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200 10$aUltimate Pandas for Data Manipulation and Visualization $eEfficiently Process and Visualize Data with Python's Most Popular Data Manipulation Library (English Edition)
205   $a1st ed.
210  1$aDelhi :$cOrange Education PVT Ltd,$d2024.
210  4$dİ2024.
215   $a1 online resource (190 pages)
311 08$aPrint version: Firdose, Tahera Ultimate Pandas for Data Manipulation and Visualization Delhi : Orange Education PVT Ltd,c2024 
327   $aCover Page -- Title Page -- Copyright Page -- Dedication Page -- About the Author -- About the Technical Reviewers -- Acknowledgements -- Preface -- Errata -- Table of Contents -- 1. Introduction to Pandas and Data Analysis --   Introduction --   Structure --   Overview of Pandas and Their Role in Data Analysis --     Pandas Popularity --     Advantages of Pandas over Traditional Data Analysis Methods --   Installation and Setup --     Installing Pandas on Windows --     Installing Pandas on MaCOS --     Installing Pandas on Linux --   IPython Notebooks and its Integration with Pandas --     Installing Jupyter Notebooks --   Understanding Pandas Objects: Series and DataFrame --     Series --     DataFrame --   Datatypes of Pandas --     Defining Datatypes --     Using the Datatypes of Pandas in Series and DataFrame --   Loading Data from Files and the Web for Pandas --     Loading Data from CSV Files Using pandas.read_csv()$7Generated by AI.
330   $aUnlock 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.
606   $aPandas$7Generated by AI
606   $aPython (Computer program language)$7Generated by AI
615  0$aPandas
615  0$aPython (Computer program language)
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