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.

library(knitr)
library(dplyr)
library(scales)
migr_asydcfsta=readRDS(file="../data/migr_asydcfsta_20180812.rds")

Syrien

cutoff=1000
CODE="SY"
COUNTRY="Syrien"
major_geo_total_sy=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 Staatsangehörigen aus r COUNTRY getroffen wurden:

library(knitr)
# Die ersten paar Spalten
kable(major_geo_total_sy[(-major_geo_total_sy$values),], caption = paste("Länder mit mehr als ", cutoff, " Entscheidungen zu Asylanträgen aus ", COUNTRY ))
major_geo_total_sy <- filter(major_geo_total_sy, geo != "TOTAL")

Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:

    other_geo_total_sy=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_sy <- sum(other_geo_total_sy$values)
dec_others_total_sy

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_sy$geo <- as.character(major_geo_total_sy$geo)
all_geo_total_sy <- rbind(major_geo_total_sy, c("XX",dec_others_total_sy))
all_geo_total_sy$values <- as.numeric(all_geo_total_sy$values) 
all_geo_total_sy$geo <- factor(all_geo_total_sy$geo, levels = arrange(all_geo_total_sy, values)$geo)
# The real thing
geo_dec_pie_sy <- ggplot(all_geo_total_sy, 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_sy

major_geo_sy <-filter(migr_asydcfsta, geo %in% major_geo_total_sy$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% 
  select(geo,decision,values) 
major_geo_sy$geo <- factor(major_geo_sy$geo, levels = arrange(filter(major_geo_sy, decision == "TOTAL"), desc(values))$geo)
# bring decisions into correct order
major_geo_sy$decision <- factor(major_geo_sy$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_sy <- ggplot(filter(major_geo_sy, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision)) 
dec_bar_sy +  scale_fill_manual(values = dec_palette_grey) + theme_bw() + theme(legend.position="bottom", axis.title.x = element_blank(), axis.title.y = element_blank()) + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in absoluten Zahlen")

dec_bar_sy_fill <- ggplot(filter(major_geo_sy, 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", axis.title.x = element_blank(), axis.title.y = element_blank()) + scale_y_continuous(label=percent) + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent")
dec_bar_sy_fill

Pakistan

COUNTRY="Pakistan"
CODE="PK"
cutoff=1000
major_geo_total_pk=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 Staatsangehörigen aus r COUNTRY getroffen wurden:

library(knitr)
# Die ersten paar Spalten
kable(major_geo_total_pk[order(-major_geo_total_pk$values),], caption = paste("Länder mit mehr als ",cutoff, " Entscheidungen zu Asylanträgen aus " , COUNTRY))
major_geo_total_pk <- filter(major_geo_total_pk, geo != "TOTAL")

Anzahl der Entscheidungen in Ländern mit weniger als r cutoff Entscheidungen - die werden im Folgenden vernachlässigt:

    other_geo_total_pk=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_pk <- sum(other_geo_total_pk$values)
dec_others_total_pk

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_pk$geo <- as.character(major_geo_total_pk$geo)
all_geo_total_pk <- rbind(major_geo_total_pk, c("XX",dec_others_total_pk))
all_geo_total_pk$values <- as.numeric(all_geo_total_pk$values) 
all_geo_total_pk$geo <- factor(all_geo_total_pk$geo, levels = arrange(all_geo_total_pk, values)$geo)
# The real thing
geo_dec_pie_pk <- ggplot(all_geo_total_pk, 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_pk

major_geo_pk <-filter(migr_asydcfsta, geo %in% major_geo_total_pk$geo, time >= "2017-01-01", sex == "T", age == "TOTAL", citizen == CODE, geo != "EU28", geo != "TOTAL") %>% 
  select(geo,decision,values) 
major_geo_pk$geo <- factor(major_geo_pk$geo, levels = arrange(filter(major_geo_pk, decision == "TOTAL"), desc(values))$geo)
# bring decisions into correct order
major_geo_pk$decision <- factor(major_geo_pk$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_pk <- ggplot(filter(major_geo_pk, decision != "TOTAL" & decision != "TOTAL_POS")) + geom_col(aes(x=geo, y=values, fill=decision)) 
dec_bar_pk +  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_pk_fill <- ggplot(filter(major_geo_pk, 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", axis.title.x = element_blank(), axis.title.y = element_blank()) + scale_y_continuous(label=percent) + ggtitle(paste("Entscheidungen über Asylanträge aus ",COUNTRY," 2017"), subtitle = "in Prozent")
dec_bar_pk_fill

more plots

• Schweden monthly

• years 2015, 2016 (simple), 2018 (quarterly data)

• Deportations? We barely have numbers from DE ... probably no way (only Dublin numbers. bpb has sth on https://www.bpb.de/gesellschaft/migration/flucht/218788/zahlen-zu-asyl-in-deutschland)

muc-fluechtlingsrat/r-eurostat-refugees documentation built on May 23, 2019, 8:20 a.m.