Open software and data

Projects

cynkra is enthusiastic about open source software and the R universe – and we contribute to it, too. Here's a selection of our freely available software and data products.

Databases

Automatically updated data collection for Switzerland and unifying the interfacing to RDBMS are the flagships features of our databases open source projects

R consortium project

Database Interface in R (DBI)

The DBI package separates the connectivity to the DBMS into a front-end and a back-end.

Applications use only the exposed “front-end” API. The facilities that communicate with specific DBMS (Oracle, PostgreSQL, etc.) are provided by “device drivers” that get invoked automatically by the S language evaluator.

The “Improving DBI” project, funded by the R consortium, includes the definition and implementation of a testable specification for DBI and making RSQLite fully compliant to the new specification.

Main use of R/S DBI is to unify the interfacing to RDBMS and to allow R/S applications to be developed on top of the DBI. It's interface resembles the one of the Python’s DBAPI which is thought of as the most relevant interface for the S language.

working with related tables

dm

The goal of dm is to provide tools for reoccurring tasks when working with a set of related tables.

The dm class stores properties of a set of related tables in a compound object:
  • a src: location of tables (database, in-memory, …)
  • a data_model: metadata about data model (keys, table & columns names, …)
  • the data: the tables itself
This concept augments dplyr/dbplyr workflows:
  • multiple related tables are kept in a single object
  • joins across multiple tables are available by stating the tables involved, no need to memoize column names or relationships
  • works with all data sources that provide a dplyr interface: local data frames, relational databases, and more

Time Series

Our time series projects are easy to use and are packed with many useful features which make work with time series much easier

seasonal adjustment

R-interface to X-13ARIMA-SEATS

seasonal is an easy-to-use and full-featured R-interface to X-13ARIMA-SEATS, the latest seasonal adjustment software from the United States Census Bureau.

seasonal offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. It also includes a Shiny-based graphical user interface.

X13binary package provides x-13 binaries and facilitates a fully-automatic installation on most platforms. X-13 handles monthly, quarterly and bi-annual time series. The newest version of X-13 offers two seasonal adjustment methods, X-11 and TRAMO-SEATS, in a singlecommand-line tool which is written in Fortran. There is an online demo site for seasonal. You can upload and adjust your own time series. No software installation is needed.

Class-Agnostic Time Series in R

Time series toolkit

tsbox makes life with R’s time series classes easy.

The R ecosystem knows a vast number of time series standards. Instead of creating the ultimate 15th time series class, tsbox provides a set of tools that are agnostic towards the existing standards. The tools also allow you to handle time series as plain data frames, thus making it easy to deal with time series in a dplyr or data.table workflow.

Use same functions for time series classes

You can write functions that work for all classes. So whether you want to smooth, scale, differentiate, chain, forecast, regularize or seasonally adjust a time series, you can use the same commands to any time series class.

Convert everything to everything

With tsbox you can convert different formats to each other. It's made possible by tsbox throught the use of converters which convert time series stored as ts, xts, data.frame, data.table, tibble, zoo, tsibble, tibbletime or timeSeries to each other.

Switzerland's data series in one place

Open data collection for Switzerland

dataseries.org provides a structured collection of most of the relevant data series for Switzerland, automatically updated from various sources.

Export Everything

You can export everything. Whatever you find interesting, you can download, as a graph or as a table. And you can import everything into R, using the new dataseries package.

Unified Interface

It shows the data series in a unified interface that starts with the series you were looking for 80% of the time, and gives you all details the rest of the time.

Save-and-Share

The save-and-share feature allows you to save the current view and share it with others, using a stable URL with parameters.

Development Tools

Automated testing made easier with our travis + tic and R + AppVeyor solutions that offer continuous integration with R under Windows and Linux

automated testing

Continous Integration

Open source solutions for continuous integration with R under Windows and Linux

travis + tic

travis + tic is a related project, whose goal is to simplify the setup of continuous integration with Travis CI. It's main purpose is to provide a command-line way in R for certain Travis tasks that are usually done in the browser (build checking, cache deletion, build restarts, etc.). Apart from automating away a few button flips, it also provides an easy method to set up push access which can be then triggered (on Travis) by the companion package tic.

R + AppVeyor

R + AppVeyor is a solution for continuous integration for R projects on Windows, using AppVeyor - a Continuous integration (CI) testing service similar to Travis-CI. Under the hood, r-travis is used to perform the testing; this works even on Windows thanks to MinGW and MSYS. AppVeyor offers facilities for hosting artifacts contrary to the Travis-CI. For this to work, section needs to be added to the appveyor.yml.