trelliscopejs v0.1.11

trelliscopejs R Package

Trelliscope is a scalable, flexible, interactive approach to visualizing data. The trelliscopejs R package provides methods that make it easy to create a Trelliscope display specification for the Trelliscope JavaScript library trelliscopejs-lib. High-level functions are provided for creating displays from within dplyr (via summarise()) or ggplot2 (via facet_trelliscope()) workflows. Low-level functions are also provided for creating new interfaces.

Note that this package, trelliscopejs is the successor of the [trelliscope] package which is available on CRAN and is part of the DeltaRho project. Eventually the trelliscopejs package will replace trelliscope and plug in to the DeltaRho ecosystem as well.

Install

devtools::install_github("hafen/trelliscopejs")

Demos

• Gapminder
• Gapminder with Plotly panels
• Monthly U.S. home prices by county
• Pokemon

Examples

The examples below are minimal. Please see the package vignettes for more.

ggplot

library(trelliscopejs)
library(ggplot2)
library(gapminder)

qplot(year, lifeExp, data = gapminder) +
  xlim(1948, 2011) + ylim(10, 95) + theme_bw() +
  facet_trelliscope(~ country + continent, nrow = 2, ncol = 7, width = 300)

tidyverse

library(trelliscopejs)
library(tidyverse)
library(rbokeh)
library(gapminder)

# nest gapminder data by country
by_country <- gapminder %>%
  group_by(country, continent) %>%
  nest()

# add in a plot column with map_plot
by_country <- by_country %>% mutate(
  panel = map_plot(data,
    ~ figure(xlim = c(1948, 2011), ylim = c(10, 95), width = 300, tools = NULL) %>%
        ly_points(year, lifeExp, data = .x, hover = .x)
  ))

# plot it
by_country %>%
  trelliscope("gapminder", nrow = 2, ncol = 7)