Calculate TSV Entropy

Calculate TSV entropy online. Paste or upload tab-separated data and instantly get per-column entropy scores for analysis, comparison, or cleanup.

Paste your input above or import a file below.
No file chosen
Supported file types: .tsv, .txt
Total columns: 0
Options
Normalize entropy
Treat numbers as text
Maximize output

How to Use:

  • Paste TSV data into the Input TSV box or click Choose File to upload a .tsv or .txt file.
  • Toggle Normalize entropy to scale values between 0 and 1 for easier comparison.
  • Enable Treat numbers as text if you want numeric columns handled as categorical instead of numeric values.
  • Use Maximize Output to expand the entropy preview window.
  • Click Calculate to run the entropy analysis.
  • Use Copy Output to copy the summary or Export to File to download the results.
  • Click Clear All to reset everything and remove the live counter.

What Calculate TSV Entropy can do:

Calculate TSV Entropy gives you a fast breakdown of information entropy per column. It shows how varied each column’s values are helping you find duplicates, randomness, or predictability. You can treat all fields as text or allow numerical columns to behave like labels. You can normalize entropy scores for consistent comparisons across uneven data sizes. Works fully in the browser with no uploads, and includes a preview and export.

Example:

Input:

name	color
apple	red
banana	yellow
apple	green
banana	yellow
apple	red

Output:

Column name: 0.9183
Column color: 1.4591

Common Use Cases:

Calculate TSV Entropy is helpful for data profiling, especially when exploring CSV/TSV logs, user datasets, exports, or survey results. Use it to spot repetitive values, measure randomness, or compare variation between columns in real-time without touching Python or R.ors.

Useful Tools & Suggestions:

Once you Calculate TSV Entropy, Display TSV Statistics gives you more context on what’s driving that complexity. And if you’re experimenting with data quality, Add Errors to TSV lets you test how entropy changes with noise.

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