Awesome

metricsgraphics

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 plot
• mjs_line: metricsgraphics.js linechart "geom"
• mjs_add_line: used to add additional columns for a multi-line chart
• mjs_hist: Shortcut for plotting MetricsGraphics histograms
• mjs_histogram: Plot Histograms with MetrisGraphics
• mjs_add_legend: adds a legend to a line (or mult-line) chart
• mjs_point: metricsgraphics.js scatterplot "geom"
• mjs_bar: metricsgraphics.js bar chart "geom"
• mjs_axis_x: Configure x axis ticks & limits
• mjs_axis_y: Configure y axis ticks & limits
• mjs_labs: Configure axis labels & plot description
• mjs_add_baseline: Sets a baseline line/label
• mjs_add_marker: Sets a marker line/label
• mjs_grid: grid.arrange-like functionality for metricsgraphics charts
• mjs_add_mouseover: provides support for MetricsGraphics custom rollovers
• mjs_add_confidence_band: provides support for confidence bands
• mjs_annotate_region: Region annotations for line charts [EXPERIMENTAL]
• mjs_add_css_rule: Add a CSS rule to the rendered htmlwidget

Installation

# stable
install.packages("metricsgraphics")
# development
# devtools::install_github("hrbrmstr/metricsgraphics")

Usage

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

Code of Conduct

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.