Line Plots in R

How to create line aplots in R. Examples of basic and advanced line 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 Line Plot

library(plotly)

x <- c(1:100)
random_y <- rnorm(100, mean = 0)
data <- data.frame(x, random_y)

fig <- plot_ly(data, x = ~x, y = ~random_y, type = 'scatter', mode = 'lines')

fig


Line Plots Mode

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')


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


Style Line Plots

library(plotly)

month <- c('January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December')
high_2000 <- c(32.5, 37.6, 49.9, 53.0, 69.1, 75.4, 76.5, 76.6, 70.7, 60.6, 45.1, 29.3)
low_2000 <- c(13.8, 22.3, 32.5, 37.2, 49.9, 56.1, 57.7, 58.3, 51.2, 42.8, 31.6, 15.9)
high_2007 <- c(36.5, 26.6, 43.6, 52.3, 71.5, 81.4, 80.5, 82.2, 76.0, 67.3, 46.1, 35.0)
low_2007 <- c(23.6, 14.0, 27.0, 36.8, 47.6, 57.7, 58.9, 61.2, 53.3, 48.5, 31.0, 23.6)
high_2014 <- c(28.8, 28.5, 37.0, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3, 39.9)
low_2014 <- c(12.7, 14.3, 18.6, 35.5, 49.9, 58.0, 60.0, 58.6, 51.7, 45.2, 32.2, 29.1)

data <- data.frame(month, high_2000, low_2000, high_2007, low_2007, high_2014, low_2014)

#The default order will be alphabetized unless specified as below:
data$month <- factor(data$month, levels = data[["month"]])

fig <- plot_ly(data, x = ~month, y = ~high_2014, name = 'High 2014', type = 'scatter', mode = 'lines',
line = list(color = 'rgb(205, 12, 24)', width = 4))
fig <- fig %>% add_trace(y = ~low_2014, name = 'Low 2014', line = list(color = 'rgb(22, 96, 167)', width = 4))
fig <- fig %>% add_trace(y = ~high_2007, name = 'High 2007', line = list(color = 'rgb(205, 12, 24)', width = 4, dash = 'dash'))
fig <- fig %>% add_trace(y = ~low_2007, name = 'Low 2007', line = list(color = 'rgb(22, 96, 167)', width = 4, dash = 'dash'))
fig <- fig %>% add_trace(y = ~high_2000, name = 'High 2000', line = list(color = 'rgb(205, 12, 24)', width = 4, dash = 'dot'))
fig <- fig %>% add_trace(y = ~low_2000, name = 'Low 2000', line = list(color = 'rgb(22, 96, 167)', width = 4, dash = 'dot'))
fig <- fig %>% layout(title = "Average High and Low Temperatures in New York",
xaxis = list(title = "Months"),
yaxis = list (title = "Temperature (degrees F)"))

fig


Mapping data to linetype

library(plotly)
library(plyr)

tg <- ddply(ToothGrowth, c("supp", "dose"), summarise, length=mean(len))

fig <- plot_ly(tg, x = ~dose, y = ~length, type = 'scatter', mode = 'lines', linetype = ~supp, color = I('black'))
fig <- fig %>% layout(title = 'The Effect of Vitamin C on Tooth Growth in Guinea Pigs by Supplement Type',
xaxis = list(title = 'Dose in milligrams/day'),
yaxis = list (title = 'Tooth length'))

fig


Connect Data Gaps

library(plotly)

x <- c(1:15)
y <- c(10, 20, NA, 15, 10, 5, 15, NA, 20, 10, 10, 15, 25, 20, 10)

data <- data.frame(x, y)

fig <- plot_ly(data, x = ~x, y = ~y, name = "Gaps", type = 'scatter', mode = 'lines')
fig <- fig %>% add_trace(y = ~y - 5, name = "<b>No</b> Gaps", connectgaps = TRUE)

fig


Line Interpolation Options

library(plotly)

x <- c(1:5)
y <- c(1, 3, 2, 3, 1)

fig <- plot_ly(x = ~x)
fig <- fig %>% add_lines(y = ~y, name = "linear", line = list(shape = "linear"))
fig <- fig %>% add_lines(y = y + 5, name = "spline", line = list(shape = "spline"))
fig <- fig %>% add_lines(y = y + 10, name = "vhv", line = list(shape = "vhv"))
fig <- fig %>% add_lines(y = y + 15, name = "hvh", line = list(shape = "hvh"))
fig <- fig %>% add_lines(y = y + 20, name = "vh", line = list(shape = "vh"))
fig <- fig %>% add_lines(y = y + 25, name = "hv", line = list(shape = "hv"))

fig


Label Lines with Annotations

library(plotly)

x <- c(2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013)
y_television <- c(74, 82, 80, 74, 73, 72, 74, 70, 70, 66, 66, 69)
y_internet <- c(13, 14, 20, 24, 20, 24, 24, 40, 35, 41, 43, 50)
data <- data.frame(x, y_television, y_internet)

xaxis <- list(title = "",
showline = TRUE,
showgrid = FALSE,
showticklabels = TRUE,
linecolor = 'rgb(204, 204, 204)',
linewidth = 2,
autotick = FALSE,
ticks = 'outside',
tickcolor = 'rgb(204, 204, 204)',
tickwidth = 2,
ticklen = 5,
tickfont = list(family = 'Arial',
size = 12,
color = 'rgb(82, 82, 82)'))

yaxis <- list(title = "",
showgrid = FALSE,
zeroline = FALSE,
showline = FALSE,
showticklabels = FALSE)

margin <- list(autoexpand = FALSE,
l = 100,
r = 100,
t = 110)

