Python Word Vect numpy 数组,在保存到 csv 时给出维度错误,预期为 1D 或 2D 数组,得到的是 0D 数组
Python Word Vect numpy array, on saving to csv gave error on dimension , Expected 1D or 2D array, got 0D array instead
保存 wordVect 出错,
from sklearn.feature_extraction.text import CountVectorizer
corpus = [
'This is the first document.',
'This document is the second document.',
'And this is the third one.',
'Is this the first document?',
]
vectorizer = CountVectorizer(ngram_range=()
X = vectorizer.fit_transform(corpus)
# Save The Vector
np.savetxt('logvect.csv', X, delimiter=',')
遇到错误
----> 1 np.savetxt('logvect.csv', X, 分隔符=',')
1375 if X.ndim == 0 or X.ndim > 2:
1376 raise ValueError(
-> 1377 "Expected 1D or 2D array, got %dD array instead" % X.ndim)
1378 elif X.ndim == 1:
1379 # Common case -- 1d array of numbers
ValueError: Expected 1D or 2D array, got 0D array instead
X.toarray() # 丢失
np.savetxt('logvect.csv', X.toarray(), delimiter=',')
保存 wordVect 出错,
from sklearn.feature_extraction.text import CountVectorizer
corpus = [
'This is the first document.',
'This document is the second document.',
'And this is the third one.',
'Is this the first document?',
]
vectorizer = CountVectorizer(ngram_range=()
X = vectorizer.fit_transform(corpus)
# Save The Vector
np.savetxt('logvect.csv', X, delimiter=',')
遇到错误
----> 1 np.savetxt('logvect.csv', X, 分隔符=',')
1375 if X.ndim == 0 or X.ndim > 2:
1376 raise ValueError(
-> 1377 "Expected 1D or 2D array, got %dD array instead" % X.ndim)
1378 elif X.ndim == 1:
1379 # Common case -- 1d array of numbers
ValueError: Expected 1D or 2D array, got 0D array instead
X.toarray() # 丢失
np.savetxt('logvect.csv', X.toarray(), delimiter=',')