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  2. ggplot2 - Wikipedia

    en.wikipedia.org/wiki/Ggplot2

    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 ...

  3. Rattle GUI - Wikipedia

    en.wikipedia.org/wiki/Rattle_GUI

    Rattle provides considerable data mining functionality by exposing the power of the R Statistical Software through a graphical user interface. Rattle is also used as a teaching facility to learn the R software Language. There is a Log Code tab, which replicates the R code for any activity undertaken in the GUI, which can be copied and pasted.

  4. Box plot - Wikipedia

    en.wikipedia.org/wiki/Box_plot

    Figure 2. Box-plot with whiskers from minimum to maximum Figure 3. Same box-plot with whiskers drawn within the 1.5 IQR value. A boxplot is a standardized way of displaying the dataset based on the five-number summary: the minimum, the maximum, the sample median, and the first and third quartiles.

  5. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    Box plots are non-parametric: they display variation in samples of a statistical population without making any assumptions of the underlying statistical distribution, thus are useful for getting an initial understanding of a data set. For example, comparing the distribution of ages between a group of people (e.g., male and females).

  6. Compact letter display - Wikipedia

    en.wikipedia.org/wiki/Compact_letter_display

    Box plot of five West Coast cities rainfall data. The box plot above is not entirely clear. It is hard to distinguish the cities that are somewhat similar (average or mean is not statistically different) vs. the ones that are dissimilar (average or mean is statistically different). Now, let's view the same boxplot using the CLD methodology.

  7. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...

  8. UpSet plot - Wikipedia

    en.wikipedia.org/wiki/UpSet_plot

    UpSet plots became popular as they became available as an R-library based on ggplot2, [3] and were subsequently re-implemented in various programming languages, such as Python, and others. [4] As of January 2024, UpSetR has been downloaded from CRAN more than 1.5 million times, although it was last updated 5 years ago. [5]

  9. Contour boxplot - Wikipedia

    en.wikipedia.org/wiki/Contour_boxplot

    Analogous to the classical boxplot and considered an expansion of the concepts defining functional boxplot, [2] [3] the descriptive statistics of a contour boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope. To construct a contour boxplot, data ordering is the first step.