Box Plots in ggplot2

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating)) + geom_boxplot()

ggplotly(p)

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot()

ggplotly(p)

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot() +
    guides(fill=FALSE) + coord_flip()

ggplotly(p)

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating)) + geom_boxplot() +
    stat_summary(fun=mean, geom="point", shape=5, size=4)

ggplotly(p)

library(plyr)
library(reshape2)
library(plotly)

set.seed(1234)
x<- rnorm(100)
y.1<-rnorm(100)
y.2<-rnorm(100)
y.3<-rnorm(100)
y.4<-rnorm(100)

df<- (as.data.frame(cbind(x,y.1,y.2,y.3,y.4)))

dfmelt<-melt(df, measure.vars = 2:5)

p <- ggplot(dfmelt, aes(x=factor(round_any(x,0.5)), y=value,fill=variable))+
    geom_boxplot()+
    facet_grid(.~variable)+
    labs(x="X (binned)")+
    theme(axis.text.x=element_text(angle=-90, vjust=0.4,hjust=1))

ggplotly(p)

library(foreign)
library(MASS)
library(Hmisc)
library(reshape2)
library(plotly)

dat <- read.dta("https://stats.idre.ucla.edu/stat/data/ologit.dta")
invisible(lapply(dat[, c("apply", "pared", "public")], table))
invisible(ftable(xtabs(~ public + apply + pared, data = dat)))

p <- ggplot(dat, aes(x = apply, y = gpa)) +
    geom_boxplot(size = .75) +
    facet_grid(pared ~ public, margins = TRUE)

ggplotly(p)

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

p <- ggplot(df, aes(cut, price, fill = cut)) + 
  geom_boxplot(outlier.shape = NA) + 
  ggtitle("Ignore outliers in ggplot2")

# Need to modify the plotly object and make outlier points have opacity equal to 0
fig <- plotly_build(p)

fig$data <- lapply(fig$data, FUN = function(x){
  x$marker = list(opacity = 0)
  return(x)
})

fig

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

p <- ggplot(df, aes(cut, price, fill = cut)) + 
  geom_boxplot(size = 1) + 
  ggtitle("Adjust line width of boxplot in ggplot2")

# Need to modify the plotly object to make sure line width is larger than default
fig <- plotly_build(p)

fig$data <- lapply(fig$data, FUN = function(x){
  x$line = list(width = 10)
  return(x)
})

fig

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

# This is how it needs to be done in ggplot
p <- ggplot(df, aes(color, price)) +
  stat_boxplot(geom ='errorbar') + 
  geom_boxplot()+
  ggtitle("Add horizontal lines to whiskers using ggplot2")

# Note that plotly will automatically add horozontal lines to the whiskers
p <- ggplot(df, aes(cut, price, fill = cut)) +
  geom_boxplot()+
  ggtitle("Add horizontal lines to whiskers using ggplot2")

ggplotly(p)

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)