---
title: Adding htmlwidgets to R Markdown posts
date: '2017-09-07'
slug: adding-htmlwidgets-to-r-markdown-posts
raw: "https://raw.githubusercontent.com/rbind/blogdown-demo/master/content/post/2017-09-07-adding-htmlwidgets-to-r-markdown-posts.Rmd"
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(comment = NA, tidy = FALSE, warning = FALSE, message = FALSE)
```

This is a minimal example of how to use [htmlwidgets](http://www.htmlwidgets.org/index.html) in R Markdown posts. We will use a tidy version of Anscombe's quartet (thanks to [David Robinson](https://rpubs.com/dgrtwo/tidy-anscombe)). To reshape the anscombe dataset, you will need the **dplyr** and **tidyr** packages loaded. You'll also need to install and load the **DT** package for example 1, and the **ggplot2** and **plotly** packages for example 2.

```{r}
library(dplyr)
library(tidyr)
library(DT)
library(ggplot2)
library(plotly)
anscombe_tidy <- anscombe %>%
    mutate(observation = seq_along(x1)) %>%
    gather(key, value, -observation) %>%
    separate(key, c("variable", "set"), 1, convert = TRUE) %>%
    mutate(set = as.character(as.roman(set))) %>%
    spread(variable, value) %>%
    arrange(set)
head(anscombe_tidy)
```

Now that it has been reshaped, we can view and plot Anscombe's quartet in our post.


# Example 1: DataTables via the **DT** package

We can interactively view the tidied Anscombe's quartet using the **DT** package:

```{r}
anscombe_tidy %>% 
datatable(rownames = FALSE, 
          options = list(
            pageLength = 11, 
            autoWidth = TRUE, 
            columnDefs = list(list(
              className = 'dt-left', 
              targets = 0),
              list(className = 'dt-center', targets = 1))))
```


# Example 2: Using the **plotly** package

We can also interactively plot the tidied Anscombe's quartet using the **plotly** package (you will need the **ggplot2** package loaded here):


```{r}
cols <- c("#0072B2", "#009E73", "#D55E00", "#CC79A7")
ans_plot <- ggplot(anscombe_tidy, aes(x, y, colour = set)) +
  geom_point(size = 3, alpha = .7) +
  geom_smooth(method = "lm", se = FALSE) + 
  facet_wrap(~ set) +
  theme_bw() +
  theme(legend.position="none") +
  scale_colour_manual(values = cols) 

ggplotly(ans_plot)
```