numpy.reshape# numpy. reshape (a, /, shape = None, order = 'C', *, newshape = None, copy = None) [source] # Gives a new shape to an array without changing its data. Parameters: a …

ndarray. reshape (shape, /, *, order = 'C', copy = None) # Returns an array containing the same data with a new shape. Refer to numpy.reshape for full documentation.

numpy.reshape# numpy. reshape (a, /, shape = None, order = 'C', *, newshape = None, copy = None) [source] # Gives a new shape to an array without changing its data. Parameters: a …

Jun 22, 2021 · numpy.reshape¶ numpy. reshape (a, newshape, order = 'C') [source] ¶ Gives a new shape to an array without changing its data. Parameters a array_like. Array to be …

Return a new array with the specified shape. If the new array is larger than the original array, then the new array is filled with repeated copies of a . Note that this behavior is different from …

reshape (a, /[, shape, order, newshape, copy]) Gives a new shape to an array without changing its data. ravel (a[, order]) Return a contiguous flattened array. ndarray.flat. A 1-D iterator over the …

You can use reshape() to reshape your array. For example, you can reshape this array to an array with three rows and two columns: >>>

The shape property is usually used to get the current shape of an array, but may also be used to reshape the array in-place by assigning a tuple of array dimensions to it. As with …

Returns an array with axes transposed. For a 1-D array, this returns an unchanged view of the original array, as a transposed vector is simply the same vector. To convert a 1-D array into a …

Return an array formed from the elements of a at the given indices. ndarray.put (indices, values[, mode]) Set a.flat[n] = values[n] for all n in indices. ndarray.repeat (repeats[, axis]) Repeat …