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Online Algorithms for Statistics, Models, and Big Data Viz

  • ⚡ High-performance single-pass algorithms for statistics and data viz.
  • ➕ Updated one observation at a time.
  • ✅ Algorithms use O(1) memory.
  • 📈 Perfect for streaming and big data.

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🚀 Quickstart

import Pkg

Pkg.add("OnlineStats")

using OnlineStats

# Create several statistics
o = Series(Mean(), Variance(), Extrema())

# Update with single data point
fit!(o, 1.0)

# Iterate through and update with lots of data
fit!(o, randn(10^6))

# Get the values of the statistics
value(o)  # (value(mean), value(variance), value(extrema))

📖 Documentation

✨ Contributing

  • Trivial PRs such as fixing typos are very welcome!
  • For nontrivial changes, you'll probably want to first discuss the changes via issue/email/slack with @joshday.

✏️ Authors

See also the list of contributors to OnlineStats.

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⚡ Single-pass algorithms for statistics ⚡

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  • Julia 100.0%