Prerequisites: Numpy
Two arrays in python can be appended in multiple ways and all possible ones are discussed below.
Method 1: Using append() method
This method is used to Append values to the end of an array.
Syntax :
numpy.append(array, values, axis = None)
Parameters :
- array: [array_like]Input array.
- values : [array_like]values to be added in the arr. Values should be
shaped so that arr[…,obj,…] = values. If the axis is defined values can be of any
shape as it will be flattened before use.- axis : Axis along which we want to insert the values. By default, array is flattened.
Return :
A copy of array with values being appended at the end as per the mentioned object, along a given axis.
Example:
Python3
import numpy array1 = numpy.array([1, 2, 3, 4, 5])array2 = numpy.array([6, 7, 8, 9, 10]) # Appending both arrays using Append methodarray1 = numpy.append(array1, array2)print(array1) |
Output:
[ 1 2 3 4 5 6 7 8 9 10]
Method 2: Using concatenate() method
Concatenate method Joins a sequence of arrays along an existing axis.
Syntax :
numpy.concatenate((arr1, arr2, …), axis=0, out=None)
Parameters :
- arr1, arr2, … : [sequence of array_like] The arrays must have the same shape, except in the dimension corresponding to axis.
- axis : [int, optional] The axis along which the arrays will be joined. If axis is None, arrays are flattened before use. Default is 0.
- out : [ndarray, optional] If provided, the destination to place the result. The shape must be correct, matching that of what concatenate would have returned if no out argument were specified.
Return : [ndarray] The concatenated array.
Example:
Python3
import numpy array1 = numpy.array([1, 2, 3, 4, 5])array2 = numpy.array([6, 7, 8, 9, 10]) # Appending both Arrays using concatenate() method.array1 = numpy.concatenate([array1, array2])print(array1) |
Output:
[ 1 2 3 4 5 6 7 8 9 10]
Method 3: Using stack() method
Stack method Joins a sequence of arrays along a new axis.
Syntax : numpy.stack(arrays, axis)
Parameters :
- arrays : [array_like] Sequence of arrays of the same shape.
- axis : [int] Axis in the resultant array along which the input arrays are stacked.
Return : [stacked ndarray] The stacked array of the input arrays which has one more dimension than the input arrays.
Example:
Python3
import numpy array1 = numpy.array([1, 2, 3, 4, 5])array2 = numpy.array([6, 7, 8, 9, 10]) # Join a sequence of arrays along a new axis.array1 = numpy.stack([array1, array2])print(array1) |
Output:
[[ 1 2 3 4 5]
[ 6 7 8 9 10]]
Method 4: Using hstack() method
hstack method Stacks arrays in sequence horizontally (column wise).
Syntax : numpy.hstack(tup)
Parameters :
- tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the second axis.
Return : [stacked ndarray] The stacked array of the input arrays.
Example:
Python3
import numpy array1 = numpy.array([1, 2, 3, 4, 5])array2 = numpy.array([6, 7, 8, 9, 10]) # Stack arrays in sequence horizontally (column wise).array1 = numpy.hstack([array1, array2])print(array1) |
Output:
[ 1 2 3 4 5 6 7 8 9 10]
Method 5: Using vstack() method
vstack method Stacks arrays in sequence vertically (row wise).
Syntax : numpy.vstack(tup)
Parameters :
- tup : [sequence of ndarrays] Tuple containing arrays to be stacked. The arrays must have the same shape along all but the first axis.
Return : [stacked ndarray] The stacked array of the input arrays.
Example:
Python3
import numpy array1 = numpy.array([1, 2, 3, 4, 5])array2 = numpy.array([6, 7, 8, 9, 10]) # Stack arrays in sequence vertically (row wise).array1 = numpy.vstack([array1, array2])print(array1) |
Output:
[[ 1 2 3 4 5]
[ 6 7 8 9 10]]
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