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Working with data

Open Source

We are enthusiastic about open source software (OSS) and the R ecosystem. Members of our team author and maintain OSS projects from database and development tools to machine learning, statistics, and time series analysis libraries.

Daniel Monteiro

Featured projects:

DBI: R Database Interface

Provides a unifying interface to relational databases in R.

Key Features
  • Unified interface for all database operations.
  • Supports multiple DB backends like MySQL, SQLite, PostgreSQL, and more.
  • Easy data fetching and manipulation within R.

dm: Relational Data Models

Framework for relational data models in R.

Key Features
  • Define and manage relational data models.
  • Ensure data integrity across related tables.
  • Facilitate complex data operations.

seasonal: R Interface to X-13

Facilitates seasonal adjustment of time series data using X-13-ARIMA-SEATS

Key Features
  • Easy-to-use Interface
  • Automatic ARIMA Model Search
  • Outlier Detection

blockr: No-Code Data Manipulation and Visualization

Simplify data manipulation and visualization with blockr.

Key Features
  • No-Code Dashboard Creation
  • Interactive Data Visualization
  • Integration with R Ecosystem

shinyMobile: Cutting edge templates for Shiny

Develop Shiny apps for iOS, Android, and desktop.

Key Features
  • Powerful input widgets such as autocomplete, smartselect, ...
  • Dark/light mode
  • 2 skins: Material and iOS.

shinyNextUI: React template for Shiny

React and Tailwind CSS for Shiny apps.

Key Features
  • More than 30 UI widgets and container such as cards, dropdown, typeahead input
  • Dark/light mode support.
  • Customisation with tailwindcss.

Outstanding User Interfaces with Shiny

Comprehensive guide to mastering Shiny UI.

Key Features
  • How to develop Shiny apps with a more professional look and feel?
  • How to design new input widgets to unleash interactivity?
  • How to better handle JS and CSS in Shiny apps?
Jan Pultin
Let us improve your software

R Packages as a service

We'd be happy to help you take your R package to the next level, and/or to CRAN. Our team is knowledgeable about the R open-source ecosystem. Contact us to get an offer.

What Our Clients Say About Us:

cynkra has been consulting for DuckDB Labs on R-related projects for over two years now. We are very impressed by the depth of their technical knowledge on the language, their deep integration into the package ecosystem and envelope-pushing regarding automation.

Hannes Mühleisen

DuckDB Labs

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I am a Senior Computational Biologist who has been coding in R for over 20 years. Since 5 years I have been hiring Kirill Müller to work with me on select projects. Our interactions are fun and highly productive and he continues to teach me to become a much better programmer.

Joseph Thorley

Poisson Consulting

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cynkra has collaborated with our research group in 2022 in the realization of an R-package integrating external libraries. They delivered a robust and reliable solution within the agreed time frame. What I appreciated most was their availability to answer questions and provide feedback even after the conclusion of the project.

Luca Carraro

Eawag

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Energie360° has been expertly supported by cynkra since 2018 and we couldn't be happier. Their quick response time, friendly can-do attitude and lighning speed at work makes their app development service absolutely recommendable.

Péter Jeszenszky

Energie360°

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Our packages

Name Description Category
DBI: R database interface Provides a unifying interface to relational databases in R, with backend packages like RSQLite, RMariaDB and RPostgres for specific databases. Database
dm: relational data models Provides tools for working with related tables, stored as data frames or in a relational database. Consume, build, and deploy relational data models in R. Database
Odds ratio calculation Simplified odds ratio calculation for GAM(M)s and GLM(M)s. Provides structured output of all predictors and their corresponding odds ratios. Statistics
Spatial error estimation Implements error estimation and variable importance measures for predictive models using spatial cross-validation and spatial block bootstrap. Statistics
wrswoR: random sampling A collection of implementations of classical and novel algorithms for weighted random sampling without replacement. Statistics
Class-agnostic time series in R tsbox proides a set of tools that are agnostic towards the existing standards. The tools allow you to handle time series as plain data frames. Time series
Seasonal adjustment by X-13 The seasonal package is an interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. x13binary provides the binaries. Time series
Temporal disaggregation Temporal disaggregation methods are used to disaggregate and interpolate a low frequency time series to a higher frequency series. Time series
dataseries: Swiss open data dataseries.org provides a structured collection of many of the relevant data series for Switzerland, automatically updated from various sources. Time series
tibble: simple data frames Tibbles are a modern reimagining of the data.frame, keeping what time has proven to be effective, and throwing out what is not. Convenience
here: a simple way to find files Two related packages to provide a simpler way to find your files. The 'root' of a project is defined as a directory that matches a certain criterion. Convenience
tv: data frames in the browser The tv package lively displays data frames. It modifies the print method of data frames to also appear in a browser or in the view pane of the RStudio IDE. Convenience
fledge: simplified versioning Wings for your R packages: Streamline the process of versioning R packages. Update your change log with relevant information from recent commit messages. Development
plogr: logging library for C++ Provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream. Development
profile + gprofiler: profiling in R Defines a data structure for profiler data as well as methods to read and write from the 'Rprof' and 'pprof' file formats. Development
Continuous integration in R Enhance and simplify working with continuous integration (CI) systems for R projects with tic, travis, circle and r-appveyor. Development
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