NumPy ndarray.T | Get View of Transposed Array Last Updated : 31 Jan, 2024 Summarize Comments Improve Suggest changes Share Like Article Like Report The NumPy ndarray.T attribute finds the view of the transposed Array. It can transpose any array having a dimension greater than or equal to 2. It works similarly to the numpy.transpose() method but it is easy and concise to use. SyntaxSyntax: ndarray.T Returns Transpose of given arrayExamplesLet's look at how to use the ndarray.T attribute of the Python's NumPy library. Example 1 Python3 import numpy as np arr = np.array([[1, 2, 3], [4, 5, 6]]) # applying ndarray.T object transposed_array = arr.T print(transposed_array) Output[[1 4] [2 5] [3 6]] Example 2 Python3 # import the important module in python import numpy as np # make an array with numpy gfg = np.array([[1, 2, 3, 4], [4, 5, 6, 7], [7, 8, 9, 0]]) # applying ndarray.T object geeks = gfg.T print(geeks) Output: [[1 4 7] [2 5 8] [3 6 9] [4 7 0]] The ndarray.T attribute finds its use in machine learning applications where input data needs to be formatted in a certain way for further processing. It does not modify the original array and only returns the view of the transposed array. Comment More infoAdvertise with us Next Article NumPy ndarray.transpose() Method | Find Transpose of the NumPy Array J jitender_1998 Follow Improve Article Tags : Numpy Python-numpy Python numpy-ndarray Similar Reads NumPy ndarray.transpose() Method | Find Transpose of the NumPy Array The ndarray.transpose() function returns a view of the array with axes transposed. For a 1-D array, this has no effect, as a transposed vector is simply the same vector.For a 2-D array, this is a standard matrix transpose.For an n-D array, if axes are given, their order indicates how the axes are pe 2 min read numpy.ndarray.view() in Python numpy.ndarray.view() helps to get a new view of array with the same data. Syntax: ndarray.view(dtype=None, type=None)Parameters: 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. type : Python type, opti 3 min read NumPy Copy and View of Array While working with NumPy, you may notice that some operations return a copy, while others return a view. A copy creates a new, independent array with its own memory, while a view shares the same memory as the original array. As a result, changes made to a view also affect the original and vice versa 4 min read Numpy MaskedArray.transpose() function | Python numpy.MaskedArray.transpose() function is used to permute the dimensions of an masked array. Syntax : numpy.ma.transpose(axis) Parameters: axis :[list of ints, optional] By default, reverse the dimensions, otherwise permute the axes according to the values given. Return : [ ndarray] Resultant array 2 min read Python | Numpy matrix.transpose() With the help of Numpy matrix.transpose() method, we can find the transpose of the matrix by using the matrix.transpose()method in Python. Numpy matrix.transpose() Syntax Syntax : matrix.transpose() Parameter: No parameters; transposes the matrix it is called on. Return : Return transposed matrix Wh 3 min read Python | Numpy numpy.transpose() With the help of Numpy numpy.transpose(), We can perform the simple function of transpose within one line by using numpy.transpose() method of Numpy. It can transpose the 2-D arrays on the other hand it has no effect on 1-D arrays. This method transpose the 2-D numpy array. Parameters: axes : [None, 2 min read Like