Survey your audience and visualise the results with R and Google forms

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Survey your audience and visualise the results with R and Google forms

I wanted to make my presentation on dataviz at the UQ School of

more interactive.

A quiz is a good way to engage your audience. Given I was giving a talk
about R datavisuals I thought it would be fun to visualise the quiz
results using R live with the audience. To top it off, we posted the
results to Twitter.

This blog describes is how I did that.

You could also use this system to survey our audience and share the
results live. Just prepare you R code and set it to run at a certain
time during your talk with a task scheduling algorithm.

Setting up the survey

I used Google Forms to do my quiz. You can take it
I posed a few questions that challenged the audience to think about the
best way to visualise data.

It is pretty easy to set up a survey if you have a gmail account. A few

  • You can add images, which is great posing questions about results.

  • I used the ‘short answer’ input for numeric answers. If you click
    the validation tab at the bottom of each ‘short answer’ question you
    can require users enter certain types of numbers (e.g. within a

  • Think carefully about limiting required inputs if you want to avoid
    bugs that might arise from unexpected answers.

  • There is a green button at the top of the form that let’s you link
    it to a google sheet. Do this.

  • You can make the sheet public, so other people can use it, but
    changing the sharing settings.

Connecting to your survey answers in R

I used the googlesheets package to read my survey answers from the
(public) spreadsheet. You will need to authenticate yourself first:


This will prompt you to login to your google account and authenticate an
app that allows the connection to happen.

Now we can load our data:

sheet_url <- ""
dataviz <- gs_url(sheet_url) #creates connection

If you want to keep your sheet private you can use gs_ls() to list all
your sheets, and then pick a name to read it in. e.g. like this:

dataviz <- gs_title("Dataviz quiz 2018 v2 (Responses)")
dat <- gs_read(dataviz)

Analysing your data

The file dat we just read in is a dataframe like object (actually a
tibble) where each column is a question and each row is a response. The
first column is a time stamp.

All other columns are titled with your questions.

It will make life easier if we rename the columns to shorter (but still
descriptive) names.

newnames <- c("timestamp", "shopping",
names(dat) <- newnames

Now let’s create some dataviz

datplot <- na.omit(dat)
ggplot(datplot, aes(x = room, y = cb_age)) +
  geom_boxplot() +
  xlab("Position in room") +
  ylab("Guess at CB's age") +
  ylim(0, 75) +

A boxplot of the audience’s guesses at my age by their position in the
room. I limited the y-axis because there were some outrageously large

Share the results

We could show the audience the results on our screen. But why not let
Twitter know too!

For this, I used the rtweet package. rtweet is pretty simple to use
once you’ve set up an app on Twitter’s API and authorised R to access
. So get rtweet then look at the vignette vignette("auth").
Follow the instructions to the letter and you shouldn’t have any

Once authorisation is done, its a simple matter to save our plot as a
png to use in a tweet:

myplot <- ggplot(datplot, aes(x = room, y = cb_age)) +
ggsave(filename = "myplot.png", myplot)

Now just write your tweet and send it off to twitter.

newstatus = "Chris age as surveyed at  #UQwinterSchool
@DoktrNick @UQwinterSchool"

post_tweet(status = newstatus,
           media = "myplot.png")

Next steps?

So I tried this as a way of doing a live R tutorial. Next step would be
to try and integrate it into a talk without showing the R coding. For
that you would either need to get a friend to run the code or use a
scheduler (like the
R package).

Be careful though! You never know what answers people may give if
allowed. So design you code to be robust to strange answers (like that I
am 100 years old).

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