Nothing
inst/doc/procs-means.R
In procs: Recreates Some 'SAS®' Procedures in 'R'
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Create sample data
# dat <- read.table(header = TRUE,
# text = 'x y z g
# 6 A 60 P
# 6 A 70 P
# 2 A 100 P
# 2 B 10 P
# 3 B 67 Q
# 2 C 81 Q
# 3 C 63 Q
# 5 C 55 Q')
#
# # View sample data
# dat
# x y z g
# 1 6 A 60 P
# 2 6 A 70 P
# 3 2 A 100 P
# 4 2 B 10 P
# 5 3 B 67 Q
# 6 2 C 81 Q
# 7 3 C 63 Q
# 8 5 C 55 Q
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Turn off printing for CRAN checks
# options("procs.print" = FALSE)
#
# # No parameters
# proc_means(dat)
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Specific variable
# proc_means(dat, var = x)
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Custom statistics options
# proc_means(dat, stats = v(median, sum, q1, q3))
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Output dataset using "report" option
# res1 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = report)
#
# # View results
# res1
# # VAR MEDIAN SUM Q1 Q3
# # 1 x 3 29 2.0 5.5
# # 2 z 65 506 57.5 75.5
#
#
# # Output dataset using "out" option
# res2 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = out)
#
# # View results
# res2
# # TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 0 8 x 3 29 2.0 5.5
# # 2 0 8 z 65 506 57.5 75.5
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
#
# # Turn off TYPE and FREQ variables
# res3 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = all,
# options = v(notype, nofreq))
#
# # View results
# res3
# # VAR MEDIAN SUM Q1 Q3
# # 1 x 3 29 2.0 5.5
# # 2 z 65 506 57.5 75.5
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Class grouping
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# class = y, options = v(maxdec = 4))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - class
# res1
# # CLASS TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 <NA> 0 8 x 3.0 29 2.0 5.5
# # 2 <NA> 0 8 z 65.0 506 57.5 75.5
# # 3 A 1 3 x 6.0 14 2.0 6.0
# # 4 A 1 3 z 70.0 230 60.0 100.0
# # 5 B 1 2 x 2.5 5 2.0 3.0
# # 6 B 1 2 z 38.5 77 10.0 67.0
# # 7 C 1 3 x 3.0 10 2.0 5.0
# # 8 C 1 3 z 63.0 199 55.0 81.0
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = y, options = v(maxdec = 4))
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - by
# res2
# # BY TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 A 0 3 x 6.0 14 2 6
# # 2 A 0 3 z 70.0 230 60 100
# # 3 B 0 2 x 2.5 5 2 3
# # 4 B 0 2 z 38.5 77 10 67
# # 5 C 0 3 x 3.0 10 2 5
# # 6 C 0 3 z 63.0 199 55 81
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Class grouping - two variables
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# class = v(g, y), options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - two class variables
# res1
# # CLASS1 CLASS2 TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 <NA> <NA> 0 8 x 3.0 29 2.0 5.5
# # 2 <NA> <NA> 0 8 z 65.0 506 57.5 75.5
# # 3 <NA> A 1 3 x 6.0 14 2.0 6.0
# # 4 <NA> A 1 3 z 70.0 230 60.0 100.0
# # 5 <NA> B 1 2 x 2.5 5 2.0 3.0
# # 6 <NA> B 1 2 z 38.5 77 10.0 67.0
# # 7 <NA> C 1 3 x 3.0 10 2.0 5.0
# # 8 <NA> C 1 3 z 63.0 199 55.0 81.0
# # 9 P <NA> 2 4 x 4.0 16 2.0 6.0
# # 10 P <NA> 2 4 z 65.0 240 35.0 85.0
# # 11 Q <NA> 2 4 x 3.0 13 2.5 4.0
# # 12 Q <NA> 2 4 z 65.0 266 59.0 74.0
# # 13 P A 3 3 x 6.0 14 2.0 6.0
# # 14 P A 3 3 z 70.0 230 60.0 100.0
# # 15 P B 3 1 x 2.0 2 2.0 2.0
# # 16 P B 3 1 z 10.0 10 10.0 10.0
# # 17 Q B 3 1 x 3.0 3 3.0 3.0
# # 18 Q B 3 1 z 67.0 67 67.0 67.0
# # 19 Q C 3 3 x 3.0 10 2.0 5.0
# # 20 Q C 3 3 z 63.0 199 55.0 81.0
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping - two variables
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = v(g, y), options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - two by variables
