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Scatter and Line Plots in R

How to create line and scatter plots in R. Examples of basic and advanced scatter plots, time series line plots, colored charts, and density plots.


New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Basic Scatter Plot

library(plotly)

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length)

fig

Styled Scatter Plot

library(plotly)

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length,
               marker = list(size = 10,
                             color = 'rgba(255, 182, 193, .9)',
                             line = list(color = 'rgba(152, 0, 0, .8)',
                                         width = 2)))
fig <- fig %>% layout(title = 'Styled Scatter',
         yaxis = list(zeroline = FALSE),
         xaxis = list(zeroline = FALSE))

fig

Plotting Markers and Lines

library(plotly)

trace_0 <- rnorm(100, mean = 5)
trace_1 <- rnorm(100, mean = 0)
trace_2 <- rnorm(100, mean = -5)
x <- c(1:100)

data <- data.frame(x, trace_0, trace_1, trace_2)

fig <- plot_ly(data, x = ~x)
fig <- fig %>% add_trace(y = ~trace_0, name = 'trace 0',mode = 'lines')
fig <- fig %>% add_trace(y = ~trace_1, name = 'trace 1', mode = 'lines+markers')
fig <- fig %>% add_trace(y = ~trace_2, name = 'trace 2', mode = 'markers')

fig

It is also possible to pass the first trace in the plot_ly function. In such cases, the type of graph has to be specified, as shown below:

library(plotly)

trace_0 <- rnorm(100, mean = 5)
trace_1 <- rnorm(100, mean = 0)
trace_2 <- rnorm(100, mean = -5)
x <- c(1:100)

data <- data.frame(x, trace_0, trace_1, trace_2)

fig <- plot_ly(data, x = ~x, y = ~trace_0, name = 'trace 0', type = 'scatter', mode = 'lines')
fig <- fig %>% add_trace(y = ~trace_1, name = 'trace 1', mode = 'lines+markers')
fig <- fig %>% add_trace(y = ~trace_2, name = 'trace 2', mode = 'markers')

fig

See more examples of line charts here.

Qualitative Colorscales

library(plotly)

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species)

fig

ColorBrewer Palette Names

library(plotly)

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, colors = "Set1")

fig

Custom Color Scales

The colors argument also accepts a character vector of any valid R color code(s).

library(plotly)

pal <- c("red", "blue", "green")

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, colors = pal)

fig

To ensure a particular data value gets mapped to particular color, provide a character vector of color codes, and match the names attribute accordingly.

library(plotly)

pal <- c("red", "blue", "green")
pal <- setNames(pal, c("virginica", "setosa", "versicolor"))

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, colors = pal)

fig

Mapping Data to Symbols

library(plotly)

fig <- plot_ly(data = iris, x = ~Sepal.Length, y = ~Petal.Length, type = 'scatter',
  mode = 'markers', symbol = ~Species, symbols = c('circle','x','o'),
  color = I('black'), marker = list(size = 10))

fig

Adding Color and Size Mapping

library(plotly)

d <- diamonds[sample(nrow(diamonds), 1000), ]

fig <- plot_ly(
  d, x = ~carat, y = ~price,
  color = ~carat, size = ~carat
)

fig

Data Labels on Hover

library(plotly)

d <- diamonds[sample(nrow(diamonds), 1000), ]

fig <- plot_ly(
  d, x = ~carat, y = ~price,
  # Hover text:
  text = ~paste("Price: ", price, '$<br>Cut:', cut),
  color = ~carat, size = ~carat
)

fig

Reference

See https://plotly.com/r/reference/#scatter for more information and chart attribute options!

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

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)