christ = both %>% filter(rlgdnm == 1 | rlgdnm == 2 | rlgdnm == 3 | rlgdnm == 4)
nones = both %>% filter(rlgblg == 2)
rm(both)
christ = christ %>% mutate(denom = 1)
nones = nones %>% mutate(denom = 2)
both = rbind(christ, nones)
all = both %>% dplyr::select(trstlgl, imwbcnt, lrscale, trstprt, trstep, atcherp, cntry, denom)
aaa1 = all %>%
group_by(denom) %>%
ct(lrscale) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Placement on <-Left-Right-> Scale") %>%
mutate(trust = lrscale)
aaa2 = all %>%
group_by(denom) %>%
ct(trstlgl) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Trust in the Legal System <- -+ ->") %>%
mutate(trust = trstlgl)
aaa3 = all %>%
group_by(denom) %>%
ct(trstprt) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Trust in Political Parties <- -+ ->") %>%
mutate(trust = trstprt)
aaa4 = all %>%
group_by(denom) %>%
ct(trstep) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Trust in the European Parliament <- -+ ->") %>%
mutate(trust = trstep)
aaa5 = all %>%
group_by(denom) %>%
ct(imwbcnt) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Immigrants Make Country <-Worse or Better-> Place to Live") %>%
mutate(trust = imwbcnt)
aaa6 = all %>%
group_by(denom) %>%
ct(atcherp) %>%
mutate(religion = car::recode(denom, "1 = 'Christian (All Denominations)'; 2 = 'None'")) %>%
mutate(issue = "Emotional Attachment to Europe <- -+ ->") %>%
mutate(trust = atcherp)
graph <- bind_df("aaa")
graph %>%
ggplot(., aes(y=pct, x= trust, color = religion)) +
geom_smooth(se = FALSE) +
theme_minimal() +
facet_wrap(~ issue, ncol =3) +
labs(color = "Religion", title = "Political Attitudes of Christians and Nones", subtitle = "France and Germany", x = "", y = "", caption = "Data: ESS 2018") +
scale_y_continuous(labels = percent) +
theme(legend.position = "bottom") +
scale_color_manual(values = c("coral2", "green3")) +
theme(text=element_text(size=17, family="saira"))
Published by Jihed Ncib
Born in Tunisia.
B.A. in Law - University of Rennes - France.
M.A. in Political Science | M.Sc. in Data Science & Statistics - Eastern Illinois University - United States. Currently PhDing at UCD Dublin in Ireland.
View all posts by Jihed Ncib