Package index

Analysis

Functions for describing and analyzing categorical and metric data. Report functions call table, plot, and effect functions.

report_counts()

Create table and plot for categorical variables

report_metrics()

Create table and plot for metric variables

tab_counts() experimental

Output a frequency table

tab_metrics() experimental

Output a table with distribution parameters

plot_counts() experimental

Output a frequency plot

plot_metrics() experimental

Output a plot with distribution parameters such as the mean values

effect_counts() experimental

Output effect sizes and test statistics for count data

effect_metrics() experimental

Output effect sizes and test statistics for metric data

Labeling

Manage and apply variable labels.

codebook()

Get variable and value labels from a data set

labs_apply() experimental

Set column and value labels

labs_clear() experimental

Remove all comments from the selected columns

labs_store() experimental

Get the current codebook and store it in the codebook attribute.

labs_restore() experimental

Restore labels from the codebook store in the codebook attribute.

Styling

Functions for customized visual styling and formatting.

theme_vlkr()

Define a default theme for volker plots

html_report()

Volker style HTML document format

pdf_report()

Volker style PDF document format

Data preparation

Functions for data preparation and calculation.

add_index() experimental

Calculate the mean value of multiple items

add_clusters() experimental

Add cluster number to a data frame

add_factors() experimental

Add PCA columns along with summary statistics (KMO and Bartlett test) to a data frame

Example data

chatgpt

ChatGPT Adoption Dataset CG-GE-APR23