# res2
# # BY1 BY2 TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 P A 0 3 x 6 14 2 6
# # 2 P A 0 3 z 70 230 60 100
# # 3 P B 0 1 x 2 2 2 2
# # 4 P B 0 1 z 10 10 10 10
# # 5 Q B 0 1 x 3 3 3 3
# # 6 Q B 0 1 z 67 67 67 67
# # 7 Q C 0 3 x 3 10 2 5
# # 8 Q C 0 3 z 63 199 55 81
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping - by and class
# res3 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = g,
# class = y,
# options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - by and class
# res3
# # BY CLASS TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 P <NA> 0 4 x 4 16 2.0 6
# # 2 P <NA> 0 4 z 65 240 35.0 85
# # 3 P A 1 3 x 6 14 2.0 6
# # 4 P A 1 3 z 70 230 60.0 100
# # 5 P B 1 1 x 2 2 2.0 2
# # 6 P B 1 1 z 10 10 10.0 10
# # 7 Q <NA> 0 4 x 3 13 2.5 4
# # 8 Q <NA> 0 4 z 65 266 59.0 74
# # 9 Q B 1 1 x 3 3 3.0 3
# # 10 Q B 1 1 z 67 67 67.0 67
# # 11 Q C 1 3 x 3 10 2.0 5
# # 12 Q C 1 3 z 63 199 55.0 81
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Shape wide
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = wide)
#
# # Wide results
# res1
# # TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 0 8 x 3 29 2.0 5.5
# # 2 0 8 z 65 506 57.5 75.5
#
# # Shape long
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = long)
#
# # Long results
# res2
# # TYPE FREQ STAT x z
# # 1 0 8 MEDIAN 3.0 65.0
# # 2 0 8 SUM 29.0 506.0
# # 3 0 8 Q1 2.0 57.5
# # 4 0 8 Q3 5.5 75.5
#
# # Shape stacked
# res3 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = stacked)
#
# # Stacked results
# res3
# # TYPE FREQ VAR STAT VALUES
# # 1 0 8 x MEDIAN 3.0
# # 2 0 8 x SUM 29.0
# # 3 0 8 x Q1 2.0
# # 4 0 8 x Q3 5.5
# # 5 0 8 z MEDIAN 65.0
# # 6 0 8 z SUM 506.0
# # 7 0 8 z Q1 57.5
# # 8 0 8 z Q3 75.5
#
Try the procs package in your browser
Any scripts or data that you put into this service are public.
procs documentation built on May 29, 2024, 2:12 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Create sample data
# dat <- read.table(header = TRUE,
# text = 'x y z g
# 6 A 60 P
# 6 A 70 P
# 2 A 100 P
# 2 B 10 P
# 3 B 67 Q
# 2 C 81 Q
# 3 C 63 Q
# 5 C 55 Q')
#
# # View sample data
# dat
# x y z g
# 1 6 A 60 P
# 2 6 A 70 P
# 3 2 A 100 P
# 4 2 B 10 P
# 5 3 B 67 Q
# 6 2 C 81 Q
# 7 3 C 63 Q
# 8 5 C 55 Q
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Turn off printing for CRAN checks
# options("procs.print" = FALSE)
#
# # No parameters
# proc_means(dat)
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Specific variable
# proc_means(dat, var = x)
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Custom statistics options
# proc_means(dat, stats = v(median, sum, q1, q3))
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Output dataset using "report" option
# res1 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = report)
#
# # View results
# res1
# # VAR MEDIAN SUM Q1 Q3
# # 1 x 3 29 2.0 5.5
# # 2 z 65 506 57.5 75.5
#
#
# # Output dataset using "out" option
# res2 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = out)
#
# # View results
# res2
# # TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 0 8 x 3 29 2.0 5.5
# # 2 0 8 z 65 506 57.5 75.5
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
#
# # Turn off TYPE and FREQ variables
# res3 <- proc_means(dat,
# stats = v(median, sum, q1, q3),
# output = all,
# options = v(notype, nofreq))
#
# # View results
# res3
# # VAR MEDIAN SUM Q1 Q3
# # 1 x 3 29 2.0 5.5
# # 2 z 65 506 57.5 75.5
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Class grouping
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# class = y, options = v(maxdec = 4))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - class
