I have a one-dimensional array with large strings in each of the elements. I am trying to use a CountVectorizer
to convert text data into numerical vectors. However, I am getting an error saying:
AttributeError: 'numpy.ndarray' object has no attribute 'lower'
mealarray
contains large strings in each of the elements. There are 5000 such samples. I am trying to vectorize this as given below:
vectorizer = CountVectorizer(
stop_words='english',
ngram_range=(1, 1), #ngram_range=(1, 1) is the default
dtype='double',
)
data = vectorizer.fit_transform(mealarray)
The full stacktrace :
File "/Library/Python/2.7/site-packages/sklearn/feature_extraction/text.py", line 817, in fit_transform
self.fixed_vocabulary_)
File "/Library/Python/2.7/site-packages/sklearn/feature_extraction/text.py", line 748, in _count_vocab
for feature in analyze(doc):
File "/Library/Python/2.7/site-packages/sklearn/feature_extraction/text.py", line 234, in <lambda>
tokenize(preprocess(self.decode(doc))), stop_words)
File "/Library/Python/2.7/site-packages/sklearn/feature_extraction/text.py", line 200, in <lambda>
return lambda x: strip_accents(x.lower())
AttributeError: 'numpy.ndarray' object has no attribute 'lower'
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