simple.summary

=====

Both dplyr and data.table have made the our data analytical job a lot easier. However, I still find that sometimes I need to type the same codes again and again to do some very simple jobs in my everyday life. For example, I found that I need to code a lot to fix the formatting to put those result into a table and get displayed through rmarkdown or shiny. This package is built to save us, at least people who are working with small-medium size data, a little bit more typing time.

To install

Type

    if (packageVersion("devtools") < 1.6) {
      install.packages("devtools")
    }
    devtools::install_github("haozhu233/simple.summary")

To use

You are recommended to use dplyr together with this package. I haven't tested data.table but it should work at a minimum base as well.

A simple exmaple is provided here.

library(dplyr)
library(simple.summary)
  mtcars %>% 
    group_by(am) %>% 
      select(cyl, gear) %>% 
        simple_summary_categorical()

And the output will look like the following table. For those who are not familar with the dplyr(pipe) syntax, this piece of script will do categorical analyses to variable cyl and gear in the mtcars dataset grouped by variable am.

Source: local data frame [10 x 4]

   am      x freq Percentage
1   0  cyl_4    3      0.158
2   0  cyl_6    4      0.211
3   0  cyl_8   12      0.632
4   1  cyl_4    8      0.615
5   1  cyl_6    3      0.231
6   1  cyl_8    2      0.154
7   0 gear_3   15      0.789
8   0 gear_4    4      0.211
9   1 gear_4    8      0.615
10  1 gear_5    5      0.385

Issues

If you ever find any issues, please feel free to report it in the issues tracking part on github. https://github.com/haozhu233/simple.summary/issues.

Thanks for using this package!