In nicolasfstgelais/dbExplore:

knitr::opts_chunk$set(fig.path='figures/',
                      echo=TRUE, warning=FALSE, message=FALSE)

# function to convert levels to numeric or characters
LtoN <- function(x) as.numeric(as.character(x))
LtoC <- function(x) as.character(x)

output=read.csv("output_cont.csv")

nb=length(unique(output$path))
cat=unique(output$category)
states=unique(output$state)

library(plyr)

#matTemp=ddply(output,"category",summarise,
      #frequency=length(nbYears)/nb,
      #years=median(nbYears),
      #depths=mean(nbDepths),
      #lakes=sum(nbLakes),
      #obs=sum(nbObs))

catSum=ddply(output,c("category","lvl2","lvl1","state"),summarise,
              frequency=length(unique(lvl1))/nb,
              years=median(nbYears),
              depths=mean(nbDepths),
              lakes=sum(nbLakes),
              obs=sum(nbObs))

lvl2Sum=ddply(catSum,c("lvl1","state"),summarise,
              frequency=max(frequency),
              years=max(years),
              depths=max(depths),
              lakes=max(lakes),
              obs=max(obs))



library(tidyr)
heatMat <- spread(lvl2Sum[,c("lvl1","state","lakes")], state, lakes)
rownames(heatMat)=heatMat$lvl1;heatMat$lvl1=NULL

heatMat=heatMat[order(rowSums(heatMat),decreasing = T),]

Number of lakes

library(plotrix)
par(mar = c(0, 10, 4, 0))
#par(mar = c(0.5, 4, 3.5, 0.5))
color2D.matplot(heatMat,
                show.values = TRUE,
                axes = F,
                xlab = "",
                ylab = "",
                vcex = 1,
                vcol = "black",
                extremes = c("white", "red"))

axis(3, at = seq_len(ncol(heatMat)) - 0.5,
     labels = colnames(heatMat), tick = FALSE, cex.axis = 1,las=2)

axis(2, at = seq_len(nrow(heatMat)) -0.5,
     labels = rev(rownames(heatMat)), tick = FALSE, las = 1, cex.axis = 1)

catSub=catSum[catSum$lvl2=="Contaminants-Inorganic",]
catSub=ddply(catSub,c("category","state"),summarise,
              frequency=max(frequency),
              years=max(years),
              depths=max(depths),
              lakes=max(lakes),
              obs=max(obs))



library(tidyr)
heatMat <- spread(catSub[,c("category","state","lakes")], state, lakes)
rownames(heatMat)=heatMat$category;heatMat$category=NULL

heatMat=heatMat[order(rowSums(heatMat),decreasing = T),]

Inorganic contaminants

library(plotrix)
par(mar = c(0, 10, 4, 0))
#par(mar = c(0.5, 4, 3.5, 0.5))
color2D.matplot(heatMat,
                show.values = TRUE,
                axes = F,
                xlab = "",
                ylab = "",
                vcex = 1,
                vcol = "black",
                extremes = c("white", "red"))

axis(3, at = seq_len(ncol(heatMat)) - 0.5,
     labels = colnames(heatMat), tick = FALSE, cex.axis = 1,las=2)

axis(2, at = seq_len(nrow(heatMat)) -0.5,
     labels = rev(rownames(heatMat)), tick = FALSE, las = 1, cex.axis = 1)

catSub=catSum[catSum$lvl2=="Contaminants-Inorganic",]
catSub=ddply(catSub,c("category","state"),summarise,
              frequency=max(frequency),
              years=max(years),
              depths=max(depths),
              lakes=max(lakes),
              obs=max(obs))



library(tidyr)
heatMat <- spread(catSub[,c("category","state","years")], state, years)
rownames(heatMat)=heatMat$category;heatMat$category=NULL

heatMat=heatMat[order(rowSums(heatMat),decreasing = T),]

library(plotrix)
par(mar = c(0, 10, 4, 0))
#par(mar = c(0.5, 4, 3.5, 0.5))
color2D.matplot(heatMat,
                show.values = TRUE,
                axes = F,
                xlab = "",
                ylab = "",
                vcex = 1,
                vcol = "black",
                extremes = c("white", "red"))

axis(3, at = seq_len(ncol(heatMat)) - 0.5,
     labels = colnames(heatMat), tick = FALSE, cex.axis = 1,las=2)

axis(2, at = seq_len(nrow(heatMat)) -0.5,
     labels = rev(rownames(heatMat)), tick = FALSE, las = 1, cex.axis = 1)

catSub=catSum[catSum$lvl1=="ions",]
catSub=ddply(catSub,c("category","state"),summarise,
              frequency=max(frequency),
              years=max(years),
              depths=max(depths),
              lakes=max(lakes),
              obs=max(obs))



library(tidyr)
heatMat <- spread(catSub[,c("category","state","lakes")], state, lakes)
rownames(heatMat)=heatMat$category;heatMat$category=NULL

heatMat=heatMat[order(rowSums(heatMat),decreasing = T),]

Ions

library(plotrix)
par(mar = c(0, 10, 4, 0))
#par(mar = c(0.5, 4, 3.5, 0.5))
color2D.matplot(heatMat,
                show.values = TRUE,
                axes = F,
                xlab = "",
                ylab = "",
                vcex = 1,
                vcol = "black",
                extremes = c("white", "red"))

axis(3, at = seq_len(ncol(heatMat)) - 0.5,
     labels = colnames(heatMat), tick = FALSE, cex.axis = 1,las=2)

axis(2, at = seq_len(nrow(heatMat)) -0.5,
     labels = rev(rownames(heatMat)), tick = FALSE, las = 1, cex.axis = 1)