186 lines
5.9 KiB
R
186 lines
5.9 KiB
R
library(sf)
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library(ggplot2)
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library(ggtext)
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library(dplyr)
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library(rnaturalearth)
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library(rnaturalearthhires)
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library(showtext)
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library(viridis)
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library(shadowtext)
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library(ggnewscale)
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# Variablen
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hintergrundfarbe <- "#f2f2f2"
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# Automatisches Laden von Schriftarten und Fira Sans aktivieren
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showtext_auto()
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font_add(family = "Fira Sans", regular = "FiraSans-Regular.ttf")
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# Geodaten für Deutschland laden
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germany_states <- ne_states(country = "Germany", returnclass = "sf")
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# CSV-Daten einlesen
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inf_qual <- read.csv2("~/Informatik-Monitor/Ländervergleich/BL_Informatik_Qualifikationsphase.csv", stringsAsFactors = FALSE)
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# Daten bereinigen : "n.a." zu NA und Spalten in numerisch umwandeln
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inf_qual_cl <- inf_qual %>%
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mutate(
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GK_Stunden_min = na_if(GK_Stunden_min, "n.a."),
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LK_Stunden_min = na_if(LK_Stunden_min, "n.a."),
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Wahl = na_if(Wahl, "n.a.")
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) %>%
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mutate(
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GK_Stunden_min = as.numeric(GK_Stunden_min),
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LK_Stunden_min = as.numeric(LK_Stunden_min),
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Wahl = as.numeric(Wahl)
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)
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# Zeilen mit NA in GK_Stunden_min filtern
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inf_qual_gefiltert <- inf_qual_cl %>%
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filter(!is.na(GK_Stunden_min))
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# Gruppieren und zusammenfassen
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inf_qual_aggregiert <- inf_qual_gefiltert %>%
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group_by(Bundesland) %>%
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summarise(
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GK_Stunden_min = min(GK_Stunden_min, na.rm = TRUE),
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LK_Stunden_min = ifelse(any(is.na(LK_Stunden_min)), "n.a.", as.character(min(LK_Stunden_min, na.rm = TRUE))),
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Wahl = ifelse(any(is.na(Wahl)), "n.a.", as.character(min(Wahl, na.rm = TRUE)))
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)
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# Spalte hinzufügen für Kategorisierung
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inf_qual_aggregiert <- inf_qual_aggregiert %>%
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mutate(
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Niveau = case_when(
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LK_Stunden_min != "n.a." ~ "e",
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LK_Stunden_min == "n.a." & !is.na(GK_Stunden_min) ~ "g",
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TRUE ~ NA_character_ # optional, falls beides nicht zutrifft
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)
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)
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# Spalten in States reduzieren
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germany_states_min <- germany_states %>%
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select(Bundesland = name, postal, geometry)
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# ACHTUNG: postal-Kürzel korrigieren: Brandenburg → "BB"
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germany_states_min <- germany_states_min %>%
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mutate(postal = ifelse(Bundesland == "Brandenburg", "BB", postal))
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# Vereinigung von Daten und Geometrie
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inf_qual_karte <- germany_states_min %>%
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left_join(inf_qual_aggregiert, by = "Bundesland")
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# Baden-Wuerttemberg anpassen
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inf_qual_karte <- inf_qual_karte %>%
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mutate(Niveau = ifelse(Bundesland == "Baden-Württemberg", "g", Niveau))
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# Nur die Grenzen extrahieren (Linien)
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karte_grenzen <- inf_qual_karte %>%
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st_geometry() %>%
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st_cast("MULTIPOLYGON") %>%
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st_boundary() %>%
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st_sf()
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# Mittelpunkte der BL-Flächenberechnen und Verschiebung für Positionierung der Labels
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bundesland_labels <- inf_qual_karte %>%
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mutate(centroid = st_centroid(geometry)) %>%
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mutate(
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x = st_coordinates(centroid)[, 1],
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y = st_coordinates(centroid)[, 2]
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) %>%
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mutate(
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x = ifelse(Bundesland == "Brandenburg", x + 0.5, x), # nach Osten
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y = ifelse(Bundesland == "Brandenburg", y - 0.4, y) # nach Süden
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) %>%
