Data Manipulation with Python: pandas and NumPy for Analysts

Raw data is rarely ready for analysis, and knowing how to clean, transform, and structure it is the most critical skill for any aspiring data professional. This text-based course guides you step-by-step through the essentials of data preparation using Python's most powerful libraries. You will transition from writing basic scripts to confidently wrangling complex datasets for analysis and reporting. By reading through clear explanations and structured code examples, you will master the foundational concepts of data structures and progress to advanced manipulation techniques. You will learn how to handle missing values, merge disparate data sources, and optimize your workflows using modern Python practices. What you'll learn: * Understand the foundational mechanics of NumPy arrays and pandas DataFrames * Clean and format messy datasets by handling missing values and inconsistent types * Reshape data structures using pivot tables, melting, and multi-indexing * Combine multiple datasets efficiently using advanced joins and merges * Calculate complex rolling statistics and group-by aggregations * Apply modern Python practices like type hinting and vectorized operations for cleaner, faster code The course begins with core definitions and fundamental structures before walking you through data cleaning, transformation, and aggregation techniques using realistic scenarios like customer transactions and census data. This program is designed for beginners with a basic understanding of Python syntax; no prior data science or statistics experience is required. Start your journey toward efficient, professional data manipulation today.