add this week
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# Josua Kugler, Christian Merten
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library(rlang)
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`%->%` <- function(value, x) eval.parent(substitute(x <- value))
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# Josua Kugler, Christian Merten
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library(tidyverse)
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library(rlang)
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variables <- LETTERS[1:7]
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names(variables) <- variables
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prop_ops <- exprs(`(`,`!`,`&`,`|`,`<=`,`>=`,`==`)
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prop_ops_str <- sapply(prop_ops, expr_text)
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ops_expr_str <- c("==", "<=", ">=", "&", "|", "!")
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ops_print_str <- c("\u2194","\u2190","\u2192","\u2227","\u2228","\u00AC")
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names(ops_print_str) <- ops_expr_str
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flip <- function(f) function(x,y) f(y,x)
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implies <- function(A, B) (!A) | B
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validate_Prop <- function(e) {
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stopifnot("class must be Prop" = "Prop" %in% class(e))
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stopifnot("only numbers 0 and 1 allowed" = !str_detect(expr_text(e), "[2-9]"))
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stopifnot("invalid operator or variable" = all(all.names(e) %in% c(variables, ops_expr_str, "(", ")")))
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e
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}
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Prop <- function(x) {
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e <- enexpr(x)
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if (typeof(e) == "symbol") e <- expr(( (!!e) ))
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validate_Prop(structure(e, class="Prop"))
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}
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tochar <- function(p) str_replace_all(expr_text(p), fixed(ops_print_str))
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print.Prop <- function(p) {
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cat(tochar(p), "\n")
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invisible(p)
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}
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interprete <- function(prop, vars, append=FALSE) {
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res <- as.logical(eval_tidy(prop, c(as.list(vars),
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`>=` = implies,
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`<=` = flip(implies))))
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var <- tochar(prop)
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if(append) add_column(vars, (!!sym(var)) := res)
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else res
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}
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combinations <- do.call(expand.grid, lapply(variables, function(v) c(0,1)))
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is_tautology <- function(prop) {
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all(interprete(prop, combinations))
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}
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# Josua Kugler, Christian Merten
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library(tidyverse)
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# a)
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rate <- function(df, expr, name) {
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t <- summarize(df, total := sum({{expr}}))
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mutate(df, {{name}} := {{expr}} / t$total)
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}
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#b)
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show_na <- function(df, expr) df %>% filter(is.na({{expr}}))
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#c)
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ggplot_line <- function(df, expr_x, expr_y)
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df %>% ggplot(aes(x = {{expr_x}}, y = {{expr_y}})) + geom_line()
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#d)
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athletes <- read_csv("athletes.csv")
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medal_color <- c(Bronze = "#6A3805", Silver = "#B4B4B4", Gold = "#AF9500")
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plot_olympia <- function(event, sex, metric) {
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athletes %>% filter(Event == event , Sex == sex) %>%
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mutate (Year = as.factor(Year)) ->
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d
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ggplot(d, aes(x = Year, y = {{metric}})) +
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geom_boxplot (na.rm = TRUE) +
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geom_point (data = drop_na (d), aes(color = Medal)) +
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scale_color_manual (values = medal_color) +
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ggtitle(str_c(event, sex, sep = ", "))
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}
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