data-viz-compare.md

title	subtitle	layout	output
Data Viz Comparison	base vs ggplot2 vs ggvis vs googleVis vs rCharts vs plotly vs ggplotly	page	html_document self_contained

base

http://www.statmethods.net/graphs/

plot(iris$Sepal.Length, iris$Petal.Length,        # x variable, y variable
     col = iris$Species,                          # colour by species
     pch = 16,                                    # type of point to use
     cex = 1,                                     # size of point to use
     xlab = "Sepal Length",                       # x axis label
     ylab = "Petal Length",                       # y axis label
     main = "Flower Characteristics in Iris")     # plot title

legend (x = 4.5, y = 7, legend = levels(iris$Species), col = c(1:3), pch = 16)


ggplot2

http://ggplot2.org/

library(ggplot2)
gg <- ggplot(iris) +
      geom_point(aes(x=Sepal.Length, y=Petal.Length, color = Species)) +
      labs(title = "Flower Characteristics in Iris", x = "Sepal Length", y = "Petal Length")
gg


ggvis

http://ggvis.rstudio.com/

library(ggvis)
data(iris)

# hack for title from: http://stackoverflow.com/questions/25018598/add-a-plot-title-to-ggvis
add_title <- function(vis, ..., x_lab = "X units", title = "Plot Title") {
  add_axis(vis, "x", title = x_lab) %>% 
    add_axis("x", orient = "top", ticks = 0, title = title,
             properties = axis_props(
               axis = list(stroke = "white"),
               labels = list(fontSize = 0)
             ), ...)
}

p <- ggvis(iris, x = ~Sepal.Length, y = ~Petal.Length, fill = ~Species) %>% add_title(title = "Flower Characteristics in Iris", 
                                                                                      x_lab = "Sepal.Length")
layer_points(p)

• Renderer: SVG | Canvas
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"data.Petal\\.Length" }, "fill": { "scale": "fill", "field": "data.Species" } }, "ggvis": { "data": { "value": "iris0" } } }, "from": { "data": "iris0" } } ], "legends": [ { "orient": "right", "fill": "fill", "title": "Species" } ], "axes": [ { "type": "x", "scale": "x", "orient": "bottom", "title": "Sepal.Length", "layer": "back", "grid": true }, { "type": "x", "scale": "x", "orient": "top", "title": "Flower Characteristics in Iris", "ticks": 0, "layer": "back", "grid": true, "properties": { "labels": { "fontSize": { "value": 0 } }, "axis": { "stroke": { "value": "white" } } } }, { "type": "y", "scale": "y", "orient": "left", "layer": "back", "grid": true, "title": "Petal.Length" } ], "padding": null, "ggvis_opts": { "keep_aspect": false, "resizable": true, "padding": {}, "duration": 250, "renderer": "svg", "hover_duration": 0, "width": 504, "height": 504 }, "handlers": null }; ggvis.getPlot("plot_id731364669").parseSpec(plot_id731364669_spec); </script>

googleVis

https://github.com/mages/googleVis#googlevis

suppressPackageStartupMessages(library(googleVis))
op <- options(gvis.plot.tag = "chart")
options(op)

iris2 = iris[, c("Sepal.Length", "Petal.Length")]
i <- sapply(iris2, is.factor)
iris2[i] <- lapply(iris2[i], as.character)
flower <- gvisScatterChart(iris2, options = list(title = "Flower Characteristics in Iris"))
# plot(flower)
print(flower, "chart")

