When it comes to software development my motto is open by default. In other words, I need a good reason to not publish the source code of the software I write. These days, I do programming with data and therefore mostly work with SQL, R and Python. Expect some web development, data visualization and devOps routines blended in from time to time.
Started back in 2014, {timeseriesdb} is my longest tenured open source project. Essentially, {timeseriesdb} maps R language time series representations to PostgreSQL relations. In addition to capabilities to persistently store time series themselves in a database, {timeseriesdb} allows for fine grained access rules, multi-lingual meta description as well as vintages (versions) of time series which allows for realtime analysis.
These features make {timeseriesdb} an ideal fit to manage and archive time series in official statistics and other time series that are potentially revised. {timeseriesdb} is reliable, light weight option to store and manage millions of time series – even from individuals to enterprises, academic researchers and public administration. Its SQL backend and architecture allows to easily add a REST interface to {timeseriesdb} and expose time series data through an REST API.
Documentation: mbannert.github.com/timeseriesdb
GitHub Development Repository: github.com/mbannert/timeseriesdb
Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/timeseriesdb/index.html
{r4googleads} is the successor of my most successful open source contribution in terms of popularity. The {r4googleads} package is an API wrapper around Google’s Ads API and succeeds the {RAdwords} package after Google is sunsetting its Adwords API and replacing it with the Google Ads API. {r4googleads} is joint work with my buddy and online marketing professional @jburkhardt.
@jburkardt and me doing open source stuff for online marketing: banboo data
{r4googleads} documentation (including migration guide): https://banboo-data.github.io/r4googleads/
Github Development Repository: https://github.com/banboo-data/r4googleads
Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/r4googleads/index.html
Plot official statistics’ time series conveniently: automatic legends, highlight windows, stacked bar chars with positive and negative contributions, sum-as-line option, two y-axes with automatic horizontal grids that fit both axes and other popular chart types. ‘tstools’ comes with a plethora of defaults to let you plot without setting an abundance of parameters first, but gives you the flexibility to tweak the defaults. In addition to charts, ‘tstools’ provides a super fast, ‘data.table’ backed time series I/O that allows the user to export / import long format, wide format and transposed wide format data to various file types.
GitHub Development Repository: https://github.com/mbannert/tstools