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mutate(
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x = ifelse(Bundesland == "Berlin", x + 0.12, x), # nach Osten
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y = ifelse(Bundesland == "Berlin", y + 0.12, y) # nach Norden
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) %>%
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mutate(
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x = ifelse(Bundesland == "Bremen", x + 0.2, x), # nach Osten
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y = ifelse(Bundesland == "Bremen", y + 0.04, y) # nach Norden
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) %>%
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mutate(
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x = ifelse(Bundesland == "Hamburg", x - 0.05, x), # nach Westen
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y = ifelse(Bundesland == "Hamburg", y - 0.15, y) # nach Süden
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)
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# Karte erzeugen
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karte <- ggplot(inf_qual_karte) +
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# Flächen ohne Grenzen
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geom_sf(data = inf_qual_karte, aes(fill = Niveau), color = NA) +
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# Innengrenzen separat: weiß, dick
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geom_sf(data = karte_grenzen, fill = NA, color = hintergrundfarbe, size = 0.3) +
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coord_sf(expand = FALSE) +
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geom_shadowtext(
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data = bundesland_labels,
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aes(x = x, y = y, label = postal),
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family = "Fira Sans", # optional
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size = 3, # anpassbar
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color = hintergrundfarbe, # evtl. Kontrastfarbe
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bg.color = "black",
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bg.r = 0.05,
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check_overlap = TRUE # verhindert Überlappung
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) +
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scale_fill_manual(
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values = c("g" = "#3b528b", "e" = "#5ec962"), # "G8/G9" = "#21918c"),
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name = "Informatik",
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labels = c(
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"g" = "grundlegendes Anforderungsniveau",
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"e" = "grundlegendes und erhöhtes Anforderungsniveau"
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),
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limits = c("g", "e") # ← Reihenfolge der Anzeige
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) +
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labs(
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title = "Informatikunterricht in der Qualifikationsphase",
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subtitle = "Informatik in der gymnasialen Oberstufe an allgemeinbildenden Schulen, 2025",
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caption = "Datenquelle: Informatik-Monitor"
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) +
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theme_minimal() +
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theme(
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text = element_text(family = "Fira Sans"),
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plot.title = element_text(face = "bold", size = 16),
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plot.subtitle = ggtext::element_markdown(size = 12, lineheight = 1.2),
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# Hintergrundfarbe überall auf #E9E9E9 setzen
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plot.background = element_rect(fill = hintergrundfarbe, color = NA),
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panel.background = element_rect(fill = hintergrundfarbe, color = NA),
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legend.background = element_rect(fill = hintergrundfarbe, color = NA),
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legend.key = element_rect(fill = hintergrundfarbe, color = NA),
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# Rest wie gehabt
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panel.grid = element_blank(),
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axis.text = element_blank(),
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axis.ticks = element_blank(),
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axis.title = element_blank(),
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# Rand
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#plot.margin = margin(0.5, 0.5, 0.5, 0.5, unit = "cm"),
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#Position Legende
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legend.position = "bottom",
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legend.direction = "horizontal", # nebeneinander statt untereinander
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# legend.justification = c(1, 0), # rechtsbündig
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legend.box.just = "right", # Box am rechten Rand ausrichten
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legend.title = element_blank(),
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plot.margin = margin(1, 1, 1, 1, unit = "cm"), # mehr Platz rechts
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plot.caption = element_text(margin = margin(t = 15))
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)
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# Karte anzeigen
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print(karte)
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# Karte speichern
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ggsave(
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filename = "BL_Oberstufe_IU_Qual_Art.svg",
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plot = karte,
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path = "~/Informatik-Monitor/Ländervergleich",
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width = 18,
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height = 27,
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unit = "cm",
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device = "svg"
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)
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