Plot3D Package and Example in R.-Data visualizat,on
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This document discusses the use of the plot3d package in R for 3D data visualization, including various functions like text3d, hist3d, and scatter3d. It provides examples using datasets such as 'usarrests', 'vadeaths', and 'iris' to demonstrate creating 3D plots, adding text labels, and visualizing relationships between multiple variables. The document includes code snippets to guide users on plotting techniques and data representation in a 3D space.
Plot3D Package and Example in R.-Data visualizat,on
- 1. Prepared by Volkan OBAN Plot3D package in R and examples,etc. Reference: http://www.sthda.com/english/wiki/impressive-package-for-3d-and-4d-graph-r- software-and-data-visualization text3D: plot 3-dimensionnal texts The function text3D() is used as follow: text3D(x, y, z, labels, ...) The USArrests data sets will be used in the example below: data(USArrests) with(USArrests, text3D(Murder, Assault, Rape, labels = rownames(USArrests), colvar = UrbanPop, col = gg.col(100), theta = 60, phi = 20, xlab = "Murder", ylab = "Assault", zlab = "Rape", main = "USA arrests", cex = 0.6, bty = "g", ticktype = "detailed", d = 2, clab = c("Urban","Pop"), adj = 0.5, font = 2))
- 3. # Plot texts with(USArrests, text3D(Murder, Assault, Rape, labels = rownames(USArrests), colvar = UrbanPop, col = gg.col(100), theta = 60, phi = 20, xlab = "Murder", ylab = "Assault", zlab = "Rape", main = "USA arrests", cex = 0.6, bty = "g", ticktype = "detailed", d = 2, clab = c("Urban","Pop"), adj = 0.5, font = 2)) # Add points with(USArrests, scatter3D(Murder, Assault, Rape - 1, colvar = UrbanPop, col = gg.col(100), type = "h", pch = ".", add = TRUE)) plotdev(xlim = c(0, 10), ylim = c(40, 150), zlim = c(7, 25))
- 4. Histogram3D data(VADeaths) # hist3D and ribbon3D with greyish background, rotated, rescaled,... hist3D(z = VADeaths, scale = FALSE, expand = 0.01, bty = "g", phi = 20, col = "#0072B2", border = "black", shade = 0.2, ltheta = 90, space = 0.3, ticktype = "detailed", d = 2)
- 5. hist3D (x = 1:5, y = 1:4, z = VADeaths, bty = "g", phi = 20, theta = -60, xlab = "", ylab = "", zlab = "", main = "VADeaths", col = "#0072B2", border = "black", shade = 0.8, ticktype = "detailed", space = 0.15, d = 2, cex.axis = 1e-9) # Use text3D to label x axis text3D(x = 1:5, y = rep(0.5, 5), z = rep(3, 5), labels = rownames(VADeaths), add = TRUE, adj = 0) # Use text3D to label yaxis text3D(x = rep(1, 4), y = 1:4, z = rep(0, 4), labels = colnames(VADeaths), add = TRUE, adj = 1)
- 9. Example: x0 <- c(0, 0, 0, 0) > y0 <- c(0, 0, 0, 0) > z0 <- c(0, 0, 0, 0) > x1 <- c(0.89, -0.46, 0.99, 0.96) > y1 <- c(0.36, 0.88, 0.02, 0.06) > z1 <- c(-0.28, 0.09, 0.05, 0.24) > cols <- c("#1B9E77", "#D95F02", "#7570B3", "#E7298A") > arrows3D(x0, y0, z0, x1, y1, z1, colvar = x1^2, col = cols, + lwd = 2, d = 3, clab = c("Quality", "score"), + main = "Arrows 3D", bty ="g", ticktype = "detailed") > # Add starting point of arrow > points3D(x0, y0, z0, add = TRUE, col="darkred", + colkey = FALSE, pch = 19, cex = 1) > # Add labels to the arrows > text3D(x1, y1, z1, c("Sepal.L", "Sepal.W", "Petal.L", "Petal.W"), + colvar = x1^2, col = cols, add=TRUE, colkey = FALSE)
- 10. EXAMPLE: data(iris) x <- iris$Sepal.Length y <- iris$Petal.Length z <- iris$Sepal.Width scatter3D(x, y, z, pch = 18, bty = "u", colkey = FALSE, + main ="bty= 'u'", col.panel ="steelblue", expand =0.4, + col.grid = "darkblue")
- 12. > scatter3D(x, y, z, bty = "g", pch = 18, col = gg.col(100)) > # ramp.col: custom palettes > scatter3D(x, y, z, bty = "g", pch = 18, + col = ramp.col(c("blue", "yellow", "red")) )
- 13. > scatter3D(x, y, z, phi = 0, bty = "g", + pch = 20, cex = 2, ticktype = "detailed")
- 14. scatter3D(x, y, z, phi = 0, bty = "g", type = "l", ticktype = "detailed", lwd = 4)
- 15. scatter3D(x, y, z, phi = 0, bty = "g", type = "h", + ticktype = "detailed", pch = 19, cex = 0.5)
- 16. > x <- mtcars$wt > y <- mtcars$disp > z <- mtcars$mpg > # Compute the linear regression (z = ax + by + d) > fit <- lm(z ~ x + y) > # predict values on regular xy grid > grid.lines = 26 > x.pred <- seq(min(x), max(x), length.out = grid.lines) > y.pred <- seq(min(y), max(y), length.out = grid.lines) > xy <- expand.grid( x = x.pred, y = y.pred) > z.pred <- matrix(predict(fit, newdata = xy), + nrow = grid.lines, ncol = grid.lines) > # fitted points for droplines to surface > fitpoints <- predict(fit) > # scatter plot with regression plane > scatter3D(x, y, z, pch = 18, cex = 2, + theta = 20, phi = 20, ticktype = "detailed", + xlab = "wt", ylab = "disp", zlab = "mpg", + surf = list(x = x.pred, y = y.pred, z = z.pred, + facets = NA, fit = fitpoints), main = "mtcars")