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NumPy - Array Manipulation

The NumPy has a number of built-in functions which can be used for manipulation of elements in ndarray object. Below is the list of most commonly used functions for array manipulation:

Changing array shape

ndarray.flat A 1-D iterator over the array.
reshape() Gives a new shape to an array without changing its data.
ravel() Returns a contiguous flattened array.
ndarray.flatten() Return a copy of the array collapsed into one dimension.

Transpose like operations

ndarray.T Returns the transposed array.
rollaxis() Roll the specified axis backwards, until it lies in a given position.
swapaxes() Interchange two axes of an array.
transpose() Reverses or permutes the axes of an array.

Joining Arrays

concatenate() Returns a concatenated array along the specified axis.
stack() Join a sequence of arrays along a new axis.
hstack() Stack arrays in sequence horizontally (column wise).
vstack() Stack arrays in sequence vertically (row wise).

Splitting Arrays

split() Split an array into multiple sub-arrays.
hsplit() Split an array into multiple sub-arrays horizontally (column-wise).
vsplit() Split an array into multiple sub-arrays vertically (row-wise).

Changing dimensions

broadcast() Produce an object that mimics broadcasting.
broadcast_to() Broadcast an array to a new shape.
expand_dims() Expand the shape of an array.
squeeze() Remove axes of length one from an array.

Adding and removing elements

append() Appends values to the end of an array.
resize() Return a new array with the specified shape.
insert() Insert values along the given axis before the given indices.
delete() Return a new array with sub-arrays along an axis deleted.
unique() Find the unique elements of an array.