Creates correlation plots for numeric variables in a data frame, optionally incorporating factors for coloring and shaping points. It supports automatic detection of factors, customization of plot aesthetics, and the generation of separate legend files.
f_corplot(
data,
detect_factors = TRUE,
factor_table = FALSE,
color_factor = "auto",
shape_factor = "auto",
print_legend = TRUE,
fancy_names = NULL,
width = 15,
height = 15,
res = 600,
pointsize = 8,
legendname = NULL,
close_generated_files = FALSE,
open_generated_files = TRUE,
output_type = "word",
output_file = NULL,
output_dir = NULL,
save_in_wdir = FALSE
)Output is a 'Word' document with:
A correlation plot (output_file).
A legend (legendname) if applicable.
Using the option "output_type", it can also generate output in the form of: R Markdown code, 'pdf', or 'PNG' files. No value is returned to the R environment; instead, files are saved, and they are opened automatically if running on Windows.
A data.frame containing the dataset to be visualized. Must include at least two numeric variables.
Logical. If TRUE, the function automatically detects factor variables in the dataset for coloring and shaping points. Defaults to TRUE.
Logical. If TRUE, prints a detailed table about the properties of the converted factors to the console. Default is FALSE, so no property table will be printed to the console.
Character. The name of the factor variable to use for point colors. If set to "auto", it is automatically determined based on detected factors. Defaults to "auto".
Character. The name of the factor variable to use for point shapes. If set to "auto", it is automatically determined based on detected factors. Defaults to "auto".
Logical. If TRUE, a separate legend file is created and displayed. Defaults to TRUE.
Named character vector or NULL. Optional mapping of column names to more readable names for display in plots and legends.
Numeric. The width of the output plot in centimeters (default 15 cm).
Numeric. The height of the output plot in centimeters (default 15 cm).
Numeric. The resolution (in dots per inch) for the output plot image (defaults 1000 dpi).
Numeric. The base font size for text in the plot image. Defaults to 8.
Character string or NULL. The name of the file (omit extension) where the legend will be saved. If NULL, a default filename is generated based on the dataset name (dataname_legend_correlation_plot). Defaults to NULL.
Logical. If TRUE, closes open 'Word' files depending on the output format. This to be able to save the newly generated files. 'Pdf' files should also be closed before using the function and cannot be automatically closed. Default is FALSE.
Logical. If TRUE, Opens the generated 'Word' output files. This to directly view the results after creation. Files are stored in tempdir(). Default is TRUE.
Character string specifying the output format: "pdf", "word", "png" or "rmd". Default is "word".
Character string or NULL. The name of the file (omit extension) where the cor_plot will be saved. If NULL, a default filename is generated based on the dataset name (dataname_correlation_plot). Defaults to NULL.
Character string specifying the name of the directory of the output file. Default is tempdir(). If the output_file already contains a directory name output_dir can be omitted, if used it overwrites the dir specified in output_file.
Logical. If TRUE, saves the file in the working directory Default is FALSE, to avoid unintended changes to the global environment. If the output_dir is specified save_in_wdir is overwritten with output_dir.
Sander H. van Delden plantmind@proton.me
Factor Detection: If detect_factors is enabled, up to two factors are automatically detected from the dataset and used for coloring (color_factor) and shaping (shape_factor) points in the plot.
Customization: Users can manually specify which factors to use by setting color_factor and/or (shape_factor). Non-factor variables are converted into factors automatically, with a message indicating this conversion.
Legend Generation: A separate legend file is created when factors are used or if print_legend is explicitly set to TRUE.
The function uses numeric variables in the dataset for scatterplots and computes Pearson correlations displayed in the upper triangle of the correlation matrix.
This function requires [Pandoc](https://github.com/jgm/pandoc/releases/tag) (version 1.12.3 or higher), a universal document converter.
Windows: Install Pandoc and ensure the installation folder
(e.g., "C:/Users/your_username/AppData/Local/Pandoc") is added to your system PATH.
macOS: If using Homebrew, Pandoc is typically installed in "/usr/local/bin". Alternatively, download the .pkg installer and verify that the binary’s location is in your PATH.
Linux: Install Pandoc through your distribution’s package manager (commonly installed in "/usr/bin" or "/usr/local/bin") or manually, and ensure the directory containing Pandoc is in your PATH.
If Pandoc is not found, this function may not work as intended.
# Example usage:
data("mtcars")
mtcars_sub <- subset(mtcars, select = -c(am, qsec, vs))
# Customizing factors:
f_corplot(mtcars_sub,
shape_factor = "cyl",
color_factor = "gear",
output_type = "png",
open_generated_files = FALSE
)
# Output to MS Word and add fancy column names, only adjusting two of the four variable names.
data(iris)
fancy_names <- c(Sepal.Length = "Sepal Length (cm)", Sepal.Width = "Sepal Width (cm)")
f_corplot(iris,
fancy_names = fancy_names,
output_type = "word",
open_generated_files = FALSE
)
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