Summarise Continuous, Date and Categorical Variables, Check for Duplicates and Missing Data.

The sumvar package

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.<p>

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)