Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data with Python's Most Popular Data Manipulation Library (English Edition)
Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data with Python's Most Popular Data Manipulation Library (English Edition)
Unlock the power of Data Manipulation with Pandas. 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 ...
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Unlock the power of Data Manipulation with Pandas. 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. 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
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