Calculate Integer Entropy

The Calculate Integer Entropy tool analyzes the digits in your input and calculates entropy a measure of how unpredictable or varied the digits are. Based on Shannon entropy, it tells you how uniformly digits are distributed, using either binary (log₂), decimal (log₁₀), or natural log (ln).

You can paste or import a block of integer data, and the tool will count how often each digit (0–9) appears. It then computes the entropy and lists digit frequencies and percentages. Whether you’re evaluating randomness, testing output uniformity, or analyzing patterns in data, this tool delivers fast, detailed insights.

It works completely in your browser, with live updates and no uploads.

Paste your input above or import a file below.
No file chosen
Supported file types: .txt, .csv, .tsv, .log, .json, .xml, .md, .ini, .yaml, .yml, .html, .htm, .css
Total digits: 0
Options

Ignore non-digits
Maximize output

How to Use:

  • Paste or type any number of integers into the Integer Input box
  • Use Choose File to import text-based files like .txt, .csv, or .log
  • Toggle Ignore non-digits to remove non-digit characters from the calculation
  • Choose a Log base:
    • log₂ = bits (default)
    • log₁₀ = base 10
    • ln = natural log
  • Enable Maximize output to expand the result area
  • Click Calculate or simply type to update the entropy result instantly
  • Use Copy Output or Export to File to save your results
  • Hit Clear All to reset everything

What Calculate Integer Entropy can do:

This tool helps you quickly assess the uniformity and variability of digit usage in any dataset. You’ll see how concentrated or evenly spread the digits are. The more uniform the digits, the higher the entropy. Useful for randomness checks, number theory, or quality testing.

Example:

Input:

1234567890
111222333

Output:

Entropy: 2.84644
Digits analyzed: 20
Frequencies:
1: 4 (20%)
2: 4 (20%)
...

Common Use Cases:

Use it for checking pseudorandom output, entropy in generated IDs, numeric password quality, or character distribution in scientific data. Great for developers, statisticians, and educators.

Useful Tools & Suggestions:

After using Calculate Integer Entropy, run Analyze Integers to get a broader view of value patterns and frequency. You can also try Find Integer Digit Average to see how much variability exists across digit positions.

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