Pandas for Financial and Economic Data Analysis

Analyzing market trends and economic indicators requires powerful tools to handle structured data efficiently. This course introduces you to data analysis using Python and the Pandas library, centered around financial and economic datasets. You will build a solid understanding of data structures, moving step by step from foundational definitions to practical analytical workflows. What you'll learn: Understand core data analysis concepts and fundamental Pandas structures like Series and DataFrames; Clean, filter, and reshape complex financial datasets for analysis; Handle time series data to track market prices, returns, and economic indicators; Compute rolling statistics, percentage changes, and key financial metrics; Load and save data efficiently using modern file formats including Parquet and CSV; Aggregate and pivot data to derive actionable economic insights. The course begins with core terminology and fundamental data operations before guiding you through practical financial manipulation techniques. Designed for beginners in data analysis, this text-based course requires no advanced prior experience. Step into financial data analysis and start building your Python skills today.