| Title: | Exploratory Data Analysis System |
| Version: | 3.1.7 |
| Description: | Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Imports: | DT, rlang, golem, shiny (≥ 1.7.4), config, plotly, loadeR, cluster, ggplot2, shinyjs, shinyAce, ggdendro, echarts4r, htmltools, FactoMineR, htmlwidgets, colourpicker, shinydashboard, shinycustomloader, shinydashboardPlus (≥ 2.0.0) |
| Depends: | R (≥ 4.4) |
| Encoding: | UTF-8 |
| URL: | https://promidat.website/, https://github.com/PROMiDAT/discoveR |
| BugReports: | https://github.com/PROMiDAT/discoveR/issues |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-02-12 19:27:14 UTC; r583594 |
| Author: | Oldemar Rodriguez [aut, cre], Diego Jiménez [aut] |
| Maintainer: | Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr> |
| Repository: | CRAN |
| Date/Publication: | 2025-02-12 20:30:02 UTC |
Exploratory Data Analysis System
Description
Performs an exploratory data analysis through a 'shiny' interface. It includes basic methods such as the mean, median, mode, normality test, among others. It also includes clustering techniques such as Principal Components Analysis, Hierarchical Clustering and the K-Means Method.
Details
| Package: | discoveR |
| Type: | Package |
| Version: | 3.1.7 |
| Date: | 2025-02-12 |
| License: | GPL (>=2) |
Author(s)
Maintainer: Oldemar Rodriguez Rojas <oldemar.rodriguez@ucr.ac.cr>
Oldemar Rodriguez Rojas <oldemar.rodriguez@ucr.ac.cr>
Diego Jiménez Alvarado
See Also
Useful links:
Report bugs at https://github.com/PROMiDAT/discoveR/issues
Calculate inter-class inertia
Description
Calculate inter-class inertia
Usage
BP(DF, clusters)
Arguments
DF |
a data.frame object. |
clusters |
a vector specifying the cluster of each individual. |
Value
numeric
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
m <- hclust(dist(iris[, -5]))
BP(iris[, -5], cutree(m, 3))
Calculate intra-class inertia
Description
Calculate intra-class inertia
Usage
WP(DF, clusters)
Arguments
DF |
a data.frame object. |
clusters |
a vector specifying the cluster of each individual. |
Value
numeric
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
m <- hclust(dist(iris[, -5]))
WP(iris[, -5], cutree(m, 3))
Calculation of the center of clusters
Description
Calculation of the center of clusters
Usage
calc.centros(data, clusters)
Arguments
data |
a data.frame object. |
clusters |
a vector specifying the cluster of each individual. |
Value
list
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
calc.centros(iris[, -5], clusters)
AFC biplot
Description
AFC biplot
Usage
e_afcbi(
modelo,
axes = c(1, 2),
colorRow = "steelblue",
colorCol = "forestgreen",
cos2Row = 0,
cos2Col = 0,
colorRowCos = "firebrick",
colorColCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorRow |
a color for the individuals well represented. |
colorCol |
a color for the variables well represented. |
cos2Row |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Col |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorRowCos |
a color for the individuals badly represented. |
colorColCos |
a color for the variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcbi(p)
AFC biplot in 3D
Description
AFC biplot in 3D
Usage
e_afcbi_3D(
modelo,
axes = c(1, 2, 3),
colorRow = "steelblue",
colorCol = "forestgreen",
cos2Row = 0,
cos2Col = 0,
colorRowCos = "firebrick",
colorColCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorRow |
a color for the individuals well represented. |
colorCol |
a color for the variables well represented. |
cos2Row |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Col |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorRowCos |
a color for individuals badly represented. |
colorColCos |
a color for variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcbi_3D(p)
AFC plot of variables
Description
AFC plot of variables
Usage
e_afccol(
modelo,
axes = c(1, 2),
colorCol = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorCol |
a color for the variables well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorCos |
a color for the variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afccol(p)
AFC plot of variables in 3D
Description
AFC plot of variables in 3D
Usage
e_afccol_3D(
modelo,
axes = c(1, 2, 3),
colorCol = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorCol |
a color for the variables well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorCos |
a color for variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afccol_3D(p)
AFCM biplot
Description
AFCM biplot
Usage
e_afcmbi(
modelo,
axes = c(1, 2),
colorInd = "steelblue",
colorVar = "forestgreen",
cos2Ind = 0,
cos2Var = 0,
colorIndCos = "firebrick",
colorVarCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
colorVar |
a color for the variables well represented. |
cos2Ind |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Var |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorIndCos |
a color for the individuals badly represented. |
colorVarCos |
a color for the variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmbi(p)
AFCM biplot in 3D
Description
AFCM biplot in 3D
Usage
e_afcmbi_3D(
modelo,
axes = c(1, 2, 3),
colorInd = "steelblue",
colorVar = "forestgreen",
cos2Ind = 0,
cos2Var = 0,
colorIndCos = "firebrick",
colorVarCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
colorVar |
a color for the variables well represented. |
