nltk.corpus.reader.ReviewsCorpusReader

class nltk.corpus.reader.ReviewsCorpusReader[source]

Bases: CorpusReader

Reader for the Customer Review Data dataset by Hu, Liu (2004). Note: we are not applying any sentence tokenization at the moment, just word tokenization.

>>> from nltk.corpus import product_reviews_1
>>> camera_reviews = product_reviews_1.reviews('Canon_G3.txt')
>>> review = camera_reviews[0]
>>> review.sents()[0]
['i', 'recently', 'purchased', 'the', 'canon', 'powershot', 'g3', 'and', 'am',
'extremely', 'satisfied', 'with', 'the', 'purchase', '.']
>>> review.features()
[('canon powershot g3', '+3'), ('use', '+2'), ('picture', '+2'),
('picture quality', '+1'), ('picture quality', '+1'), ('camera', '+2'),
('use', '+2'), ('feature', '+1'), ('picture quality', '+3'), ('use', '+1'),
('option', '+1')]

We can also reach the same information directly from the stream:

>>> product_reviews_1.features('Canon_G3.txt')
[('canon powershot g3', '+3'), ('use', '+2'), ...]

We can compute stats for specific product features:

>>> n_reviews = len([(feat,score) for (feat,score) in product_reviews_1.features('Canon_G3.txt') if feat=='picture'])
>>> tot = sum([int(score) for (feat,score) in product_reviews_1.features('Canon_G3.txt') if feat=='picture'])
>>> mean = tot / n_reviews
>>> print(n_reviews, tot, mean)
15 24 1.6
CorpusView[source]

alias of StreamBackedCorpusView

__init__(root, fileids, word_tokenizer=WordPunctTokenizer(pattern='\\w+|[^\\w\\s]+', gaps=False, discard_empty=True, flags=re.UNICODE | re.MULTILINE | re.DOTALL), encoding='utf8')[source]
Parameters

  • root – The root directory for the corpus.

  • fileids – a list or regexp specifying the fileids in the corpus.

  • word_tokenizer – a tokenizer for breaking sentences or paragraphs into words. Default: WordPunctTokenizer

  • encoding – the encoding that should be used to read the corpus.

features(fileids=None)[source]

Return a list of features. Each feature is a tuple made of the specific item feature and the opinion strength about that feature.

Parameters

fileids – a list or regexp specifying the ids of the files whose features have to be returned.

Returns

all features for the item(s) in the given file(s).

Return type

list(tuple)

reviews(fileids=None)[source]

Return all the reviews as a list of Review objects. If fileids is specified, return all the reviews from each of the specified files.

Parameters

fileids – a list or regexp specifying the ids of the files whose reviews have to be returned.

Returns

the given file(s) as a list of reviews.

sents(fileids=None)[source]

Return all sentences in the corpus or in the specified files.

Parameters

fileids – a list or regexp specifying the ids of the files whose sentences have to be returned.

Returns

the given file(s) as a list of sentences, each encoded as a list of word strings.

Return type

list(list(str))

words(fileids=None)[source]

Return all words and punctuation symbols in the corpus or in the specified files.

Parameters

fileids – a list or regexp specifying the ids of the files whose words have to be returned.

Returns

the given file(s) as a list of words and punctuation symbols.

Return type

list(str)

abspath(fileid)[source]

Return the absolute path for the given file.

Parameters

fileid (str) – The file identifier for the file whose path should be returned.

Return type

PathPointer

abspaths(fileids=None, include_encoding=False, include_fileid=False)[source]

Return a list of the absolute paths for all fileids in this corpus; or for the given list of fileids, if specified.

Parameters

  • fileids (None or str or list) – Specifies the set of fileids for which paths should be returned. Can be None, for all fileids; a list of file identifiers, for a specified set of fileids; or a single file identifier, for a single file. Note that the return value is always a list of paths, even if fileids is a single file identifier.

  • include_encoding – If true, then return a list of (path_pointer, encoding) tuples.

Return type

list(PathPointer)

citation()[source]

Return the contents of the corpus citation.bib file, if it exists.

encoding(file)[source]

Return the unicode encoding for the given corpus file, if known. If the encoding is unknown, or if the given file should be processed using byte strings (str), then return None.

ensure_loaded()[source]

Load this corpus (if it has not already been loaded). This is used by LazyCorpusLoader as a simple method that can be used to make sure a corpus is loaded – e.g., in case a user wants to do help(some_corpus).

fileids()[source]

Return a list of file identifiers for the fileids that make up this corpus.

license()[source]

Return the contents of the corpus LICENSE file, if it exists.

open(file)[source]

Return an open stream that can be used to read the given file. If the file’s encoding is not None, then the stream will automatically decode the file’s contents into unicode.

Parameters

file – The file identifier of the file to read.

raw(fileids=None)[source]
Parameters

fileids – A list specifying the fileids that should be used.

Returns

the given file(s) as a single string.

Return type

str

readme()[source]

Return the contents of the corpus README file, if it exists.

property root

The directory where this corpus is stored.

Type

PathPointer