Plotly in R

Author

Tony Duan

Code

library(gapminder)
library(plotly)
packageVersion("plotly")

[1] '4.10.4'

1 Scatter Plot

Code

library(reshape2)
tips=tips
head(tips)

  total_bill  tip    sex smoker day   time size
1      16.99 1.01 Female     No Sun Dinner    2
2      10.34 1.66   Male     No Sun Dinner    3
3      21.01 3.50   Male     No Sun Dinner    3
4      23.68 3.31   Male     No Sun Dinner    2
5      24.59 3.61 Female     No Sun Dinner    4
6      25.29 4.71   Male     No Sun Dinner    4

Code

fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip)
fig

1.1 color by group

Code

fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip,color=~sex)
fig

1.2 size by group

Code

fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip,color=~sex,size=~size)
fig

1.3 line Plot

Code

data001=gapminder
data002= data001 %>% group_by(continent,year) %>% summarise(pop=sum(pop))

Code

fig <- plot_ly(data = data002 %>%filter(continent=='Asia'), x = ~year, y = ~pop,mode = 'lines')
fig

1.4 line width and colour

Code

fig <- plot_ly(data = data002 %>%filter(continent=='Asia'), x = ~year, y = ~pop,mode = 'lines',line = list(color = 'rgb(205, 12, 24)', width = 8))
fig

1.5 color by group

Code

fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines')
fig

2 histogram

Code

fig <- plot_ly(data=tips,x = ~total_bill, type = "histogram")

fig

2.1 set bin number

Code

fig <- plot_ly(data=tips,x = ~total_bill, type = "histogram",nbinsx = 5 )
fig

2.2 color by group

Code

fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram")

fig

3 bar chart

Code

tips2=tips %>% group_by(sex) %>% summarise(total_bill=sum(total_bill))

Code

fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar")

fig

3.1 show number

Code

fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,text=~total_bill, type = "bar")

fig

3.2 Horizontal Barplot

Code

fig <- plot_ly(data=tips2,y = ~sex,x=~total_bill,color=~sex, type = "bar",orientation = 'h')

fig

3.3 bar chart order

Code

fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar")%>% 
  layout(xaxis = list(categoryorder = "total ascending"))

fig

Code

fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar")%>% 
  layout(xaxis = list(categoryorder = "total descending"))

fig

4 box plot

Code

fig <- plot_ly(data=tips,y=~total_bill, type = "box")

fig

4.1 color by group

Code

fig <- plot_ly(data=tips,x = ~sex,y=~total_bill,color=~sex, type = "box")

fig

5 strip plot

create ggplot and then covert to plotly

Code

p=ggplot(tips, aes(day,tip)) + geom_jitter(width = 0.1)
ggplotly(p)

5.1 color by group

Code

p=ggplot(tips, aes(day,tip,color=sex)) + geom_jitter(position=position_jitterdodge())
ggplotly(p)

6 Facet plot

create ggplot and then covert to plotly

Code

p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day")

ggplotly(p)

7 title,size,x y name,footnote

7.1 add title

Code

fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title')

fig

7.2 adjust size

Code

fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram"
               ,width = 500, height = 200)

fig

7.3 change x y name

Code

fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title'
                                                                                   ,xaxis = list(title = 'new x')
                                                                                  ,yaxis = list(title = 'new y') 
                                                                                    )

fig

7.4 change x y axis range

Code

fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title'
                                                                                   ,xaxis = list(title = 'new x',range=c(20,40))
                                                                                  ,yaxis = list(title = 'new y',range=c(20,40)) 
                                                                                    )

fig

7.5 add footnote

Code

fig%>% layout(annotations = 
                         list(x = 0, y = -0.1, 
                              text = "this is footnote", 
                              showarrow = F, 
                              xref='paper', 
                              yref='paper')
    )

