为什么Nltk中的词根\词形化不能在熊猫数据帧上正确执行？

Question

我正在尝试从Pandas数据帧上的nltk包中实现词干提取和词条抽取。我编写了以下函数，但在某处未执行词干和词根化。请让我知道需要进行的更改。

from nltk.tokenize import RegexpTokenizer
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.stem import LancasterStemmer

stemmer=LancasterStemmer()
lemmer=WordNetLemmatizer()

alpha_tokenizer=RegexpTokenizer('[A-Za-z]\w+')
def process_sentence(words):
    words=words.lower()
    tokens=alpha_tokenizer.tokenize(words)
    for index,word in enumerate(tokens):
        tokens[index]=stemmer.stem(word)
        tokens[index]=lemmer.lemmatize(word,'v')
        tokens[index]=lemmer.lemmatize(word,'n')

    return tokens

print([process_sentence(item) for item in ['abaci', 'happy dogs']])

# [['abacus'], ['happy', 'dog']]