Test whether similar data types of different sizes are not subdtypes of each other in Python

To check whether similar 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 Nump to check for similar datatypes with different sizes. Checking for float datatype with different sizes −

print("Result...",np.issubdtype(np.float32, np.float64))
print("Result...",np.issubdtype(np.float64, np.float32))

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))

Example

import numpy as np

# To check whether similar 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 similar datatypes with different sizes

# Checking for float datatype with different sizes
print("Result...",np.issubdtype(np.float32, np.float64))
print("Result...",np.issubdtype(np.float64, np.float32))

# 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))

Output

Using the issubdtype() method in Numpy

Result... False
Result... False
Result... False
Result... False
Result... False
Result... False