On CRAN: http://cran.r-project.org/web/packages/metricsgraphics/index.html
Vignette: http://cran.r-project.org/web/packages/metricsgraphics/vignettes/introductiontometricsgraphics.html
metricsgraphics is an 'htmlwidget' interface to the MetricsGraphics.js D3-based charting library.
Charts look best in a Boostrap page (unless you customize your own CSS).
You can see [core examples] (http://rpubs.com/hrbrmstr/53741) and fairly extended grid example on RPubs.
The following functions are implemented:
mjs_plot: Create a new metricsgraphics.js plotmjs_line: metricsgraphics.js linechart "geom"mjs_add_line: used to add additional columns for a multi-line chartmjs_hist: Shortcut for plotting MetricsGraphics histogramsmjs_histogram: Plot Histograms with MetrisGraphicsmjs_add_legend: adds a legend to a line (or mult-line) chartmjs_point: metricsgraphics.js scatterplot "geom"mjs_bar: metricsgraphics.js bar chart "geom"mjs_axis_x: Configure x axis ticks & limitsmjs_axis_y: Configure y axis ticks & limitsmjs_labs: Configure axis labels & plot descriptionmjs_add_baseline: Sets a baseline line/labelmjs_add_marker: Sets a marker line/labelmjs_grid:grid.arrange-like functionality formetricsgraphicschartsmjs_add_mouseover: provides support for MetricsGraphics custom rolloversmjs_add_confidence_band: provides support for confidence bandsmjs_annotate_region: Region annotations for line charts [EXPERIMENTAL]mjs_add_css_rule: Add a CSS rule to the rendered htmlwidget
# stable
install.packages("metricsgraphics")
# development
# devtools::install_github("hrbrmstr/metricsgraphics")library(metricsgraphics)
library(RColorBrewer)
tmp <- data.frame(year=seq(1790, 1970, 10), uspop=as.numeric(uspop))
tmp %>%
mjs_plot(x=year, y=uspop) %>%
mjs_line() %>%
mjs_add_marker(1850, "Something Wonderful") %>%
mjs_add_baseline(150, "Something Awful")
tmp %>%
mjs_plot(x=year, y=uspop, width=600) %>%
mjs_line(area=TRUE)
tmp %>%
mjs_plot(x=uspop, y=year, width=500, height=400) %>%
mjs_bar() %>%
mjs_axis_x(xax_format = 'plain')
mtcars %>%
mjs_plot(x=wt, y=mpg, width=600, height=500) %>%
mjs_point(color_accessor=carb, size_accessor=carb) %>%
mjs_labs(x="Weight of Car", y="Miles per Gallon")
mtcars %>%
mjs_plot(x=wt, y=mpg, width=600, height=500) %>%
mjs_point(color_accessor=cyl,
x_rug=TRUE, y_rug=TRUE,
size_accessor=carb,
size_range=c(5, 10),
color_type="category",
color_range=brewer.pal(n=11, name="RdBu")[c(1, 5, 11)]) %>%
mjs_labs(x="Weight of Car", y="Miles per Gallon")
mtcars %>%
mjs_plot(x=wt, y=mpg, width=400, height=300) %>%
mjs_point(least_squares=TRUE) %>%
mjs_labs(x="Weight of Car", y="Miles per Gallon")
set.seed(1492)
dat <- data.frame(date=seq(as.Date("2014-01-01"),
as.Date("2014-01-31"),
by="1 day"),
value=rnorm(n=31, mean=0, sd=2))
dat %>%
mjs_plot(x=date, y=value) %>%
mjs_line() %>%
mjs_axis_x(xax_format = "date")
# Custom rollovers
dat %>%
mjs_plot(x=date, y=value) %>%
mjs_line() %>%
mjs_axis_x(xax_format = "date") %>%
mjs_add_mouseover("function(d, i) {
$('{{ID}} svg .mg-active-datapoint')
.text('custom text : ' + d.date + ' ' + i);
}")
# also works for scatterplots with a slight mod
set.seed(1492)
dat <- data.frame(value=rnorm(n=30, mean=5, sd=1),
value2=rnorm(n=30, mean=4, sd=1),
test = c(rep(c('test', 'test2'), 15)))
dat %>%
mjs_plot(x = value, y = value2) %>%
mjs_point() %>%
mjs_add_mouseover("function(d, i) {
$('{{ID}} svg .mg-active-datapoint')
.text('custom text : ' + d.point.test + ' ' + i);
}")
set.seed(1492)
stocks <- data.frame(
time = as.Date('2009-01-01') + 0:9,
X = rnorm(10, 0, 1),
Y = rnorm(10, 0, 2),
Z = rnorm(10, 0, 4))
stocks %>%
mjs_plot(x=time, y=X) %>%
mjs_line() %>%
mjs_axis_x(show=FALSE) %>%
mjs_axis_y(show=FALSE)
stocks %>%
mjs_plot(x=time, y=X) %>%
mjs_line() %>%
mjs_add_line(Y) %>%
mjs_add_line(Z) %>%
mjs_axis_x(xax_format="date")
mjs_plot(rnorm(10000)) %>%
mjs_histogram(bins=30, bar_margin=1)
movies <- ggplot2movies::movies[sample(nrow(ggplot2movies::movies), 1000), ]
mjs_plot(movies$rating) %>% mjs_histogram()
mjs_plot(movies, rating) %>%
mjs_histogram() %>%
mjs_labs(x_label="Histogram of movie ratings",
y_label="Frequency")
mjs_plot(movies$rating) %>% mjs_histogram(bins=30)
mjs_plot(runif(10000)) %>%
mjs_labs(x_label="runif(10000)") %>%
mjs_histogram()
mjs_plot(rbeta(10000, 2, 5)) %>%
mjs_labs(x_label="rbeta(10000, 2, 3)") %>%
mjs_histogram(bins=100) %>%
mjs_axis_y(extended_ticks=TRUE)
bimod <- c(rnorm(1000, 0, 1), rnorm(1000, 3, 1))
mjs_plot(bimod) %>% mjs_histogram()
mjs_plot(bimod) %>% mjs_histogram(bins=30)
bimod %>% mjs_hist(30)
library(shiny)
library(metricsgraphics)
ui = shinyUI(fluidPage(
h3("MetricsGraphics Example", style="text-align:center"),
metricsgraphicsOutput('mjs1'),
br(),
metricsgraphicsOutput('mjs2')
))
server = function(input, output) {
mtcars %>%
mjs_plot(x=wt, y=mpg, width=400, height=300) %>%
mjs_point(color_accessor=carb, size_accessor=carb) %>%
mjs_labs(x="Weight of Car", y="Miles per Gallon") -> m1
set.seed(1492)
stocks <- data.frame(
time = as.Date('2009-01-01') + 0:9,
X = rnorm(10, 0, 1),
Y = rnorm(10, 0, 2),
Z = rnorm(10, 0, 4))
stocks %>%
mjs_plot(x=time, y=X) %>%
mjs_line() %>%
mjs_add_line(Y) %>%
mjs_add_line(Z) %>%
mjs_axis_x(xax_format="date") %>%
mjs_add_legend(legend=c("X", "Y", "Z")) -> m2
output$mjs1 <- renderMetricsgraphics(m1)
output$mjs2 <- renderMetricsgraphics(m2)
}
shinyApp(ui = ui, server = server)There's another example provided by https://github.com/DocOfi which can be viewed at http://rpubs.com/DocOfi/352947. The Rmd file that created the example can be found at https://github.com/DocOfi/datasciencecoursera/tree/master/Exploratory_Data_Analysis/MetricsGraphics
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
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