9  Effekte von Lehrveranstaltungen und Hochschulen

9.1 Setup

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library(tidyverse)
#library(lubridate)
#library(gt)
library(targets)
#library(ggpubr)
#library(scales)
# library(ggfittext)
library(easystats)
#library(data.table)
#library(tinytable)
# library(ggokabeito)
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source("_common.r")
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tar_load(c(
  course_and_uni_per_visit,
  time_spent_w_course_university
))

9.2 Anzahl an Lehrveranstaltungen nach Hochschule

9.2.1 idvisit

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course_and_uni_per_visit |>
  count(university)
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course_and_uni_per_visit |>
  count(university) |>
  drop_na() |>
  ggplot(aes(y = reorder(university, n), x = n)) +
  geom_col() +
  theme_minimal() +
  labs(
    title = "TH Nürnberg hosts the most courses on HaNS by far.",
    y = "University"
  )

9.2.2 fingerprint unique

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course_and_uni_per_visit |>
  distinct(fingerprint, .keep_all = TRUE) |>
  count(university) |>
  ggplot(aes(y = reorder(university, n), x = n)) +
  geom_col() +
  theme_minimal() +
  labs(
    title = "TH Nürnberg hosts the most courses on HaNS by far.",
    y = "University"
  )

9.3 Visits nach Lehrveranstaltung pro Jahr

9.3.1 idvisit

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time_spent_w_course_university |>
  count(year, course)
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time_spent_w_course_university |>
  count(year, course) |>
  drop_na() |>
  ggplot(aes(x = n, y = course, fill = factor(year), )) +
  geom_col(position = "dodge") +
  labs(title = "The course 'GeSOA' is the most active course on HaNS.")

9.3.2 fingerprint unique

Show the code
time_spent_w_course_university |>
  distinct(fingerprint, .keep_all = TRUE) |>
  count(year, course) |>
  drop_na() |>
  ggplot(aes(x = n, y = course, fill = factor(year), )) +
  geom_col(position = "dodge") +
  labs(title = "The course 'GeSOA' is the most active course on HaNS.")