In muc-fluechtlingsrat/r-eurostat-refugees: Download and Visualise Eurostat Asylum Data (Applications and Decisions)
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
Plots und Analysen zum Hauptartikel
Hauptartikel ist "Aylsentscheidungen in Europa, Fokus Afghanistan". Dies gehört zu den ergänzenden Analysen.
Extra-Ergänzung
Entscheidungsdaten von Eurostat holen
library(knitr)
library(dplyr)
migr_asydcfsta=readRDS(file="/tmp/migr_asydcfsta_20180812.rds")
Gambia
cutoff=200
CODE="GM"
COUNTRY="Gambia"
major_geo_total_gm=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>%
select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cutoff Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr)
# Die ersten paar Spalten
kable(major_geo_total_gm[(-major_geo_total_gm$values),], caption = paste("Länder mit mehr als ", cutoff, " Entscheidungen zu Asylanträgen aus ", COUNTRY ))
major_geo_total_gm <- filter(major_geo_total_gm, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_gm=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values))
dec_others_total_gm <- sum(other_geo_total_gm$values)
dec_others_total_gm
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2)
# some technical workarounds for adding the row with the others (XX),
# and for sorting
major_geo_total_gm$geo <- as.character(major_geo_total_gm$geo)
all_geo_total_gm <- rbind(major_geo_total_gm, c("XX",dec_others_total_gm))
all_geo_total_gm$values <- as.numeric(all_geo_total_gm$values)
all_geo_total_gm$geo <- factor(all_geo_total_gm$geo, levels = arrange(all_geo_total_gm, values)$geo)
# The real thing
geo_dec_pie_gm <- ggplot(all_geo_total_gm, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle (paste("Entscheidungen über Asyl, ",COUNTRY,", 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank())
geo_dec_pie_gm
major_geo_gm <-filter(migr_asydcfsta, geo %in% major_geo_total_gm$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>%
select(geo,decision,values)
major_geo_gm$geo <- factor(major_geo_gm$geo, levels = arrange(filter(major_geo_gm, decision == "TOTAL"), desc(values))$geo)
# bring decisions into correct order
major_geo_gm$decision <- factor(major_geo_gm$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080")
dec_bar <- ggplot(filter(major_geo_gm, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision))
dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_gm, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent")
dec_bar_fill
Senegal
COUNTRY="Senegal"
CODE="SN"
cutoff=200
major_geo_total_sn=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>%
select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cut1off Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr)
# Die ersten paar Spalten
kable(major_geo_total_sn[order(-major_geo_total_sn$values),], caption = paste("Länder mit mehr als ",cutoff, " Entscheidungen zu Asylanträgen aus " , COUNTRY))
major_geo_total_sn <- filter(major_geo_total_sn, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_sn=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values))
dec_others_total_sn <- sum(other_geo_total_sn$values)
dec_others_total_sn
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2)
# some technical workarounds for adding the row with the others (XX),
# and for sorting
major_geo_total_sn$geo <- as.character(major_geo_total_sn$geo)
all_geo_total_sn <- rbind(major_geo_total_sn, c("XX",dec_others_total_sn))
all_geo_total_sn$values <- as.numeric(all_geo_total_sn$values)
all_geo_total_sn$geo <- factor(all_geo_total_sn$geo, levels = arrange(all_geo_total_sn, values)$geo)
# The real thing
geo_dec_pie_sn <- ggplot(all_geo_total_sn, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle(paste("Entscheidungen über Asyl, ",COUNTRY, " , 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank())
geo_dec_pie_sn
major_geo_sn <-filter(migr_asydcfsta, geo %in% major_geo_total_sn$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>%
select(geo,decision,values)
major_geo_sn$geo <- factor(major_geo_sn$geo, levels = arrange(filter(major_geo_sn, decision == "TOTAL"), desc(values))$geo)
# bring decisions into correct order
major_geo_sn$decision <- factor(major_geo_sn$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080")
dec_bar <- ggplot(filter(major_geo_sn, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision))
dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY,", 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_sn, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent")
dec_bar_fill
Mali
COUNTRY="Mali"
CODE="ML"
cutoff=200
major_geo_total_ml=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>%
