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Test whether int datatype of different sizes are not subdtypes of each other in Python
# To check whether int data types of different sizes are not subdtypes of each other, use the numpy.issubdtype() method in Python Numpy.
# The parameters are the dtype or object coercible to one
Steps
At first, import the required library −
import numpy as np
Using the issubdtype() method in Numpy. Checking for int datatype with different sizes −
print("Result...",np.issubdtype(np.int16, np.int32))
print("Result...",np.issubdtype(np.int32, np.int16))
print("Result...",np.issubdtype(np.int64, np.int32))
print("Result...",np.issubdtype(np.int32, np.int64))
print("Result...",np.issubdtype(np.int16, np.int64))
print("Result...",np.issubdtype(np.int64, np.int16))Example
import numpy as np
# To check whether int data types of different sizes are not subdtypes of each other, use the numpy.issubdtype() method in Python Numpy.
# The parameters are the dtype or object coercible to one
print("Using the issubdtype() method in Numpy\n")
# Checking for int datatype with different sizes
print("Result...",np.issubdtype(np.int16, np.int32))
print("Result...",np.issubdtype(np.int32, np.int16))
print("Result...",np.issubdtype(np.int64, np.int32))
print("Result...",np.issubdtype(np.int32, np.int64))
print("Result...",np.issubdtype(np.int16, np.int64))
print("Result...",np.issubdtype(np.int64, np.int16))Output
Using the issubdtype() method in Numpy Result... False Result... False Result... False Result... False Result... False Result... False
Updated on: 24-Feb-2022
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