If you use R then you are very familiar with the SUMMARY function.

If you use R then you are very familiar with the name Hadley Wickham. He has produced some really cool packages for R.

He has produced a new R package and function that complements the commonly used SUMMARY R function.

The following outlines how you can install this new R package from GitHub (Hadley's GitHub is https://github.com/hadley/).

Install the R devtools package. This will allow you to download the package code from GitHub.

install.packages("devtools")

Install the package from Hadley's GitHub repository.

devtools::install_github("hadley/precis")

Load the library.

library(precis)

The following displays information produced by the SUMMARY and the PRECIS function.

> summary(mtcars)
mpg cyl disp hp drat wt
Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0 Min. :2.760 Min. :1.513
1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5 1st Qu.:3.080 1st Qu.:2.581
Median :19.20 Median :6.000 Median :196.3 Median :123.0 Median :3.695 Median :3.325
Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7 Mean :3.597 Mean :3.217
3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0 3rd Qu.:3.920 3rd Qu.:3.610
Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0 Max. :4.930 Max. :5.424
qsec vs am gear carb
Min. :14.50 Min. :0.0000 Min. :0.0000 Min. :3.000 Min. :1.000
1st Qu.:16.89 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
Median :17.71 Median :0.0000 Median :0.0000 Median :4.000 Median :2.000
Mean :17.85 Mean :0.4375 Mean :0.4062 Mean :3.688 Mean :2.812
3rd Qu.:18.90 3rd Qu.:1.0000 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
Max. :22.90 Max. :1.0000 Max. :1.0000 Max. :5.000 Max. :8.000
> precis(mtcars)
# data.frame [32 x 11]
name type precis
1    mpg   dbl  10.4 [ 15.4 ( 19.2)  22.8]  33.9
2 cyl dbl 4 (11) 6 (7) 8 (14)
3 disp dbl 71.1 [121.0 (196.0) 334.0] 472.0
4 hp dbl 52 [ 96 ( 123) 180] 335
5 drat dbl 2.76 [ 3.08 ( 3.70) 3.92] 4.93
6 wt dbl 1.51 [ 2.54 ( 3.32) 3.65] 5.42
7 qsec dbl 14.5 [ 16.9 ( 17.7) 18.9] 22.9
8 vs dbl 0 (18) 1 (14)
9 am dbl 0 (19) 1 (13)
10 gear dbl 3 (15) 4 (12) 5 (5)
11 carb dbl 1 [ 2 ( 2) 4] 8
> precis(mtcars, histogram=TRUE)
# data.frame [32 x 11]
name type precis

1 mpg dbl 10.4 ▂▁▇▃▅▅▂▂▁▁▂▂ 33.9
2 cyl dbl 4 ▅▁▁▁▁▁▁▁▁▃▁▁▁▁▁▁▁▁▁▇ 8
3 disp dbl 71.1 ▅▁▁▃▇▂▁▁▁▁▃▁▃▁▅▁▁▁▁▁▁ 472.0
4 hp dbl 52 ▁▅▅▇▂▂▇▁▂▁▂▁▁▁▁ 335
5 drat dbl 2.76 ▂▂▇▂▁▅▇▃▂▁▁▁ 4.93
6 wt dbl 1.51 ▁▁▂▂▁▁▂▁▂▁▇▂▂▁▁▁▁▁▁▂▁ 5.42
7 qsec dbl 14.5 ▂▂▁▁▃▇▅▁▇▂▂▂▁▁▁▁▁ 22.9
8 vs dbl 0 ▇▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▅ 1
9 am dbl 0 ▇▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▅ 1
10 gear dbl 3 ▇▁▁▁▁▁▁▁▁▅▁▁▁▁▁▁▁▁▁▂ 5
11 carb dbl 1 ▅▇▁▂▁▇▁▁▁▁▁▁▁▁ 8

 

About the Author

Brendan Tierney

Brendan Tierney, Oracle ACE Director, is an independent consultant and lectures on Data Mining and Advanced Databases in the Dublin Institute of Technology in Ireland. He has 22+ years of extensive experience working in the areas of Data Mining, Data Warehousing, Data Architecture and Database Design. Brendan has worked on projects in Ireland, UK, Belgium and USA and is the editor of the UKOUG Oracle Scene magazine and deputy chair of the OUG Ireland BI SIG. Brendan is a regular speaker at conferences across Europe and the USA and has written technical articles for OTN, Oracle Scene, IOUG SELECT Journal and ODTUG Technical Journal.

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