The numpy.promote_types() method returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. Returns the promoted data type. The returned data type is always in native byte order. The 1st parameter is the first data type. The 2nd parameter is the second data type.
Steps
At first, import the required library −
import numpy as np
Checking with promote_types() method in Numpy −
print("Result...",np.promote_types('f4', 'f8')) print("Result...",np.promote_types('i8', 'f4')) print("Result...",np.promote_types('>i8', '<c8')) print("Result...",np.promote_types('i4', 'S8')) print("Result...",np.promote_types(np.int32, np.int64)) print("Result...",np.promote_types(np.float64, complex)) print("Result...",np.promote_types(complex, float))
Example
import numpy as np # The numpy.promote_types() method returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. print("Checking with promote_types() method in Numpy\n") print("Result...",np.promote_types('f4', 'f8')) print("Result...",np.promote_types('i8', 'f4')) print("Result...",np.promote_types('>i8', '<c8')) print("Result...",np.promote_types('i4', 'S8')) print("Result...",np.promote_types(np.int32, np.int64)) print("Result...",np.promote_types(np.float64, complex)) print("Result...",np.promote_types(complex, float))
Output
Checking with promote_types() method in Numpy Result... float64 Result... float64 Result... complex128 Result... |S11 Result... int64 Result... complex128 Result... complex128