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Wiebke Torsten
bwi2022
Commits
4173ba4b
Commit
4173ba4b
authored
9 months ago
by
Schmidt Sebastian
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lfe_bwi/R_bwi/Veraenderungsrechnungen.qmd
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lfe_bwi/R_bwi/Veraenderungsrechnungen.qmd
lfe_bwi/R_bwi/Veraenderungsrechnungen_files/figure-revealjs/ver-gf-bb-eig-22-ssch-1.png
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lfe_bwi/R_bwi/Veraenderungsrechnungen.qmd
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4173ba4b
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@@ -218,7 +218,7 @@ ist_waldfl_ba_2022_long <- ist_waldfl_ba_2022_long %>%
mutate(Prozent = round((Waldfläche/sum(ist_waldfl_ba_2022_long$Waldfläche))*100,digits=2)) # add column Prozent (rounded with 2 digits)
# Filter the top four rows
top_five <- head(ist_waldfl_ba_2022_long, 5)
top_five <- head(
arrange(
ist_waldfl_ba_2022_long,
desc(Waldfläche)),
5)
ist_waldfl_ba_2022_plot22 <- ggplot(ist_waldfl_ba_2022_long, aes(x = "", y = Prozent, fill = reorder(Baumartengruppe, Waldfläche, FUN = sum))) +
geom_bar(stat = "identity", width = 1) +
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@@ -468,7 +468,7 @@ ggplot(combined_data %>%
#### Interpretation
### Vergleich Schichtigkeit nach Waldtyp
### Vergleich Schichtigkeit nach Waldtyp
```{r vergl_bestock_schicht_watyp, echo=FALSE}
# Assuming jung$bb_waldtyp_bestockungsaufbau13 and jung$bb_waldtyp_bestockungsaufbau22 are your data frames
...
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@@ -616,7 +616,7 @@ ggplot(tot_typ_22_long %>%
ggtitle("Totholzvorrat nach Totholztyp in m³/ha über alle Länder in Deutschland (BWI2022)") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 65, hjust = 1),
plot.title = element_text(margin = margin(b =
2
0))) +
plot.title = element_text(margin = margin(b =
3
0))) +
guides(fill = guide_legend(title = "Totholztyp", title.position = "top"))
```
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