Pandas Data Analysis

Data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib. 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: - Covers DataFrame and Series creation, indexing, filtering, and type conversions for structured data handling - Includes data cleaning techniques: missing value handling, deduplication, string operations, and date/time parsing - Provides GroupBy aggregation, pivot tables, multi-level indexing, and window functions for exploratory analysis - Integrates Matplotlib and Seaborn for statistical plotting, trend visualization, and correlation analysis - Three hands-on projects cover customer analytics, time series analysis, and automated data quality reporting - Load and manipulate data from various sources (CSV, Excel, SQL, APIs) - Clean and transform messy datasets - Perform...