7.6 legend

7.6.1 hide legend

Code

fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(showlegend = FALSE)
fig

7.6.2 show legend and change legend name

Code

fig <- plot_ly(data = data002 %>% filter(continent=='Asia'), x = ~year, y = ~pop,color = ~continent,mode = 'lines',name='Asia pop') %>% layout(showlegend = TRUE)
fig

7.6.3 change legend and change legend Position

Code

fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(legend = list(orientation = 'h'))

fig

8 add image

add online image ::: {.cell}

Code

fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(
    images = list(  
      list(  
        source =  "https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/vox.png"
        ,xref = "paper"
        ,yref = "paper" 
        ,x = 0.1
        ,y = 0.1
        ,sizex = 0.1 
        ,sizey = 0.1
       ,xanchor="left"  
      )  
    )
    ) 
                                                                                           
fig

:::

add local image ::: {.cell}

Code

fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(
    images = list(  
      list(  
        source = base64enc::dataURI(file = "bee.png")
        ,xref = "paper"
        ,yref = "paper" 
        ,x = 0.1
        ,y = 0.1
        ,sizex = 0.1 
        ,sizey = 0.1
       ,xanchor="left"  
       # image at the back
         ,layer = "below"
       
      )  
    )
    ) 
                                                                                           
fig

:::

9 applying themes

create ggplot and then covert to plotly

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")

ggplotly(p+ theme_bw())

Code

ggplotly(p+ theme_light())

Code

library("ggthemes")
ggplotly(p+ theme_economist())

10 Save plot

install orca in https://github.com/plotly/orca#installation

conda install -c plotly plotly-orca ::: {.cell}

Code

#install.packages('processx')

:::

Code

#orca(p, "surface-plot.png")

11 Animation plot

Code

fig <- plot_ly(data=gapminder,x = ~gdpPercap,y=~lifeExp,color=~continent, type = "scatter",frame = ~year,text = ~country)

fig %>% animation_opts(
    1000, easing = "elastic", redraw = FALSE
  )

12 reference:

