Chapter: Python Numpy Last Updated: 09-07-2021 09:59:00 UTC

Program:

` ````
/* ............... START ............... */
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr)
print(type(arr))
/* Output
[1 2 3 4 5]
<class 'numpy.ndarray'>
*/
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr)
/ * Output
[[1 2 3]
[4 5 6]]
*/
import numpy as np
one = np.array(45)
two = np.array([1, 2, 6, 4, 5])
three = np.array([[1, 2, 3], [4, 5, 6]])
four = np.array([[[1, 2, 3], [4, 6, 6]], [[1, 9, 3], [6, 8, 6]]])
print(one.ndim)
print(two.ndim)
print(three.ndim)
print(four.ndim)
/*Output
0
1
2
3
*/
/* ............... END ............... */
```

Notes:

- Numpy is the python library used to create array. We can create a NumPy ndarray object by using the array() function.
- type() is function in python used to give the type of object. In the above program you can see that array is ndarray.
- By using numpy you can also create a two diamentional array also. These are often used to represent matrix or 2nd order tensors.
- ndim attribute in Numpy is used to know the dimensions of the array.

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