文本分析不会展示?词云+频率统计是最直观的高级可视化,适合评论、标题、反馈文本分析。场景:用户评论文本,提取高频词,生成美观词云图。核心:jieba分词、Counter频率、WordCloud自定义字体/颜色/形状。① 生成测试数据
import pandas as pdimport numpy as np words = ["好用","推荐","流畅","卡顿","一般","差","快","稳定","服务好","垃圾"]comments = [" ".join(np.random.choice(words, 8)) for _ in range(100)]df = pd.DataFrame({"comment": comments})df.to_excel("comments.xlsx", index=False)print(" comments.xlsx 生成完成")
② 核心代码
import pandas as pdfrom collections import Counterimport jiebafrom wordcloud import WordClouddf = pd.read_excel("comments.xlsx")text = " ".join(df["comment"].astype(str))# 分词统计words = [w for w in jieba.lcut(text) if len(w) > 1]counter = Counter(words)print("高频词:", counter.most_common(10))# 词云wc = WordCloud( font_path="SimHei.ttf", # 需确保有中文字体 width=1000, height=500, background_color="white").generate_from_frequencies(counter)wc.to_file("wordcloud.png")print("词云已保存为 wordcloud.png")