In Python ,Numpy creates an array which is called as ndarray. It is table of elements. It is the n-dimensional array.It is used in python because it is faster than list. It describes the collection of items of the same type.
Create Ndarray:
In numpy, we can create array by using array() function.
Syntax:
numpy.array()0-D Array:
Example:
import numpy
a = numpy.array(89)
print(a)Output: 89
1-D Array:
Example:
import numpy
a = numpy.array(["a","b","c"])
print(a)Output: ['a' 'b' 'c']
2-D Array:
Example:
import numpy
a = numpy.array([[1,2,3],[4,5,6]])
print(a)Output:
[[1 2 3] [4 5 6]]
3-D Array:
Example:
import numpy
a = numpy.array([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]])
print(a)Output:
[[[ 1 2 3] [ 4 5 6]] [[ 7 8 9] [10 11 12]]]
Access Elements in Ndarray:
Each element of an array is having the same size in the memory. Elements in Numpy arrays are accessed by using square brackets and it can be accessed using a zero-based index.The elements of an ndarray can be accessed using by indexing or slicing the array.
Example:
import numpy
a = numpy.array([1, 2, 3])
print(a[0])
print(a[1])
print(a[2])Output:
1 2 3