Pandas Data Analysis

Master data analysis with Pandas, the powerful Python library for data manipulation and analysis. Learn to clean, transform, analyze, and visualize data effectively. Code Example: Code Example: Code Example: Code Example: Analyze customer purchase behavior and segmentation. Requirements: Key Skills: Data cleaning, aggregation, visualization Analyze sales trends and forecast future performance. Requirements: Key Skills: Time series operations, rolling windows, plotting Build automated data quality assessment tool. Requirements: Key Skills: Data validation, statistical analysis, reporting After mastering Pandas, explore: - Load and manipulate data from various sources (CSV, Excel, SQL, APIs) - Clean and transform messy datasets - Perform exploratory data analysis (EDA) - Aggregate and group data for insights - Create compelling visualizations - Optimize performance for large datasets - Creating DataFrames from various sources - Indexing and selecting data (loc, iloc, at, iat) - Filtering and boolean indexing - Adding/removing columns and rows - Data types and conversions - Handling missing data (dropna, fillna, interpolate) - Removing duplicates - String operations and text cleaning - Date/time parsing and manipulation - Type conversions and casting - Applying custom functions (apply, map, applymap) - GroupBy operations - Aggregation functions (sum, mean, count, etc.) - Pivot...