# How to Slice a 2D NumPy Array (With Examples)

You can use the following methods to slice a 2D NumPy array:

Method 1: Select Specific Rows in 2D NumPy Array

```#select rows in index positions 2 through 5
arr[2:5, :]
```

Method 2: Select Specific Columns in 2D NumPy Array

```#select columns in index positions 1 through 3
arr[:, 1:3]```

Method 3: Select Specific Rows & Columns in 2D NumPy Array

```#select rows in range 2:5 and columns in range 1:3
arr[2:5, 1:3]```

The following examples show how to use each method in practice with the following 2D NumPy array:

```import numpy as np

#create NumPy array
arr = np.arange(24).reshape(6,4)

#view NumPy array
print(arr)

[[ 0  1  2  3]
[ 4  5  6  7]
[ 8  9 10 11]
[12 13 14 15]
[16 17 18 19]
[20 21 22 23]]
```

## Example 1: Select Specific Rows of 2D NumPy Array

We can use the following syntax to select the rows in index positions 2 through 5:

```#select rows in index positions 2 through 5
arr[2:5, :]

array([[ 8,  9, 10, 11],
[12, 13, 14, 15],
[16, 17, 18, 19]])
```

Note that the syntax 2:5 tells NumPy to select rows 2 up to 5, but doesn’t include 5.

Thus, this syntax selects all of the values in the rows with index positions of 2, 3 and 4.

## Example 2: Select Specific Columns of 2D NumPy Array

We can use the following syntax to select the columns in index positions 1 through 3:

```#select columns in index positions 1 through 3
arr[, 1:3]

array([[ 1,  2],
[ 5,  6],
[ 9, 10],
[13, 14],
[17, 18],
[21, 22]]))
```

Note that the syntax 1:3 tells NumPy to select columns 1 up to 3, but doesn’t include 3.

Thus, this syntax selects all of the values in the columns with index positions of 1 and 2.

## Example 3: Select Specific Rows & Columns of 2D NumPy Array

We can use the following syntax to select the rows in index positions 2 through 5 and the columns in index positions 1 through 3:

```#select rows in 2:5 and columns in 1:3
arr[2:5, 1:3]

array([[ 9, 10],
[13, 14],
[17, 18]])
```

This syntax returns all of the values in the 2D NumPy array between row index positions 2 through 5 and column index positions 1 through 3.