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--- r:graphics [2016/12/02 09:18] – [Plotting Multiple Datasets] hkimscil
+++ r:graphics [2017/11/27 09:57] (current) – [Adding Confidence Intervals to a Bar Chart] hkimscil
@@ Line 193: / Line 193: @@
 </code>
+===== e.g. 1 =====
+<code># Creating a Graph
+attach(mtcars)
+plot(wt, mpg)
+abline(lm(mpg~wt))
+title("Regression of MPG on Weight")</code>
+{{:R:regression_line.png}}
+===== e.g. 2 =====
+<code>?LifeCycleSavings
+lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
+> summary(lm.SR)
+Call:
+lm(formula = sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
+Residuals:
+    Min      1Q  Median      3Q     Max
+-8.2422 -2.6857 -0.2488  2.4280  9.7509
+Coefficients:
+              Estimate Std. Error t value Pr(>|t|)
+(Intercept) 28.5660865  7.3545161   3.884 0.000334 ***
+pop15       -0.4611931  0.1446422  -3.189 0.002603 **
+pop75       -1.6914977  1.0835989  -1.561 0.125530
+dpi         -0.0003369  0.0009311  -0.362 0.719173
+ddpi         0.4096949  0.1961971   2.088 0.042471 *
+---
+Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+Residual standard error: 3.803 on 45 degrees of freedom
+Multiple R-squared:  0.3385,	Adjusted R-squared:  0.2797
+F-statistic: 5.756 on 4 and 45 DF,  p-value: 0.0007904
+> plot(LifeCycleSavings)
+> plot(lm.SR)
+</code>
+{{:r:LifeCycleSavings.jpeg}}
+{{:R:regression_model.png}}
 ====== Plotting All Variables Against All Other Variables ======
@@ Line 378: / Line 421: @@
 +         names.arg=c("May", "Jun", "Jul", "Aug", "Sep"),
 +         ylab="Temp (deg. F)")</code>
-{{:R:barplot_heights.png}}
+{{:R:barplot_heights.2.png}}
 ====== Adding Confidence Intervals to a Bar Chart ======
@@ Line 389: / Line 432: @@
 </code>
-<code>tmean <- tapply(Temp, list(as.factor(Month)), mean)  # mean for each month
+<code>tmean <- tapply(Temp, list(as.factor(Month)), mean)
-tsd <- tapply(Temp, list(as.factor(Month)),sd)  # sd for each month
+# mean for each month
-tse <- tsd/sqrt(length(Temp))  # se for each month
+tsd <- tapply(Temp, list(as.factor(Month)),sd)
+# sd for each month
+tse <- tsd/sqrt(length(Temp))
+# se for each month
 lower <- tmean - 1.96*tse
@@ Line 426: / Line 472: @@
 plot(pressure, type="l")</code>
 {{:R:barplot_points_line.png}}
+<code>> par(mfrow=c(2, 2), cex=0.6, mar=c(4, 4, 1, 1))
+> y <- rnorm(20)
+> plot(y, type="p")
+> plot(y, type="l")
+> plot(y, type="b")
+> plot(y, type="h")
+></code>
+{{:r:plot_types.png}}
 ====== Plotting Multiple Datasets ======
-<code>> x <- rnorm(10,sd=5,mean=20)
+<code>x <- rnorm(10,sd=5,mean=20)
-> y <- 2.5*x - 1.0 + rnorm(10,sd=9,mean=0)
+y <- 2.5*x - 1.0 + rnorm(10,sd=9,mean=0)
-> cor(x,y)
+cor(x,y)
 [1] 0.7400576
-> plot(x,y,xlab="Independent",ylab="Dependent",main="Random Stuff")
+plot(x,y,xlab="Independent",ylab="Dependent",main="Random Stuff")
-> x1 <- runif(8,15,25)
+x1 <- runif(8,15,25)
-> y1 <- 2.5*x1 - 1.0 + runif(8,-6,6)
+y1 <- 2.5*x1 - 1.0 + runif(8,-6,6)
-> points(x1,y1,col=2)</code>
+points(x1,y1,col=2)
+</code>
+{{:R:plotting_multiple_datasets.png}}
@@ Line 449: / Line 507: @@
 ====== Creating One Box Plot for Each Factor Level ======
 <code>boxplot(Cars93$MPG.city~Cars93$Origin)</code>
+{{:R:boxplot.png}}
 <code>> library(MASS)
 > UScereal
@@ Line 724: / Line 782: @@
         xlab="Shelf", ylab="Sugar (grams per portion)")
 </code>
+{{:R:boxplot2.png}}
 ====== Creating a Histogram ======
@@ Line 734: / Line 793: @@
 </code>
+{{:r:hist_Cars93.png}}
 ====== Creating a Normal Quantile-Quantile (Q-Q) Plot ======
@@ Line 745: / Line 805: @@
 qqline(log(Cars93$Price))</code>
+{{:R:qqplot.png}}
+====== E.G. ======
+<code>
+#
+#  Comment:
+#
+#  Examples of the use of standard high-level plotting functions.
