etl - Extract-Transform-Load Framework for Medium Data
A predictable and pipeable framework for performing ETL (extract-transform-load) operations on publicly-accessible medium-sized data set. This package sets up the method structure and implements generic functions. Packages that depend on this package download specific data sets from the Internet, clean them up, and import them into a local or remote relational database management system.
Last updated 1 years ago
7.15 score 127 stars 1 packages 37 scripts 394 downloadsmdsr - Complement to 'Modern Data Science with R'
A complement to all editions of *Modern Data Science with R* (ISBN: 978-0367191498, publisher URL: <https://www.routledge.com/Modern-Data-Science-with-R/Baumer-Kaplan-Horton/p/book/9780367191498>). This package contains data and code to complete exercises and reproduce examples from the text. It also facilitates connections to the SQL database server used in the book. All editions of the book are supported by this package.
Last updated 3 months ago
7.03 score 38 stars 426 scripts 1.1k downloadsteamcolors - Color Palettes for Pro Sports Teams
Provides color palettes corresponding to professional and amateur, sports teams. These can be useful in creating data graphics that are themed for particular teams.
Last updated 20 days ago
6.51 score 47 stars 197 scripts 220 downloadsmacleish - Retrieve Data from MacLeish Field Station
Download data from the Ada and Archibald MacLeish Field Station in Whately, MA. The Ada and Archibald MacLeish Field Station is a 260-acre patchwork of forest and farmland located in West Whately, MA that provides opportunities for faculty and students to pursue environmental research, outdoor education, and low-impact recreation (see <https://www.smith.edu/about-smith/sustainable-smith/macleish> for more information). This package contains weather data over several years, and spatial data on various man-made and natural structures.
Last updated 2 years ago
5.70 score 2 stars 84 scripts 360 downloadstidychangepoint - A Tidy Framework for Changepoint Detection Analysis
Changepoint detection algorithms for R are widespread but have different interfaces and reporting conventions. This makes the comparative analysis of results difficult. We solve this problem by providing a tidy, unified interface for several different changepoint detection algorithms. We also provide consistent numerical and graphical reporting leveraging the 'broom' and 'ggplot2' packages.
Last updated 3 months ago
5.06 score 1 stars 8 scripts 140 downloads