1 frames
/usr/local/lib/python3.6/dist-packages/numpy/core/numerictypes.py in issubdtype(arg1, arg2)
386 “”"
387 if not issubclass_(arg1, generic):
–> 388 arg1 = dtype(arg1).type
389 if not issubclass_(arg2, generic):
390 arg2 = dtype(arg2).type
TypeError: Cannot interpret ‘UInt32Dtype()’ as a data type
I already run this notebook before and it run fine.
Maybe somebody else also experienced such a problem?
I can manually resolve this problem by changing the data type of the saleWeek to int64, but it throws a simmilar error with ProductSize which is a “category”.
Tnx!
This was a PR done by someone recently. Could you open up an issue for it in the fastai github? (And if possible just a minimal reproducer of what’s needed? It would be great if that were a colab notebook )
Change saleWeek from UInt32 to uint32 df = df.astype({'saleWeek' : 'uint32'})
Modify cont_cat_split to detect ProductSize which is a CategoricalDtype properly by using the name property:
def cont_cat_split(df, max_card=20, dep_var=None):
cont_names, cat_names = [], []
for label in df:
if label in L(dep_var): continue
# mod to detect ProductSize type properly
if (df[label].dtype.name == 'category'):
cat_names.append(label)
continue
if (np.issubdtype(df[label].dtype, np.integer) and
df[label].unique().shape[0] > max_card or
np.issubdtype(df[label].dtype, np.floating)):
cont_names.append(label)
else: cat_names.append(label)
return cont_names, cat_names
Hey @sylvaint , I did as you instructed, but I still have the same issue:
TypeError: Cannot interpret ‘CategoricalDtype(categories=[‘Large’, ‘Large / Medium’, ‘Medium’, ‘Small’, ‘Mini’,
‘Compact’],
ordered=True)’ as a data type
@sylvaint Initially, I redefined the function cont_cat_split in the script core.py. Now, I had to copy the function cont_cat_split from the script and paste it into my code to redefine it there. And it worked. Thanks.
)