Unlock the power of Data Manipulation with Pandas. Key Features ? Master Pandas from basics to advanced and its data manipulation techniques. ? Visualize data effectively with Matplotlib and explore data efficiently. ? Learn through hands-on examples and practical real-world use cases. Book Description Unlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. What you will learn ? Wrangle data efficiently using Pandas' cleaning, filtering, and transformation techniques. ? Unlock hidden patterns with advanced grouping, joining, and merging operations. ? Master time series analysis with Pandas to extract valuable insights from your data. ? Apply Pandas to real-world scenarios like customer churn analysis and financial modeling. Who is this book for? This book is ideal for aspiring data scientists, analysts, and Python enthusiasts looking to enhance their data manipulation skills using Pandas. Familiarity with Python programming basics and a basic understanding of data structures will greatly benefit readers as they delve into the concepts presented in this book. Table of Contents 1. Introduction to Pandas and Data Analysis 2. Pandas Series 3. Pandas DataFrame 4. Data Cleaning with Pandas 5. Data Filtering with Pandas 6. Grouping and Aggregating Data 7. Reshaping and Pivoting in Pandas 8. Joining and Merging Data in Pandas 9. Introduction to Time Series Analysis in Pandas 10. Visualization Using Matplotlib 11. Analyzing Bank Customer Churn Using Pandas Index About the Author Tahera Firdose holds a postgraduate degree in Artificial Intelligence and has made significant strides in the fields of data analysis and machine learning. Her academic background, combined with her passion for these domains, has propelled her into a prominent position as an educator, blogger, and community influencer. Tahera's expertise in Artificial Intelligence extends beyond theoretical knowledge; she has applied her skills in various practical and impactful projects. Her work in machine learning, particularly in developing innovative algorithms and predictive models, has been recognized for its excellence and practical applications. She is known for her ability to simplify complex concepts and make them accessible to a broader audience. An avid writer, Tahera frequently shares her insights and discoveries through her well-regarded blog.