Effective Pandas: Patterns for Data Manipulation by Matt Harrison (Author)
- Publisher: COMPUTER SCIENCE
- Availability: In Stock
- SKU: 52982
- Number of Pages: 391
Rs.990.00
Rs.1,295.00
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Effective Pandas: Patterns for Data Manipulation by Matt Harrison is a practical guide that delves into the powerful capabilities of the Pandas library for data analysis and manipulation in Python. This book presents efficient and reusable patterns for handling and transforming data, making it an essential resource for anyone working with data in Python. Harrison introduces best practices for using Pandas, focusing on how to streamline common tasks such as data cleaning, reshaping, merging, and aggregating. The book emphasizes writing clean, efficient code and provides a range of examples that demonstrate the most effective ways to use Pandas in real-world data manipulation tasks. With a focus on performance, flexibility, and scalability, Effective Pandas serves as both a reference and a tutorial for data scientists, analysts, and developers who want to master data manipulation in Python.
Key Points:
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Data Cleaning Techniques: The book covers best practices for cleaning raw data, including handling missing values, duplicate data, and data inconsistencies, ensuring that data is ready for analysis.
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Efficient Data Transformation: Harrison provides effective techniques for transforming data, such as reshaping, pivoting, and melting, to facilitate better insights and analysis.
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Data Aggregation and Grouping: The book explores powerful methods for grouping and aggregating data, using Pandas’ groupby functionality to compute summary statistics and perform advanced analysis.
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Performance Optimization: Effective Pandas highlights how to optimize data manipulation tasks for performance, such as avoiding common pitfalls that slow down data processing and using vectorized operations for efficiency.
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Merging and Joining Data: It provides strategies for combining datasets, focusing on methods like merging, joining, and concatenating, which are essential for working with multiple data sources.
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Handling Time Series Data: The book includes techniques for working with time series data, covering topics like resampling, time-based indexing, and handling date/time conversions.
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Advanced Indexing and Selection: Harrison introduces advanced techniques for indexing and selecting data efficiently, including multi-level indexing, slicing, and conditional selection, to improve workflow.
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Custom Data Manipulation Functions: The book demonstrates how to write custom functions and apply them to datasets using Pandas’
apply
andmap
methods, allowing for more flexible data manipulation. -
Visualization with Pandas: Harrison also covers simple plotting and visualization techniques using Pandas in conjunction with libraries like Matplotlib, enhancing the ability to explore and present data.
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Real-World Examples: The book provides numerous real-world examples and case studies to showcase how to apply these techniques to practical data analysis problems in business, finance, and other industries.
Conclusion:
Effective Pandas: Patterns for Data Manipulation by Matt Harrison is an indispensable guide for those looking to enhance their Python data manipulation skills with Pandas. By focusing on reusable patterns and performance-optimized techniques, the book helps readers streamline their data workflows, making it easier to work with large datasets. Whether you're an experienced data scientist or a beginner, this book equips you with the tools and best practices needed to perform sophisticated data manipulation tasks effectively and efficiently in Pandas
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Writer ✤ Matt Harrison (Author)