Augmenting data exploration with interactive web graphics

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# Augmenting data exploration with interactive web graphics
### Carson Sievert, PhD
### Slides: <a href="https://talks.cpsievert.me" class="uri">https://talks.cpsievert.me</a> <br /> <br /> <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"/></svg> <a href="https://twitter.com/cpsievert"><span class="citation">@cpsievert</span></a> <br /> <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> <a href="https://github.com/cpsievert"><span class="citation">@cpsievert</span></a> <br /> <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 17.4 52.1 39.5 154.1 113.6 21.1 15.4 56.7 47.8 92.2 47.6 35.7.3 72-32.8 92.3-47.6 102-74.1 131.6-96.3 154-113.7zM256 320c23.2.4 56.6-29.2 73.4-41.4 132.7-96.3 142.8-104.7 173.4-128.7 5.8-4.5 9.2-11.5 9.2-18.9v-19c0-26.5-21.5-48-48-48H48C21.5 64 0 85.5 0 112v19c0 7.4 3.4 14.3 9.2 18.9 30.6 23.9 40.7 32.4 173.4 128.7 16.8 12.2 50.2 41.8 73.4 41.4z"/></svg> <a href="mailto:cpsievert1@gmail.com" class="email">cpsievert1@gmail.com</a> <br /> <svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M336.5 160C322 70.7 287.8 8 248 8s-74 62.7-88.5 152h177zM152 256c0 22.2 1.2 43.5 3.3 64h185.3c2.1-20.5 3.3-41.8 3.3-64s-1.2-43.5-3.3-64H155.3c-2.1 20.5-3.3 41.8-3.3 64zm324.7-96c-28.6-67.9-86.5-120.4-158-141.6 24.4 33.8 41.2 84.7 50 141.6h108zM177.2 18.4C105.8 39.6 47.8 92.1 19.3 160h108c8.7-56.9 25.5-107.8 49.9-141.6zM487.4 192H372.7c2.1 21 3.3 42.5 3.3 64s-1.2 43-3.3 64h114.6c5.5-20.5 8.6-41.8 8.6-64s-3.1-43.5-8.5-64zM120 256c0-21.5 1.2-43 3.3-64H8.6C3.2 212.5 0 233.8 0 256s3.2 43.5 8.6 64h114.6c-2-21-3.2-42.5-3.2-64zm39.5 96c14.5 89.3 48.7 152 88.5 152s74-62.7 88.5-152h-177zm159.3 141.6c71.4-21.2 129.4-73.7 158-141.6h-108c-8.8 56.9-25.6 107.8-50 141.6zM19.3 352c28.6 67.9 86.5 120.4 158 141.6-24.4-33.8-41.2-84.7-50-141.6h-108z"/></svg> <a href="https://cpsievert.me/" class="uri">https://cpsievert.me/</a> <br /> <br /> Slides released under <a href="https://github.com/cpsievert/talks/blob/gh-pages/LICENSE">Creative Commons</a>

---

background-image: url(../20171207/workflow.svg)
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# Data science workflow

---
background-image: url(../20171207/workflow1.svg)
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## Interactive web graphics are great for sharing insight

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## Interactivity also enhances the sense-making process

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## Problem: Web technologies aren't designed for this phase

## Solution: bring them to R, Python, etc

---
background-image: url(htmlwidgets.png)
background-size: contain

## htmlwidgets: a standard for implementing R interfaces to JS

<h3><a href="https://htmlwidgets.org">htmlwidgets.org</a></h3>

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background-image: url(htmlwidgets-gallery.png)
background-size: contain

<h3><a href="http://gallery.htmlwidgets.org">gallery.htmlwidgets.org</a></h3>

<!--
class: principles

## The problem with a 'naive' R->JS binding

* Most JS libraries don't natively support multiple linked views.

* Instead, it's common for interactions to fire events, which _can be_ used to implement linked views.

* Many `{htmlwidgets}` make it possible to listen to such events in `{shiny}`.

* Some `{htmlwidgets}` 
-->

---
### plotly: an advanced htmlwidget

Make static `{ggplot2}` plots interactive with `plotly::ggplotly()`!

```r
library(plotly)
p <- ggplot(diamonds, aes(x = log(price), color = clarity)) + 
    geom_freqpoly(stat = "density") + 
    facet_wrap(~cut)
ggplotly(p)
```

---
### plotly: an advanced htmlwidget

Or, use the underlying [plotly.js graphing library](https://github.com/plotly/plotly.js) more directly:

```r
library(plotly)
plot_ly(diamonds, x = ~cut, color = ~clarity)
```

---
class: principles

### plotly: an advanced htmlwidget

* All plots come pre-packaged with "within-widget" interaction (e.g., tooltip, zoom, and legend filter).

* `{shiny}` provides the tools to implement any type of other interactivity that you want.

* `{plotly}` has two ways to share information across widgets (with or without `{shiny}`).

