ngramr.plus
This package has functions for processing Google’s Ngram repositories without having to download them locally. These repositories vary in their size, but the larger ones (like th one for the letter s or common bigrams) contain multiple gigabytes.
The main function uses chunking from the readr package to reduce memory load. Still, depending on the specific word forms being searched, loading and processing the data tables can take up to a couple of minutes.
If you only want to plot and analyze trends, I would highly recommend the ngramr package, which is extremely efficient.
The advantage of ngramr.plus is that it returns the underlying data, enabling more precise identification of peaks and troughs, the use of variability-based neighbor clustering for ground-up periodization (see the vnc package), etc.
Installing ngramr.plus
Use devtools to install the package.
devtools::install_github("browndw/ngramr.plus")
Running ngramr.plus
The google_ngram() function takes three arguments: word_forms, variety, and by. The first can be a single word like teenager or lemmas like walk, walks and walked that are put into a vector: c("walk", "walks", "walked"). The same principal applies to ngrams > 1: c("teenager is", "teenagers are". The first word in an ngram sequence should be from the same root. So the function would fail to process c("teenager is", "child is"). The function will combine the counts of all forms in the returned data frame.
The variety argument can be one of: eng, gb, us, or fiction, for all English, British English, American English, or fiction, respectively.
The function can also return counts summed and normalized by year or by decade using the by argument: by="year" or by="decade").
The following would return counts for the word x-ray in US English by year:
xray_year <- google_ngram(word_forms = "x-ray", variety = "us", by = "year")
Alternatively, the following would return counts of the combined forms xray and xrays in British English by decade:
xray_decade <- google_ngram(word_forms = c("x-ray", "x-rays"), variety = "gb", by = "decade")
Warning
Google’s data tables are HUGE. Sometime running into multiple gigabytes for simple text files. Thus, depending on the table being accessed, the return time can be slow. For example, asscessing the 1-gram Q file should take only a few seconds, but the 1-gram T file might take 10 minutes to process. The 2-gram, 3-gram, etc. files are even larger and slower to process.