Research on the Application of Python Big Data in Financial Analysis
Abstract
With the rapid development of big data technology and the widespread use of the Python programming language in data science, financial analysis is gradually shifting from traditional manual calculations and analysis to automated and intelligent approaches. This paper explores the application of Python in financial analysis within a big data environment, examining its specific uses in data collection, processing, analysis, and the automation of financial reporting. First, it introduces the advantages of Python and big data technology, along with their integration methods. Next, it outlines the basic concepts and common techniques of financial analysis. Then, it delves into Python’s applications in financial analysis, including data preprocessing, financial statement analysis, predictive modeling, and risk management. Through case studies, the paper demonstrates how Python enhances the efficiency and accuracy of financial analysis for businesses. Finally, it summarizes the current state of Python’s application in financial analysis, addressing challenges such as data quality issues and the integration of artificial intelligence, while also exploring future trends. This study provides practical guidance for professionals in the financial sector and offers insights for future research.
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