Numpy ndarray.setfield() function | Python

Numpy ndarray.setfield() function | Python

Last Updated : 22 Apr, 2020

numpy.ndarray.setfield() function Put a value into a specified place in a field defined by a data-type. Place val into a’s field defined by dtype and beginning offset bytes into the field.

Syntax : numpy.ndarray.setfield(val, dtype, offset=0) Parameters : val : [object] Value to be placed in field. dtype : [dtype object] Data-type of the field in which to place val. offset : [int, optional] The number of bytes into the field at which to place val. Return : None.

Code #1 :

Python3

# Python program explaining
# numpy.ndarray.setfield() function

# importing numpy as geek 
import numpy as geek 
          
arr = geek.eye(4)
          
arr.setfield(4, geek.int32)
gfg = arr.getfield(geek.int32)
    
print(gfg)

Output :

[[4 4 4 4]
 [4 4 4 4]
 [4 4 4 4]
 [4 4 4 4]]

Code #2 :

Python3

# Python program explaining
# numpy.ndarray.setfield() function

# importing numpy as geek 
import numpy as geek 
          
arr = geek.eye(2)
          
arr.setfield(2, geek.int32)
gfg = arr.getfield(geek.int32)
    
print(gfg)

Output :

[[2 2]
 [2 2]]

Numpy ndarray.setfield() function | Python

sanjoy_62

Improve

Article Tags :

Practice Tags :

Similar Reads

numpy.ndarray.resize() function - Python

numpy.ndarray.resize() function change shape and size of array in-place. Syntax : numpy.ndarray.resize(new_shape, refcheck = True) Parameters : new_shape :[tuple of ints, or n ints] Shape of resized array. refcheck :[bool, optional] If False, reference count will not be checked. Default is True. Ret

Numpy ndarray.tobytes() function | Python

numpy.ndarray.tobytes() function construct Python bytes containing the raw data bytes in the array. Syntax : numpy.ndarray.tobytes(order='C') Parameters : order : [{â€˜Câ€™, â€˜Fâ€™, None}, optional] Order of the data for multidimensional arrays: C, Fortran, or the same as for the original array. Return : P

numpy.ndarray.view() in Python

numpy.ndarray.view() helps to get a new view of array with the same data.Â Syntax: ndarray.view(dtype=None, type=None)Parameters:Â dtype : Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a.Â type : Python type, opti

Numpy ndarray.getfield() function | Python

numpy.ndarray.getfield() function return a field of the given array as a certain type. Syntax : numpy.ndarray.getfield(dtype, offset=0) Parameters : dtype : [str or dtype] The dtype size of the view can not be larger than that of the array itself. offset : [int] Number of bytes to skip before beginn

numpy.ndarray.flat() in Python

The numpy.ndarray.flat() function is used as a 1_D iterator over N-dimensional arrays.Â It is not a subclass of, Pythonâ€™s built-in iterator object, otherwise it a numpy.flatiter instance.Â Syntax :Â numpy.ndarray.flat() Parameters :Â index : [tuple(int)] index of the values to iterate Return :Â Â 1-D i

numpy.select() function - Python

The numpy.select() function is used to construct an array by selecting elements from a list of choices based on multiple conditions. It is particularly useful when dealing with conditional replacements or transformations in NumPy arrays. Example:Pythonimport numpy as np arr = np.array([10, 20, 30, 4

Numpy ndarray.flatten() function in Python

The flatten() function is used to convert a multi-dimensional NumPy array into a one-dimensional array. It creates a new copy of the data so that original array stays unchanged. If your array has rows and columns or even more dimensions, then flatten() line up every single value into a straight list

Python | Numpy matrix.setfield()

With the help of matrix.setfield() method, all the fields in the matrix is set to the value which is passed in the form of parameter. Syntax : matrix.setfield() Return : new matrix having the value passed as parameter Example #1 : In this example we can see that matrix.setfield() method is used to g

numpy.ndarray.fill() in Python

numpy.ndarray.fill() method is used to fill the numpy array with a scalar value. If we have to initialize a numpy array with an identical value then we use numpy.ndarray.fill(). Suppose we have to create a NumPy array a of length n, each element of which is v. Then we use this function as a.fill(v).

Python | Numpy ndarray.__copy__()

With the help of Numpy ndarray.__copy__() method, we can make a copy of all the data elements that is present in numpy array. If you change any data element in the copy, it will not affect the original numpy array. Syntax : numpy.__copy__() Return : Copy of all the data elements Example #1 : In this