ggvis @ Rfun

class: center, middle, inverse, title-slide

# ggvis @ Rfun
### John Little
### 2017-03-06

---

## Visualization with ggvis

When in the data exploratory phase, you can quickly generate basic visualizations with minimal effort.

---
## Grammar of Graphics

- The ggvis visualization package combines 
    - the grammar of graphics in ggplot
    - reactive programming from shiny
    - data transformations pipelines (e.g. dplyr/tidyverse)
    
- Video:  https://www.youtube.com/watch?v=qtgQMxhAJLQ

---

## Impressions

- Very similar to ggplot2
    - layers
        - data
        - geom
        - coordinate system
    - a transferable training for ggplot2

- easier to learn if you are into the tidyverse
    - same syntax, pipes `%>%`
    - generates basic plots
    - see [cookbook](http://ggvis.rstudio.com/cookbook.html)

---

## Impressions: Continued

- works with shiny

- everything you can do in ggvis you can transfer to ggplot2 (or shiny)
    
- not a replacement for advanced graphics of ggplot2

- Still "under development"
    - version 0.4.3
    
But, very capable, quick, good for development, great for casual vis and can be fine for formal vis

---

```r
library(tidyverse)
library(ggvis)
cars <- mtcars
```

---

### Scatter Plot
Linear model and 95% confidence interval

```r
cars %>% 
  ggvis(~wt, ~mpg) %>% 
  layer_points() %>% 
  layer_model_predictions(model = "lm", se=TRUE)
```

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<div id="plot_id157230722" class="ggvis-output"></div>
<div class="plot-gear-icon">
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<ul class="ggvis-dropdown">
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<a id="plot_id157230722_renderer_svg" class="ggvis-renderer-button" onclick="return false;" data-plot-id="plot_id157230722" data-renderer="svg">SVG</a>
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<a id="plot_id157230722_renderer_canvas" class="ggvis-renderer-button" onclick="return false;" data-plot-id="plot_id157230722" data-renderer="canvas">Canvas</a>
</li>
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<a id="plot_id157230722_download" class="ggvis-download" data-plot-id="plot_id157230722">Download</a>
</li>
</ul>
</nav>
</div>
</div>
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---
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See [cookbook for more information on ggvis scatterplots](http://ggvis.rstudio.com/cookbook.html#scatterplots)

---

### Bar Graph

```r
cars %>% 
  mutate(cyl = factor(cyl, labels = c("four","six","eight"))) %>% 
  ggvis(~cyl) %>% 
  layer_bars()
```

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---
class: bottom, center
background-image: url(images/bar1.svg)

See [cookbook for more information on ggvis bar graphs](http://ggvis.rstudio.com/cookbook.html#bar-graphs)

---

### Bargraph 2
managing color and sort order

```r
mpg %>% 
  ggvis(~factor(mpg$class, 
                levels = names(sort(table(mpg$class), 
                                    decreasing = TRUE))), 
        ~hwy, 
        fill := "navy",
        stroke := "black")
```

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</nav>
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---
background-image: url(images/bar2.svg)

---

### Histogram

```r
cars %>% 
  ggvis(~mpg) %>% 
  layer_histograms()
```

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---
class: bottom, center
background-image: url(images/hist1.svg)

See [cookbook for more information on ggvis histograms](http://ggvis.rstudio.com/cookbook.html#histograms)

---

### Line graph

```r
cars %>% 
  ggvis( ~wt, ~mpg) %>% 
  group_by(cyl) %>% 
  layer_lines(stroke = ~factor(cyl)) %>% 
  layer_points(~wt, ~mpg, stroke := "black", fill = ~factor(cyl))
```

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---
class: bottom, center
background-image: url(images/line1.svg)

See [cookbook for more information on line graphs](http://ggvis.rstudio.com/cookbook.html#line-graphs)

---

```r
cars %>% 
  ggvis(~wt, ~mpg) %>% 
  group_by(cyl) %>% 
  layer_model_predictions(model="lm", se = TRUE) %>% 
  layer_points(~wt, ~mpg, stroke := "black", 
               fill = ~factor(cyl), size := ~hp, opacity := 0.7) 
```

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---
background-image: url(images/line2.svg)
---

### Boxplot

```r
cars %>% 
  mutate(cyl = factor(cyl, labels = c("four","six","eight"))) %>% 
  ggvis(~cyl, ~mpg) %>% 
  layer_boxplots()
```

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---
class: bottom, center
background-image: url(images/box1.svg)

See [cookbook for more information on boxplots](http://ggvis.rstudio.com/cookbook.html)

