New versions of modeldb and tidypredict now on CRAN

modeldb 0.1.2 Removes pipes and other dplyr dependencies from internal mlr() function Consolidates duplicated database operations in mlr() Fixes an issue in simple_kmeans_db() when specifying variables tidypredict 0.3.0 New features Adds support for MARS models provided by the earth package Improvements New parsed models are now list objects as opposed to data frames. tidypredict_to_column() no longer supports ranger and randomForest because of the multiple queries generated by multiple trees. Read more →

bigrquery 1.1.0 Now on CRAN

The new version of bigrquery is now available on CRAN. This is a minor release, with some improved type support, and SQL translation. Please see the official release announcement in the site: Read more →

bigrquery 1.0.0 Now on CRAN

The new version of bigrquery is now available on CRAN. Here are some highlights: The low-level API provides thin wrappers over the underlying REST API. In this version, all the low-level functions start with bq_, and mostly have the form bq_noun_verb(). This level of abstraction is most appropriate if you’re familiar with the REST API and you want do something not supported in the higher-level APIs. The DBI interface wraps the low-level API and makes working with BigQuery like working with any other database system. Read more →

tidypredict 0.2.0 Now on CRAN

Run predictions inside the database. tidypredict parses a fitted R model object, and returns a formula in ‘Tidy Eval’ code that calculates the predictions. It works with several databases back-ends because it leverages dplyr and dbplyr for the final SQL translation of the algorithm. It currently supports lm(), glm(), randomForest() and ranger() models. More information is available in the package’s official site: Read more →

dbplyr 1.2.0 Now on CRAN

We are very excited to announce that dbplyr 1.2.0 is now available on CRAN! The full announcement was posted in Here are the highlights: New custom translation for Microsoft Access and Teradata Amazon Redshift connections now point to the PostgreSQL translation. Adds support for two new database R packages. These new packages are fully DBI-compliant and tested with DBItest. We recommend to use these instead of older packages: RMariaDB, use in favor of RMySQL RPostgres, use in favor of RPostgreSQL ROracle connections now point to the Oracle translation. Read more →