Type: Package
Title: Data and Functions for Web-Based Analysis
Version: 0.1.5
Imports: moonBook, ggplot2, shiny, stringr, sjlabelled, flextable, magrittr, rrtable, dplyr, tibble, purrr, rlang, tidyr, tidyselect, psych, grid, ztable, ggforce, scales, vcd
URL: https://github.com/cardiomoon/webr
BugReports: https://github.com/cardiomoon/webr/issues
Description: Several analysis-related functions for the book entitled "Web-based Analysis without R in Your Computer"(written in Korean, ISBN 978-89-5566-185-9) by Keon-Woong Moon. The main function plot.htest() shows the distribution of statistic for the object of class 'htest'.
Depends: R (≥ 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Suggests: testthat, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-01-26 13:59:13 UTC; cardiomoon
Author: Keon-Woong Moon [aut, cre], Tommaso Martino [ctb]
Maintainer: Keon-Woong Moon <cardiomoon@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-26 14:20:02 UTC

Extract bivariate variables

Description

Extract bivariate variables

Usage

BiVar(df)

Arguments

df

a data.frame

Extract continuous variables

Description

Extract continuous variables

Usage

ContinuousVar(df)

Arguments

df

a data.frame

Extract categorical variables

Description

Extract categorical variables

Usage

GroupVar(df, max.ylev = 20)

Arguments

df

a data.frame

max.ylev

maximal length of unique values of catergorical variables

Draw a PieDonut plot

Description

Draw a PieDonut plot

Usage

PieDonut(
  data,
  mapping,
  start = getOption("PieDonut.start", 0),
  addPieLabel = TRUE,
  addDonutLabel = TRUE,
  showRatioDonut = TRUE,
  showRatioPie = TRUE,
  ratioByGroup = TRUE,
  showRatioThreshold = getOption("PieDonut.showRatioThreshold", 0.02),
  labelposition = getOption("PieDonut.labelposition", 2),
  labelpositionThreshold = 0.1,
  r0 = getOption("PieDonut.r0", 0.3),
  r1 = getOption("PieDonut.r1", 1),
  r2 = getOption("PieDonut.r2", 1.2),
  explode = NULL,
  selected = NULL,
  explodePos = 0.1,
  color = "white",
  pieAlpha = 0.8,
  donutAlpha = 1,
  maxx = NULL,
  showPieName = TRUE,
  showDonutName = FALSE,
  title = NULL,
  pieLabelSize = 4,
  donutLabelSize = 3,
  titlesize = 5,
  explodePie = TRUE,
  explodeDonut = FALSE,
  use.label = TRUE,
  use.labels = TRUE,
  family = getOption("PieDonut.family", "")
)

Arguments

data

A data.frame

mapping

Set of aesthetic mappings created by aes or aes_.

start

offset of starting point from 12 o'clock in radians

addPieLabel

A logical value. If TRUE, labels are added to the Pies

addDonutLabel

A logical value. If TRUE, labels are added to the Donuts

showRatioDonut

A logical value. If TRUE, ratios are added to the DonutLabels

showRatioPie

A logical value. If TRUE, ratios are added to the PieLabels

ratioByGroup

A logical value. If TRUE, ratios ara calculated per group

showRatioThreshold

An integer. Threshold to show label as a ratio of total. default value is 0.02.

labelposition

A number indicating the label position

labelpositionThreshold

label position threshold. Default value is 0.1.

r0

Integer. start point of pie

r1

Integer. end point of pie

r2

Integer. end point of donut

explode

pies to explode

selected

donuts to explode

explodePos

explode position

color

color

pieAlpha

transparency of pie

donutAlpha

transparency of pie

maxx

maximum position of plot

showPieName

logical. Whether or not show Pie Name

showDonutName

logical. Whether or not show Pie Name

title

title of plot

pieLabelSize

integer. Pie label size

donutLabelSize

integer. Donut label size

titlesize

integer. Title size

explodePie

Logical. Whether or not explode pies

explodeDonut

Logical. Whether or not explode donuts

use.label

Logical. Whether or not use column label in case of labelled data

use.labels

Logical. Whether or not use value labels in case of labelled data

family

font family

Examples

require(moonBook)
require(ggplot2)
browser=c("MSIE","Firefox","Chrome","Safari","Opera")
share=c(50,21.9,10.8,6.5,1.8)
df=data.frame(browser,share)
PieDonut(df,aes(browser,count=share),r0=0.7,start=3*pi/2,labelpositionThreshold=0.1)

