An API interface for Google Book NGrams.

pip install google-pygram

from google_pygram import GooglePyGram as gpg

pygram = gpg(
    corpus='English',
    corpus_year=2019,
    start_year=1800,
    end_year=2000,
    smoothing=3,
    case_sensitive=False,
    phrases=['hello', 'world']
)

print(pygram.to_df())

#         year         hello     world
# 1800  1800.0  9.921164e-08  0.000379
# 1801  1801.0  6.075895e-08  0.000423
# 1802  1802.0  7.149158e-08  0.000353
# 1803  1803.0  2.593483e-08  0.000338
# 1804  1804.0  8.450996e-08  0.000398
# ...      ...           ...       ...
# 1996  1996.0  1.331358e-06  0.000306
# 1997  1997.0  1.430890e-06  0.000308
# 1998  1998.0  1.523893e-06  0.000317
# 1999  1999.0  1.650712e-06  0.000326
# 2000  2000.0  2.076080e-06  0.000337

• corpus: The corpus to use. Can be one of the following:

  • English
  • Chinese (simplified)
  • French
  • German
  • Hebrew
  • Italian
  • Russian
  • Spanish

• corpus_year: The year of the corpus to use. Can be one of the following:

  • 2019
  • 2012
  • 2009

• start_year: The start year of the ngram. Must be between 1800 and 2000.

• end_year: The end year of the ngram. Must be between 1800 and 2000.

• smoothing: The smoothing parameter. Must be between 0 and 5.

• case_sensitive: Whether or not the ngram is case sensitive. Must be a boolean.

• phrases: A list of phrases to search for. Must be a list of strings.

• add_phrase(phrase): Adds a phrase to the ngram query.
• to_df(): Returns a pandas DataFrame of the ngram.
• to_csv(filename): Saves the ngram to a csv file.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

MIT