Elm-stat

The elm-stat package provides tools for statistics and visualization of n-column data files. Most of the features of the package are exposed in the the demo apps, found in the ./examples folder of the source code. The package is intended to be a long-term research and development effort which will gradually add features over time. I'd be very interested in finding collaborators with some background in mathematics and/or statistics.

The API

The elm-stat package consists of seven modules divided into three groups

Statistical Functions

StatRandom provides commonly used probability distributions
Stat provides many common functions used in statistics

Data

RawData is used for extracting raw data from a text string or file: metadata such as comments about the data, column headings, and an m*n table of strings representing the actual data.
SampleData provides several data sets: Global temperature anomalies, sea level data, Edwin Hubble's galactic recession data, and historic speed of light data

Charts

Chart provides tools for building graphs and charts. A chart consists of one more graphs. Graphs come in various types, e.g, line and scatter.
Data provides types and functions for extracting lists of 2D points both from strings and RawData values. This module is used in Chart
ErrorBars provides utilities for drawing error bars. Used in Chart.

Example usage

Let's import the above modules to see how some of this works. For more details, see the documentation for the individual modules. First, some test data:

> SampleData.temperature
 """
 Global Land and Ocean Temperature Anomalies
 January-December 1880-2016
 Units: Degrees Celsius
 Base Period: 1901-2000
 Missing: -999
  Year  Value
  1880  -0.12
  1881  -0.07
  1882  -0.08
  1883  -0.15
  ...

Transform this text to a RawData value using RawData.get, a function which automatically detects the type of data represented by the text: space-delimited, tab-delimited, or comma-delimited (csv).

> data = RawData.get SampleData.temperature
 Just {
  columnHeaders = ["Year","Value"]
 , data = [["1880","-0.12"],["1881","-0.07"],["1882","-0.08"], ...
 , metadata = [
   "Global Land and Ocean Temperature Anomalies"
   , "January-December 1880-2016"
   , "Units: Degrees Celsius"
  ]

Extract the first column of the data which represents the temperature anomalies:

> tempAnom = RawData.getColumn data 1
  [-0.12,-0.07,-0.08,-0.15,-0.22,-0.22,-0.21, ...

Statistics can be computed for the tempAnom list:

> Stat.mean tempAnom
Just 0.048759 : Maybe Float

> Stat.median tempAnom
Just -0.05 : Maybe Float

> Stat.standardDeviation tempAnom
Just 0.31324402291377174 : Maybe Float

Extract two columns as a tuple list:

> yearTemp = RawData.toData 0 1 (Maybe.withDefault (RawData.RawData [] [] [[]]) data)
[(1880,-0.12),(1881,-0.07),(1882,-0.08),(1883,-0.15),(1884,-0.22),(1885,-0.22),(1886,-0.21)...

Calculate correlation between the years and temperature anomalies:

> Stat.correlation yearTemp
Just 0.8635859634657297 : Maybe Float

Demo Apps

There are three examples in ./src.

Main.elm provides usage examples for the functions in the modules Stat and StatRandom
Hubble.elm provides a scatter plot and regression line for Edwin Hubble's 1929 galactic recession data.
Temperature.elm provides a line graph and regression line for global temperature anomalies for the period 1880-2016. The temperature anomaly for a given year is the difference between the mean temperature for the year and the mean global temperature for a reference period.

Code for the demo apps is in ./examples. Compile the first example by saying

elm make src/Main.elm

then opening index.html in a browser.

Notes

This is a major update to version 4.0.3. The API for the statistical functions in module Stat has been completely rewritten, and a new module, StatRandom, featuring generators for many common statistical packages has been added. Both are contributions of Raul Fleischman (FleischmanRaul on Github)

Thanks to Mattia Verticchio for numerous performance updates.

jxxcarlson / elm-stat