AttributeError:'float'对象没有属性'lower'

我正面临着这个属性错误,如果它们出现在推文中,我就会陷入如何处理浮点值.流媒体推文必须更低,并且标记化,所以我使用了分割功能.

有人可以帮我处理它,任何解决方法或解决方案..？

这是我犯的错误 ....

AttributeError                            Traceback (most recent call last)
 in ()
      1 stop_words = []
----> 2 negfeats = [(word_feats(x for x in p_test.SentimentText[f].lower().split() if x not in stop_words), 'neg') for f in l]
      3 posfeats = [(word_feats(x for x in p_test.SentimentText[f].lower().split() if x not in stop_words), 'pos') for f in p]
      4 
      5 trainfeats = negfeats+ posfeats

AttributeError: 'float' object has no attribute 'lower'

这是我的代码

p_test = pd.read_csv('TrainSA.csv')

stop_words = [ ]

def word_feats(words):

    return dict([(word, True) for word in words])


l = [ ]

for f in range(len(p_test)):

    if p_test.Sentiment[f] == 0:

        l.append(f)



p = [ ]

for f in range(len(p_test)):

    if p_test.Sentiment[f] == 1:

        p.append(f) 




negfeats = [(word_feats(x for x in p_test.SentimentText[f].lower().split() if x not in stop_words), 'neg') for f in l]

posfeats = [(word_feats(x for x in p_test.SentimentText[f].lower().split() if x not in stop_words), 'pos') for f in p]


trainfeats = negfeats+ posfeats

print len(trainfeats)


import random 

random.shuffle(trainfeats)

print(len(trainfeats))




p_train = pd.read_csv('TrainSA.csv')


l_t = []

for f in range(len(p_train)):

    if p_train.Sentiment[f] == 0:

        l_t.append(f)


p_t = []

for f in range(len(p_train)):

    if p_train.Sentiment[f] == 1:

        p_t.append(f)        

print len(l_t)

print len(p_t)

我尝试了很多方法,但仍然无法让它们使用较低和分离功能.

我觉得你的问题在pd.read_csv('TrainSA.csv')函数中有根源.虽然你没有发布这个例程但我认为它是Pandas read_csv.此例程智能地将输入转换为python数据类型.但是,这意味着在您的情况下,某些值可以转换为浮点数.您可以通过指定每列所期望的数据类型来阻止此智能(？)行为.

谢谢@Dick Kniep ...是的,这是熊猫csv读者.你的建议工作.通过指定字段数据类型,以下代码为我工作...

p_test = pd.read_csv('TrainSA.csv')
p_test.SentimentText=p_test.SentimentText.astype(str)