+#
+#  In each case, extra output is also added using low-level
+#  plotting functions.
+#
+par(mfrow=c(3, 2))
+# Scatterplot
+x <- c(0.5, 2, 4, 8, 12, 16)
+y1 <- c(1, 1.3, 1.9, 3.4, 3.9, 4.8)
+y2 <- c(4, .8, .5, .45, .4, .3)
+par(las=1, mar=c(4, 4, 2, 4))
+plot.new()
+plot.window(range(x), c(0, 6))
+lines(x, y1)
+lines(x, y2)
+points(x, y1, pch=16, cex=2)
+points(x, y2, pch=21, bg="white", cex=2)
+par(col="grey50", fg="grey50", col.axis="grey50")
+axis(1, at=seq(0, 16, 4))
+axis(2, at=seq(0, 6, 2))
+axis(4, at=seq(0, 6, 2))
+box(bty="u")
+mtext("Travel Time (s)", side=1, line=2, cex=0.8)
+mtext("Responses per Travel", side=2, line=2, las=0, cex=0.8)
+mtext("Responses per Second", side=4, line=2, las=0, cex=0.8)
+text(4, 5, "Bird 131")
+par(mar=c(5.1, 4.1, 4.1, 2.1), col="black", fg="black", col.axis="black")
+# Histogram
+# Random data
+Y <- rnorm(50)
+# Make sure no Y exceed [-3.5, 3.5]
+Y[Y < -3.5 | Y > 3.5] <- NA
+x <- seq(-3.5, 3.5, .1)
+dn <- dnorm(x)
+par(mar=c(4.5, 4.1, 3.1, 0))
+hist(Y, breaks=seq(-3.5, 3.5), ylim=c(0, 0.5),
+     col="grey80", freq=FALSE)
+lines(x, dnorm(x), lwd=2)
+par(mar=c(5.1, 4.1, 4.1, 2.1))
+# Barplot
+# Modified from example(barplot)
+par(mar=c(2, 3.1, 2, 2.1))
+midpts <- barplot(VADeaths, col=grey(0.5 + 1:5/12),
+                  names=rep("", 4))
+mtext(sub(" ", "\n", colnames(VADeaths)),
+      at=midpts, side=1, line=0.5, cex=0.5)
+text(rep(midpts, each=5), apply(VADeaths, 2, cumsum) - VADeaths/2,
+     VADeaths, col=rep(c("white", "black"), times=2:3, cex=0.8))
+par(mar=c(5.1, 4.1, 4.1, 2.1))
+# Boxplot
+# Modified example(boxplot) - itself from suggestion by Roger Bivand
+par(mar=c(3, 4.1, 2, 0))
+     boxplot(len ~ dose, data = ToothGrowth,
+             boxwex = 0.25, at = 1:3 - 0.2,
+             subset= supp == "VC", col="grey90",
+             xlab="",
+             ylab="tooth length", ylim=c(0,35))
+     mtext("Vitamin C dose (mg)", side=1, line=2.5, cex=0.8)
+     boxplot(len ~ dose, data = ToothGrowth, add = TRUE,
+             boxwex = 0.25, at = 1:3 + 0.2,
+             subset= supp == "OJ", col="grey70")
+     legend(1.5, 9, c("Ascorbic acid", "Orange juice"), bty="n",
+            fill = c("grey90", "grey70"))
+par(mar=c(5.1, 4.1, 4.1, 2.1))
+# Persp
+# Almost exactly example(persp)
+    x <- seq(-10, 10, length= 30)
+     y <- x
+     f <- function(x,y) { r <- sqrt(x^2+y^2); 10 * sin(r)/r }
+     z <- outer(x, y, f)
+     z[is.na(z)] <- 1
+# 0.5 to include z axis label
+par(mar=c(0, 0.5, 0, 0), lwd=0.1)
+     persp(x, y, z, theta = 30, phi = 30, expand = 0.5, col = "grey80")
+par(mar=c(5.1, 4.1, 4.1, 2.1), lwd=1)
+# Piechart
+# Example 4 from help(pie)
+par(mar=c(0, 2, 1, 2), xpd=FALSE, cex=0.5)
+     pie.sales <- c(0.12, 0.3, 0.26, 0.16, 0.04, 0.12)
+     names(pie.sales) <- c("Blueberry", "Cherry",
+         "Apple", "Boston Cream", "Other", "Vanilla")
+     pie(pie.sales, col = gray(seq(0.4,1.0,length=6)))
+</code>
+{{:R:various_graphs.png}}
+<code>#
+# Comment:
+#
+# A bit of mucking around is required to get the second (whole-world)
+# map positioned correctly;  this provides an example of calling a
+# plotting function to perform calculations but do no drawing (see the
+# second call to the map() function).
