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ggplot2 is an open-source data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a ...
R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.
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]
This is a list of POSIX (Portable Operating System Interface) commands as specified by IEEE Std 1003.1-2024, which is part of the Single UNIX Specification (SUS). These commands can be found on Unix operating systems and most Unix-like operating systems.
R – free implementation of the S (programming language) Programming with Big Data in R (pbdR) – a series of R packages enhanced by SPMD parallelism for big data analysis; R Commander – GUI interface for R; Rattle GUI – GUI interface for R; Revolution Analytics – production-grade software for the enterprise big data analytics
Plots play an important role in statistics and data analysis. The procedures here can broadly be split into two parts: quantitative and graphical. Quantitative techniques are a set of statistical procedures that yield numeric or tabular output. Examples of quantitative techniques include: [1] hypothesis testing; analysis of variance
Generates a ranked list of several plots & visualizations based on an analysis of the data provided, allowing the user to choose their favorite graphic, share it, and export it as an image. DataGraph: GUI, command line: Proprietary: No 2006: February 17, 2020 / 4.5.1: macOS: 2D graphing, animations, data analysis, linear and non-linear curve ...
The algorithm for computing a dot plot is closely related to kernel density estimation. The size chosen for the dots affects the appearance of the plot. Choice of dot size is equivalent to choosing the bandwidth for a kernel density estimate. In the R programming language this type of plot is also referred to as a stripchart [3] or stripplot. [4]