create data.frame

gistfile1.r

# tokenize each status. split on comma period or whitespace
status_tokens = strsplit(statuses, ",|\\.|\\s+")

matching_tokens = sapply(status_tokens, function(x) {
    x[which(x %in% tiobe_langs)]
})

# Now have the languages mentioned in #code2013 which are in TIOBE
code2013_langs = unlist(matching_tokens)
code2013_lang_table = as.data.frame(sort(table(code2013_langs), decreasing=TRUE))
colnames(code2013_lang_table) = "Count"
# Create a column describing the rough place of the code2013 langs
code2013_lang_table$code2013_tier = ordered(c(rep("1-5", 5), rep("6-10", 5), rep("11-15", 5),
    rep("16-25", 10), rep("26-39", 14)), levels=c("1-5", "6-10", "11-15", "16-25", "26-39"))
# Order by the TIOBE rankings
code2013_lang_table$code2013_langs = ordered(rownames(code2013_lang_table),
    levels=rev(tiobe[, "lang"]))