cos2Ind |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Var |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorIndCos |
a color for individuals badly represented. |
colorVarCos |
a color for variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmbi_3D(p)
AFCM plot of categories
Description
AFCM plot of categories
Usage
e_afcmcat(
modelo,
axes = c(1, 2),
colorCat = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorCat |
a color for the categories well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the categories. |
colorCos |
a color for the categories badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmcat(p)
AFCM plot of categories in 3D
Description
AFCM plot of categories in 3D
Usage
e_afcmcat_3D(
modelo,
axes = c(1, 2, 3),
colorCat = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorCat |
a color for the categories well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the categories. |
colorCos |
a color for categories badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmcat_3D(p)
AFCM plot of individuals
Description
AFCM plot of individuals
Usage
e_afcmind(
modelo,
axes = c(1, 2),
colorInd = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmind(p)
AFCM plot of individuals in 3D
Description
AFCM plot of individuals in 3D
Usage
e_afcmind_3D(
modelo,
axes = c(1, 2, 3),
colorInd = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmind_3D(p)
AFCM plot of variables
Description
AFCM plot of variables
Usage
e_afcmvar(modelo, axes = c(1, 2), colorVar = "forestgreen")
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorVar |
a color for the variables. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmvar(p)
AFCM plot of variables in 3D
Description
AFCM plot of variables in 3D
Usage
e_afcmvar_3D(modelo, axes = c(1, 2, 3), colorVar = "forestgreen")
Arguments
modelo |
an object of class AFCM [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorVar |
a color for the variables well represented. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
data("poison", package = "FactoMineR")
poison.active <- poison[1:55, 5:15]
p <- FactoMineR::MCA(poison.active, graph = FALSE)
e_afcmvar_3D(p)
AFC plot of individuals
Description
AFC plot of individuals
Usage
e_afcrow(
modelo,
axes = c(1, 2),
colorRow = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorRow |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcrow(p)
AFC plot of individuals in 3D
Description
AFC plot of individuals in 3D
Usage
e_afcrow_3D(
modelo,
axes = c(1, 2, 3),
colorRow = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = T
)
Arguments
modelo |
an object of class CA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorRow |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::CA(iris[, -5], graph = FALSE)
e_afcrow_3D(p)
Balloonplot
Description
Balloonplot
Usage
e_balloon(datos)
Arguments
datos |
a data frame object. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
e_balloon(iris)
Barplot for categoric variable by clusters.
Description
Barplot for categoric variable by clusters.
Usage
e_cat(clusters, var, colores = NULL, escalar = T)
Arguments
clusters |
a vector specifying the cluster of each individual. |
var |
a factor column of a data.frame. |
colores |
a vector of color for each cluster. |
escalar |
a boolean value specifying if use percentage or real values. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_cat(clusters, iris[, 5], colores = c("steelblue", "pink", "forestgreen"))
Horizontal representation for centers of clusters.
Description
Horizontal representation for centers of clusters.
Usage
e_horiz(centros, colores = NULL)
Arguments
centros |
a data.frame object with the centers of the clusters. |
colores |
a vector of color for each cluster. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_horiz(c$real, c("steelblue", "pink", "forestgreen"))
Inertia plot of clusterization
Description
Inertia plot of clusterization
Usage
e_inercia(
data,
titulos = c("Inercia", "Inercia Inter-Clase", "Inercia Inter-Clase")
)
Arguments
data |
a data.frame object with the inertia values. |
titulos |
a character vector of length 3 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Jambu Elbow plot
Description
Jambu Elbow plot
Usage
e_jambu(data, max.clusters)
Arguments
data |
a data.frame object. |
max.clusters |
a numeric value specifying the number of times to generate the model. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
e_jambu(iris[, -5], 10)
PCA plot of individuals colored by clusters
Description
PCA plot of individuals colored by clusters
Usage
e_mapa(pca.model, clusters, colores = NULL, ejes = c(1, 2), etq = F)
Arguments
pca.model |
an object of class PCA [FactoMineR]. |
clusters |
a vector specifying the cluster of each individual. |
colores |
a vector of color for each cluster. |
ejes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_mapa(p, clusters, c("steelblue", "pink", "forestgreen"), etq = FALSE)
PCA plot of individuals colored by clusters
Description
PCA plot of individuals colored by clusters
Usage
e_mapa_3D(pca.model, clusters, colores = NULL, ejes = c(1, 2, 3), etq = F)
Arguments
pca.model |
an object of class PCA [FactoMineR]. |
clusters |
a vector specifying the cluster of each individual. |
colores |
a vector of color for each cluster. |
ejes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
e_mapa_3D(p, clusters, c("steelblue", "pink", "forestgreen"), etq = FALSE)
PCA biplot
Description
PCA biplot
Usage
