Parallel Coordinates Plot in R
How to create parallel coordinates plots in R with Plotly.
New to Plotly?
Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
Adding Dimensions
library(plotly)
fig <- plot_ly(type = 'parcoords', line = list(color = 'blue'),
dimensions = list(
list(range = c(1,5),
constraintrange = c(1,2),
label = 'A', values = c(1,4)),
list(range = c(1,5),
tickvals = c(1.5,3,4.5),
label = 'B', values = c(3,1.5)),
list(range = c(1,5),
tickvals = c(1,2,4,5),
label = 'C', values = c(2,4),
ticktext = c('text 1', 'text 2', 'text 3', 'text 4')),
list(range = c(1,5),
label = 'D', values = c(4,2))
)
)
fig
Basic Parallel Cordinates Plot
library(plotly)
df <- read.csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/iris.csv")
fig <- df %>% plot_ly(type = 'parcoords',
line = list(color = ~species_id,
colorscale = list(c(0,'red'),c(0.5,'green'),c(1,'blue'))),
dimensions = list(
list(range = c(2,4.5),
label = 'Sepal Width', values = ~sepal_width),
list(range = c(4,8),
constraintrange = c(5,6),
label = 'Sepal Length', values = ~sepal_length),
list(range = c(0,2.5),
label = 'Petal Width', values = ~petal_width),
list(range = c(1,7),
label = 'Petal Length', values = ~petal_length)
)
)
fig
Advanced Parallel Coordinates Plot
library(plotly)
df <- read.csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/parcoords_data.csv")
fig <- df %>%
plot_ly(width = 1000, height = 600)
fig <- fig %>% add_trace(type = 'parcoords',
line = list(color = ~colorVal,
colorscale = 'Jet',
showscale = TRUE,
reversescale = TRUE,
cmin = -4000,
cmax = -100),
dimensions = list(
list(range = c(~min(blockHeight),~max(blockHeight)),
constraintrange = c(100000,150000),
label = 'Block Height', values = ~blockHeight),
list(range = c(~min(blockWidth),~max(blockWidth)),
label = 'Block Width', values = ~blockWidth),
list(tickvals = c(0,0.5,1,2,3),
ticktext = c('A','AB','B','Y','Z'),
label = 'Cyclinder Material', values = ~cycMaterial),
list(range = c(-1,4),
tickvals = c(0,1,2,3),
label = 'Block Material', values = ~blockMaterial),
list(range = c(~min(totalWeight),~max(totalWeight)),
visible = TRUE,
label = 'Total Weight', values = ~totalWeight),
list(range = c(~min(assemblyPW),~max(assemblyPW)),
label = 'Assembly Penalty Weight', values = ~assemblyPW),
list(range = c(~min(HstW),~max(HstW)),
label = 'Height st Width', values = ~HstW),
list(range = c(~min(minHW),~max(minHW)),
label = 'Min Height Width', values = ~minHW),
list(range = c(~min(minWD),~max(minWD)),
label = 'Min Width Diameter', values = ~minWD),
list(range = c(~min(rfBlock),~max(rfBlock)),
label = 'RF Block', values = ~rfBlock)
)
)
fig
Reference
See https://plotly.com/r/reference/#parcoords for more information and options!
What About Dash?
Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash for R at https://dashr.plot.ly/installation.
Everywhere in this page that you see fig
, you can display the same figure in a Dash for R application by passing it to the figure
argument of the Graph
component from the built-in dashCoreComponents
package like this:
library(plotly)
fig <- plot_ly()
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... )
library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)
app <- Dash$new()
app$layout(
htmlDiv(
list(
dccGraph(figure=fig)
)
)
)
app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)