Sistemas de graficación

• Visualización estática:
  • graphics
  • lattice
  • ggplot2
  • ggvis
• Visualización interactiva:
  • plotly
  • dygraphs
  • taucharts
  • metricsgraphics
  • highcharter
  • echarts4r

graphics

with(cars, scatter.smooth(speed, dist, pch = 18, col = "dodgerblue4",
               lpars = list(col = "red3", lwd = 2)))
grid(col = "gray80")

lattice

library(lattice)
xyplot(dist ~ speed, data = cars, type = c("p", "smooth"), pch = 18,
       grid = TRUE, col = "dodgerblue4", col.line = "red3", lwd = 2)

ggplot2

library(ggplot2)
library(dplyr)
cars %>% 
  ggplot(data = ., aes(x = speed, y = dist)) +
  geom_point(pch = 18, size = 2, color = "dodgerblue4") +
  geom_smooth(se = FALSE, color = "red3", method = "loess", span = 2/3) +
  theme_light()

ggvis

library(ggvis)
cars %>% 
  ggvis(x = ~speed, y = ~dist) %>%  
  layer_points(shape := "diamond", fill = "dodgerblue4", stroke := "black") %>% 
  layer_smooths(stroke := "firebrick", span = 2/3) %>% 
  hide_legend("fill")

plotly

library(plotly)
cars %>% 
  plot_ly(x = ~speed, y = ~dist, color = I("dodgerblue4"), stroke = I("black"),
          symbol = I("diamond"), type = "scatter") %>% 
  add_lines(y = ~fitted(loess(dist ~ speed, span = 2/3)), color = I("red3")) %>% 
  layout(showlegend = FALSE)

dygraphs

library(dygraphs)
lungDeaths <- cbind(mdeaths, fdeaths)
dygraph(lungDeaths)

taucharts

#devtools::install_github("hrbrmstr/taucharts")
library(taucharts)
CO2 %>%
  tauchart( ) %>%
  tau_point( "conc", c("Treatment","uptake"), "Plant" ) %>%
  tau_tooltip( ) %>%
  tau_trendline( )

metricsgraphics

library(metricsgraphics)
mtcars %>%
  mjs_plot(x=wt, y=mpg, width=600, height=500) %>%
  mjs_point(least_squares=TRUE) %>%
  mjs_labs(x="Weight of Car", y="Miles per Gallon")

highcharter

library("highcharter")
data(diamonds, mpg, package = "ggplot2")

hchart(mpg, "scatter", hcaes(x = displ, y = hwy, group = class))

echarts4r

library(echarts4r)
e1 <- iris %>% 
  group_by(Species) %>% 
  e_charts(
    Sepal.Length,
    elementId = "chart"
  ) %>% 
  e_scatter(Petal.Length, Sepal.Width) %>% 
  e_datazoom(show = FALSE, y_index = 0) %>% 
  e_x_axis(min = 4)
e1