From a4f437f1ab775e9a9d9e583b013a2e95c2a43845 Mon Sep 17 00:00:00 2001
From: phmycqkit <656078035@qq.com>
Date: Wed, 18 Sep 2024 18:55:57 +0800
Subject: [PATCH] Delete 'GetWordCloud.py'

---
 GetWordCloud.py | 48 ------------------------------------------------
 1 file changed, 48 deletions(-)
 delete mode 100644 GetWordCloud.py

diff --git a/GetWordCloud.py b/GetWordCloud.py
deleted file mode 100644
index bf132e0..0000000
--- a/GetWordCloud.py
+++ /dev/null
@@ -1,48 +0,0 @@
-import pandas as pd
-import jieba
-from wordcloud import WordCloud
-from imageio import imread
-def GetWordCloud():
-    """根据弹幕以及词频制作词云图"""
-    # 读取弹幕文件并转为字典类型
-    df = pd.read_csv("danmu.csv")
-    danmus = dict(zip(df["弹幕"], df["数量"]))
-    
-    # 读取停用词
-    with open('stopwords.txt', 'r', encoding='utf-8') as f:
-        stopwords = f.readlines()
-    stopwords = [stopword.strip() for stopword in stopwords]
-    
-    # 将所有评论合并为一个字符串
-    txt = ''
-    for key, value in danmus.items():
-        for i in range(value):
-            txt += key
-            
-    # 获得每个词汇及其数量
-    words = jieba.lcut(txt)
-    words_dict = {}
-    for word in words:
-        if len(word) == 1:
-            continue
-        if word not in stopwords:
-            words_dict[word] = words_dict.get(word, 0) + 1
-    words_list = list(words_dict.items())
-    words_list.sort(key = lambda x:x[1], reverse=True)
-    words_count = dict(words_list)
-    
-    # 生成词云图
-    wordcloud = WordCloud(
-        background_color="white",
-        width=1000,
-        height=800,
-        font_path="msyh.ttc",
-        max_words=1000,
-        mask=imread("mask.png"),
-    ).generate_from_frequencies(words_count)
-    
-    #词云图保存文件
-    wordcloud.to_file("wordcloud.png")
-    
-if __name__ == '__main__':
-    GetWordCloud()