Getting started with GoFigr in R

Getting started with GoFigr in R is easy! We support both interactive sessions in RStudio as well as integration with knitr.

Step 1: Register for a GoFigr account

Step 2: install the client library

library(devtools)
devtools::install_github("https://github.com/gofigr/gofigR")

Step 3: Load the library and configure with gfconfig

The wizard will prompt you for a username and password, and will automatically generate an API key for you.

> library(gofigR)
Attaching package: ‘gofigR’

> gfconfig()
-------------------------------------------------------------------
Welcome to GoFigr! This wizard will help you get up and running.
-------------------------------------------------------------------

Username: demo
Password: *******************
Testing connection...
  => Success
API key (leave blank to generate a new one): 
Key name (e.g. Alyssa's laptop): work laptop
Fetching workspaces...


| Number|Name              |Description                  |API.ID                               |
|------:|:-----------------|:----------------------------|:------------------------------------|
|      1|Primary Workspace |demouser's primary workspace |98f328fc-f984-482c-b7f6-8ed272527a42 |
|      2|Rocketship Bio    |Let's do some science        |bff6c952-fb2c-4333-80e5-5dc7291d47cc |
|      3|Plotly demos      |N/A                          |1424ea0f-7d42-4ef5-9ba8-41aa9c5b1a94 |

Please select a default workspace (1-3): 1

Configuration saved to /Users/maciej/.gofigr. Happy analysis!

Step 4: Open your Rd file and call gofigR::enable in the setup chunk

```{r setup, include=FALSE}
library(gofigR)

gofigR::enable(auto_publish=TRUE)
```

That’s it! From now on, all ggplots will be published automatically:

```{r correlations}
p <- ggplot(mtcars, aes(x=wt, y=mpg, color=cyl, size=cyl)) +
      geom_point() +
      theme(legend.position="none")
plot(p)
```

If you do not wish to enable automatic publishing, you can still publish plots manually with publish:

p <- ggplot(mtcars, aes(x=wt, y=mpg, color=cyl, size=cyl)) +
      geom_point() +
      theme(legend.position="none")
publish(p, "My manually published figure")

Both knitr and interactive use within RStudio are supported:

If you want to publish output from base R plotting functions, you can capture those manually with gofigR::publish_base. Use the name argument to supply the figure name. For example:

```{r manual_capture, fig.width=8, fig.height=8}
library(RColorBrewer)

gofigR::publish_base({
  base::plot(pressure, main="Pressure vs temperature")
  text(200, 50, "Note the non-linear relationship")
}, data=pressure, figure_name="Pressure vs temperature")

gofigR::publish_base({
  # The mtcars dataset:
  data <- as.matrix(mtcars)

  coul <- colorRampPalette(brewer.pal(8, "PiYG"))(25)
  heatmap(data, scale="column", col = coul, main="Visualizing mtcars")
}, data=mtcars, figure_name="Cars")
```

The data argument, if provided, specifies which data to associate with the figure (it will be stored as an RDS file). Here’s what that looks like inside RStudio:

Example Knitr output

You can view the knitted output for the examples above here:

example Download

Next steps & getting help

For more documentation, please checkout the README included with the library, also available here: https://github.com/GoFigr/gofigR/.

You can also reach out to support@gofigr.io with any questions!