dplyr

dplyr: A Grammar of Data Manipulation. A fast, consistent tool for working with data frame like objects, both in memory and out of memory.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 10 articles )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Anthony Ebert, Paul Wu, Kerrie Mengersen, Fabrizio Ruggeri: Computationally Efficient Simulation of Queues: The R Package queuecomputer (2017) arXiv
  2. Antoine Filipovic-Pierucci, Kevin Zarca, Isabelle Durand-Zaleski: Markov Models for Health Economic Evaluations: The R Package heemod (2017) arXiv
  3. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
  4. Beckerman, Andrew P.; Petchey, Owen L.: Getting started with R. An introduction for biologists. (2017)
  5. David Kahle, Christopher O’Neill, Jeff Sommars: A computer algebra system for R: Macaulay2 and the m2r package (2017) arXiv
  6. Peter E. DeWitt, Samantha MaWhinney, Nichole E. Carlson: cpr: An R Package For Finding Parsimonious B-Spline Regression Models via Control Polygon Reduction and Control Net Reduction (2017) arXiv
  7. Przemyslaw Biecek, Marcin Kosinski: archivist: An R Package for Managing, Recording and Restoring Data Analysis Results (2017) arXiv
  8. Kamiński, Bogumił: A method for the updating of stochastic Kriging metamodels (2015)
  9. Unwin, Antony: Graphical data analysis with R (2015)
  10. David Robinson: broom: An R Package for Converting Statistical Analysis Objects Into Tidy Data Frames (2014) arXiv