# res1
# # CLASS TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 <NA> 0 8 x 3.0 29 2.0 5.5
# # 2 <NA> 0 8 z 65.0 506 57.5 75.5
# # 3 A 1 3 x 6.0 14 2.0 6.0
# # 4 A 1 3 z 70.0 230 60.0 100.0
# # 5 B 1 2 x 2.5 5 2.0 3.0
# # 6 B 1 2 z 38.5 77 10.0 67.0
# # 7 C 1 3 x 3.0 10 2.0 5.0
# # 8 C 1 3 z 63.0 199 55.0 81.0
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = y, options = v(maxdec = 4))
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - by
# res2
# # BY TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 A 0 3 x 6.0 14 2 6
# # 2 A 0 3 z 70.0 230 60 100
# # 3 B 0 2 x 2.5 5 2 3
# # 4 B 0 2 z 38.5 77 10 67
# # 5 C 0 3 x 3.0 10 2 5
# # 6 C 0 3 z 63.0 199 55 81
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Class grouping - two variables
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# class = v(g, y), options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - two class variables
# res1
# # CLASS1 CLASS2 TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 <NA> <NA> 0 8 x 3.0 29 2.0 5.5
# # 2 <NA> <NA> 0 8 z 65.0 506 57.5 75.5
# # 3 <NA> A 1 3 x 6.0 14 2.0 6.0
# # 4 <NA> A 1 3 z 70.0 230 60.0 100.0
# # 5 <NA> B 1 2 x 2.5 5 2.0 3.0
# # 6 <NA> B 1 2 z 38.5 77 10.0 67.0
# # 7 <NA> C 1 3 x 3.0 10 2.0 5.0
# # 8 <NA> C 1 3 z 63.0 199 55.0 81.0
# # 9 P <NA> 2 4 x 4.0 16 2.0 6.0
# # 10 P <NA> 2 4 z 65.0 240 35.0 85.0
# # 11 Q <NA> 2 4 x 3.0 13 2.5 4.0
# # 12 Q <NA> 2 4 z 65.0 266 59.0 74.0
# # 13 P A 3 3 x 6.0 14 2.0 6.0
# # 14 P A 3 3 z 70.0 230 60.0 100.0
# # 15 P B 3 1 x 2.0 2 2.0 2.0
# # 16 P B 3 1 z 10.0 10 10.0 10.0
# # 17 Q B 3 1 x 3.0 3 3.0 3.0
# # 18 Q B 3 1 z 67.0 67 67.0 67.0
# # 19 Q C 3 3 x 3.0 10 2.0 5.0
# # 20 Q C 3 3 z 63.0 199 55.0 81.0
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping - two variables
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = v(g, y), options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - two by variables
# res2
# # BY1 BY2 TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 P A 0 3 x 6 14 2 6
# # 2 P A 0 3 z 70 230 60 100
# # 3 P B 0 1 x 2 2 2 2
# # 4 P B 0 1 z 10 10 10 10
# # 5 Q B 0 1 x 3 3 3 3
# # 6 Q B 0 1 z 67 67 67 67
# # 7 Q C 0 3 x 3 10 2 5
# # 8 Q C 0 3 z 63 199 55 81
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # By grouping - by and class
# res3 <- proc_means(dat, stats = v(median, sum, q1, q3),
# by = g,
# class = y,
# options = v(maxdec = 0))
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # View results - by and class
# res3
# # BY CLASS TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 P <NA> 0 4 x 4 16 2.0 6
# # 2 P <NA> 0 4 z 65 240 35.0 85
# # 3 P A 1 3 x 6 14 2.0 6
# # 4 P A 1 3 z 70 230 60.0 100
# # 5 P B 1 1 x 2 2 2.0 2
# # 6 P B 1 1 z 10 10 10.0 10
# # 7 Q <NA> 0 4 x 3 13 2.5 4
# # 8 Q <NA> 0 4 z 65 266 59.0 74
# # 9 Q B 1 1 x 3 3 3.0 3
# # 10 Q B 1 1 z 67 67 67.0 67
# # 11 Q C 1 3 x 3 10 2.0 5
# # 12 Q C 1 3 z 63 199 55.0 81
#
## ----eval=FALSE, echo=TRUE----------------------------------------------------
# # Shape wide
# res1 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = wide)
#
# # Wide results
# res1
# # TYPE FREQ VAR MEDIAN SUM Q1 Q3
# # 1 0 8 x 3 29 2.0 5.5
# # 2 0 8 z 65 506 57.5 75.5
#
# # Shape long
# res2 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = long)
#
# # Long results
# res2
# # TYPE FREQ STAT x z
# # 1 0 8 MEDIAN 3.0 65.0
# # 2 0 8 SUM 29.0 506.0
# # 3 0 8 Q1 2.0 57.5
# # 4 0 8 Q3 5.5 75.5
#
# # Shape stacked
# res3 <- proc_means(dat, stats = v(median, sum, q1, q3),
# output = stacked)
#
# # Stacked results
# res3
# # TYPE FREQ VAR STAT VALUES
# # 1 0 8 x MEDIAN 3.0
# # 2 0 8 x SUM 29.0
# # 3 0 8 x Q1 2.0
# # 4 0 8 x Q3 5.5
# # 5 0 8 z MEDIAN 65.0
# # 6 0 8 z SUM 506.0
# # 7 0 8 z Q1 57.5
# # 8 0 8 z Q3 75.5
#
Try the procs package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.