select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cut1off Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr)
# Die ersten paar Spalten
kable(major_geo_total_ml[order(-major_geo_total_ml$values),], caption = paste("Länder mit mehr als ",cutoff, " Entscheidungen zu Asylanträgen aus " , COUNTRY))
major_geo_total_ml <- filter(major_geo_total_ml, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_ml=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values))
dec_others_total_ml <- sum(other_geo_total_ml$values)
dec_others_total_ml
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2)
# some technical workarounds for adding the row with the others (XX),
# and for sorting
major_geo_total_ml$geo <- as.character(major_geo_total_ml$geo)
all_geo_total_ml <- rbind(major_geo_total_ml, c("XX",dec_others_total_ml))
all_geo_total_ml$values <- as.numeric(all_geo_total_ml$values)
all_geo_total_ml$geo <- factor(all_geo_total_ml$geo, levels = arrange(all_geo_total_ml, values)$geo)
# The real thing
geo_dec_pie_ml <- ggplot(all_geo_total_ml, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle(paste("Entscheidungen über Asyl, ",COUNTRY, " , 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank())
geo_dec_pie_ml
major_geo_ml <-filter(migr_asydcfsta, geo %in% major_geo_total_ml$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>%
select(geo,decision,values)
major_geo_ml$geo <- factor(major_geo_ml$geo, levels = arrange(filter(major_geo_ml, decision == "TOTAL"), desc(values))$geo)
# bring decisions into correct order
major_geo_ml$decision <- factor(major_geo_ml$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080")
dec_bar <- ggplot(filter(major_geo_ml, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision))
dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY,", 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_ml, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent")
dec_bar_fill
muc-fluechtlingsrat/r-eurostat-refugees documentation built on May 23, 2019, 8:20 a.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
Plots und Analysen zum Hauptartikel
Hauptartikel ist "Aylsentscheidungen in Europa, Fokus Afghanistan". Dies gehört zu den ergänzenden Analysen. Extra-Ergänzung
Entscheidungsdaten von Eurostat holen
library(knitr) library(dplyr) migr_asydcfsta=readRDS(file="/tmp/migr_asydcfsta_20180812.rds")
Gambia
cutoff=200 CODE="GM" COUNTRY="Gambia" major_geo_total_gm=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>% select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cutoff Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr) # Die ersten paar Spalten kable(major_geo_total_gm[(-major_geo_total_gm$values),], caption = paste("Länder mit mehr als ", cutoff, " Entscheidungen zu Asylanträgen aus ", COUNTRY )) major_geo_total_gm <- filter(major_geo_total_gm, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_gm=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values)) dec_others_total_gm <- sum(other_geo_total_gm$values) dec_others_total_gm
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2) # some technical workarounds for adding the row with the others (XX), # and for sorting major_geo_total_gm$geo <- as.character(major_geo_total_gm$geo) all_geo_total_gm <- rbind(major_geo_total_gm, c("XX",dec_others_total_gm)) all_geo_total_gm$values <- as.numeric(all_geo_total_gm$values) all_geo_total_gm$geo <- factor(all_geo_total_gm$geo, levels = arrange(all_geo_total_gm, values)$geo) # The real thing geo_dec_pie_gm <- ggplot(all_geo_total_gm, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle (paste("Entscheidungen über Asyl, ",COUNTRY,", 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank()) geo_dec_pie_gm
major_geo_gm <-filter(migr_asydcfsta, geo %in% major_geo_total_gm$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% select(geo,decision,values) major_geo_gm$geo <- factor(major_geo_gm$geo, levels = arrange(filter(major_geo_gm, decision == "TOTAL"), desc(values))$geo) # bring decisions into correct order major_geo_gm$decision <- factor(major_geo_gm$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080") dec_bar <- ggplot(filter(major_geo_gm, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision)) dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_gm, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent") dec_bar_fill
Senegal
