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