heatmap.r

library(openxlsx)
library(ggplot2)
library(reshape2)
library(plyr)

# Fix the path!
cd = read.xlsx("countdata.xlsx", "Sheet1")

# Summarize counts to get average weekdays
cntByDay.1 = ddply(cd, .(DayOfWeek, CntTimeTxt), summarize, NB = mean(NB), SB = mean(SB))

# Reformat data to what ggplot2 wants
cntByDay = melt(cntByDay.1, id.vars = c("DayOfWeek", "CntTimeTxt"))

# We need some of these to be factors, and we need to reformat a little
cntByDay$CntTimeTxt = factor(cntByDay$CntTimeTxt)
cntByDay$DayTime = paste(cntByDay$DayOfWeek, cntByDay$variable, sep = " - ")
cntByDay$DayTime = factor(cntByDay$DayTime, levels= c("Monday - NB", "Monday - SB", "Tuesday - NB", "Tuesday - SB", "Wednesday - NB", "Wednesday - SB", "Thursday - NB", "Thursday - SB", "Friday - NB", "Friday - SB", "Saturday - NB", "Saturday - SB", "Sunday - NB", "Sunday - SB"))

# Plot the data
heatmap = ggplot(cntByDay, aes(x = DayTime, y = CntTimeTxt, fill = value, color = NULL))+
  geom_bin2d()+xlab("Day and Direction") + ylab("Time of Day") + 
  ggtitle("Average Weekday Count") +
  scale_fill_gradient(low="green", high="red") +
  scale_y_discrete(limits = rev(levels(cntByDay$CntTimeTxt)))