I’ve updated my [metricsgraphics](https:\/\/github.com\/hrbrmstr\/metricsgraphics) package to version [0.7](https:\/\/github.com\/hrbrmstr\/metricsgraphics\/releases\/tag\/v0.7). The core [MetricsGraphics](http:\/\/metricsgraphicsjs.org) JavaScript library has been updated to version 2.1.0 (from 1.1.0). Two blog-worthy features since releasing version 0.5 are `mjs_grid` (which is a `grid.arrange`-like equivalent for `metricsgraphics` plots and `mjs_add_rollover` which lets you add your own custom rollover text to the plots.<\/p>\n
The `grid.arrange` (and `arrangeGrob`) functions from the `gridExtra` package come in handy when combining `ggplot2` charts. I wanted a similar way to arrange independent or linked `metricsgraphics` charts, hence `mjs_grid` was born. <\/p>\n
`mjs_grid` uses the tag functions in `htmltools` to arrange `metricsgraphics` plot objects into an HTML `<\/p>\n
` structure. At present, only uniform tables are supported, but I’m working on making the grid feature more flexible (just like `grid.arrange`). The current functionality is pretty straightforward:<\/p>\n– You build individual `metricsgraphics` plots;
\n– Optionally combine them in a `list`;
\n– Pass in the plots\/lists into `mjs_grid`;
\n– Tell `mjs_grid` how many rows & columns are in the grid; and
\n– Specify the column widths<\/p>\n
But, code > words, so here are some examples. To avoid code repetition, note that you’ll need the following packages available to run most of the snippets below:<\/p>\n
library(metricsgraphics)\r\nlibrary(htmlwidgets)\r\nlibrary(htmltools)\r\nlibrary(dplyr)<\/pre>\nFirst, we’ll combine a few example plots:<\/p>\n
tmp <- data.frame(year=seq(1790, 1970, 10), uspop=as.numeric(uspop))\r\ntmp %>%\r\n mjs_plot(x=year, y=uspop, width=300, height=300) %>%\r\n mjs_line() %>%\r\n mjs_add_marker(1850, \"Something Wonderful\") %>%\r\n mjs_add_baseline(150, \"Something Awful\") -> mjs1\r\n\r\nmjs_plot(rnorm(10000), width=300, height=300) %>%\r\n mjs_histogram(bins=30, bar_margin=1) -> mjs2\r\n\r\nmovies <- ggplot2::movies[sample(nrow(ggplot2::movies), 1000), ]\r\nmjs_plot(movies$rating, width=300, height=300) %>% mjs_histogram() -> mjs3\r\n\r\ntmp %>%\r\n mjs_plot(x=year, y=uspop, width=300, height=300) %>%\r\n mjs_line(area=TRUE) -> mjs4\r\n\r\nmjs_grid(mjs1, mjs2, mjs3, mjs4, ncol=2, nrow=2)<\/pre>\n