# ggcorrmat

##### Visualization of a correlalogram (or correlation matrix) using 'ggplot2'/'ggcorrplot'

Visualization of a correlalogram (or correlation matrix) using 'ggplot2'/'ggcorrplot'

##### Usage

```
ggcorrmat(data, cor.vars, cor.vars.names = NULL, output = "plot",
type = "full", method = "square", corr.method = "pearson", digits = 2,
sig.level = 0.05, hc.order = FALSE, hc.method = "complete",
lab = TRUE, colors = c("#6D9EC1", "white", "#E46726"),
outline.color = "black", ggtheme = ggplot2::theme_gray, title = NULL,
subtitle = NULL, caption = NULL, lab_col = "black", lab_size = 4.5,
insig = "pch", pch = 4, pch.col = "blue", pch.cex = 10, tl.cex = 12,
tl.col = "black", tl.srt = 45)
```

##### Arguments

- data
Dataframe from which variables specified are preferentially to be taken.

- cor.vars
List of vairables for which the correlation matrix is to be computed and visualized.

- cor.vars.names
Optional list of names to be used for

`cor.vars`

. The names should be entered in the same order.- output
Expected output from this function: "plot" (visualization matrix) or "correlations" (correlation matrix) or #' "p-values" (matrix of p-values).

- type
Character, "full" (default), "upper" or "lower", display full matrix, lowe triangular or upper triangular matrix.

- method
Character argument that decides the visualization method of correlation matrix to be used. Allowed values are "square" (default), "circle".

- corr.method
A character string indicating which correlation coefficient is to be computed ("pearson" (default) or "kendall", or "spearman").

- digits
Decides the number of decimal digits to be added into the plot (Default: 2).

- sig.level
Significance level (Dafault: 0.05). If the p-value in p-mat is bigger than sig.level, then the correspondi#' ng correlation coefficient is regarded as insignificant.

- hc.order
Logical value. If

`TRUE`

, correlation matrix will be hc.ordered using`hclust`

function (Default is`FALSE`

).- hc.method
The agglomeration method to be used in

`hclust`

(see`?hclust`

).- lab
Logical value. If

`TRUE`

, correlation coefficient values will be displayed in the plot.- colors
A vector of 3 colors for low, mid, and high correlation values.

- outline.color
The outline color of square or circle. Default value is "gray".

- ggtheme
A function,

`ggplot2`

theme name. Default value is theme_minimal. Allowed values are the official`ggplot2`

themes including`theme_gray`

,`theme_bw`

,`theme_minimal`

,`theme_classic`

,`theme_void`

, etc.- title
The text for the plot title.

- subtitle
The text for the plot subtitle.

- caption
The text for the plot caption.

- lab_col
Color to be used for the correlation coefficient labels (applicable only when

`lab = TRUE`

).- lab_size
Size to be used for the correlation coefficient labels (applicable only when

`lab = TRUE`

).- insig
Character used to show specialized insignificant correlation coefficients ("pch" (default) or "blank"). If "blank", the corresponding glyphs will be removed; if "pch" is used, characters (see

`pch`

for details) will be added on #' the corresponding glyphs.- pch
Decides the glyphs to be used for insignificant correlation coefficients (only valid when

`insig = "pch"`

). Default value is 4.- pch.col, pch.cex
The color and the cex (size) of

`pch`

(only valid when`insig = "pch"`

). Defaults are`pch.col = "blue"`

and`pch.cex = 10`

.- tl.cex, tl.col, tl.srt
The size, the color, and the string rotation of text label (variable names).

##### Value

Correlation matrix plot or correlation coefficient matrix or matrix of p-values.

##### Examples

```
# NOT RUN {
library(datasets)
library(ggplot2)
# to get the correlalogram
ggstatsplot::ggcorrmat(
data = datasets::iris,
cor.vars = c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width)
)
# to get the correlation matrix
ggstatsplot::ggcorrmat(
data = datasets::iris,
cor.vars = c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width),
output = "correlations"
)
# setting output = "p-values" will return the p-value matrix
# modifying few elements of the correlation matrix by changing function defaults
ggstatsplot::ggcorrmat(
data = datasets::iris,
cor.vars = c(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width),
sig.level = 0.01,
ggtheme = ggplot2::theme_gray,
hc.order = TRUE, type = "lower", outline.col = "white",
title = "Dataset: Iris",
subtitle = "The threshold of significance = 0.01"
)
# }
```

*Documentation reproduced from package ggstatsplot, version 0.0.1, License: GPL-3 | file LICENSE*