index.rmd

---
title: "Interactive Graphics in R"
subtitle: "<a href='https://plot.ly/r/'>with Plotly</a>"
author: "Morten Andersen & Andreas Hald Espensen"
date: "2019-04-23 (updated: `r Sys.Date()`)"
output:
  xaringan::moon_reader:
    #chakra: libs/remark-latest.min.js
    css: [default, default-fonts, custom.css]
    lib_dir: libs
    nature:
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---

# Basics

Plotly in R website: https://plot.ly/r/

--

"Plotly is an R package for creating interactive web-based graphs via the open source JavaScript graphing library [plotly.js](https://plot.ly/javascript/)."

--

Rendered locally through the [htmlwidgets](http://www.htmlwidgets.org/) framework.

--

**Installation**: 

```{r echo=TRUE, message=FALSE, warning=FALSE}
if (!require("plotly")) install.packages("plotly")
library(plotly)
```

--

**Getting Started**: https://plot.ly/r/getting-started/

--

*How did we come across the Plotly library?*

???

By no means exhaustive. Only an introduction to plotly. 

Working on shiny apps as a Student Assistant at Grundfos' Data Analytics department. 

---

# Creating a Plot

`plot_ly`: Maps R objects to plotly.js. 

**Usage**: 

```{r eval=FALSE}
plot_ly(data = data.frame(), ..., type = NULL, name, color, colors = NULL,
  alpha = NULL, stroke, strokes = NULL, alpha_stroke = 1, size,
  sizes = c(10, 100), span, spans = c(1, 20), symbol, symbols = NULL,
  linetype, linetypes = NULL, split, frame, width = NULL, height = NULL,
  source = "A")
```

`data`: Data frame (optional)

`...`: Arguments passed along to the trace type. E.g. `x = 1:10`, `x = ~Time`, `y`, etc.

???

---

# Creating a Plot - Let's see it in action!

```{r echo=TRUE, fig.height=5.5, fig.width=12}
p <- plot_ly(midwest, x = ~percollege, color = ~state, type = "box")
p
```

???

`Midwest` data set: Demographic information of midwest counties.
`percollege`: Percent college educated.

---

# Connection with ggplot2

Contains the function `ggplotly` which will convert `ggplot2` figures into a Plotly object. 

--

You have the option to manipulate the object with the `style` function.

--

More information at: https://plot.ly/ggplot2/extending-ggplotly/

???

---

# Connection with ggplot2

```{r fig.height=5.5, fig.width=12}
p <- ggplot(fortify(forecast::gold), aes(x, y)) + geom_line()
p
```

???

`gold`: Gold price time series - Daily morning gold prices in US dollars. 1 January 1985 - 31 March 1989.

---

# Connection with ggplot2

```{r fig.height=5.5, fig.width=12}
p <- ggplot(fortify(forecast::gold), aes(x, y)) + geom_line()
gg <- ggplotly(p)
gg
```


???

---

# Connection with ggplot2

```{r fig.height=5.5, fig.width=12}
p <- ggplot(fortify(forecast::gold), aes(x, y)) + geom_line()
gg <- ggplotly(p)
gg <- style(gg, line = list(color = 'gold'), hoverinfo = "y", traces = 1)
gg
```


???

---

# Cheatsheet + Cookbook

Handy cheatsheet available at: https://images.plot.ly/plotly-documentation/images/r_cheat_sheet.pdf.

--

Cookbook available at: https://plotly-r.com/index.html 

???

---

# Creating a Plot


```{r fig.height=5.5, fig.width=12}
trace_0 <- rnorm(100, mean = 5)
trace_1 <- rnorm(100, mean = 0)
trace_2 <- rnorm(100, mean = -5)
x <- c(1:100)
data <- data.frame(x, trace_0, trace_1, trace_2)
head(data)
```

???
---

# Creating a Plot


```{r fig.height=4.5, fig.width=12}
p <- plot_ly(data, x = ~x, y = ~trace_0, name = 'trace 0', type = 'scatter', mode = 'lines') %>%
  add_trace(y = ~trace_1, name = 'trace 1', mode = 'lines+markers') %>%
  add_trace(y = ~trace_2, name = 'trace 2', mode = 'markers')
#p <- p %>% layout(hovermode = 'compare') 
p
```

???
---
# Creating a Plot


```{r fig.height=4.5, fig.width=12}
p_hist <- data %>% plot_ly(alpha = 0.6) %>%
  add_histogram(x = ~trace_0) %>% add_histogram(x = ~trace_1) %>% add_histogram(x = ~trace_2) %>% 
  layout(barmode = "overlay", xaxis = list(title = "My x-axis title"))
p_hist
```

???

---
# Iris


```{r fig.height=4, fig.width=12}
pal <- c("red", "blue", "green")

p <- iris %>% plot_ly(x = ~Sepal.Length, y = ~Petal.Length, color = ~Species, colors = pal,
                      type = "scatter", mode = "markers", hoverinfo = 'text',
        text = ~paste('</br> Species: ', Species,
                      '</br> Petal Lenght: ', Petal.Length,
                      '</br> Petal Width: ', Petal.Width))
p

```

???


---
# dygraphs for R

dygraphs in R website: https://rstudio.github.io/dygraphs/index.html

"The dygraphs package is an R interface to the dygraphs JavaScript charting library. It provides rich facilities for charting time-series data in R" (https://rstudio.github.io/dygraphs/index.html)

```{r echo=TRUE, message=FALSE, warning=FALSE}
if (!require("dygraphs")) install.packages("dygraphs")
library(dygraphs)
```


???

---
# dygraphs for R


```{r fig.height=5.5, fig.width=12}
lungDeaths <- cbind(mdeaths, fdeaths)
dygraph(lungDeaths) %>% dyRangeSelector()
``` 

???

---
# Custom plots


```{r fig.height=4.5, fig.width=12}
lungDeaths <- cbind(mdeaths, fdeaths)
dygraph(lungDeaths) %>%
  dyRangeSelector() %>%
  dyBarSeries('fdeaths') %>% 
  dyFilledLine('mdeaths')
``` 
???



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class: center, middle

# Thank you!

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