Summarise Continuous and Categorical Variables, Check for Duplicates and Missing Data • sumvar

The sumvar package quickly explores continuous and categorical variables.
sumvar aims to bring the ease and simplicity of the “sum” and “tab” functions from stata, to R.

dist_sum() is for exploring a continuous variable. Can stratify by a grouping variable, for example: df %>% dist_sum (var, group).
dist_date() is for dates, use the same way as dist_sum().
tab1() is to explore a single categorical variable, for example: df %>% tab1(var)
tab() is for a twoway table from two categorical variables, for example: df %>% tab(var1, var2).
dup() explores duplicates and missing values, across a single variable, or a whole database

Both dist_sum() and tab() include options for performing frequentist hypothesis tests, have a look at the help files.

All functions are tidyverse/dplyr-friendly and accept the %>% pipe from a tibble or data frame, outputting results as a tibble. You can save and further manipulate outputs, e.g. summary <- df %>% dist_sum(var)