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Understanding the array.sum() Function in Pine Script

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This article dives deep into its syntax, overloads, and practical applications of array.sum().

Syntax and Overloads

The array.sum() function in Pine Script is designed to calculate the sum of elements within an array. It supports two primary data types: int (integer) and float (floating point numbers). Depending on the array’s data type, the function can return a sum in the form of a series float or a series int. Here’s a look at the syntax:

  • array.sum(id) → series float
  • array.sum(id) → series int


  • id (array<int/float>): Represents the array object whose elements are to be summed up.


To elucidate the functionality of array.sum(), let’s consider a practical example:

indicator("Sum Array Example")
sumArray = array.new_float(0)
for index = 0 to 9
    array.push(sumArray, close[index])


  • sumArray = array.new_float(0): Initializes an empty floating-point array.
  • for index = 0 to 9: Iterates through the last 10 bars.
  • array.push(sumArray, close[index]): Adds the closing price of each bar to sumArray.
  • plot(array.sum(sumArray)): Computes and plots the sum of the elements in sumArray.

Key Features and Takeaways

  • Function Useability: The array.sum() function simplifies the process of aggregating values in an array, making it invaluable for summarizing data points within a given dataset.
  • Syntax and Application: With support for int and float arrays, it caters to a wide range of numerical data types, ensuring flexibility in its application.
  • Practical Example: Through the example provided, it’s clear how array.sum() can be leveraged to sum up a series of closing prices, demonstrating its practicality in financial data analysis.

In conclusion, the array.sum() function in Pine Script is a powerful tool for data aggregation. Its ability to handle both integers and floating-point numbers makes it versatile, and when applied as shown in the example, it can significantly aid in the analysis and visualization of financial data.

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