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This tutorial demonstrates how to generate a wide range of 2D and 3D charts—including line, bar, scatter, pie, map, word cloud, gauge, funnel, tree, parallel, sankey, geo, timeline, and 3D visualizations—using the Python library pyecharts, providing complete code snippets and rendering instructions for each chart type.
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This article explains why passing pandas data directly to Pyecharts results in blank charts due to NumPy data types, and shows how converting pandas Series to Python lists with .tolist() resolves the issue, providing corrected example code.
This tutorial demonstrates how to crawl approximately 40,000 Maoyan movie reviews for the film “Chinese Doctors,” preprocess the data, and create visualizations such as rating pie charts, city distribution maps, top‑viewer bar charts, and a word cloud using Python libraries like requests, pyecharts, and wordcloud.
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This tutorial demonstrates how to collect, clean, and visualize historical Chinese National Games medal data using Python, covering data extraction with regular expressions, organization into pandas DataFrames, and creating both static line charts with Matplotlib and interactive charts with PyEcharts, complete with code snippets and practical tips.
This article demonstrates how to use the Python pyecharts library to generate impressive visualizations, including a basic 2D map, a detailed map of Guizhou province, and an interactive rotating globe, with step-by-step code examples and screenshots for each visualization.
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This tutorial shows how to fetch restaurant review data from online platforms, clean and structure it in Python, and then use pyecharts along with Python's Counter to create bar and pie visualizations that reveal overall impressions and star‑rating distributions.