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منتج #:
35515253
Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization
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منتج #:
35515253
EGP 4788
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Hands-On Data Analysis with Pandas is an essential guide for beginners, data analysts and scientists who want to explore each stage of data analysis and scientific computing using a wide range of datasets.
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Comprehensive Guidance
Offers in-depth insight into utilizing Pandas for effective data analysis, equipping users with essential skills for data wrangling and visualization.
Practical Examples
Includes real-world scenarios and hands-on exercises that enhance learning, ensuring that readers can apply concepts effectively in their projects.
Updated Techniques
Covers the latest features and improvements in Pandas, providing users with relevant tools and practices to optimize their data analysis workflow.
تفاصيل المنتج
- Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasksKey FeaturesPerform efficient data analysis and manipulation tasks using pandas 1.xApply pandas to different real-world domains with the help of step-by-step examplesMake the most of pandas as an effective data exploration toolBook DescriptionExtracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time.This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn.Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling using PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsSolve common data representation and analysis problems using pandasBuild Python scripts, modules, and packages for reusable analysis codeWho this book is forThis book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress.You’ll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.Table of ContentsIntroduction to Data AnalysisWorking with Pandas DataFramesData Wrangling with PandasAggregating Pandas DataFramesVisualizing Data with Pandas and MatplotlibPlotting with Seaborn and Customization TechniquesFinancial Analysis - Bitcoin and the Stock MarketRule-Based Anomaly DetectionGetting Started with Machine Learning in PythonMaking Better Predictions - Optimizing ModelsMachine Learning Anomaly DetectionThe Road Ahead
| Publisher | Packt Publishing |
| Publication date | April 29, 2021 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 788 pages |
| ISBN-10 | 1800563450 |
| ISBN-13 | 978-1800563452 |
| Item Weight | 2.93 pounds (1.33 kg) |
| Dimensions | 7.5 x 1.78 x 9.25 inches (19.1 x 4.5 x 23.5 cm) |
من يجب أن يشتري؟
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Data Scientists
Ideal for data scientists seeking to enhance their skills in data manipulation and analysis with Python's Pandas library.
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Beginners
A great resource for those new to data science and Python, offering hands-on examples and practical exercises.
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Data Analysts
Perfect for data analysts looking to deepen their knowledge of data analysis and visualization techniques using Pandas.
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Complete Beginners
Not suitable for absolute beginners without any programming background, as prior knowledge of Python is assumed.
وصف المنتج
About This Item
Are you looking to level up your data analysis skills using Python? Look no further, as we are thrilled to present the "Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition"! This comprehensive guide is perfect for both beginners and experienced data analysts who want to harness the power of Pandas for their data projects. Whether you are a data scientist, business analyst, or simply curious about data analysis, this book offers a practical and hands-on approach to help you become proficient in data collection, wrangling, analysis, and visualization using Python and Pandas. With the "Hands-On Data Analysis with Pandas", you will explore the world of data science through easy-to-follow tutorials and step-by-step examples. This second edition has been updated and improved, offering even more content and real-world case studies to enhance your learning experience. Inside, you will find: 1. Comprehensive coverage: This book covers all the essential concepts and techniques needed for effective data analysis.
From data manipulation and cleaning to advanced statistical analysis and visualization, you will gain a deep understanding of the entire data analysis process. 2. Hands-on exercises: The book includes a wealth of hands-on exercises and projects that allow you to apply your newfound knowledge. By working through these exercises, you will reinforce your understanding and develop the skills necessary for real-world data analysis. 3.
Real-world case studies: The author presents a range of real-world case studies, showcasing how Python and Pandas can be used to solve complex data analysis problems. By studying these case studies, you will learn valuable insights and techniques that can be applied to your own data projects. 4. Practical examples: The book provides numerous practical examples and code snippets that demonstrate how to effectively use Pandas for data analysis.
These examples will help you grasp the concepts quickly and enable you to start analyzing data on your own. 5. Updated content: This second edition includes updated content and examples to reflect the latest advancements in the field of data analysis. Stay up-to-date with the best practices and techniques used by data scientists worldwide. Whether you are a beginner or an experienced data analyst, "Hands-On Data Analysis with Pandas" is your go-to resource for mastering Python data analysis.
Unlock the potential of your data with the powerful combination of Python and Pandas. Get your copy now and start your data science journey today!.
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أسئلة العملاء & الإجابات
-
سؤال:
What topics does 'Hands-On Data Analysis with Pandas - Second Edition' cover?
إجابه: This handbook offers comprehensive insights into data collection, wrangling, analysis, and visualization using Python's Pandas library. It covers fundamental concepts such as data manipulation, working with data frames, and performing complex analyses. Additionally, it delves into data visualization techniques with libraries like Matplotlib and Seaborn, providing readers with practical examples and real-world use cases that enhance their understanding of data science. -
سؤال:
Is this book suitable for beginners in data science?
