# Get the Median of Numpy Array – (With Examples)

The Numpy library in Python comes with a number of useful built-in functions for computing common descriptive statistics like mean, median, standard deviation, etc. In this tutorial, we will look at how to get the median value in a Numpy array with the help of some examples.

## How do you get the median of an array in Numpy?

You can use the Numpy `median()` function to get the median value of a Numpy array. Pass the array as an argument.

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The following is the syntax –

```# median of all values in array
numpy.median(ar)```

It returns the median of the values in the array. For multi-dimensional arrays, you can specify the axis along which you want to compute the median (see the examples below).

## Examples

Let’s now look at some examples of using the above syntax on single and multi-dimensional arrays.

### Example 1 – Median of a one-dimensional Numpy array

Let’s first create a one-dimensional Numpy array.

```import numpy as np

# create numpy array
ar = np.array([1, 3, 4, 5, 7])
# display the array
print(ar)```

Output:

`[1 3 4 5 7]`

Here, we used the `numpy.array()` function to create a one-dimensional array containing some numeric values.

Let’s now get the median value in the above array.

```# median of array
print(np.median(ar))```

Output:

`4.0`

We get the median as 4.0 since 4 is the middle value in the above array. Note that the array need not be sorted for using the `numpy.median()` function. The function will do that internally when estimating the middle value.

### Example 2 – Median of multi-dimensional Numpy array

First, let’s create a 2-D Numpy array.

```# create 2-D numpy array
ar = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
# display the array
print(ar)```

Output:

```[[1 2 3]
[4 5 6]
[7 8 9]]```

Here, we used the `numpy.array()` function to create an array with three rows and three columns.

If you use the Numpy `median()` function on an array without specifying the axis, it will return the median taking into consideration all the values inside the array.

```# median of array
print(np.median(ar))```

Output:

`5.0`

We get the median of all the values inside the 2-D array as 5.0 (which is the middle value if you line up all the values in the above 2-D array in sorted order).

Use the `numpy.median()` function with `axis=1` to get the median value for each row in the array.

```# median of each row in array
print(np.median(ar, axis=1))```

Output:

`[2. 5. 8.]`

We get the median of each row in the above 2-D array. The median of values – in the first row (1, 2, 3) is 2, in the second row (4, 5, 6) is 5, and in the third row (7, 8, 9) is 8.

Use the `numpy.median()` function with `axis=0` to get the median of each column in the array.

```# median of each column in array
print(np.median(ar, axis=0))```

Output:

`[4. 5. 6.]`

We get the median of each column in the above 2-D array. The median of values – in the first column (1, 4, 7) is 4, in the second column (2, 5, 8) is 5, and in the third column (3, 6, 9) is 6.

## Summary

In this tutorial, we looked at how to use the `numpy.median()` function to get the median of values in an array. The following are the key takeaways from this tutorial.

• Use the `numpy.median()` function without any arguments to get the median of all the values inside the array.
• For multi-dimensional arrays, use the `axis` parameter to specify the axis along which to compute the median. For example, for a 2-D array –
• Pass `axis=1` to get the median of each row.
• Pass `axis=0` to get the median of each column.

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