COUNTRY="Senegal" CODE="SN" cutoff=200 major_geo_total_sn=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>% select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cut1off Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr) # Die ersten paar Spalten kable(major_geo_total_sn[order(-major_geo_total_sn$values),], caption = paste("Länder mit mehr als ",cutoff, " Entscheidungen zu Asylanträgen aus " , COUNTRY)) major_geo_total_sn <- filter(major_geo_total_sn, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_sn=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values)) dec_others_total_sn <- sum(other_geo_total_sn$values) dec_others_total_sn
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2) # some technical workarounds for adding the row with the others (XX), # and for sorting major_geo_total_sn$geo <- as.character(major_geo_total_sn$geo) all_geo_total_sn <- rbind(major_geo_total_sn, c("XX",dec_others_total_sn)) all_geo_total_sn$values <- as.numeric(all_geo_total_sn$values) all_geo_total_sn$geo <- factor(all_geo_total_sn$geo, levels = arrange(all_geo_total_sn, values)$geo) # The real thing geo_dec_pie_sn <- ggplot(all_geo_total_sn, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle(paste("Entscheidungen über Asyl, ",COUNTRY, " , 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank()) geo_dec_pie_sn
major_geo_sn <-filter(migr_asydcfsta, geo %in% major_geo_total_sn$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% select(geo,decision,values) major_geo_sn$geo <- factor(major_geo_sn$geo, levels = arrange(filter(major_geo_sn, decision == "TOTAL"), desc(values))$geo) # bring decisions into correct order major_geo_sn$decision <- factor(major_geo_sn$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080") dec_bar <- ggplot(filter(major_geo_sn, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision)) dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY,", 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_sn, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent") dec_bar_fill
Mali
COUNTRY="Mali" CODE="ML" cutoff=200 major_geo_total_ml=filter(migr_asydcfsta, values > cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28") %>% select(geo,values)
Die Anzahl Entscheidungen pro Antragsland
Dies sind die europäischen Länder, in denen im Jahr 2017 mehr als cut1off Entscheidungen über Asylanträge von syrischen Staatsangehörigen getroffen wurden:
library(knitr) # Die ersten paar Spalten kable(major_geo_total_ml[order(-major_geo_total_ml$values),], caption = paste("Länder mit mehr als ",cutoff, " Entscheidungen zu Asylanträgen aus " , COUNTRY)) major_geo_total_ml <- filter(major_geo_total_ml, geo != "TOTAL")
Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:
other_geo_total_ml=filter(migr_asydcfsta, values <= cutoff, time == "2017-01-01", decision == "TOTAL", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% arrange(desc(values)) dec_others_total_ml <- sum(other_geo_total_ml$values) dec_others_total_ml
Eine Visualisierung der Gesamtanzahl von Entscheidungen zu COUNTRY im Jahr 2017:
library(ggplot2) # some technical workarounds for adding the row with the others (XX), # and for sorting major_geo_total_ml$geo <- as.character(major_geo_total_ml$geo) all_geo_total_ml <- rbind(major_geo_total_ml, c("XX",dec_others_total_ml)) all_geo_total_ml$values <- as.numeric(all_geo_total_ml$values) all_geo_total_ml$geo <- factor(all_geo_total_ml$geo, levels = arrange(all_geo_total_ml, values)$geo) # The real thing geo_dec_pie_ml <- ggplot(all_geo_total_ml, aes(x="", y=values, fill=geo)) + geom_col(colour = "black") + coord_polar("y", start=0) + scale_fill_grey(start = 0.4, end = 0.9) + ggtitle(paste("Entscheidungen über Asyl, ",COUNTRY, " , 2017"), subtitle = paste("EU-Länder; XX ist die Summe aller Länder mit < ", cutoff, " Entscheidungen")) + theme_bw() + theme(axis.title=element_blank()) geo_dec_pie_ml
major_geo_ml <-filter(migr_asydcfsta, geo %in% major_geo_total_ml$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% select(geo,decision,values) major_geo_ml$geo <- factor(major_geo_ml$geo, levels = arrange(filter(major_geo_ml, decision == "TOTAL"), desc(values))$geo) # bring decisions into correct order major_geo_ml$decision <- factor(major_geo_ml$decision, levels=c("REJECTED","TEMP_PROT","HUMSTAT","SUB_PROT","GENCONV","TOTAL_POS","TOTAL"))
dec_palette_grey=c("#000000","#C0C0C0","#D3D3D3","#E4E4E4","#E8E8E8","#C8C8C8","#808080") dec_bar <- ggplot(filter(major_geo_ml, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision)) dec_bar + scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY,", 2017"), subtitle = "in absoluten Zahlen")
dec_bar_fill <- ggplot(filter(major_geo_ml, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision), position="fill") + scale_fill_grey() + theme_bw() + theme(legend.position="bottom") + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent") dec_bar_fill
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