first

Author: chriddyp

README.md

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+ggplot2 example code from the *Cookbook for R* with Plotly figure conversions

axes.R

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+library(plotly)
+set_credentials_file("ggplot2-cookbook", "gzcn4660jr")
+py <- plotly();
+
+library(ggplot2)
+
+bp <- ggplot(PlantGrowth, aes(x=group, y=weight)) + geom_boxplot()
+bp
+
+bp + coord_flip()
+
+# Manually set the order of a discrete-valued axis
+bp + scale_x_discrete(limits=c("trt1","trt2","ctrl"))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/discrete valued axes'))
+
+# Reverse the order of a discrete-valued axis
+# Get the levels of the factor
+flevels <- levels(PlantGrowth$group)
+# "ctrl" "trt1" "trt2"
+# Reverse the order
+flevels <- rev(flevels)
+# "trt2" "trt1" "ctrl"
+bp + scale_x_discrete(limits=flevels)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/reversed ordered axes - 1'))
+
+# Or it can be done in one line:
+bp + scale_x_discrete(limits = rev(levels(PlantGrowth$group)) )
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/reversed ordered axes - 2'))
+
+bp + scale_x_discrete(breaks=c("ctrl", "trt1", "trt2"), labels=c("Control", "Treat 1", "Treat 2"))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/setting tick mark labels'))
+
+# Hide x tick marks, labels, and grid lines
+bp + scale_x_discrete(breaks=NULL)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden tick marks, labels, gridline'))
+
+# Hide all tick marks and labels (on X axis), but keep the gridlines
+bp + theme(axis.ticks = element_blank(), axis.text.x = element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden tick marks and labels'))
+
+# Set the range of a continuous-valued axis
+# These are equivalent
+bp + ylim(0,8)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/set range of continuous-valued axis - 1'))
+bp + scale_y_continuous(limits=c(0,8))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/set range of continuous-valued axis - 2'))
+
+# These two do the same thing; all data points outside the graphing range are dropped,
+# resulting in a misleading box plot
+bp + ylim(5, 7.5)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/misleading range'))
+bp + scale_y_continuous(limits=c(5, 7.5))
+
+# Using coord_cartesian "zooms" into the area
+bp + coord_cartesian(ylim=c(5, 7.5))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/coord_cartesian'))
+
+# Specify tick marks directly
+bp + coord_cartesian(ylim=c(5, 7.5)) +
+    scale_y_continuous(breaks=seq(0, 10, 0.25))  # Ticks from 0-10, every .25
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/specify tick marks directly'))
+
+# Reverse order of a continuous-valued axis
+bp + scale_y_reverse()
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/reverse y scale'))
+
+# Setting the tick marks on an axis
+# This will show tick marks on every 0.25 from 1 to 10
+# The scale will show only the ones that are within range (3.50-6.25 in this case)
+bp + scale_y_continuous(breaks=seq(1,10,1/4))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/manual tick marks'))
+
+# The breaks can be spaced unevenly
+bp + scale_y_continuous(breaks=c(4, 4.25, 4.5, 5, 6,8))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/uneven tick marks'))
+
+# Suppress ticks and gridlines
+bp + scale_y_continuous(breaks=NULL)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/suppress y ticks, labels, and gridlines'))
+
+# Hide tick marks and labels (on Y axis), but keep the gridlines
+bp + theme(axis.ticks = element_blank(), axis.text.y = element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/suppress y ticks and labels'))
+
+# Create some noisy exponentially-distributed data
+set.seed(201)
+n <- 100
+dat <- data.frame(xval = (1:n+rnorm(n,sd=5))/20, yval = 2*2^((1:n+rnorm(n,sd=5))/20))
+
+# A scatterplot with regular (linear) axis scaling
+sp <- ggplot(dat, aes(xval, yval)) + geom_point()
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/linear axes'))
+sp
+
+# log2 scaling of the y axis (with visually-equal spacing)
+library(scales)     # Need the scales package
+sp + scale_y_continuous(trans=log2_trans())
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/ln y axes with visual-equal spacing'))
+
+# log2 coordinate transformation (with visually-diminishing spacing)
+sp + coord_trans(y="log2")
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/ln y axes with visually diminishing spacing'))
+
+sp + scale_y_continuous(trans = log2_trans(),
+                        breaks = trans_breaks("log2", function(x) 2^x),
+                        labels = trans_format("log2", math_format(2^.x)))
