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  2. Tidyverse - Wikipedia

    en.wikipedia.org/wiki/Tidyverse

    For example, there is the TidyTuesday social data project organised by the Data Science Learning Community (DSLC), [16] where varied real-world datasets are released each week for the community to participate, share, practice, and make learning to work with data easier. [17] Critics of the tidyverse have argued it promotes tools that are harder ...

  3. dplyr - Wikipedia

    en.wikipedia.org/wiki/Dplyr

    dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language. [1]

  4. Hadley Wickham - Wikipedia

    en.wikipedia.org/wiki/Hadley_Wickham

    Hadley Alexander Wickham (born 14 October 1979) is a New Zealand statistician known for his work on open-source software for the R statistical programming environment.He is the chief scientist at Posit PBC and an adjunct professor of statistics at the University of Auckland, Stanford University, and Rice University.

  5. Easystats - Wikipedia

    en.wikipedia.org/wiki/Easystats

    The easystats collection of open source R packages was created in 2019 and primarily includes tools dedicated to the post-processing of statistical models. [1] [2] As of May 2022, the 10 packages composing the easystats ecosystem have been downloaded more than 8 million times, and have been used in more than 1000 scientific publications.

  6. Help:Cheatsheet - Wikipedia

    en.wikipedia.org/wiki/Help:Cheatsheet

    To ask a question, see Wikipedia:Questions to locate the appropriate venue(s) Find this page confusing? Just use this link to ask for help on your talk page ; a volunteer will visit you there shortly!

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  8. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  9. Programming with Big Data in R - Wikipedia

    en.wikipedia.org/wiki/Programming_with_Big_Data_in_R

    Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...