Learning Numpy - Simple Tutorial For Beginners - NumPy - Array Manipulation Part 12

Several routines are available in NumPy package for manipulation of elements in ndarray object. They can be classified into the following types −

Changing Shape

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

Transpose Operations

Parameter	Description
transpose	Permutes the dimensions of an array
ndarray.T	Same as self.transpose()
rollaxis	Rolls the specified axis backwards
swapaxes	Interchanges the two axes of an array

Changing Dimensions

Parameter	Description
broadcast	Produces an object that mimics broadcasting
broadcast_to	Broadcasts an array to a new shape
expand_dims	Expands the shape of an array
squeeze	Removes single-dimensional entries from the shape of an array

Joining Arrays

Parameter	Description
concatenate	Joins a sequence of arrays along an existing axis
stack	Joins a sequence of arrays along a new axis
hstack	Stacks arrays in sequence horizontally (column wise)
vstack	Stacks arrays in sequence vertically (row wise)

Splitting Arrays

Parameter	Description
concatenate	Joins a sequence of arrays along an existing axis
stack	Joins a sequence of arrays along a new axis
hstack	Stacks arrays in sequence horizontally (column wise)
vstack	Stacks arrays in sequence vertically (row wise)

Adding / Removing Elements

Parameter	Description
resize	Returns a new array with the specified shape
append	Appends the values to the end of an array
insert	Inserts the values along the given axis before the given indices
delete	Returns a new array with sub-arrays along an axis deleted
unique	Finds the unique elements of an array

References

• Learning Numpy - Array From Existing Data Part 6
• Learning Numpy - Array Creation Routines Part 5
• Learning Numpy - Array Attributes Part 4
• Learning Numpy - Data Types Part 3