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/ln y axes with exponent tick marks'))
+
+set.seed(205)
+n <- 100
+dat10 <- data.frame(xval = (1:n+rnorm(n,sd=5))/20, yval = 10*10^((1:n+rnorm(n,sd=5))/20))
+
+sp10 <- ggplot(dat10, aes(xval, yval)) + geom_point()
+
+# log10
+sp10 + scale_y_log10()
+py$ggplotly(sp10, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/log_10 y axes'))
+
+# log10 with exponents on tick labels
+sp10 + scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x),
+                     labels = trans_format("log10", math_format(10^.x)))
+py$ggplotly(sp10, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/log_10 y axes with exponent tick marks'))
+
+# Data where x ranges from 0-10, y ranges from 0-30
+set.seed(202)
+dat <- data.frame(xval = runif(40,0,10), yval = runif(40,0,30))
+sp <- ggplot(dat, aes(xval, yval)) + geom_point()
+
+# Force equal scaling
+sp + coord_fixed()
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/forced equal spacing'))
+
+# Equal scaling, with each 1 on the x axis the same length as y on x axis
+sp + coord_fixed(ratio=1/3)
+py$ggplotly(sp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/forced equal scaling'))
+
+bp + theme(axis.title.x = element_blank()) +   # Remove x-axis label
+     ylab("Weight (Kg)")                    # Set y-axis label
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/axes labels'))
+
+# Also possible to set the axis label with the scale
+# Note that vertical space is still reserved for x's label
+bp + scale_x_discrete(name="") +
+     scale_y_continuous(name="Weight (Kg)")
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/axes labels set with scale'))
+
+# Change font options:
+# X-axis label: bold, red, and 20 points
+# X-axis tick marks: rotate 90 degrees CCW, move to the left a bit (using vjust,
+#   since the labels are rotated), and 16 points
+bp + theme(axis.title.x = element_text(face="bold", colour="#990000", size=20),
+           axis.text.x  = element_text(angle=90, vjust=0.5, size=16))
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/axes labels with formatting'))
+
+# Label formatters
+library(scales)   # Need the scales package
+bp + scale_y_continuous(labels=percent) +
+     scale_x_discrete(labels=abbreviate)  # In this particular case, it has no effect
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/axes labels with percent labels'))
+
+# Self-defined formatting function for times.
+timeHMS_formatter <- function(x) {
+    h <- floor(x/60)
+    m <- floor(x %% 60)
+    s <- round(60*(x %% 1))                   # Round to nearest second
+    lab <- sprintf('%02d:%02d:%02d', h, m, s) # Format the strings as HH:MM:SS
+    lab <- gsub('^00:', '', lab)              # Remove leading 00: if present
+    lab <- gsub('^0', '', lab)                # Remove leading 0 if present
+}
+
+bp + scale_y_continuous(label=timeHMS_formatter)
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/axes labels with custom time labels'))
+
+# Hide all the gridlines
+bp + theme(panel.grid.minor=element_blank(), panel.grid.major=element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden gridlines'))
+
+# Hide just the minor gridlines
+bp + theme(panel.grid.minor=element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden minor gridlines'))
+
+# Hide all the horizontal gridlines
+bp + theme(panel.grid.minor.x=element_blank(), panel.grid.major.x=element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden horizontal gridlines'))
+
+# Hide all the vertical gridlines
+bp + theme(panel.grid.minor.y=element_blank(), panel.grid.major.y=element_blank())
+py$ggplotly(bp, kwargs=list(fileopt='overwrite', filename='R-Cookbook/axes/hidden vertical gridlines'))

bars.R

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+df <- data.frame(time = factor(c("Lunch","Dinner"), levels=c("Lunch","Dinner")),
+                 total_bill = c(14.89, 17.23))
+#   time total_bill
+#  Lunch      14.89
+# Dinner      17.23
+
+# Load the ggplot2 library
+library(ggplot2)
+
+
+# Very basic bar graph
+ggplot(data=df, aes(x=time, y=total_bill)) + geom_bar(stat="identity")
+
+# Map the time of day to different fill colors. These both have the same result.
+ggplot(data=df, aes(x=time, y=total_bill, fill=time)) + geom_bar(stat="identity")
+ggplot(data=df, aes(x=time, y=total_bill)) + geom_bar(aes(fill=time), stat="identity")
+
+
+# Add a black outline
+ggplot(data=df, aes(x=time, y=total_bill, fill=time)) + geom_bar(colour="black", stat="identity")
+
+
+# No legend, since the information is redundant
+ggplot(data=df, aes(x=time, y=total_bill, fill=time)) +
+    geom_bar(colour="black", stat="identity") +
+    guides(fill=FALSE)