In rOpenGov/bibliographica: Bibliographic Data Analysis

Language

r length(unique(unlist(strsplit(as.character(df$languages), ";"))))-1 unique languages
r length(unique(df$language_primary))-1 unique primary languages
r sum(!df$multilingual, na.rm = TRUE) single-language documents (r round(100 * mean(!df$multilingual, na.omit = TRUE), 2)%)
r sum(df$multilingual, na.rm = TRUE) multilingual documents (r round(100 * mean(df$multilingual, na.omit = TRUE), 2)%)
Conversions from raw to preprocessed language entries
r sum(is.na(df$languages) | df$language_primary == "Undetermined") documents (r round(100*mean(is.na(df$languages) | df$language_primary == "Undetermined"), 2)%) with unrecognized language

Language codes are from MARC; new custom abbreviations can be added in this table.

Title count per language (including multi-language documents; note the log10 scale):

top_plot(df, "languages", ntop = ntop, log10 = TRUE)

Top languages

Number of documents assigned with each language (top-10). For a complete list, see accepted languages.

x <- top(df, "languages")
tab <- cbind(names(x), unname(x), round(100 * unname(x/nrow(df)), 1))
colnames(tab) <- c("Language", "Documents (n)", "Fraction (%)")
kable(head(tab, 10))