# Build the annotations

television_1 <- list(
xref = 'paper',
yref = 'y',
x = 0.05,
y = y_television[1],
xanchor = 'right',
yanchor = 'middle',
text = ~paste('Television ', y_television[1], '%'),
font = list(family = 'Arial',
size = 16,
color = 'rgba(67,67,67,1)'),
showarrow = FALSE)

internet_1 <- list(
xref = 'paper',
yref = 'y',
x = 0.05,
y = y_internet[1],
xanchor = 'right',
yanchor = 'middle',
text = ~paste('Internet ', y_internet[1], '%'),
font = list(family = 'Arial',
size = 16,
color = 'rgba(49,130,189, 1)'),
showarrow = FALSE)

television_2 <- list(
xref = 'paper',
x = 0.95,
y = y_television[12],
xanchor = 'left',
yanchor = 'middle',
text = paste('Television ', y_television[12], '%'),
font = list(family = 'Arial',
size = 16,
color = 'rgba(67,67,67,1)'),
showarrow = FALSE)

internet_2 <- list(
xref = 'paper',
x = 0.95,
y = y_internet[12],
xanchor = 'left',
yanchor = 'middle',
text = paste('Internet ', y_internet[12], '%'),
font = list(family = 'Arial',
size = 16,
color = 'rgba(67,67,67,1)'),
showarrow = FALSE)

fig <- plot_ly(data, x = ~x)
fig <- fig %>% add_trace(y = ~y_television, type = 'scatter', mode = 'lines', line = list(color = 'rgba(67,67,67,1)', width = 2))
fig <- fig %>% add_trace(y = ~y_internet, type = 'scatter', mode = 'lines', line = list(color = 'rgba(49,130,189, 1)', width = 4))
fig <- fig %>% add_trace(x = ~c(x[1], x[12]), y = ~c(y_television[1], y_television[12]), type = 'scatter', mode = 'markers', marker = list(color = 'rgba(67,67,67,1)', size = 8))
fig <- fig %>% add_trace(x = ~c(x[1], x[12]), y = ~c(y_internet[1], y_internet[12]), type = 'scatter', mode = 'markers', marker = list(color = 'rgba(49,130,189, 1)', size = 12))
fig <- fig %>% layout(title = "Main Source for News", xaxis = xaxis, yaxis = yaxis, margin = margin,
autosize = FALSE,
showlegend = FALSE,
annotations = television_1)
fig <- fig %>% layout(annotations = internet_1)
fig <- fig %>% layout(annotations = television_2)
fig <- fig %>% layout(annotations = internet_2)

fig


Filled Lines

library(plotly)

month <- c('January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December')
high_2014 <- c(28.8, 28.5, 37.0, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3, 39.9)
low_2014 <- c(12.7, 14.3, 18.6, 35.5, 49.9, 58.0, 60.0, 58.6, 51.7, 45.2, 32.2, 29.1)
data <- data.frame(month, high_2014, low_2014)
data$average_2014 <- rowMeans(data[,c("high_2014", "low_2014")]) #The default order will be alphabetized unless specified as below: data$month <- factor(data$month, levels = data[["month"]]) fig <- plot_ly(data, x = ~month, y = ~high_2014, type = 'scatter', mode = 'lines', line = list(color = 'transparent'), showlegend = FALSE, name = 'High 2014') fig <- fig %>% add_trace(y = ~low_2014, type = 'scatter', mode = 'lines', fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'transparent'), showlegend = FALSE, name = 'Low 2014') fig <- fig %>% add_trace(x = ~month, y = ~average_2014, type = 'scatter', mode = 'lines', line = list(color='rgb(0,100,80)'), name = 'Average') fig <- fig %>% layout(title = "Average, High and Low Temperatures in New York", paper_bgcolor='rgb(255,255,255)', plot_bgcolor='rgb(229,229,229)', xaxis = list(title = "Months", gridcolor = 'rgb(255,255,255)', showgrid = TRUE, showline = FALSE, showticklabels = TRUE, tickcolor = 'rgb(127,127,127)', ticks = 'outside', zeroline = FALSE), yaxis = list(title = "Temperature (degrees F)", gridcolor = 'rgb(255,255,255)', showgrid = TRUE, showline = FALSE, showticklabels = TRUE, tickcolor = 'rgb(127,127,127)', ticks = 'outside', zeroline = FALSE)) fig  See more examples of filled line charts here. Density Plot library(plotly) dens <- with(diamonds, tapply(price, INDEX = cut, density)) df <- data.frame( x = unlist(lapply(dens, "[[", "x")), y = unlist(lapply(dens, "[[", "y")), cut = rep(names(dens), each = length(dens[[1]]$x))
)

fig <- plot_ly(df, x = ~x, y = ~y, color = ~cut)
fig <- fig %>% add_lines()

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)