PieDonut(df,aes(browser,count=share),r0=0.7,explode=5,start=3*pi/2)
PieDonut(mtcars,aes(gear,carb),start=3*pi/2,explode=3,explodeDonut=TRUE,maxx=1.7)
PieDonut(mtcars,aes(carb,gear),r0=0)
PieDonut(acs,aes(smoking,Dx),title="Distribution of smoking status by diagnosis")
PieDonut(acs,aes(Dx,smoking),ratioByGroup=FALSE,r0=0)
PieDonut(acs,aes(Dx,smoking),selected=c(1,3,5,7),explodeDonut=TRUE)
PieDonut(acs,aes(Dx,smoking),explode=1,selected=c(2,4,6,8),labelposition=0,explodeDonut=TRUE)
PieDonut(acs,aes(Dx,smoking),explode=1)
PieDonut(acs,aes(Dx,smoking),explode=1,explodeDonut=TRUE,labelposition=0)
PieDonut(acs,aes(Dx,smoking),explode=1,explodePie=FALSE,explodeDonut=TRUE,labelposition=0)
PieDonut(acs,aes(Dx,smoking),selected=c(2,5,8), explodeDonut=TRUE,start=pi/2,labelposition=0)
PieDonut(acs,aes(Dx,smoking),r0=0.2,r1=0.9,r2=1.3,explode=1,start=pi/2,explodeDonut=TRUE)
PieDonut(acs,aes(Dx,smoking),r0=0.2,r1=0.9,r2=1.3,explode=1,start=pi/2,labelposition=0)
PieDonut(acs,aes(Dx,smoking),explode=1,start=pi,explodeDonut=TRUE,labelposition=0)
require(dplyr)
df=mtcars %>% group_by(gear,carb) %>% summarize(n=n())
PieDonut(df,aes(pies=gear,donuts=carb,count=n),ratioByGroup=FALSE)

Cox-Stuart test for trend analysis The Cox-Stuart test is defined as a little powerful test (power equal to 0.78), but very robust for the trend analysis. It is therefore applicable to a wide variety of situations, to get an idea of the evolution of values obtained. The proposed method is based on the binomial distribution. This function was written by Tommaso Martino<todoslogos@gmail.com> (See 'References')

Description

Cox-Stuart test for trend analysis The Cox-Stuart test is defined as a little powerful test (power equal to 0.78), but very robust for the trend analysis. It is therefore applicable to a wide variety of situations, to get an idea of the evolution of values obtained. The proposed method is based on the binomial distribution. This function was written by Tommaso Martino<todoslogos@gmail.com> (See 'References')

Usage

cox.stuart.test(x)

Arguments

x

A numeric vector

Value

A list with class "htest"

References

Original code: http://statistic-on-air.blogspot.kr/2009/08/trend-analysis-with-cox-stuart-test-in.html

Examples

customers = c(5, 9, 12, 18, 17, 16, 19, 20, 4, 3, 18, 16, 17, 15, 14)
cox.stuart.test(customers)

Extract labels

Description

Extract labels

Usage

extractLabels(x)

Arguments

x

a vector

Make table summarizing frequency

Description

Make table summarizing frequency

Usage

freqSummary(x, digits = 1, lang = "en")

Arguments

x

A vector

digits

integer indicating the number of decimal places

lang

Language. choices are one of c("en","kor")

Examples

require(moonBook)
freqSummary(acs$Dx)
#freqSummary(acs$smoking,lang="kor")

Make flextable summarizing frequency

Description

Make flextable summarizing frequency

Usage

freqTable(
  x,
  digits = 1,
  lang = getOption("freqTable.lang", "en"),
  vanilla = FALSE,
  ...
)

Arguments

x

A vector

digits

integer indicating the number of decimal places

lang

Language. choices are one of c("en","kor")

vanilla

Logical. Whether make vanilla table or not

...

Further arguments to paseed to the df2flextable function

Value

An object of clss flextable

Examples

require(moonBook)
freqTable(acs$Dx)
#freqTable(acs$smoking,lang="kor",vanilla=TRUE,fontsize=12)

Make default palette

Description

Make default palette

Usage

gg_color_hue(n)

Arguments

n

number of colors

Select word

Description

Select word

Usage

langchoice1(id, lang = "en")

Arguments

id

data id

lang

language. Possible choices are c("en","kor")

Make subtitle

Description

Make subtitle

Usage

makeSub(x)

Arguments

x

An object of class "htest"

Make subcolors with main colors

Description

Make subcolors with main colors

Usage

makeSubColor(main, no = 3)

Arguments

main

character. main colors

no

number of subcolors

My chisquare test

Description

My chisquare test

Usage

mychisq.test(x)

Arguments

x

a table

Numerical Summary

Description

Numerical Summary

Usage

numSummary(x, ..., digits = 2, lang = "en")

numSummary1(x, ..., digits = 2, lang = "en")

numSummary2(x, ..., digits = 2, lang = "en")

Arguments

x

A numeric vector or a data.frame or a grouped_df

...