إجابه: Yes, this book is well-suited for beginners. It starts with foundational concepts and gradually progresses to more complex topics, making it accessible for those new to Python and data analysis. The clear explanations and hands-on exercises allow readers to practice what they've learned, enabling them to build a solid understanding of how to effectively use Pandas for data manipulation and analysis. -
سؤال:
What programming skills are required to benefit from this book?
إجابه: Some familiarity with Python programming is beneficial, but the book is designed to guide readers through the basics required for data analysis. Basic understanding of Python syntax and concepts will allow you to get the most out of the exercises and examples presented. The book includes practical scenarios that help build your coding skills as you learn how to wrangle and analyze data effectively. -
سؤال:
How is this second edition different from the first?
إجابه: The second edition of 'Hands-On Data Analysis with Pandas' has been updated to include the latest features and enhancements in the Pandas library. Additionally, it incorporates improved examples, expanded topics on data visualization, and best practices from industry professionals. This ensures that readers are equipped with the most current knowledge and techniques in data analysis, making it a valuable resource for both new and experienced practitioners. -
سؤال:
Can I use this book for learning data visualization?
إجابه: Absolutely! This book includes substantial content dedicated to data visualization using Matplotlib and Seaborn. It teaches readers how to effectively present analyzed data through visual formats, which is crucial in making data-driven decisions. By working through the examples in the book, you’ll gain hands-on experience in creating meaningful visualizations that can communicate insights clearly. -
سؤال:
Are there any real-world examples included in the book?
إجابه: Yes, the book incorporates real-world examples that illustrate how to apply data analysis techniques in practical scenarios. These examples are designed to reflect common challenges faced in data science, such as cleaning messy datasets or performing exploratory data analysis. This relevance helps readers understand the applicability of their skills in real situations, making the learning process much more relatable. -
سؤال:
What makes Pandas a favorite among data scientists?
إجابه: Pandas is favored for its powerful data manipulation and analysis capabilities, allowing users to handle large datasets efficiently. It offers easy-to-use data structures like Series and DataFrames that facilitate complex operations such as filtering, aggregation, and merging of datasets. These features, along with extensive documentation and community support, make Pandas a go-to choice for data scientists working on diverse projects. -
سؤال:
Is there any prerequisite knowledge needed for this book?
إجابه: While previous experience with Python is advantageous, it's not strictly necessary. The book is designed to cater to beginners, introducing key concepts as it progresses. Familiarity with basic data science principles will enhance your understanding, but the structured approach ensures that you can grasp the concepts just by following the text and practice exercises. It creates an ideal learning pathway for enthusiasts looking to dive into data analysis. -
سؤال:
What types of data analysis can I expect to learn?
إجابه: Readers can expect to learn a variety of data analysis techniques, from basic descriptive statistics to more advanced topics like time series analysis and machine learning integrations. The book's hands-on exercises encourage you to apply these techniques to real datasets, enabling you to uncover insights, predict trends, and make informed decisions based on your analyses. The knowledge gained allows for applications across multiple fields including finance, marketing, and healthcare. -
سؤال:
Where can I buy 'Hands-On Data Analysis with Pandas - Second Edition'?
إجابه: You can conveniently purchase 'Hands-On Data Analysis with Pandas - Second Edition' on Ubuy in Egypt. Ubuy offers a wide selection of books and tech resources to support your learning journey. By choosing Ubuy, you can easily access this valuable Python data science handbook and enhance your skills in data collection, wrangling, and visualization.
Data Mining Editorial Review
"Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition" is a well-received book in the field of data science. The author is praised for taking the reader through accessing and working with real-world data, even with missing or messy observations. The book is easy to follow and covers topics like data cleaning, data wrangling, and data enrichment in great depth. It has a great structure, with chapters explaining the different parts of pandas combined with chapters that have complete practical examples of analysis. The book is also praised for its examples with real datasets and explained software engineering concepts for writing better code as a data scientist.
مراجعات العملاء وتقييماتهم
112 تقييمات العملاء
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5 نجمة
65%
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4 نجمة
17%
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3 نجمة
9%
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2 نجمة
3%
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1 نجمة
6%
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إيجابيات
- Accesses real-world data which is missing or messy
- Well-structured with a combination of theoretical and practical examples
- Covers data cleaning, data wrangling, and data enrichment in great depth
- Examples are based on real datasets
- Teaches software engineering concepts to write better code as a data scientist
سلبيات
- One review expressed the book as having a superficial approach to learning Pandas.
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المميزات والفوائد
- Learn how to analyze and manipulate data using pandas
- Understand how to conduct exploratory data analysis to identify patterns
- Apply machine learning algorithms for predictions based on past data
- Create data visualizations with pandas, matplotlib, and seaborn
- Includes step-by-step examples and real-world datasets
- Valuable knowledge that can be applied across multiple domains
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