R Plotly Tutorial - Code Snippets

Rplotlytutorial.r

#### Brief introduction to R Plotly package ####
# The plotly package in R is an interface to open source Javascript charting library plotly.js
# Plots can be created online in the plotly web GUI or offline using the plotly package
# Interactive plots that can be easily shared online using the plotly API/account
# Plotly plots can embed into R Markdown, R Shiny
# Tool tip feature and other controls
# ggplot2 graphs can be easily converted to interactive plotly objects using ggplotly() function

# Package documentation
# https://cran.r-project.org/web/packages/plotly/plotly.pdf


#### Install the 'plotly' package ####
install.packages("plotly")

#### load the 'plotly' package ####
library(plotly)


#### General Syntax plot_ly() #### 
# Plot_ly functions creates a plotly object and produces interactive visualization based on data and arguments supplied
# plot_ly (data, x, y , type, mode, color, size,....)
plot_ly()
# data = a dataframe
# x and y axis values
# type = specifies the type of plot or trace such as 'histogram', 'scatter', 'bar', 'box', 'heatmap', 'histogram', 'histogram2d', 'histogram2dcontour', 'pie', 'contour', 'scatter3d', 
# 'surface', 'mesh3d', 'scattergeo', 'choropleth', 'scattergl', 'scatterternary', 'scattermapbox', 'area'
# mode = specifies the mode, such as 'line', 'points', 'markers' 
# color = specifies the color of data points usually a function of I() to avoid scaling
# colors = colourbrewer pallete, vector of color in hexa format
# size = name or expression that defines the size of the data points
# We can use other functions such as layout() for axis formating
# and other functions that comes with plotly package



#### Simple Scatter Plot ####
# Type of plot is not exclusively defined. 
# Plotly will guess the best type based on the data type.

p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg
            )
p


#### Define the plot type exclusively as "scatter" ####
# & mode as "markers" ###

p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers"
            )
p


#### Change color of scatter data points  ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            color = I("black")
)
p

#### Change color of data points using marker argument ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            marker = list(color="green", size=5)
)
p


#### Styled Marker ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            marker = list(size = 7,
                          color = 'rgba(255, 182, 193, .9)',
                          line = list(color = 'rgba(152, 0, 0, .8)',
                                      width = 3))
)
p




#### Set the color scale based on a factor variable ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            color = ~as.factor(cyl))

p


#### Use color Brewer palletes for data point colors ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            color = ~as.factor(cyl),
            colors = "Set1")

p

#### Use customized pallete for data point colors ####
pal <- c("red", "blue", "green")
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            color = ~as.factor(cyl),
            colors = pal)

p

#### Change data point shape based on factor variable ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg,
            type = "scatter",
            mode = "markers",
            symbol = ~as.factor(cyl),
            symbols =  c('circle','x','o'),
            marker = list(size = 5)
            )

p


#### Set the color scale based on a continous variable ####
p= plot_ly(data=mtcars, x=~wt, y=~mpg, mode="markers", color = ~disp)
p

#### Scatter plot with diffent data point size based on a continous variable ####
p = plot_ly(data=mtcars, 
            x=~wt, 
            y=~mpg, 
            type="scatter",
            mode="markers", 
            color = ~as.factor(cyl),
            size = ~hp)

p



#### Hide the legend ####
p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  layout(showlegend = FALSE)

p

#### Change the orientation of the legend (below the plot) ####
p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  layout(legend = list(orientation = 'h'))

p

#### Change the orientation of the legend (inside the plot) ####
p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  layout(legend = list(x = 0.8, y = 0.9))

p

#### Change the orientation of the legend (outside the plot) ####
p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  layout(legend = list(x = 1, y = 0.5))

p



#### Add title to the legen ####
p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  layout(legend = list(x = 1, y = 0.5))


p


#### Adding chart title and axis labels ####

p <- plot_ly(data=mtcars, 
             x=~wt, 
             y=~mpg,
             type = "scatter",
             mode = "markers",
             symbol = ~as.factor(cyl),
             symbols =  c('circle','x','o'),
             marker = list(size = 5)) %>%
  
  layout(title="Scatter plot using R Plotly",  
         xaxis=list(title="Weight", showgrid = F),
         yaxis=list(title="MPG", showgrid = F))

p

### Customizing mouse hover text ####
p = plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers",
        hoverinfo = "text", 
        text = paste("Miles per gallon: ", mtcars$mpg, 
                     "<br>", 
                     "Weight: ", mtcars$wt)
        )

p

#### Add annotations to the plot - add_annotations() function syntax ####
# add_annotations() function is used to add annotations to the plot along with the following arguments
# x = set annotations x coordinate position (x axis value based on the dataset)
# y = set annotations y coordinate position (y axis value based on the dataset)
# text = text associated with annotation
# showarrow = 0 or 1 depending whether to show arrow or not
# xref = "paper" telling plotly to set x reference to the plot (in which case x=0 means the left most, x=1 means right most)
# yref = "paper" telling plotly to set y reference to the plot (in which case y=0 means the bottom, y=1 means top)
# xref = "x" (non paper x coordinates)
# yref = "y (non paper y coordinates)
# arrowhead, arrowsize, font, ax, ay 



### Example of annotations on a single data points ####
## display annotations for good mileage
plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers") %>% 
  add_annotations(
    x=mtcars$mpg[which.max(mtcars$mpg)],
    y=mtcars$wt[which.max(mtcars$mpg)],
    text="Good mileage",
    showarrow=F
  )
#### Example of annotations - placing text at a desired location on the plot ####
## Display Data Source
## Demo of x/y ref as "paper"

plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers") %>% 
  add_annotations(
    xref="paper",
    yref="paper",
    x=1,
    y=-0.2,
    text="Data Source : mtcars",
    showarrow= F
  )

#### Example #1 of annotations on multiple data points ####
## display annotation for low and high mileage ##
plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers") %>% 
  add_annotations(x=mtcars$mpg[which.max(mtcars$mpg)],
                  y=mtcars$wt[which.max(mtcars$mpg)],
                  text="high mileage"
  ) %>% 
  add_annotations(x=mtcars$mpg[which.min(mtcars$mpg)],
                  y=mtcars$wt[which.min(mtcars$mpg)],
                  text="low mileage"
  )

### Example #2 of annotations on multiple data points ####
# display annotations for automatic transission cars
plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers") %>% 
  add_annotations(
    x = mtcars$mpg[mtcars$am==0],
    y= mtcars$wt[mtcars$am==0],
    text="auto",
    showarrow=F
    
  )
#### Styling annotations ####
# using font argument
plot_ly(data = mtcars, 
        x=~mpg, 
        y=~wt, 
        type = "scatter", 
        mode="markers") %>% 
  add_annotations(x=mtcars$mpg[which.max(mtcars$mpg)],
                  y=mtcars$wt[which.max(mtcars$mpg)],
                  text="Good mileage",
                  font = list(color = "green", 
                              family="sans serif", 
                              size = 20))