File size: 3,509 Bytes
2f8aa81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 |
#create_pop_table
OUTPUTDIR_data_wrangling <- here("data_wrangling")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_data_wrangling)) {
dir.create(OUTPUTDIR_data_wrangling)
}
#Glottolog df for ISO_639 merging
glottolog_df <-
read_tsv("data_wrangling/glottolog_cldf_wide_df.tsv", col_types = cols()) %>%
dplyr::select(
Glottocode,
Language_ID,
"ISO_639" = ISO639P3code,
Language_level_ID,
level,
Family_ID,
Longitude,
Latitude
) %>%
mutate(Language_level_ID = if_else(is.na(Language_level_ID), Glottocode, Language_level_ID)) %>%
mutate(Family_ID = ifelse(is.na(Family_ID), Language_level_ID, Family_ID)) %>%
dplyr::select(
Glottocode,
Language_ID,
ISO_639,
Language_level_ID,
level,
Family_ID,
Longitude,
Latitude
)
if (sample == "full") {
data_ethnologue <-
read_tsv("data_wrangling/ethnologue_pop_full.tsv")
}
if (sample == "reduced") {
#double check if the file below needs to be changed
data_ethnologue <-
read_tsv("data_wrangling/ethnologue_pop_SM.tsv", show_col_types = F) %>%
rename(L1_log10_st = L1_log10_scaled) %>%
dplyr::select(ISO_639, Language_ID, L1_log10_st, L2_prop)
}
social_vars <-
readxl::read_xlsx(
"data/lang_endangerment_predictors.xlsx",
sheet = "Supplementary data 1",
skip = 1,
col_types = "text",
na = "NA"
) %>%
left_join(glottolog_df, by = c("ISO" = "ISO_639")) %>%
rename("ISO_639" = "ISO") %>%
dplyr::select(
Language_ID = Glottocode,
ISO_639,
official_status,
language_of_education,
bordering_language_richness
) %>%
rename(Official = official_status) %>%
# naniar::replace_with_na(replace = list(L1_log10 = -Inf, L2_log10 = -Inf)) #removing for now
dplyr::mutate(neighboring_languages = bordering_language_richness, Education =
language_of_education) %>%
dplyr::mutate(neighboring_languages = as.numeric(neighboring_languages)) %>%
#dplyr::mutate(neighboring_languages_log10 = log10(neighboring_languages+1)) %>%
dplyr::mutate(neighboring_languages_st = scale(neighboring_languages)[, 1]) %>%
#dplyr::mutate(neighboring_languages_log10_st = scale(neighboring_languages_log10)[,1]) %>%
dplyr::select(Language_ID, Education, Official, neighboring_languages_st)
if (sample == "full") {
social_vars %>%
left_join(data_ethnologue, by = c("Language_ID")) %>%
dplyr::select(
Language_ID,
L1_log10_st,
L1_log10,
L2_prop,
Education,
Official,
neighboring_languages_st
) %>%
write_tsv(here(OUTPUTDIR_data_wrangling, "pop_full.tsv"))
} else{
social_vars %>%
left_join(data_ethnologue, by = c("Language_ID")) %>%
dplyr::select(Language_ID,
L1_log10_st,
L2_prop,
Education,
Official,
neighboring_languages_st) %>%
write_tsv(here(OUTPUTDIR_data_wrangling, "pop_reduced.tsv"))
}
glottolog_df_ISO <- glottolog_df %>%
dplyr::select("Language_ID", "ISO_639")
if (sample == "reduced") {
social_vars %>%
left_join(data_ethnologue, by = c("Language_ID")) %>%
dplyr::select(Language_ID,
L1_log10_st,
L2_prop,
Education,
Official,
neighboring_languages_st) %>%
left_join(glottolog_df_ISO,
by = c("Language_ID")) %>%
write_tsv(here(OUTPUTDIR_data_wrangling, "pop_reduced_with_ISO.tsv"))
}
|