Research Article
Stock Data Analysis and Empirical Research Based on Python Data Visualization
@INPROCEEDINGS{10.4108/eai.22-5-2026.2365151, author={Yichang Sun}, title={Stock Data Analysis and Empirical Research Based on Python Data Visualization}, proceedings={Proceedings of the 4th International Conference on Image, Algorithms, and Artificial Intelligence, ICIAAI 2026, 22-24 May 2026, Singapore, Singapore}, publisher={EAI}, proceedings_a={ICIAAI}, year={2026}, month={8}, keywords={Data Analysis Finance Big Data Data Visualization}, doi={10.4108/eai.22-5-2026.2365151} }- Yichang Sun
Year: 2026
Stock Data Analysis and Empirical Research Based on Python Data Visualization
ICIAAI
EAI
DOI: 10.4108/eai.22-5-2026.2365151
Abstract
With the continuous improvement of financial market informatization, stock data continues to grow in terms of scale, dimension, and complexity, and traditional numerical analysis methods are gradually showing limitations in terms of intuitiveness and interpretation. Therefore, this paper takes stock data as the research object. Based on the data visualization technology of the Python platform, the stock price, trading volume, and technical indicators are visualized and presented, and empirical analysis is carried out in combination with the simple trading model. The research results show that reasonable data visualization can effectively reveal the dynamic characteristics and market structure information of stock prices, while significantly improving the interpretability of model analysis and strategy evaluation. The research in this article provides practical reference for the application of Python data visualization in stock analysis, which has certain theoretical significance and application value in improving the efficiency and research quality of financial data analysis.
