One thought on “Why are you showing a 0% flatline when I know the phrase in my
query occurred in at least one book?”
Arti says:
Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Yes! The ngram data is available for
download here. Yes! The ngrams within
each file are not alphabetically sorted. Publishing was a relatively rare event in the 16th and 17th
centuries. To make the file sizes
manageable, we’ve grouped them by their starting letter and then
grouped the alternative ngram sizes in separate files. The same rules are
applied to parse both the ngrams typed by users and the ngrams
extracted from the corpora, which means that if you’re searching
for don’t, don’t be alarmed by the fact that the Ngram Viewer
rewrites it to do not; it’s accurately depicting usages of
both don’t and do not in the corpus. The same rules are
applied to parse both the ngrams typed by users and the ngrams
extracted from the corpora, which means that if you’re searching
for don’t, don’t be alarmed by the fact that the Ngram Viewer
rewrites it to do not; it’s accurately depicting usages of
both d
Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Perhaps for one of these reasons: Yes! The ngram data is available for
download here. Yes! The ngrams within
each file are not alphabetically sorted. Publishing was a relatively rare event in the 16th and 17th
centuries. To make the file sizes
manageable, we’ve grouped them by their starting letter and then
grouped the alternative ngram sizes in separate files. The same rules are
applied to parse both the ngrams typed by users and the ngrams
extracted from the corpora, which means that if you’re searching
for don’t, don’t be alarmed by the fact that the Ngram Viewer
rewrites it to do not; it’s accurately depicting usages of
both don’t and do not in the corpus. The same rules are
applied to parse both the ngrams typed by users and the ngrams
extracted from the corpora, which means that if you’re searching
for don’t, don’t be alarmed by the fact that the Ngram Viewer
rewrites it to do not; it’s accurately depicting usages of
both d