can you write a programming tutorial blog on array.median function in pine script? The blog should properly use h2 and h3 headings. Include every thing that you think is needed Also, include 2 unique different use case examples and explain each line of code in the example. The article should be close to 1000 words start straight away with the topic at hand please. Please add key take away before conclusion.

**Introduction to Array.Median Function**

The ** array.median** function is used to find the median value of the elements in an array. It’s particularly useful for removing noise and outliers from data, as the median is less sensitive to extreme values than the mean.

**Syntax**

array.median(a)

Where ** a** is the input array.

**Return value**: The median value of the elements in the input array.

**Implementing Array.Median**

Now that we have a basic understanding of arrays in Pine Script, let’s implement the ** array.median** function.

//@version=5 indicator('Array Median Example', shorttitle='AME', overlay=true) length = input.int(14, minval=1, title='Length') src = close arraySrc = array.new_float(0) for i = 0 to length - 1 by 1 array.push(arraySrc, src[i]) medianValue = array.median(arraySrc) plot(medianValue, color=color.new(color.red, 0), linewidth=2, title='Median') label newLable = na if barstate.islast newLable := label.new(x=bar_index, y=medianValue, style=label.style_label_left, color=#E6E6FA, textcolor=color.black, size=size.large, text="Array Median = " + str.tostring(medianValue)) label.delete(newLable[1])

In this example, we’re creating a simple script that plots the median value of the last ** length** close prices. Let’s go through the code step by step:

- We define the
input variable, which represents the number of past close prices to consider.`length`

- We set the
variable to`src`

, which means we’ll be using the close prices as our data source.`close`

- We create an empty array called
of type`arraySrc`

.`float`

- We use a
loop to iterate through the past close prices and add each price to the`for`

array.`arraySrc`

- We calculate the median value of the elements in the
array using the`arraySrc`

function.`array.median`

- Finally, we plot the median value using the
function.`plot`

**Use Case 1: Median-Based Moving Average**

In this use case, we’ll create a median-based moving average indicator using the ** array.median** function. The median-based moving average smooths the price data while being less sensitive to extreme values, providing a more robust representation of the trend.

//@version=5 indicator('Median-Based Moving Average', shorttitle='MBMA', overlay=true) length = input.int(14, minval=1, title='Length') src = close arraySrc = array.new_float(0) for i = 0 to length - 1 by 1 array.push(arraySrc, src[i]) medianValue = array.median(arraySrc) mbma = ta.sma(medianValue, length) plot(mbma, color=color.new(color.blue, 0), linewidth=2, title='MBMA') label newLable = na if barstate.islast newLable := label.new(x=bar_index, y=mbma, style=label.style_label_left, color=#E6E6FA, textcolor=color.black, size=size.large, text='Median-Based Moving Average = ' + str.tostring(mbma)) newLable label.delete(newLable[1])

In this example, we modify the previous script to calculate the simple moving average (SMA) of the median value:

- We calculate the median value of the elements in the
array using the`arraySrc`

function, just like before.`array.median`

- We calculate the simple moving average (SMA) of the median value using the
function.`sma`

- Finally, we plot the median-based moving average using the
function.`plot`

**Key Takeaways**

- The
function in Pine Script is useful for finding the median value of elements in an array, which can help reduce the impact of extreme values in data.`array.median`

- Arrays in Pine Script can be created using the
function and manipulated using functions such as`array.new`

.`array.push`

- The
function can be used in a variety of applications, such as creating median-based moving averages and price channels.`array.median`

**Conclusion**

In this tutorial, we explored the ** array.median** function in Pine Script and demonstrated its implementation in two unique use cases. Understanding the

**function and its potential applications can help you create more robust and reliable indicators and strategies in your trading toolbox.**

`array.median`