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portada Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data With Python's Most Popular Data Manipulation Library
Type
Physical Book
Publisher
Author
Language
English
Pages
361
Format
Paperback
ISBN13
9788197256240

Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data With Python's Most Popular Data Manipulation Library

Tahera Firdose (Author) · Orange Education Pvt. Ltd · Paperback

Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data With Python's Most Popular Data Manipulation Library - Tahera Firdose

New Book Imported to South Africa
Delivery: 09 Jul - 03 Aug Shipping: 4 to 5 business days.
R 717
R 717

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Synopsis "Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data With Python's Most Popular Data Manipulation Library"

Unlock the power of Data Manipulation with Pandas. Book DescriptionUnlock 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. Table of Contents1. Introduction to Pandas and Data Analysis2. Pandas Series3. Pandas DataFrame4. Data Cleaning with Pandas5. Data Filtering with Pandas6. Grouping and Aggregating Data7. Reshaping and Pivoting in Pandas8. Joining and Merging Data in Pandas9. Introduction to Time Series Analysis in Pandas10. Visualization Using Matplotlib11. Analyzing Bank Customer Churn Using Pandas Index

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