---
### shiny: create a web UI to re-execute R code

.pull-left[
```r
library(shiny)
library(plotly)

ui <- fluidPage(
* selectInput(
*   "y", "Choose a variable", 
*   choices = names(diamonds)
* ),
  plotlyOutput("p")
)

server <- function(input, output) {

output$p <- renderPlotly({
    plot_ly(
*     y = diamonds[[input$y]]
    )
  })
  
}

shinyApp(ui, server)
```
]

.pull-right[
<img src="shiny-plotly-y.gif" width="100%" >
]

---
### Use {plotly} like an input control

.pull-left[
```r
library(shiny)
library(plotly)

ui <- fluidPage(
  selectInput(
    "y", "Choose a variable", 
    choices = names(diamonds)
  ),
  plotlyOutput("p"),
  verbatimTextOutput("hover")
)

server <- function(input, output) {
  output$p <- renderPlotly({
    plot_ly(y = diamonds[[input$y]])
  })
* output$hover <- renderPrint({
*   #Think of this like an input value
*   event_data("plotly_hover")
* })
}

shinyApp(ui, server)
```
]

.pull-right[
<img src="shiny-plotly-hover.gif" width="90%" >
]

---
### Linking htmlwidgets with shiny

Many `{htmlwidgets}` provide `{shiny}` 'hooks' into user events.

---
### Linking htmlwidgets with shiny

Lots of different user events available (e.g., `{leaflet}` zoom)!

---
### Linking htmlwidgets with shiny

`{shiny}` provides tools for [managing state](https://plotly-r.com/linking-views-with-shiny.html#reactive-vals), -- useful for making multiple comparisons:

---
### Linking htmlwidgets with shiny

Managing state is also useful for 'drill-down' apps:

---
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### Linking with shiny, in general

Super powerful and flexible, but requires advanced `{shiny}` programming as well as an R process running _somewhere_.

---
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### Linking without shiny

* [`{crosstalk}`](https://rstudio.github.io/crosstalk/) provides a standard for linking `{htmlwidgets}` entirely client-side (i.e., in JavaScript).

---

### Link plotly with DT via crosstalk

```r
library(plotly)
library(crosstalk)
*sd <- SharedData$new(mpg)
p <- plot_ly(sd, x = ~displ, y = ~hwy) %>%
  add_markers() %>%
  highlight("plotly_selected")
bscols(p, DT::datatable(sd))
```

---

### Link plotly with DT via crosstalk

```r
library(plotly)
library(crosstalk)
*sd <- SharedData$new(mpg)
p <- plot_ly(sd, x = ~displ, y = ~hwy) %>%
  add_markers() %>%
  highlight("plotly_selected")
bscols(p, DT::datatable(sd))
```

* Most [`{crosstalk}`-compatible widgets](https://rstudio.github.io/crosstalk/widgets.html) only support this sort of "simple transient selection". 
* However, when linking multiple `{plotly}` widgets via `{crosstalk}`, you can do a lot more!

---
### Generalized selection in plotly

```r
library(plotly)
*tx <- SharedData$new(txhousing, ~city)
p <- ggplot(tx) + geom_line(aes(date, median, group = city))
gg <- ggplotly(p)
*highlight(gg, on = "plotly_click")
```

---
### Persistent selection and search

```r
*highlight(gg, on = "plotly_hover", persistent = T, selectize = T, dynamic = T)
```

---
### Works with facetting

```r
TX <- SharedData$new(tx, ~year)
p <- ggplot(TX, aes(month, median, group = year)) + geom_line() +
*  facet_wrap(~city, ncol = 2)
highlight(ggplotly(p), persistent = T, selectize = T, dynamic = T)
```

---
background-image: url(https://i.imgur.com/Id2nVFG.gif)
background-size: contain

---
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background-image: url(https://i.imgur.com/Id2nVFG.gif)
background-size: contain

# Generally useful for comparing within/across panels!

---
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# Have _lots_ of panels?

### Check out [TrelliscopeJS with Plotly](http://ryanhafen.com/blog/trelliscopejs-plotly)

---
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# Beyond trellis (i.e. facet) displays

---
### Query missing values by city

```r
demo("crosstalk-highlight-pipeline", package = "plotly")
```

---
background-image: url(pipeline.svg)
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## "Linking as a <br> database query"

---
background-image: url(pipeline.svg)
background-size: contain
class: bottom, left

.pull-left[
```sql
SELECT * FROM table 
  WHERE city == "South Padre Island"
```
]

---
### Works with 'aggregated' traces

---
class: middle, principles

## The implementation

```r
d <- SharedData$new(mpg)
dots <- plot_ly(d, color = ~class, x = ~displ, y = ~cyl)
*boxs <- plot_ly(d, color = ~class, x = ~class, y = ~cty) %>% add_boxplot()
*bars <- plot_ly(d, x = ~class, color = ~class)

subplot(dots, boxs) %>%
  subplot(bars, nrows = 2) %>%
  layout(barmode = "overlay") %>%
  highlight("plotly_selected")
```

plotly.js dynamically recomputes summary stats as a function of selection

---
### See relationships evolve over time ([made via ggplot2](https://plotly-book.cpsievert.me/linking-animated-views.html))

---
background-image: url(../20170803/tour.gif)
background-size: contain
class: middle

### Interactively [plot models in data space](../20180118/tour.html) ([code](https://github.com/ropensci/plotly/blob/master/demo/animation-tour-USArrests.R))

---
## Summary

* Interactive (web) graphics can enhance the sense-making process for data analysts (as well as for their audience).

* In particular, multiple linked views is a powerful paradigm for exploring data.

* `{htmlwidgets}` such as `{plotly}` make it easy to leverage web graphics from R.

* `{shiny}` provides a reactive programming framework, which we can leverage to link multiple `{htmlwidgets}`.

* `{crosstalk}` and `{plotly}` make it possible to link views without `{shiny}`.

---
class: middle, center, principles

## Thanks! Questions?

Slides: <https://talks.cpsievert.me>

Learn more: <https://plotly-book.cpsievert.me>

#### Contact