How To Add Numpy Arrays ?
Table Of Contents:
- ‘+’ Operator
- np.concatenate()
(1) ‘+’ Operator
- The ‘+’ operator will ‘sum’ the elements of numpy array.
Example-1
a = np.array([1,2,3,4,5])
b = np.array([6,7,8,9,10])
a + bOutput:
array([ 7, 9, 11, 13, 15])Example-2
a = np.array([1,2,3,4,5])
b = np.array([6,7,8,9,10])
c = np.array([11,12,13,14,15])
a + b + cOutput:
array([18, 21, 24, 27, 30])(2) np.concatenate()
- Join a sequence of arrays along an existing axis.
Syntax:
numpy.concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind")Parameters:
- a1, a2, …sequence of array_like – The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).
- 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.
- dtype: str or type – If provided, the destination array will have this dtype. Cannot be provided together with out.
- casting – {‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional – Controls what kind of data casting may occur. Defaults to ‘same_kind’.
Returns:
- res: ndarray – The concatenated array.
Example-1
a = np.array([1,2,3,4,5])
b = np.array([6,7,8,9,10])
np.concatenate((a,b))Output:
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])Example-2
x = np.array([[1, 2], [3, 4]])
y = np.array([[5, 6]])
np.concatenate((x, y), axis=0)Output:
array([[1, 2],
[3, 4],
[5, 6]])