This package handles access to small to medium size time series datasets (in the Megabytes) to be used in Julia.

Since the number of datasets could be potentially large and relatively big in size they are not downloaded when the package is installed, but only when they are called to then be stored locally as a Julia artifact.

The format chosen to return the time series is via a DataFrame with its first column using Dates when appropiate.

In general time series available in ForecastData will be "unique" in one of these two ways:

  • They are a combination of publicly available datasets (e.g. london dataset)
  • They are publicly available datasets with some preparation to facilitate their use (e.g. quakes dataset)

Simple publicly available datasets will not be generally considered, for instance R datasets like AirPassengers will not be stored in ForecastData since they can be easily accessed via RCall.

The current available datasets are:

Name Description
co2 Atmospheric Carbon Dioxide Dry Air Mole Fractions from quasi-continuous measurements at Mauna Loa, Hawaii from 1973 to 2020
london Monthly data on weather and crime in Greater London from 2008 to 2018
quakes Earthquakes with a magnitude higher or equal to six from 1638-06-11 to 2021-10-02
seaborne Seaborne trade for France, Germany and the United Kingdom from 2015-04-01 to 2021-05-02


using ForecastData
co2_ts = co2("paper")

[ Info: Dataset used in Cleveland et al. paper
4609×2 DataFrame
  Row  date        co2        
       Date       Float64?   
    1  1974-05-17      333.38
    2  1974-05-18      333.11
    3  1974-05-19      333.46


if you would like to contribute new datasets to the package please consider a Pull Request with the following actions:

  • Create a data/[new_dataset].tar.gz file with a [new_dataset].md description file.
  • Create a src/[new_dataset].jl file
  • Create a test/[new_dataset].jl file
  • Update the and Forecast.jl files with the new dataset information
  • Update Artifacts.toml with the new dataset

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