search
Search
Unlock 100+ guides
search toc
close
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
What does this mean?
Why is this true?
Give me some examples!
search
keyboard_voice
close
Searching Tips
Search for a recipe:
"Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
Doc Search
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Shrink
Navigate to

# NumPy | median method

schedule Aug 12, 2023
Last updated
local_offer
PythonNumPy
Tags
mode_heat
Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!

Numpy's `median(~)` method computes the median along the specified axis.

# Parameters

1. `a` | `array-like`

The input array.

2. `axis` | `int` or `sequence` of `int` | `optional`

The axis along which to compute the median. For 2D arrays, the allowed values are as follows:

Axis

Meaning

0

Row-wise computation of median

1

Column-wise computation of median

None

All values used to compute the median

By default, `axis=None`.

3. `out` | `Numpy array` | `optional`

Instead of creating a new array, you can place the computed median into the array specified by `out`.

4. `overwrite_input` | `boolean` | `optional`

Whether to mutate the content of the input array during the computation of the median. This would save memory space, but will render the input array unusable. By default, `overwrite_input=False`.

# Return value

If axis is unset, then a scalar is returned. Otherwise, a Numpy array is returned.

# Examples

## Computing median of 1D array

``` np.median([4,2,3]) 3.0 ```

## Computing median of 2D array

Consider the following 2D array:

``` a = np.array([[1,2],[3,4]])a array([[1, 2], [3, 4]]) ```

### Median of all values

``` np.median(a) 2.5 ```

### Median of each column

``` np.median(a, axis=0) array([2., 3.]) ```

### Median of each row

``` np.median(a, axis=1) array([1.5, 3.5]) ```
Edited by 0 others
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!