This article demonstrates how to calculate word frequencies in Chinese text using Python's jieba library, collections.Counter, and xlwt to export results to Excel, providing complete code examples and alternative approaches for effective text analysis.
This article demonstrates how to use Python's requests and BeautifulSoup to crawl text from a news site, process it with collections, numpy, and jieba for word‑frequency analysis, and then visualize the top terms using pyecharts, providing complete code snippets and explanations.
This article walks through cleaning chaotic Taobao CSV data using Python's regular expressions and pandas, removing unwanted characters with stop‑words, performing word segmentation, and generating word‑frequency statistics through both a classic approach and a pandas‑optimized method, complete with code snippets and visual results.
This tutorial explains how to count word frequencies using Python's collections.Counter from static, random, or file‑based text sources and then visualize the results with the WordCloud library, covering code examples, parameter settings, and available colormaps.
