Function reference • vdocs

General Visualization Functions A library of general functions for making beautiful visualizations.
ggplot Wrappers Function wrappers around common ggplot geoms.
`plot_bar()`	Plot pretty bar plots using custom ggplot theme.
`plot_boxplot()`	Plot pretty boxplots using custom ggplot theme.
`plot_density()`	Plot pretty kernel density plots using custom ggplot theme.
`plot_histogram()`	Plot pretty histogram plots using custom ggplot theme.
`plot_line()`	Plot pretty line plots using custom ggplot theme.
`plot_point()`	Plot pretty scatter plots using custom ggplot theme.
Exploratory Data Analysis (EDA) Plots Functions to create common EDA plots.
`plot_data_distribution()`	Plots summary of data distribution
`plot_data_heatmap()`	Plots heatmap of (X, y) data
`plot_data_split()`	Plots summary of data split distributions
`plot_hclust()`	Plot pretty hierarchical clustering dendrograms.
`plot_heatmap()` `plot_hclust_heatmap()` `plot_cor_heatmap()`	Plot (clustered) heatmaps using pretty ggplot theme.
`plot_pairs()`	Plot pretty pair plots using custom ggplot theme.
`plot_pca()`	Plot pretty PCA plots using custom ggplot theme.
`plot_horizontal_dotplot()`	Plot horizontal dot plot.
Exploratory Data Analysis (EDA) Tables Functions to create common EDA tables.
`get_data_summary()`	Summary table of (X, y) data
`get_data_types()`	Summary table of data types in (X, y)
`get_data_dimensions()`	Text summary of the data dimensions
Data Cleaning and Preprocessing Functions A library of functions to preprocess or clean data.
`split_data()`	Splits data into training, validation, and test sets
`filter_cols_by_var()`	Filter out columns in data to reduce dimension.
`remove_na_cols()` `remove_constant_cols()` `remove_duplicate_cols()`	Basic cleaning functions to remove columns in data.
Modeling Functions Functions to fit, predict, evaluate, and interpret models using caret, h2o, or tidymodels backends.
`fit_caret()` `fit_h2o()` `fit_tidymodels()`	Wrappers for fitting a model using common modeling backends
`fit_models()`	Wrapper for fitting models using common modeling backends
`print_caret_fit()` `print_h2o_fit()` `print_tidymodels_fit()`	Wrappers for printing model fits from common modeling backends
`predict_caret()` `predict_h2o()` `predict_tidymodels()`	Wrappers for making predictions from a fitted model using common modeling backends
`predict_models()`	Wrapper for making predictions from fitted models using common modeling backends
`evaluate_models()`	Wrapper for evaluating predictions from fitted models using common modeling backends
`interpret_caret()` `interpret_h2o()` `interpret_tidymodels()`	Wrappers for extracting feature importances from a fitted model using common modeling backends
`interpret_models()`	Wrapper for extracting feature importances from fitted models using common modeling backends
`plot_feature_importance()` `plot_feature_importance_pair()` `plot_feature_importance_stability()`	Feature importance plots
vdocs and Rmarkdown Utilities Utility functions for creating the vdocs Rmarkdown template.
`veridical()`	veridical design - bootstrap HTML output format
`load_saved_responses()`	Load in saved responses in vdocs Rmd template
`load_file()`	Load in data file
`print_fit_results()`	Print fit results summary
`print_eval_results()`	Display evaluation results summary in Rmd
`validate_data()`	Validate data inputs for (X, y)
`validate_data_split()`	Validate inputs for data splitting proportions
`vdocs_knitr_setup()`	Knitr options setup for vdocs Rmd template

Reference

General Visualization Functions

ggplot Wrappers

Exploratory Data Analysis (EDA) Plots

Exploratory Data Analysis (EDA) Tables

Data Cleaning and Preprocessing Functions

Modeling Functions

vdocs and Rmarkdown Utilities