Data Analysis with Python: Methods, Tools and Practices-Data Processing, Visualization and Prediction Based on Python

With the growing influence of artificial intelligence, the Internet of Things, and cloud computing, data analysis has moved from a supportive tool to playing a central role in business innovation. Python, thanks to its open-source framework and wide range of libraries, has become a favorite tool among data analysts. This paper focuses on how Python can be applied to real-world financial data, taking Xiaomi Corporations stock history as an example. Using libraries such as Pandas, Matplotlib, and mplfinance, we walk through the steps of data cleaning, calculating technical indicators like moving averages and the Relative Strength Index, and producing clear visualizations to observe market trends. Beyond the technical implementation, this study shows how Python can help users uncover meaningful patterns in stock data, improving the basis for investment decisions. The case study illustrates that even complex datasets can be handled smoothly with the right tools, and Pythons simplicity, flexibility, and community support make it especially suited for this kind of task.