Mode Calculator

Step-by-Step Guide

1. 1Enter Your Dataset: Type or paste values separated by commas, spaces, or new lines — or click a sample dataset to try it instantly.
2. 2Choose a Separator (Optional): Leave on Auto Detect, or force Comma, Space, New Line, or Tab if your data needs a specific split.
3. 3Choose a Value Type (Optional): Leave on Auto Detect, or force Numbers or Text if your dataset mixes formats in a way you want handled a specific way.
4. 4Review the Mode and Frequency: Check the Mode (or Modes), Frequency, Number of Modes, Total Values, and Unique Values — all updating instantly with a 150ms debounce.
5. 5Explore the Frequency Chart and Table: See a bar chart and sortable table of every value's frequency, with the mode highlighted.
6. 6Copy, Export, or Share: Copy the full report, download it as CSV, JSON, or TXT, print it, or copy a shareable URL with your dataset encoded.

Key Features

• ✓Supports both numbers and text values
• ✓Automatic separator detection (comma, space, new line, tab, mixed)
• ✓Automatic number/text type detection
• ✓Multiple mode (multimodal) detection
• ✓No-mode detection when all values occur equally
• ✓Efficient single-pass frequency counting using JavaScript Map
• ✓Interactive frequency bar chart with the mode highlighted
• ✓Sortable frequency table (original, ascending, descending)
• ✓Handles datasets with 100,000+ values without freezing
• ✓Random dataset generator for quick testing
• ✓Shareable calculation URL using query parameters
• ✓Export report as CSV, JSON, or TXT
• ✓Print-ready formatted report
• ✓Copy full report to clipboard in one click
• ✓Calculation history — save and reload up to 20 past datasets
• ✓No signup required, 100% free, and fully private

Pro Tips

• 💡Use the frequency table alongside the mode — the mode alone doesn't tell you how much more common it is than the next most frequent value.
• 💡Check the Number of Modes card before assuming a dataset has a single, clear mode — multimodal datasets are common in real survey and categorical data.
• 💡Force Text mode explicitly if your numeric-looking values should be treated as labels (like zip codes or IDs) rather than numbers.
• 💡Use sorting by frequency-adjacent value order (ascending/descending) when you want to scan the frequency table for patterns rather than just seeing input order.
• 💡For text data, remember matching is case-sensitive — "Red" and "red" are counted as different values, so normalize case before pasting if that's not the intended behavior.

Common Mistakes to Avoid

• ✕Don't assume every dataset has exactly one mode — some have several tied values (multimodal) and some have none at all.
• ✕Don't confuse mode with mean or median — mode identifies the most common value, not a central or average one, and can be very different from either.
• ✕Don't ignore the "No Mode" result as an error — it's a valid and meaningful statistical outcome when every value occurs equally.
• ✕Don't mix numeric and non-numeric tokens and expect Auto Detect to treat them as numbers — a single non-numeric token switches the whole dataset to text mode under auto-detection.
• ✕Don't rely on mode alone to summarize a large, mostly-unique dataset — with many unique values, no single mode may be particularly meaningful, and a frequency distribution view is more informative.