数据分析|Python 疫情数据的可视化与分析（二）数据可视化|大数据|python

Python处理数据疫情词云 Python 疫情数据的可视化与分析第二弹来袭。
上次通过数据的预处理已经将疫情的数据清洗到excel中，详情见
https://blog.csdn.net/qq_42695315/article/details/111411789
这次将通过处理得到词云。

import openpyxlfrom wordcloud import WordCloud# 读取数据wb = openpyxl.load_workbook('data.xlsx') # 获取工作表 ws = wb['国内疫情'] frequency = {} for row in ws.values: if row[0] == '省份': pass else: frequency[row[0]] = float(row[1])wordcloud = WordCloud(font_path="C:/Windows/Fonts/SIMLI.TTF", background_color="white", width=1920, height=1080)# 根据确诊病例生成词云wordcloud.generate_from_frequencies(frequency)# 保存词云 wordcloud.to_file('wordcloude.png')

得到如图的中国词云

文章图片

同理生成全球的词云

wb = openpyxl.load_workbook('data1.xlsx') frequency_out = {} sheet_name = wb.sheetnames for each in sheet_name: if "洲" in each: ws = wb[each] for row in ws.values: if row[0] == '国家': pass else: frequency[row[0]] = float(row[1])wordcloud = WordCloud(font_path="C:/Windows/Fonts/SIMLI.TTF", background_color="white", width=1920, height=1080) wordcloud.generate_from_frequencies(frequency)# 保存词云 wordcloud.to_file('wordcloude1.png')

【数据分析|Python 疫情数据的可视化与分析（二）】