DataSet.select_dtypes does not support custom dtypes about reciprocalspaceship HOT 2 CLOSED

In my mind, this is a behavior that was made by pandas so I hesitate to overload it to change it. For example, this method also doesn't differentiate between np.int64 and pd.Int64Dtype (the nullable pandas int64 implementation):

In [17]: df = pd.DataFrame(np.arange(12).reshape(3, 4),
    ...:                   columns=['A', 'B', 'C', 'D'])
    ...: df["A"] = df["A"].astype(pd.Int64Dtype())

In [18]: df.dtypes
Out[18]: 
A    Int64         <----- Note capitalization
B    int64
C    int64
D    int64
dtype: object

In [19]: df.select_dtypes(pd.Int64Dtype())
Out[19]: 
   A  B   C   D
0  0  1   2   3
1  4  5   6   7
2  8  9  10  11

I do agree that their documentation doesn't make it clear that this operates to return columns based on the underlying numpy dtype though. It is always possible to get this behavior with a list comprehension, so if we do want this sort of method, I would rather implement it as a custom DataSet method rather than overload the DataFrame one. Something like this, but with added support to handle inputting the dtype as str or object:

def select_mtzdtype(self, dtype):
    return self[[k for k in self if isinstance(self.dtypes[k], dtype)]]

from reciprocalspaceship.

I'm totally happy with your proposed solution.

from reciprocalspaceship.