
-> 1736     if not (col_dtypes == self_dtypes).all():
   1737         new_dtypes = self_dtypes.copy()
   1738         new_dtype = pandas.api.types.pandas_dtype(col_dtypes)

AttributeError: 'bool' object has no attribute 'all'

When the type argument is a single value (i.e. astype(pd.Int64Dtype())) then it seems that col_dtypes == self_dtypes works out as a single bool value (hence no all attribute).

Note that this works Ok if the argument is a dictionary of column namess to dtypes.

This also seems to be the same for Series, i.e.:

df["a"].astype(pd.Int64Dtype())

Fails with the same error

Expected Behavior

In native Pandas

df.astype(pd.Int64Dtype())

casts the DataFrame/series to the argument type

Error Logs

No response

Installed Versions

'0.31.0'