Hint: the info is at the bottom of the page

---

### BoxPlot with *mpg* dataset

```r
mpg %>% 
  ggvis(~class, ~hwy) %>% 
  layer_boxplots()
```

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---
background-image: url(images/box2.svg)

---

## Comparison to ggplot2

- [Comparison - Stack Exchange](http://stats.stackexchange.com/questions/117078/for-plotting-with-r-should-i-learn-ggplot2-or-ggvis/125124#125124)

- [Comparison - @ggvis v ggplot2](http://ggvis.rstudio.com/ggplot2.html)

---

### Scatterplot:  X Y axis

```r
# ggplot2
#
# ggplot(mpg, aes(displ, hwy)) +
#    geom_point()

#ggivs
mpg %>% 
  ggvis(~displ, ~hwy)
```

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</li>
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<a id="plot_id265331342_download" class="ggvis-download" data-plot-id="plot_id265331342">Download</a>
</li>
</ul>
</nav>
</div>
</div>
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ggvis.getPlot("plot_id265331342").parseSpec(plot_id265331342_spec);
</script>

---
background-image: url(images/mpg-scatter.svg)

---

### Color Points

fill = ~class

fill = "#339999"

fill = "red"

```r
# ggplot2
# ggplot(mpg, aes(displ, hwy)) +
#    geom_point(aes(color = class))

# ggvis
mpg %>% 
  ggvis(~displ, ~hwy) %>% 
  layer_points(fill = ~class)
```

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ggvis.getPlot("plot_id930524030").parseSpec(plot_id930524030_spec);
</script>

---
background-image: url(images/scatter-color.svg)

---

### Labels

add_axis("x", title = "foo title here")

```r
# ggplot2
# ggplot(mpg, aes(displ, hwy)) +
#    geom_point(aes(color = class)) +
#    labs(x = "Engine Displacement, in Liters", 
#                      y="Highway Miles per Gallon")

# ggvis
mpg %>% 
  ggvis(~displ, ~hwy) %>% 
  layer_points(fill = ~class) %>% 
  add_axis("x", title = "Engine Displacement, in Liters") %>%   
  add_axis("y", title = "Highway Miles per Gallon")
```

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ggvis.getPlot("plot_id235009597").parseSpec(plot_id235009597_spec);
</script>

---
background-image: url(images/scatter-legend.svg)

---

### Size

size:= 150

```r
# ggplot2
# ggplot(mpg, aes(displ, hwy)) +
#    geom_point(aes(color = class), size=7) +
#    labs(x = "Engine Displacement, in Liters", 
#                      y="Highway Miles per Gallon")

# ggviz
mpg %>% 
  ggvis(~displ, ~hwy) %>% 
  layer_points(fill = ~class, size := 150) %>% 
  add_axis("x", title = "Engine Displacement, in Liters") %>%
  add_axis("y", title = "Highway Miles per Gallon")
```

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<a id="plot_id302408362_download" class="ggvis-download" data-plot-id="plot_id302408362">Download</a>
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ggvis.getPlot("plot_id302408362").parseSpec(plot_id302408362_spec);
</script>

---
background-image: url(images/mpg-size.svg)

---

### Opacity

opacity := 0.5

```r
# ggplot2
# ggplot(mpg, aes(displ, hwy)) +
#    geom_point(aes(color = class), size=7, alpha=0.5) +
#    labs(x = "Engine Displacement, in Liters", 
#                      y="Highway Miles per Gallon")

# ggviz
mpg %>% 
  ggvis(~displ, ~hwy) %>% 
  layer_points(fill = ~class, size := 150, opacity := 0.5) %>% 
  add_axis("x", title = "Engine Displacement, in Liters") %>%
  add_axis("y", title = "Highway Miles per Gallon")
```

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---
background-image: url(images/mpg-opacity.svg)

---

### Interactivity

size := input_slider(10, 700, value = 75)

```{}
mpg %>% 
  ggvis(~displ, ~hwy) %>% 
  layer_points(fill = ~class, 
               size := input_slider(10, 700, value = 75), 
               opacity := 0.5) %>% 
  add_axis("x", title = "Engine Displacement, in Liters") %>%
  add_axis("y", title = "Highway Miles per Gallon")
```

To see this output, run this in your RStudio.  The output wil be in the Viewer pane. Ideally, this interactive output is done in concert with Shiny.

Learn more about itneractivity at the [ggvis-interactive documentation](http://ggvis.rstudio.com/interactivity.html).

---
class: center, middle

### Shareable under CC BY-NC license

Data, presentation, and handouts are shareable under [CC BY-NC license](https://creativecommons.org/licenses/by-nc/4.0/)

![This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.](https://licensebuttons.net/l/by-nc/4.0/88x31.png "This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License")