There are data from two sources: Standard cross-cultural sample sources (SCCS) and Ethnographic Atlas (EA)
wide_features_all <- clean_features %>%
select(ETS_code, variable_name) %>%
mutate(present = 1) %>%
acast(variable_name ~ ETS_code, value.var="present") %>%
data.frame()
wide_features_all[wide_features_all == 0] <- NA
vis_miss(wide_features_all)
wide_features_SCCS <- clean_features %>%
filter(soc_source == "Standard cross-cultural sample") %>%
select(ETS_code, variable_name) %>%
mutate(present = 1) %>%
acast(variable_name ~ ETS_code, value.var="present") %>%
data.frame()
wide_features_SCCS[wide_features_SCCS == 0] <- NA
vis_miss(wide_features_SCCS)
wide_features_EA <- clean_features %>%
filter(soc_source == "Ethnographic Atlas") %>%
select(ETS_code, variable_name) %>%
mutate(present = 1) %>%
acast(variable_name ~ ETS_code, value.var="present") %>%
data.frame()
wide_features_EA[wide_features_EA == 0] <- NA
vis_miss(wide_features_EA)
wide_features_EA_env <- clean_features %>%
filter(soc_source == "Ethnographic Atlas") %>%
filter(var_type == "env") %>%
select(ETS_code, variable_name) %>%
mutate(present = 1) %>%
acast(variable_name ~ ETS_code, value.var="present") %>%
data.frame()
wide_features_EA_env[wide_features_EA_env == 0] <- NA
vis_miss(wide_features_EA_env)
EA_vars_env <- wide_features_EA_env %>%
rownames_to_column(var = "var_id") %>%
select(var_id) %>%
left_join(vars, by = c("var_id" = "name"))
DT::datatable(EA_vars_env %>% select(-codebook_info))
wide_features_EA_trait <- clean_features %>%
filter(soc_source == "Ethnographic Atlas") %>%
filter(var_type == "trait") %>%
select(ETS_code, variable_name) %>%
mutate(present = 1) %>%
acast(variable_name ~ ETS_code, value.var="present") %>%
data.frame()
wide_features_EA_trait[wide_features_EA_trait == 0] <- NA
vis_miss(wide_features_EA_trait)
Features:
EA_vars_trait <- wide_features_EA_trait %>%
rownames_to_column(var = "var_id") %>%
select(var_id) %>%
left_join(vars, by = c("var_id" = "label"))
DT::datatable(EA_vars_trait)