# Python Program to create a data type object
import numpy as np
 
# np.int16 is converted into a data type object.
print(np.dtype(np.int16))

int16

# Python Program to create a data type object
# containing a 32 bit big-endian integer
import numpy as np
 
# i4 represents integer of size 4 byte
# > represents big-endian byte ordering and < represents little-endian encoding.
# dt is a dtype object
dt = np.dtype('>i4')
 
print("Byte order is:",dt.byteorder)
 
print("Size is:",dt.itemsize)
 
print("Data type is:",dt.name)

Byte order is: >
Size is: 4
Name of data type is: int32

# Python program to differentiate
# between type and dtype.
import numpy as np
 
a = np.array([1])
 
print("type is: ",type(a))
print("dtype is: ",a.dtype)

type is:    
dtype is:  int32

# Python program for demonstrating
# the use of fields
import numpy as np
 
# A structured data type containing a 16-character string (in field ‘name’) 
# and a sub-array of two 64-bit floating-point number (in field ‘grades’):
 
dt = np.dtype([('name', np.unicode_, 16), ('grades', np.float64, (2,))])
 
# Data type of object with field grades
print(dt['grades'])
 
# Data type of object with field name 
print(dt['name'])

('<f8', (2,))

# Python program to demonstrate 
# the use of data type object with structured array.
import numpy as np
 
dt = np.dtype([('name', np.unicode_, 16), ('grades', np.float64, (2,))])
 
# x is a structured array with names and marks of students.
# Data type of name of the student is np.unicode_ and 
# data type of marks is np.float(64)
x = np.array([('Sarah', (8.0, 7.0)), ('John', (6.0, 7.0))], dtype=dt)
 
print(x[1])
print("Grades of John are: ",x[1]['grades'])
print("Names are: ",x['name'])

('John', [ 6.,  7.])
Grades of John are:  [ 6.  7.]
Names are:  ['Sarah' 'John']