# 示例数据 reviews = [ {"reviewerID": "AO1Z63O9CTT95", "asin": "B000H29TXU", "reviewerName": "James Westervelt", "helpful": [0, 0], "reviewText": "he's OK. His humor consists mainly of varying between a Vietnamese accent and a smooth articulate presentation of ironic situations.", "overall": 2.0, "summary": "same routine he did on last comic standing", "unixReviewTime": 1394064000, "reviewTime": "03 6, 2014"}, # 添加更多评论数据... ]把这个代码换成读取excel数据呢

若您的评论数据存储在 Excel 文件中，您可以使用 pandas 库来读取 Excel 文件并提取评论文本。以下是一个修改后的示例代码：

import re
import pandas as pd
from collections import Counter

def count_word_frequency(reviews):
    word_freq = Counter()
    
    for review in reviews:
        review_text = review["reviewText"]
        # 清洗文本数据
        review_text = re.sub(r"[^a-zA-Z\s]", "", review_text)
        review_text = review_text.lower()
        
        # 分割文本为单词
        words = review_text.split()
        
        # 统计词频
        word_freq.update(words)
    
    return word_freq

# 读取 Excel 文件
df = pd.read_excel("your_file_path.xlsx")

# 将数据转换为字典列表
reviews = df.to_dict(orient="records")

# 统计词频
word_frequency = count_word_frequency(reviews)

# 打印前10个常见词
most_common_words = word_frequency.most_common(10)
for word, freq in most_common_words:
    print(f"{word}: {freq}")

请确保将 "your_file_path.xlsx" 替换为您实际的文件路径。此示例假设您的 Excel 文件包含与示例数据相同的列和字段名称，如果有所不同，请相应地进行调整。

此外，确保您已安装所需的库，可以使用 `pip install pandas` 和 `pip install xlrd` 来安装 pandas 和 xlrd 库。