library(ggplot2) library(data.table) gs <- read.delim("student_information.tsv") d <- gs[,c(2,5)] colnames(d) <- c("student.num", "discord.name") call.list <- do.call("rbind", lapply(list.files(".", pattern="^call_list-.*tsv$"), function (x) {read.delim(x)[,1:4]})) colnames(call.list) <- gsub("_", ".", colnames(call.list)) call.list$day <- as.Date(call.list$timestamp) ## drop calls where the person wasn't present call.list.full <- call.list call.list[!call.list$answered,] call.list <- call.list[call.list$answered,] call.counts <- data.frame(table(call.list$discord.name)) colnames(call.counts) <- c("discord.name", "num.calls") d <- merge(d, call.counts, all.x=TRUE, all.y=TRUE, by="discord.name"); d ## set anything that's missing to zero d$num.calls[is.na(d$num.calls)] <- 0 attendance <- unlist(lapply(list.files(".", pattern="^attendance-.*tsv$"), function (x) {d <- read.delim(x); strsplit(d[[2]], ",")})) file.to.attendance.list <- function (x) { tmp <- read.delim(x) d.out <- data.frame(discord.name=unlist(strsplit(tmp[[2]], ","))) d.out$day <- rep(as.Date(tmp[[1]][1]), nrow(d.out)) return(d.out) } attendance <- do.call("rbind", lapply(list.files(".", pattern="^attendance-.*tsv$"), file.to.attendance.list)) ## create list of folks who are missing in class missing.in.class <- call.list.full[is.na(call.list.full$answered) | (!is.na(call.list.full$answered) & !call.list.full$answered), c("discord.name", "day")] missing.in.class <- unique(missing.in.class) setDT(attendance) setkey(attendance, discord.name, day) setDT(missing.in.class) setkey(missing.in.class, discord.name, day) ## drop presence for people on missing days attendance[missing.in.class,] attendance <- as.data.frame(attendance[!missing.in.class,]) attendance.counts <- data.frame(table(attendance$discord.name)) colnames(attendance.counts) <- c("discord.name", "num.present") d <- merge(d, attendance.counts, all.x=TRUE, all.y=TRUE, by="discord.name") days.list <- lapply(unique(attendance$day), function (day) { day.total <- table(call.list.full$day == day)[["TRUE"]] lapply(d$discord.name, function (discord.name) { num.present <- nrow(attendance[attendance$day == day & attendance$discord.name == discord.name,]) if (num.present/day.total > 1) {print(day)} data.frame(discord.name=discord.name, days.present=(num.present/day.total)) }) }) days.tmp <- do.call("rbind", lapply(days.list, function (x) do.call("rbind", x))) days.tbl <- tapply(days.tmp$days.present, days.tmp$discord.name, sum) attendance.days <- data.frame(discord.name=names(days.tbl), days.present=days.tbl, days.absent=length(list.files(".", pattern="^attendance-.*tsv$"))-days.tbl) d <- merge(d, attendance.days, all.x=TRUE, all.y=TRUE, by="discord.name") d[sort.list(d$days.absent), c("discord.name", "num.calls", "days.absent")] ## make some visualizations of whose here/not here ####################################################### png("questions_absence_histogram_combined.png", units="px", width=800, height=600) ggplot(d) + aes(x=as.factor(num.calls), fill=days.absent, group=days.absent) + geom_bar(color="black") + scale_x_discrete("Number of questions asked") + scale_y_continuous("Number of students") + scale_fill_continuous("Days absent", low="red", high="blue")+ theme_bw() dev.off() png("questions_absenses_boxplots.png", units="px", width=800, height=600) ggplot(data=d) + aes(x=as.factor(num.calls), y=days.absent) + geom_boxplot() + scale_x_discrete("Number of questions asked") + scale_y_continuous("Days absent") dev.off()