https://plotly.com/r/

--- title: "Plotly in R" author: "Tony Duan" execute: warning: false error: false format: html: toc: true toc-location: right code-fold: show code-tools: true number-sections: true code-block-bg: true code-block-border-left: "#31BAE9" --- ![](images/Plotly-logo.png){width="800"} ```{r} library(gapminder) library(plotly) packageVersion("plotly") ``` # Scatter Plot ```{r} library(reshape2) tips=tips head(tips) ``` ```{r} fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip) fig ``` ## color by group ```{r} fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip,color=~sex) fig ``` ## size by group ```{r} fig <- plot_ly(data = tips, x = ~total_bill, y = ~tip,color=~sex,size=~size) fig ``` ## line Plot ```{r} data001=gapminder data002= data001 %>% group_by(continent,year) %>% summarise(pop=sum(pop)) ``` ```{r} fig <- plot_ly(data = data002 %>%filter(continent=='Asia'), x = ~year, y = ~pop,mode = 'lines') fig ``` ## line width and colour ```{r} fig <- plot_ly(data = data002 %>%filter(continent=='Asia'), x = ~year, y = ~pop,mode = 'lines',line = list(color = 'rgb(205, 12, 24)', width = 8)) fig ``` ## color by group ```{r} fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') fig ``` # histogram ```{r} fig <- plot_ly(data=tips,x = ~total_bill, type = "histogram") fig ``` ## set bin number ```{r} fig <- plot_ly(data=tips,x = ~total_bill, type = "histogram",nbinsx = 5 ) fig ``` ## color by group ```{r} fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") fig ``` # bar chart ```{r} tips2=tips %>% group_by(sex) %>% summarise(total_bill=sum(total_bill)) ``` ```{r} fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar") fig ``` ## show number ```{r} fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,text=~total_bill, type = "bar") fig ``` ## Horizontal Barplot ```{r} fig <- plot_ly(data=tips2,y = ~sex,x=~total_bill,color=~sex, type = "bar",orientation = 'h') fig ``` ## bar chart order ```{r} fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar")%>% layout(xaxis = list(categoryorder = "total ascending")) fig ``` ```{r} fig <- plot_ly(data=tips2,x = ~sex,y=~total_bill,color=~sex, type = "bar")%>% layout(xaxis = list(categoryorder = "total descending")) fig ``` # box plot ```{r} fig <- plot_ly(data=tips,y=~total_bill, type = "box") fig ``` ## color by group ```{r} fig <- plot_ly(data=tips,x = ~sex,y=~total_bill,color=~sex, type = "box") fig ``` # strip plot create ggplot and then covert to plotly ```{r} p=ggplot(tips, aes(day,tip)) + geom_jitter(width = 0.1) ggplotly(p) ``` ## color by group ```{r} p=ggplot(tips, aes(day,tip,color=sex)) + geom_jitter(position=position_jitterdodge()) ggplotly(p) ``` # Facet plot create ggplot and then covert to plotly ```{r} p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day") ggplotly(p) ``` # title,size,x y name,footnote ## add title ```{r} fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title') fig ``` ## adjust size ```{r} fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram" ,width = 500, height = 200) fig ``` ## change x y name ```{r} fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title' ,xaxis = list(title = 'new x') ,yaxis = list(title = 'new y') ) fig ``` ## change x y axis range ```{r} fig <- plot_ly(data=tips,x = ~total_bill,color=~sex, type = "histogram") %>% layout(title = 'new title' ,xaxis = list(title = 'new x',range=c(20,40)) ,yaxis = list(title = 'new y',range=c(20,40)) ) fig ``` ## add footnote ```{r} fig%>% layout(annotations = list(x = 0, y = -0.1, text = "this is footnote", showarrow = F, xref='paper', yref='paper') ) ``` ## legend ### hide legend ```{r} fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(showlegend = FALSE) fig ``` ### show legend and change legend name ```{r} fig <- plot_ly(data = data002 %>% filter(continent=='Asia'), x = ~year, y = ~pop,color = ~continent,mode = 'lines',name='Asia pop') %>% layout(showlegend = TRUE) fig ``` ### change legend and change legend Position ```{r} fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout(legend = list(orientation = 'h')) fig ``` # add image add online image ```{r} fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout( images = list( list( source = "https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/vox.png" ,xref = "paper" ,yref = "paper" ,x = 0.1 ,y = 0.1 ,sizex = 0.1 ,sizey = 0.1 ,xanchor="left" ) ) ) fig ``` add local image ```{r} fig <- plot_ly(data = data002, x = ~year, y = ~pop,color = ~continent,mode = 'lines') %>% layout( images = list( list( source = base64enc::dataURI(file = "bee.png") ,xref = "paper" ,yref = "paper" ,x = 0.1 ,y = 0.1 ,sizex = 0.1 ,sizey = 0.1 ,xanchor="left" # image at the back ,layer = "below" ) ) ) fig ``` # applying themes create ggplot and then covert to plotly ::: {.panel-tabset .nav-pills} ## theme_bw() ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") ggplotly(p+ theme_bw()) ``` ## theme_light() ```{r} ggplotly(p+ theme_light()) ``` ## theme_economist() ```{r} library("ggthemes") ggplotly(p+ theme_economist()) ``` ::: # Save plot install orca in https://github.com/plotly/orca#installation conda install -c plotly plotly-orca ```{r} #install.packages('processx') ``` ```{r} #orca(p, "surface-plot.png") ``` # Animation plot ```{r} fig <- plot_ly(data=gapminder,x = ~gdpPercap,y=~lifeExp,color=~continent, type = "scatter",frame = ~year,text = ~country) fig %>% animation_opts( 1000, easing = "elastic", redraw = FALSE ) ``` # reference: https://plotly.com/r/