Online R and Plotly Graphs: Canadian and U.S. Maps, Old Faithful with Multiple Axes, & Overlaid Histograms

Guest post by Matt Sundquist of

Plotly is a social graphing and analytics platform. Plotly’s R library lets you make and share publication-quality graphs online. Your work belongs to you, you control privacy and sharing, and public use is free (like GitHub). We are in beta, and would love your feedback, thoughts, and advice.

1. Installing Plotly

Let’s install Plotly. Our documentation has more details.


Then signup online or like this:

response = signup (username = 'yourusername', email= 'youremail')

Thanks for signing up to plotly! Your username is: MattSundquist Your temporary password is: pw. You use this to log into your plotly account at Your API key is: “API_Key”. You use this to access your plotly account through the API.

2. Canadian Population Bubble Chart

Our first graph was made at a Montreal R Meetup by Plotly’s own Chris Parmer. We’ll be using the maps package. You may need to load it:



p <- plotly(username="MattSundquist", key="4om2jxmhmn")
trace1 <- list(x=map(regions="canada")$x,

trace2 <- list(x= canada.cities$long,

response <- p$plotly(trace1,trace2)
url <- response$url
filename <- response$filename

In our graph, the bubble size represents the city population size. Shown below is the GUI, where you can annotate, select colors, analyze and add data, style traces, place your legend, change fonts, and more.


Editing from the GUI, we make a styled version. You can zoom in and hover on the points to find out about the cities. Want to make one for another country? We’d love to see it.


And, here is said meetup, in action:


You can also add in usa and us.cities:


3. Old Faithful and Multiple Axes

Ben Chartoff’s graph shows the correlation between a bimodal eruption time and a bimodal distribution of eruption length. The key series are: a histogram scale of probability, Eruption Time scale in minutes, and a scatterplot showing points within each bin on the x axis. The graph was made with this gist.


4. Plotting Two Histograms Together

Suppose you are studying correlations in two series (Popular Stack Overflow ?). You want to find overlap. You can plot two histograms together, one for each series. The overlapping sections are the darker orange, automatically rendered if you set barmode to ‘overlay’.

p <- plotly(username="Username", key="API_KEY")

x0 <- rnorm(500)
x1 <- rnorm(500)+1

data0 <- list(x=x0,
  name = "Series One",
  opacity = 0.8)

data1 <- list(x=x1,
  name = "Series Two",
  opacity = 0.8)

layout <- list(
  xaxis = list(
  ticks = "",
  gridcolor = "white",zerolinecolor = "white",
  linecolor = "white"
 yaxis = list(
  ticks = "",
  gridcolor = "white",
  zerolinecolor = "white",
  linecolor = "white"
 # style background color. You can set the alpha by adding an a.
 plot_bgcolor = 'rgba(249,249,251,.85)'

response <- p$plotly(data0, data1, kwargs=list(layout=layout))
url <- response$url
filename <- response$filename


5. Plotting y1 and y2 in the Same Plot

Plotting two lines or graph types in Plotly is straightforward. Here we show y1 and y2 together (Popular SO ?). 

p <- plotly(username="Username", key="API_KEY")

# enter data
x <- seq(-2, 2, 0.05)
y1 <- pnorm(x)
y2 <- pnorm(x,1,1)

# format, listing y1 as your y.
First <- list(
  x = x,
  y = y1,
  type = 'scatter',
  mode = 'lines',
  marker = list(
   color = 'rgb(0, 0, 255)',
   opacity = 0.5)

# format again, listing y2 as your y.
Second <- list(
  x = x,
  y = y2,
  type = 'scatter',
  mode = 'lines',
  opacity = 0.8,
  marker = list(
   color = 'rgb(255, 0, 0)')


And a shot of the Plotly gallery, as seen at the Montreal meetup. Happy plotting!


Montreal R User Group – Dr. Ramnath Vaidyanathan on his rCharts package

Monday, October 28, 2013. 6:00pm at Notman House 51 Sherbrooke W., Montreal, QC.

We are very pleased to welcome back Dr. Ramnath Vaidyanathan for a talk on interactive documents as it relates to his excellent rCharts package.

Bringing a laptop to follow along is highly encouraged. I would recommend installing rCharts prior to the workshop.


pkgs <- c(‘rCharts’, ‘slidify’, ‘slidifyLibraries’)

install_github(pkgs, ‘ramnathv’, ref = ‘dev’)

Alternately, you would also be able to try out rCharts online at


Montreal R User group meetup at Wajam

This Thursday (Jan 24th), 5:30pm, the good folks at Wajam are hosting a meetup of the Montreal R User Group.

The event will be at Bolidea at 4115 St Laurent, Montréal, QC. Be sure to RSVP.

From Benjamin Rollert:

This is an opportunity for people interested in R to hang out at our office, eat pizza and drink beer! We’ll also show some of the cool stuff we’ve done with R as part of live applications for our business intelligence.

Hope to see you there!

Montreal R User Group meetup Nov. 14th

After a bit of a summer lull, the Montreal R User Group is meeting up again! We’re trying out a new venue this time. Notman House is the home of the web in Montreal. They hold hackathons and other tech user group meetups, and they are all around great people in an all around great space in downtown Montreal.

Our meetup will feature R super-user Etienne Low-Decarie, who will give a walk through of some of the most powerful packages in R, many of which were built by rstats rock star Hadley Wickham.

I will also kick off the meetup with a short session on how R is revolutionizing data science in academia, journalism, business and beyond.

  • November 14th, 7pm at 51 Sherbrooke W.
  • BYOL&D (Bring Your Own Laptop & Data)

Don’t forget to RSVP. Hope to see you there!

New R User Group in Montreal

The Montreal R User Group is now official. You can join the group by visiting the meetup site.

The group has existed since 2010 in a narrower incarnation as the BGSA R/Stats Workshop Series. Previous workshops have featured invited facilitators on topics such as Causal Analysis, GLMs, GAMs, Multi-model inference, Phylogenetic analysis, Bayesian modeling, Meta-analysis, Ordination, Programming and more. Our goal is to broaden the scope of the workshops to incorporate topics from a wide variety of applied fields.

We are kicking off with a meetup on Monday, March 19th. At the meeting, I will be facilitating a workshop on building and estimating Maximum Likelihood models and doing model selection using AIC.

We look forward to seeing you at the next meetup!

Montreal R User Group Organizers
Corey Chivers
Etienne Low-Décarie
Zofia Ecaterina Taranu
Eric Pedersen