+#
+# Makes use of the "maps" and "mapproj" packages to draw the maps.
+#
+library(maps)
+par(mar=rep(0, 4))
+map("nz", fill=TRUE, col="grey80")
+points(174.75, -36.87, pch=16, cex=2)
+arrows(172, -36.87, 174, -36.87, lwd=3)
+text(172, -36.87, "Auckland  ", adj=1, cex=2)
+# mini world map as guide
+maplocs <- map(projection="sp_mercator", wrap=TRUE, lwd=0.1,
+               col="grey", ylim=c(-60, 75),
+               interior=FALSE, orientation=c(90, 180, 0), add=TRUE,
+               plot=FALSE)
+xrange <- range(maplocs$x, na.rm=TRUE)
+yrange <- range(maplocs$y, na.rm=TRUE)
+aspect <- abs(diff(yrange))/abs(diff(xrange))
+# customised to 6.5 by 4.5 figure size
+par(fig=c(0.99 - 0.5, 0.99, 0.01, 0.01 + 0.5*aspect*4.5/6.5),
+    mar=rep(0, 4), new=TRUE)
+plot.new()
+plot.window(xlim=xrange,
+            ylim=yrange)
+map(projection="sp_mercator", wrap=TRUE, lwd=0.1, ylim=c(-60, 75),
+    interior=FALSE, orientation=c(90, 180, 0), add=TRUE)
+symbols(-.13, -0.8, circles=1, inches=0.1, add=TRUE)</code>
+{{:R:using_maps_R.png}}
+<code>par(mfrow=c(2, 2))
+z <- 2 * volcano        # Exaggerate the relief
+x <- 10 * (1:nrow(z))   # 10 meter spacing (S to N)
+y <- 10 * (1:ncol(z))   # 10 meter spacing (E to W)
+# Don't draw the grid lines :  border = NA
+par(mar=rep(0, 4))
+persp(x, y, z, theta = 135, phi = 30, col = "light grey", scale = FALSE,
+      ltheta = -120, shade = 0.75, border = NA, box = FALSE)
+mtext("persp()", side=3, line=-2)
+par(mar=c(3, 3, 2, 0.5))
+# Note that  example(trees)  shows more sensible plots!
+N <- nrow(trees)
+attach(trees)
+# Girth is diameter in inches
+symbols(Height, Volume, circles=Girth/24, inches=FALSE,
+        main="", xlab="", ylab="", bg=grey(Girth/max(Girth)))
+mtext("symbols()", side=3, line=0.5)
+par(mar=rep(0.5, 4))
+contour(x, y, z, asp=1, labcex=0.35, axes=FALSE)
+rect(0, 0, 870, 620)
+mtext("contour()", side=3, line=-1.5)
+image(x, y, z, asp=1, col=grey(0.5 + 1:12/24), xlab="", ylab="", axes=FALSE)
+rect(min(x)-5, min(y)-5, max(x)+5, max(y)+5)
+mtext("image()", side=3, line=-1.5)
+</code>
+{{:R:poly_graph.png}}