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# dim_median

Computes the median of a variable's rightmost dimension at all other dimensions.

## Prototype

```	function dim_median (
x  : numeric
)

return_val  :  float or double
```

## Arguments

x

A variable of numeric type and any dimensionality.

## Return value

The output will be double if x is double, and float otherwise.

The output dimensionality is the same as the first n-2 dimensions of the input variable. That is, the dimension rank of the input variable will be reduced by one.

## Description

The dim_median function determines the median of all elements of the n-1th (rightmost) dimension for each index of the dimensions 0...n-2. Missing values are ignored.

The median is a robust estimate of the mean.

Use dim_median_n if you want to specify which dimension(s) to do the median across.

## Examples

Example 1

Let x be a 1-dimensional array, then:

```   xMed = dim_median(x)   ; xMed is a scalar
```
Example 2

Create a variable (q) of size (3,5,10) array. Then calculate the median of the rightmost dimension.

```    q    = random_uniform(-20,100,(/3,5,10/))
qMed = dim_median(q)   ;==>  qMed(3,5)
```
Example 3

Let x be of size (ntim,nlat,mlon) and with named dimensions "time", "lat" and "lon", respectively. Then, for each time and latitude, the median longitude value may be obtained via:

```    xMedLon = dim_median( x )    ; ==> xMedLon(ntim,nlat)
```
Example 4

Let x be defined as in Example 3: x(time,lat,lon). Determine the median value over all time at each latitude/longitude grid point. Use NCL's named subscripting to reorder the input array such that "time" is the rightmost dimension.

Note: in V5.1.1, you will be able to use dim_median_n to avoid having to reorder your data.

```    xMedTime = dim_median( x(lat|:, lon|:, time|:) )    ; ==> xMedTime(nlat,nlon)

xMedTime = dim_median_n( x, 0 )                     ; no reordering needed
```