Find the mode of a TradingView Pine Script array

Find the mode of a TradingView Pine Script array

TL;DR
Count the most common element in a numeric array with array.mode() so you can summarise signals, votes, or histogram data.

At a Glance

Difficulty	Beginner
Time to implement	5-10 min
Category	Arrays

Quick Actions

• Open in AI Editor
• Browse PineScript Examples
• Connect to Live Trading

Quick Start

//@version=5
indicator("Array mode demo", overlay=false)

arr = array.new_int()
array.push(arr, 3)
array.push(arr, 3)
array.push(arr, 1)
array.push(arr, 5)

modeValue = array.mode(arr)
plot(modeValue, "Mode", color=color.orange)

Note. If multiple values share the highest frequency, `array.mode()` returns `na`. Handle that case before using the result.

Why It Matters

The mode highlights which value appears most often in a dataset—helpful for majority voting systems, indicator histograms, or cluster detection. Pine Script’s array helpers make it straightforward to calculate the mode without writing your own frequency map.

What You’ll Learn

• Creating and populating arrays
• Retrieving a mode using array.mode()
• Handling ties and empty arrays safely
• Applying the mode in practical indicator logic

Quick Reference

Call	Purpose
array.new_int() / array.new_float()	Creates a numeric array that supports array.mode().
array.push(id, value)	Adds elements to the end of the array.
array.unshift(id, value)	Adds elements to the front (useful for weighting early values).
array.mode(id)	Returns the most frequent element or na on ties/empty arrays.
array.size(id)	Lets you guard against empty arrays before calling mode().

Implementation Blueprint

1. Create an array and add values
   The array must be integer or float based—mode isn’t supported for other types.

   arr = array.new_int()
   array.push(arr, 4)
   array.push(arr, 2)
   array.push(arr, 4)

2. Guard against empty arrays
   array.mode() returns na when the array is empty. Check size first.

   modeVal = array.size(arr) > 0 ? array.mode(arr) : na

3. React to ties
   When two or more values share the top frequency, the mode is na. Use alternative logic (e.g., lowest value wins) if needed.

   modeVal := na(modeVal) ? math.min(array.max(arr), array.min(arr)) : modeVal

Example Playbook

//@version=5
indicator("Majority vote mode", overlay=false)

votes = array.new_int()

if barstate.isnew
    // Simulated votes from different signals
    array.clear(votes)
    array.push(votes, close > open ? 1 : 0)
    array.push(votes, ta.rsi(close, 14) > 70 ? 1 : 0)
    array.push(votes, ta.crossover(ta.ema(close, 10), ta.ema(close, 30)) ? 1 : 0)

modeVote = array.size(votes) > 0 ? array.mode(votes) : na

plot(modeVote, "Mode vote", color=color.new(color.green, 0), style=plot.style_columns)
bgcolor(modeVote == 1 ? color.new(color.green, 85) : na)

Why this works.

• Votes are binary (0 or 1), so ties resolve cleanly—`na` means a split.
• Clearing and reusing the array prevents size creep and stale values.
• The background tint highlights when the majority vote is bullish.

Pro Tips & Pitfalls

• array.mode() can be expensive on very large arrays. Clear or reuse arrays thoughtfully.
• For tie-breaking, consider counting frequencies manually or sorting the array.
• Use array.new_float() when working with decimal-based modes (e.g., price clusters).
• Remember to array.clear() before repopulating arrays each bar to avoid accumulating historical values unless intentional.

Troubleshooting & FAQ

Why do I keep getting na?

Likely either the array is empty or there is a tie for the highest frequency. Inspect array contents (e.g., via array.get()) before calling array.mode().

Can I get all modes when there are ties?

array.mode() returns only one value or na. For multi-mode detection, loop through the array and build your own frequency map.

Key Takeaways

• array.mode() offers a quick way to find the most common array element.
• Always guard against empty arrays and handle ties gracefully.
• Combine the mode with chart visuals or trading logic to summarise majority signals.
• Clear arrays when sampling new data to keep memory use predictable.

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Keep Going

• Open AI Editor to apply the pattern with guided assistance
• Browse PineScript Examples for ready-to-run templates
• Connect to Live Trading when you are ready to automate

Adapted from tradingcode.net, optimised for Algo Trade Analytics users.