<script type="text/javascript"> // jsData function gvisDataScatterChartID116e13813ab4 () { var data = new google.visualization.DataTable(); var datajson = [ [ 5.1, 1.4 ], [ 4.9, 1.4 ], [ 4.7, 1.3 ], [ 4.6, 1.5 ], [ 5, 1.4 ], [ 5.4, 1.7 ], [ 4.6, 1.4 ], [ 5, 1.5 ], [ 4.4, 1.4 ], [ 4.9, 1.5 ], [ 5.4, 1.5 ], [ 4.8, 1.6 ], [ 4.8, 1.4 ], [ 4.3, 1.1 ], [ 5.8, 1.2 ], [ 5.7, 1.5 ], [ 5.4, 1.3 ], [ 5.1, 1.4 ], [ 5.7, 1.7 ], [ 5.1, 1.5 ], [ 5.4, 1.7 ], [ 5.1, 1.5 ], [ 4.6, 1 ], [ 5.1, 1.7 ], [ 4.8, 1.9 ], [ 5, 1.6 ], [ 5, 1.6 ], [ 5.2, 1.5 ], [ 5.2, 1.4 ], [ 4.7, 1.6 ], [ 4.8, 1.6 ], [ 5.4, 1.5 ], [ 5.2, 1.5 ], [ 5.5, 1.4 ], [ 4.9, 1.5 ], [ 5, 1.2 ], [ 5.5, 1.3 ], [ 4.9, 1.4 ], [ 4.4, 1.3 ], [ 5.1, 1.5 ], [ 5, 1.3 ], [ 4.5, 1.3 ], [ 4.4, 1.3 ], [ 5, 1.6 ], [ 5.1, 1.9 ], [ 4.8, 1.4 ], [ 5.1, 1.6 ], [ 4.6, 1.4 ], [ 5.3, 1.5 ], [ 5, 1.4 ], [ 7, 4.7 ], [ 6.4, 4.5 ], [ 6.9, 4.9 ], [ 5.5, 4 ], [ 6.5, 4.6 ], [ 5.7, 4.5 ], [ 6.3, 4.7 ], [ 4.9, 3.3 ], [ 6.6, 4.6 ], [ 5.2, 3.9 ], [ 5, 3.5 ], [ 5.9, 4.2 ], [ 6, 4 ], [ 6.1, 4.7 ], [ 5.6, 3.6 ], [ 6.7, 4.4 ], [ 5.6, 4.5 ], [ 5.8, 4.1 ], [ 6.2, 4.5 ], [ 5.6, 3.9 ], [ 5.9, 4.8 ], [ 6.1, 4 ], [ 6.3, 4.9 ], [ 6.1, 4.7 ], [ 6.4, 4.3 ], [ 6.6, 4.4 ], [ 6.8, 4.8 ], [ 6.7, 5 ], [ 6, 4.5 ], [ 5.7, 3.5 ], [ 5.5, 3.8 ], [ 5.5, 3.7 ], [ 5.8, 3.9 ], [ 6, 5.1 ], [ 5.4, 4.5 ], [ 6, 4.5 ], [ 6.7, 4.7 ], [ 6.3, 4.4 ], [ 5.6, 4.1 ], [ 5.5, 4 ], [ 5.5, 4.4 ], [ 6.1, 4.6 ], [ 5.8, 4 ], [ 5, 3.3 ], [ 5.6, 4.2 ], [ 5.7, 4.2 ], [ 5.7, 4.2 ], [ 6.2, 4.3 ], [ 5.1, 3 ], [ 5.7, 4.1 ], [ 6.3, 6 ], [ 5.8, 5.1 ], [ 7.1, 5.9 ], [ 6.3, 5.6 ], [ 6.5, 5.8 ], [ 7.6, 6.6 ], [ 4.9, 4.5 ], [ 7.3, 6.3 ], [ 6.7, 5.8 ], [ 7.2, 6.1 ], [ 6.5, 5.1 ], [ 6.4, 5.3 ], [ 6.8, 5.5 ], [ 5.7, 5 ], [ 5.8, 5.1 ], [ 6.4, 5.3 ], [ 6.5, 5.5 ], [ 7.7, 6.7 ], [ 7.7, 6.9 ], [ 6, 5 ], [ 6.9, 5.7 ], [ 5.6, 4.9 ], [ 7.7, 6.7 ], [ 6.3, 4.9 ], [ 6.7, 5.7 ], [ 7.2, 6 ], [ 6.2, 4.8 ], [ 6.1, 4.9 ], [ 6.4, 5.6 ], [ 7.2, 5.8 ], [ 7.4, 6.1 ], [ 7.9, 6.4 ], [ 6.4, 5.6 ], [ 6.3, 5.1 ], [ 6.1, 5.6 ], [ 7.7, 6.1 ], [ 6.3, 5.6 ], [ 6.4, 5.5 ], [ 6, 4.8 ], [ 6.9, 5.4 ], [ 6.7, 5.6 ], [ 6.9, 5.1 ], [ 5.8, 5.1 ], [ 6.8, 5.9 ], [ 6.7, 5.7 ], [ 6.7, 5.2 ], [ 6.3, 5 ], [ 6.5, 5.2 ], [ 6.2, 5.4 ], [ 5.9, 5.1 ] ]; data.addColumn('number','Sepal.Length'); data.addColumn('number','Petal.Length'); data.addRows(datajson); return(data); } // jsDrawChart function drawChartScatterChartID116e13813ab4() { var data = gvisDataScatterChartID116e13813ab4(); var options = {}; options["allowHtml"] = [true]; options["title"] = ["Flower Characteristics in Iris"]; var chart = new google.visualization.ScatterChart( document.getElementById('ScatterChartID116e13813ab4') ); chart.draw(data,options); } // jsDisplayChart (function() { var pkgs = window.__gvisPackages = window.__gvisPackages || []; var callbacks = window.__gvisCallbacks = window.__gvisCallbacks || []; var chartid = "corechart"; // Manually see if chartid is in pkgs (not all browsers support Array.indexOf) var i, newPackage = true; for (i = 0; newPackage && i < pkgs.length; i++) { if (pkgs[i] === chartid) newPackage = false; } if (newPackage) pkgs.push(chartid); // Add the drawChart function to the global list of callbacks callbacks.push(drawChartScatterChartID116e13813ab4); })(); function displayChartScatterChartID116e13813ab4() { var pkgs = window.__gvisPackages = window.__gvisPackages || []; var callbacks = window.__gvisCallbacks = window.__gvisCallbacks || []; window.clearTimeout(window.__gvisLoad); // The timeout is set to 100 because otherwise the container div we are // targeting might not be part of the document yet window.__gvisLoad = setTimeout(function() { var pkgCount = pkgs.length; google.load("visualization", "1", { packages:pkgs, callback: function() { if (pkgCount != pkgs.length) { // Race condition where another setTimeout call snuck in after us; if // that call added a package, we must not shift its callback return; } while (callbacks.length > 0) callbacks.shift()(); } }); }, 100); } // jsFooter </script> <script type="text/javascript" src="https://www.google.com/jsapi?callback=displayChartScatterChartID116e13813ab4"></script>

rCharts

http://rcharts.io/

library(rCharts)
names(iris) = gsub("\\.", "", names(iris))
rPlot(PetalLength ~ SepalLength , data = iris, color = 'Species', type = 'point')

## Error in myChart$copy(): could not find function "new"

plotly

https://plot.ly/r/

library(plotly)
data(iris)
plot_ly(iris, x = Sepal.Length, y = Petal.Length, color = Species, mode = "markers") %>% 
  layout(title = "Flower Characteristics in Iris")

## Error in file(con, "rb"): cannot open the connection

ggplotly

https://plot.ly/ggplot2/

p <- ggplot(iris) +
      geom_point(aes(x=Sepal.Length, y=Petal.Length, color = Species)) +
      labs(title = "Flower Characteristics in Iris")

ggplotly(p)

## Error in file(con, "rb"): cannot open the connection