e_pcabi(
modelo,
axes = c(1, 2),
colorInd = "steelblue",
colorVar = "forestgreen",
cos2Ind = 0,
cos2Var = 0,
colorIndCos = "firebrick",
colorVarCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = F
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
colorVar |
a color for the variables well represented. |
cos2Ind |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Var |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorIndCos |
a color for the individuals badly represented. |
colorVarCos |
a color for the variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcabi(p)
PCA biplot in 3D
Description
PCA biplot in 3D
Usage
e_pcabi_3D(
modelo,
axes = c(1, 2, 3),
colorInd = "steelblue",
colorVar = "forestgreen",
cos2Ind = 0,
cos2Var = 0,
colorIndCos = "firebrick",
colorVarCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados"),
etq = F
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
colorVar |
a color for the variables well represented. |
cos2Ind |
a numeric value from 0 to 1 specifying the quality of the individuals. |
cos2Var |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorIndCos |
a color for individuals badly represented. |
colorVarCos |
a color for variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcabi_3D(p)
PCA plot of individuals
Description
PCA plot of individuals
Usage
e_pcaind(
modelo,
axes = c(1, 2),
colorInd = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = F
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcaind(p)
PCA plot of individuals in 3D
Description
PCA plot of individuals in 3D
Usage
e_pcaind_3D(
modelo,
axes = c(1, 2, 3),
colorInd = "steelblue",
cos2 = 0,
colorCos = "firebrick",
titulos = c("Bien Representados", "Mal Representados"),
etq = F
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorInd |
a color for the individuals well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the individuals. |
colorCos |
a color for individuals badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
etq |
a boolean, whether to add label to graph or not. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcaind_3D(p)
PCA plot of variables
Description
PCA plot of variables
Usage
e_pcavar(
modelo,
axes = c(1, 2),
colorVar = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 2 specifying the dimensions to be plotted. |
colorVar |
a color for the variables well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorCos |
a color for the variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcavar(p)
PCA plot of variables in 3D
Description
PCA plot of variables in 3D
Usage
e_pcavar_3D(
modelo,
axes = c(1, 2, 3),
colorVar = "forestgreen",
cos2 = 0,
colorCos = "darkorchid",
titulos = c("Bien Representados", "Mal Representados")
)
Arguments
modelo |
an object of class PCA [FactoMineR]. |
axes |
a numeric vector of length 3 specifying the dimensions to be plotted. |
colorVar |
a color for the variables well represented. |
cos2 |
a numeric value from 0 to 1 specifying the quality of the variables. |
colorCos |
a color for variables badly represented. |
titulos |
a character vector of length 2 specifying the titles to use on legend. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
p <- FactoMineR::PCA(iris[, -5], graph = FALSE)
e_pcavar_3D(p)
Radar representation for centers of clusters.
Description
Radar representation for centers of clusters.
Usage
e_radar(centros, colores = NULL)
Arguments
centros |
a data.frame object with the centers of the clusters. |
colores |
a vector of color for each cluster. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_radar(c$porcentual, c("steelblue", "pink", "forestgreen"))
Silhouette plot
Description
Silhouette plot
Usage
e_silhouette(data, max.clusters)
Arguments
data |
a data.frame object. |
max.clusters |
a numeric value specifying the number of times to generate the model. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
e_silhouette(iris[, -5], 10)
Vertical representation for centers of clusters.
Description
Vertical representation for centers of clusters.
Usage
e_vert(centros, colores = NULL)
Arguments
centros |
a data.frame object with the centers of the clusters. |
colores |
a vector of color for each cluster. |
Value
echarts4r plot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Examples
clusters <- factor(kmeans(iris[, -5], 3)$cluster)
c <- calc.centros(iris[, -5], clusters)
e_vert(c$real, c("steelblue", "pink", "forestgreen"))
Dendrogram plot
Description
Dendrogram plot
Usage
gg_dendrograma(model, k, colors = NULL)
Arguments
model |
an object of class hclust. |
k |
a vector specifying the cluster of each individual. |
colors |
a vector of color for each cluster. |
Value
ggplot
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
Calculate total inertia
Description
Calculate total inertia
Usage
inercia.total(DF)
Arguments
DF |
a data.frame object. |
Value
numeric
Author(s)
Diego Jimenez <diego.jimenez@promidat.com>
acp Server Function
Description
acp Server Function
Usage
mod_acp_server(id, updateData, codedioma)
cj Server Function
Description
cj Server Function
Usage
mod_cj_server(id, updateData, codedioma)
kmedias Server Function
Description
kmedias Server Function
Usage
mod_kmedias_server(id, updateData, codedioma)
Run the Shiny Application
Description
Run the Shiny Application
Usage
run_app(...)
Arguments
... |
A series of options to be used inside the app. |
Examples
if(interactive()) {
run_app()
}