tidyr

R package tidyr: Easily Tidy Data with ’spread()’ and ’gather()’ Functions. An evolution of ’reshape2’. It’s designed specifically for data tidying (not general reshaping or aggregating) and works well with ’dplyr’ data pipelines.

Keywords for this software

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References in zbMATH (referenced in 19 articles )

Showing results 1 to 19 of 19.
Sorted by year (citations)

  1. Dewey W. Dunnington, Nell Libera, Joshua Kurek, Ian S. Spooner, Graham A. Gagnon: tidypaleo: Visualizing Paleoenvironmental Archives Using ggplot2 (2022) not zbMATH
  2. Speegle, Darrin; Clair, Bryan: Probability, statistics, and data. A fresh approach using R (2022)
  3. Barneche DR, Coleman G, Fermor D, Klein E, Robinson T, Smith J, Sheehan JL, Dowley S, Ditton D, Gunn K, Ericson G, Logan M, Rehbein M : dataaimsr: An R Client for the Australian Institute of Marine Science Data Platform API which provides easy access to AIMS Data Platform (2021) not zbMATH
  4. Christian Thiele; Gerrit Hirschfeld: cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R (2021) not zbMATH
  5. Radojičić, Una; Nordhausen, Klaus; Virta, Joni: Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit (2021)
  6. Sam Parsons: splithalf: robust estimates of split half reliability (2021) not zbMATH
  7. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2021)
  8. Irizarry, Rafael A.: Introduction to data science. Data analysis and prediction algorithms with R (2020)
  9. Matthias Speidel, Jörg Drechsler, Shahab Jolani: The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond (2020) not zbMATH
  10. Michael David Wilson; Luke Strickland; Timothy Ballard: FIPS: An R Package for Biomathematical Modelling of Human Fatigue Related Impairment (2020) not zbMATH
  11. Tian-Yuan Huang; Bin Zhao: tidyfst: Tidy Verbs for Fast Data Manipulation (2020) not zbMATH
  12. Anne Petersen; Claus Ekstrøm: dataMaid: Your Assistant for Documenting Supervised Data Quality Screening in R (2019) not zbMATH
  13. Roman Luštrik; Žan Kuralt: wolfexplorer: a tool for visualization and exploration of complex multi-year multi-specimen datasets (2018) not zbMATH
  14. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
  15. Benjamin R. Fitzpatrick, Kerrie Mengersen: A network flow approach to visualising the roles of covariates in random forests (2017) arXiv
  16. 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
  17. Neeraj Bokde, Kishore Kulat, Marcus W Beck, Gualberto Asencio-Cortes: R package imputeTestbench to compare imputations methods for univariate time series (2016) arXiv
  18. David Robinson: broom: An R Package for Converting Statistical Analysis Objects Into Tidy Data Frames (2014) arXiv
  19. Gandrud, Christopher: Reproducible research with R and RStudio (2014)