Contents

## Get a Row from Numpy Array

To get specific row of elements, access the numpy array with all the specific index values for other dimensions and `:`

for the row of elements you would like to get. It is special case of array slicing in Python.

For example, consider that we have a 3D numpy array of shape (m, n, p). And we would like to get the row of elements at i^{th} element along axis=0, and k^{th} element along axis=2. Use the following syntax to get this desired row of elements.

`row = ndarray[i, :, k]`

Run ### Example 1: Access a specific row of elements

In the following example, we will initialize a 3D array and access a specific row of elements present at index=0 along axis=0, and index=1 along axis=2.

**Python Program**

```
import numpy as np
#initialize an array
arr = np.array([[[11, 11, 9, 9],
[11, 0, 2, 0]],
[[10, 14, 9, 14],
[0, 1, 11, 11]]])
# print shape of array
print('Array Shape: ',arr.shape)
# get the desired row
row = arr[0, :, 1]
print('Desired Row of Elements: ', row)
```

Run **Output**

```
Array Shape: (2, 2, 4)
Desired Row of Elements: [11 0]
```

### Example 2: Access a Specific Row or Column in 2D Numpy Array

In the following example, we will initialize a 2D array and access a row and column using array slicing.

**Python Program**

```
import numpy as np
#initialize an array
arr = np.array([[11, 11, 9, 9],
[11, 0, 2, 0]])
print('Array\n',arr)
# get index=1 along axis=0 - this means a row in 2D
row = arr[1, :]
print('arr[1, :] : ', row)
# get index=2 along axis=1 - this means a column in 2D
row = arr[:, 2]
print('arr[:, 2] : ', row)
```

Run **Output**

```
Array
[[11 11 9 9]
[11 0 2 0]]
arr[1, :] : [11 0 2 0]
arr[:, 2] : [9 2]
```

### Summary

In this Numpy Tutorial of Python Examples, we learned how to access a row from a Numpy 2D and 3D arrays, with the help of well detailed example programs.