小编ctj*_*232的帖子

我意识到我对标题的措辞并不是最好的,但我希望有一个例子可以清楚这一点.

我如何转换像这样的列表

example_list = ["asdf" , "4", "asdfasdf" , "8" , "9" ,"asdf"]

到像这样的列表

converted_list = ["asdf" , 4, "asdfasdf", 8 , 9 , "asdf"]

那么基本上我如何创建一个列表,其中可以转换为整数的字符串转换为整数,而无法转换的字符串保留为字符串？

作为旁注,如果converted_list整数中的每个项目是否为整数,我将如何在for循环中进行测试？

这个问题的上下文是我试图在可能的情况下将pandas中的头转换为整数,因为所有整数都是现在的字符串.然后如果列有一个带有标题的字符串,我会取列的平均值.现在,我已将所有标题放入列表中.

import nltk
from nltk.corpus import movie_reviews
from nltk.tokenize import word_tokenize

documents = [(list(movie_reviews.words(fileid)), category)
             for category in movie_reviews.categories()
             for fileid in movie_reviews.fileids(category)]


all_words = []

for w in movie_reviews.words():
    all_words.append(w.lower())

all_words = nltk.FreqDist(all_words)

word_features = list(all_words.keys())[:3000]

def find_features(document):
    words = set(document)
    features = {}
    for w in word_features:
        features[w] = (w in words)

    return features

featuresets = [(find_features(rev), category) for (rev, category) in documents]

training_set = featuresets[500:1500]
testing_set = featuresets[:1500]

classifier = nltk.DecisionTreeClassifier.train(training_set)

print "Classifier accuracy percent:",(nltk.classify.accuracy(classifier, testing_set))*100 , "%" …