Provides Batch Functions and Visualisation for Basic Statistical Procedures
Perform multiple aov() functions with optional data transformation, ...
f_bestNormalize: Automated Data Normalization with bestNormalize
f_boxcox: A User-Friendly Box-Cox Transformation
Generate a Boxplot Report of a data.frame
Chi-squared Test with Post-hoc Analysis
f_clear: Clear Various Aspects of the R Environment
Conditional Rounding for Numeric Values
Correlation Plots with Factor Detection and Customization
Convert multiple columns to Factors in a data frame
Perform multiple glm() functions with diagnostics, assumption checki...
Plot a Histogram with an Overlaid Normal Curve
Perform multiple Kruskal-Wallis tests with a user-friendly output file...
Install and Load Multiple R Packages
Compare Two Statistical Models
Open a File with the Default Application
Apply a black or white 'RStudio' Theme and Zoom Level
Plot an f_bestNormalize object
Plot an f_boxcox object
Print method for f_summary objects
Fancy Pander Table Output
Normal Q-Q Plot with Confidence Bands
Rename Specific Columns in a Data Frame
Rename Elements of a Vector Based on a Mapping
Set Working Directory Based on Current File or Specified Path
Summarize a Data Frame with Grouping Variables
Designed to streamline data analysis and statistical testing, reducing the length of R scripts while generating well-formatted outputs in 'pdf', 'Microsoft Word', and 'Microsoft Excel' formats. In essence, the package contains functions which are sophisticated wrappers around existing R functions that are called by using 'f_' (user f_riendly) prefix followed by the normal function name. This first version of the 'rfriend' package focuses primarily on data exploration, including tools for creating summary tables, f_summary(), performing data transformations, f_boxcox() in part based on 'MASS/boxcox' and 'rcompanion', and f_bestNormalize() which wraps and extends functionality from the 'bestNormalize' package. Furthermore, 'rfriend' can automatically (or on request) generate visualizations such as boxplots, f_boxplot(), QQ-plots, f_qqnorm(), histograms f_hist(), and density plots. Additionally, the package includes four statistical test functions: f_aov(), f_kruskal_test(), f_glm(), f_chisq_test for sequential testing and visualisation of the 'stats' functions: aov(), kruskal.test(), glm() and chisq.test. These functions support testing multiple response variables and predictors, while also handling assumption checks, data transformations, and post hoc tests. Post hoc results are automatically summarized in a table using the compact letter display (cld) format for easy interpretation. The package also provides a function to do model comparison, f_model_comparison(), and several utility functions to simplify common R tasks. For example, f_clear() clears the workspace and restarts R with a single command; f_setwd() sets the working directory to match the directory of the current script; f_theme() quickly changes 'RStudio' themes; and f_factors() converts multiple columns of a data frame to factors, and much more. If you encounter any issues or have feature requests, please feel free to contact me via email.