further arguments to be passed

digits

integer indicating the number of decimal places

lang

Language. choices are one of c("en","kor")

Functions

Examples

require(moonBook)
require(magrittr)
require(dplyr)
require(rrtable)
require(webr)
require(tibble)
numSummary(acs)
numSummary(acs$age)
numSummary(acs,age,EF)
acs %>% group_by(sex) %>% numSummary(age,BMI)
acs %>% group_by(sex) %>% select(age) %>% numSummary
acs %>% group_by(sex) %>% select(age,EF) %>% numSummary
acs %>% group_by(sex,Dx) %>% select(age,EF) %>% numSummary
acs %>% group_by(sex,Dx) %>% select(age) %>% numSummary
#acs %>% group_by(sex,Dx) %>% numSummary(age,EF,lang="kor")

Make a table showing numerical summary

Description

Make a table showing numerical summary

Usage

numSummaryTable(
  x,
  ...,
  lang = getOption("numSummaryTable.lang", "en"),
  vanilla = FALSE,
  add.rownames = NULL
)

Arguments

x

A grouped_df or a data.frame or a vector

...

further argument to be passed

lang

Language. choices are one of c("en","kor")

vanilla

Logical. Whether make vanilla table or not

add.rownames

Logical. Whether or not add rownames

Examples

require(moonBook)
require(dplyr)
numSummaryTable(acs)
numSummaryTable(acs$age)
acs %>% group_by(sex) %>% select(age) %>% numSummaryTable
acs %>% group_by(sex) %>% select(age,EF) %>% numSummaryTable
acs %>% group_by(sex,Dx) %>% select(age,EF) %>% numSummaryTable(vanilla=FALSE)
acs %>% group_by(sex,Dx) %>% numSummaryTable(age,EF,add.rownames=FALSE)

Plotting distribution of statistic for object "htest"

Description

Plotting distribution of statistic for object "htest"

Usage

## S3 method for class 'htest'
plot(x, ...)

Arguments

x

object of class "htest"

...

further arguments to ggplot

Value

a ggplot or NULL

Examples


require(moonBook)
require(webr)
## chi-square test
x=chisq.test(table(mtcars$am,mtcars$cyl))
plot(x)

#Welch Two Sample t-test
x=t.test(mpg~am,data=mtcars)
plot(x)

x=t.test(BMI~sex,data=acs)
plot(x)

# F test to compare two variances
x=var.test(age~sex,data=acs,alternative="less")
plot(x)

# Paired t-test
x=t.test(iris$Sepal.Length,iris$Sepal.Width,paired=TRUE)
plot(x)

# One sample t-test
plot(t.test(acs$age,mu=63))

# Two sample t-test
x=t.test(age~sex, data=acs,conf.level=0.99,alternative="greater",var.equal=TRUE)
plot(x)

Renew dictionary Renew dictionary

Description

Renew dictionary Renew dictionary

Usage

renew_dic()

Runs test for randomness

Description

Runs test for randomness

Usage

runs.test(
  y,
  plot.it = FALSE,
  alternative = c("two.sided", "positive.correlated", "negative.correlated")
)

Arguments

y

A vector

plot.it

A logical. whether or not draw a plot

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

Value

A list with class "htest" containing the following components: statistic,p-value,method and data.name

Examples

y=c(1,2,2,1,1,2,1,2)
runs.test(y)
y=c("A","B","B","A","A","B","A","B")
runs.test(y,alternative="p")

Make transparent theme

Description

Make transparent theme

Usage

transparent(size = 0)

Arguments

size

border size. default value is 0

Make a chisquare result table

Description

Make a chisquare result table

Usage

x2Table(
  data,
  x,
  y,
  margin = 1,
  show.percent = TRUE,
  show.label = TRUE,
  show.stat = TRUE,
  vanilla = FALSE,
  fontsize = 12,
  ...
)

Arguments

data

A data.frame

x

a column name

y

a column name

margin

numeric If 1 row percent, if 2 col percent

show.percent

logical

show.label

logical

show.stat

logical

vanilla

logical whether or not make vanilla table

fontsize

A numeric

...

Further arguments to be passed to df2flextable()

Examples

require(moonBook)
x2Table(acs,sex,DM)

Extract x2 statistical result

Description

Extract x2 statistical result

Usage

x2result(x)

Arguments

x

a table

Summarize chisquare result

Description

Summarize chisquare result

Usage

x2summary(
  data = NULL,
  x = NULL,
  y = NULL,
  a,
  b,
  margin = 1,
  show.percent = TRUE,
  show.label = TRUE
)

Arguments

data

A data.frame

x

a column name

y

a column name

a

a vector

b

a vector

margin

numeric If 1 row percent, if 2 col percent

show.percent

logical

show.label

logical

Examples

require(moonBook)
x2summary(acs,sex,DM)