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

Question

I'm facing this attribute error and I'm stuck at how to handle float values if they appear in a tweet.The streaming tweet has to be lower cased and tokenized so i have used split function.

Can somebody please help me to deal with it, any workaround or solution ..?

Here's the error which m gettin....

AttributeError                            Traceback (most recent call last)
<ipython-input-28-fa278f6c3171> in <module>()
      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'

---

Here is my code

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)

---

I tried many ways but still not able to get them to use lower and split function.

Answer 1

Thank you @Dick Kniep. Yes,it is Pandas CSV reader. Your suggestion worked. Following is the python code which worked for me by specifying the field datatype, (in this case, its string)

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