Python is widely used in data analytics for data cleaning, transformation, visualization, and predictive modeling. With libraries like Pandas, NumPy, and Matplotlib, analysts can process large datasets efficiently. Python also integrates with SQL databases and APIs, making data collection seamless. Machine learning libraries like Scikit-learn enable predictive insights, while Jupyter Notebooks provide interactive analysis. Many professionals pursuing a Google data analytics certification use Python to automate repetitive tasks, create dashboards, and generate actionable insights. Its versatility, combined with a strong community, makes Python a go-to tool for building end-to-end data analytics workflows in both business and research environments.