numpy.stack() function is used to join a sequence of same dimension arrays along a new axis.The axis parameter specifies the index of the new axis in the dimensions of the result. Numpy arrays have to be rectangular, so what you are trying to get is not possible with a numpy array. You need a different data structure. Which o... Following the import, we initialized, declared, and stored two numpy arrays in variable ‘x and y’. Get NumPy Array Length axis – specifies along which axis we connect the input arrays. array (array_object): Creates an array of the given shape from the list or tuple. For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension. Examples of NumPy concatenate arrays. Usage. #. numpy arrays This section will present several examples of using NumPy array manipulation to access data and subarrays, and to split, reshape, and join the arrays. Improve this answer. ; I have taken two arrays as Even_array and Odd_array, to pass the elements of the array np.array is used. Basics of NumPy Arrays. ): ''' Fits arrays into a single numpy array, even if they are different sizes. The shape of an array is the number of elements in each dimension. Using numpy hstack() to horizontally stack arrays arr = np.array ( [1, 2, 3, 4]) Stack arrays in sequence vertically (row wise). For example, if axis=0 it will be the first dimension and if axis=-1 it will be the last dimension. numpy. New in version 1.10.0. I am going to send a C++ array to a Python function as NumPy array and get back another NumPy array.