Return the type that results from applying the NumPy type promotion rules to the arguments in Python

The numpy.result_type() method returns the type that results from applying the NumPy type promotion rules to the arguments. The 1st parameter is the operands of some operation whose result type is needed. Type promotion in NumPy works similarly to the rules in languages like C++, with some slight differences. When both scalars and arrays are used, the array’s type takes precedence and the actual value of the scalar is taken into account.

Steps

At first, import the required library −

import numpy as np

The numpy.result_type() method returns the type that results from applying the NumPy type promotion rules to the arguments −

print("Using the result_type() method in Numpy\n")
print("Result...",np.result_type(2, np.arange(4,dtype='i1')))
print("Result...",np.result_type(5, 8))
print("Result...",np.result_type('i4', 'c8'))
print("Result...",np.result_type(3.8, 8))
print("Result...",np.result_type(5, 20.7))
print("Result...",np.result_type(-8, 20.7))
print("Result...",np.result_type(10.0, -4))

Example

import numpy as np
# The numpy.result_type() method returns the type that results from applying the NumPy type promotion rules to the arguments.
# The 1st parameter is the operands of some operation whose result type is needed.
print("Using the result_type() method in Numpy\n")

print("Result...",np.result_type(2, np.arange(4,dtype='i1')))
print("Result...",np.result_type(5, 8))
print("Result...",np.result_type('i4', 'c8'))
print("Result...",np.result_type(3.8, 8))
print("Result...",np.result_type(5, 20.7))
print("Result...",np.result_type(-8, 20.7))
print("Result...",np.result_type(10.0, -4))

Output

Using the result_type() method in Numpy

Result... int8
Result... int64
Result... complex128
Result... float64
Result... float64
Result... float64
Result... float64