## online-statistics

Blazingly fast, generic, and serializable online statistics

### 8 releases

 0.2.6 Sep 10, 2022 Sep 9, 2022 Aug 27, 2022 Jul 23, 2022

#27 in #stream-processing

74KB
1.5K SLoC

# Online statistics in Rust 🦀

`online-statistics` is crate 🦀 for Blazingly fast, generic and serializable online statistics.

## Quickstart

Let's compute the online median and then serialize it:

``````use online_statistics::quantile::Quantile;
use online_statistics::stats::Univariate;
let data: Vec<f64> = vec![9., 7., 3., 2., 6., 1., 8., 5., 4.];
let mut running_median: Quantile<f64> = Quantile::new(0.5_f64).unwrap();
for x in data.into_iter() {
running_median.update(x); // update the current statistics
println!("The actual median value is: {}", running_median.get());
}
assert_eq!(running_median.get(), 5.0);

// Convert the statistic to a JSON string.
let serialized = serde_json::to_string(&running_median).unwrap();

// Convert the JSON string back to a statistic.
let deserialized: Quantile<f64> = serde_json::from_str(&serialized).unwrap();

``````

Now let's compute the online sum using the iterators:

``````use online_statistics::iter::IterStatisticsExtend;
let data: Vec<f64> = vec![1., 2., 3.];
let vec_true: Vec<f64> = vec![1., 3., 6.];
for (d, t) in data.into_iter().online_sum().zip(vec_true.into_iter()) {
assert_eq!(d, t); //       ^^^^^^^^^^
}
``````

You can also compute rolling statistics; in the following example let's compute the rolling sum on 2 previous data:

``````
use online_statistics::rolling::Rolling;
use online_statistics::stats::Univariate;
use online_statistics::variance::Variance;
let data: Vec<f64> = vec![9., 7., 3., 2., 6., 1., 8., 5., 4.];
let mut running_var: Variance<f64> = Variance::default();
// We wrap `running_var` inside the `Rolling` struct.
let mut rolling_var: Rolling<f64> = Rolling::new(&mut running_var, 2).unwrap();
for x in data.into_iter() {
rolling_var.update(x);
}
assert_eq!(rolling_var.get(), 0.5);
``````

## Installation

Add the following line to your `cargo.toml`:

``````[dependencies]
online-statistics = "0.2.6"
``````

## Statistics available

Statistics Rollable ?
Mean
Variance
Sum
Min
Max
Count
Quantile
Peak to peak
Exponentially weighted mean
Exponentially weighted variance
Interquartile range
Kurtosis
Skewness
Covariance

## Inspiration

The `stats` module of the `river` library in `Python` greatly inspired this crate.

~1.4–2.3MB
~50K SLoC