What is covered in the 'Ultimate Data Science Programming in Python' book?

The book is a comprehensive guide to Python programming for data science, covering key libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. It includes 300 programs to provide hands-on experience, making it suitable for beginners and advanced users alike. Readers will also find two intricate projects and extensive coverage of Exploratory Data Analysis (EDA) using GUI tools. This blend ensures a practical understanding of theoretical concepts, allowing readers to apply their skills in real-world scenarios.

Who is the target audience for this book?

This book caters to a diverse audience, including aspiring data scientists, students in computer science and analytics, as well as professionals looking to upskill in Python and data science applications. With its carefully structured content, it serves both novices who need foundational knowledge and experienced programmers seeking to master data science libraries. The practical examples prepare readers for projects in various domains, ranging from finance to healthcare analytics.

What programming languages do I need to know before starting this book?

While prior knowledge of Python is highly beneficial, the book is designed for users at all skill levels. Beginners can follow along with foundational programming concepts introduced in the early chapters, making it accessible. For those familiar with Python, the book deepens understanding of data science techniques using Python libraries. This dual approach ensures that all readers find value, whether they are just starting or looking to enhance their programming capabilities.

Are there real-world projects included in this book?

Yes, the book features two detailed projects designed to integrate and apply the concepts learned throughout the chapters. These projects guide the reader through the entire data science workflow, from data gathering and processing to analysis and visualization. The inclusion of real-world applications helps reinforce learning by empowering readers to implement solutions to challenges they may face in professional environments. Completing these projects builds confidence and practical skills in data science.

What data science libraries are emphasized in the book?

The book emphasizes several fundamental Python libraries essential for data science, including Pandas for data manipulation, NumPy for numerical computing, Matplotlib, and Seaborn for data visualization, and Scikit-learn for machine learning. Each library's capabilities are explored through 300 practical examples, allowing readers to explore various functions and their applications. Mastering these libraries equips readers with robust tools to analyze and manipulate data effectively.

How does the book address Exploratory Data Analysis (EDA)?

Exploratory Data Analysis (EDA) is crucial for understanding the data before modeling, and this book dedicates significant attention to it. Using GUI tools, the book teaches readers to visualize data distributions and relationships intuitively. EDA helps identify patterns, anomalies, and insights that guide analytical decision-making. The focus on GUI tools makes EDA more approachable for readers who may prefer graphical overcoding-intensive methods, thus broadening its appeal.

Is this book suitable for someone who's not technically inclined?

Absolutely! The book is structured to accommodate readers with varying technical backgrounds. Complex concepts are broken down into manageable sections, with thorough explanations and practical examples promoting understanding. The hands-on approach through numerous coding exercises further aids retention and learning. This makes the book ideal for anyone interested in data science, regardless of their initial confidence in programming or analytical skills.

Can this book help in preparing for data science job interviews?

Yes, the insights and skills gained from 'Ultimate Data Science Programming in Python' are invaluable for preparing for data science job interviews. The book covers essential topics that employers often prioritize, such as coding in Python, data manipulation, machine learning techniques, and EDA. By working through the exercises and projects, readers can build a solid portfolio of practical skills to showcase at interviews, helping them demonstrate their competence and readiness for data science roles.

What are the benefits of using GUI tools for learning data science?

Using GUI tools in learning data science offers several advantages, notably enhancing interactivity and visual learning. GUI tools provide immediate feedback on data visualizations and manipulations, making it easier to grasp complex concepts. They enable users to explore data in an intuitive manner without deep coding requirements, appealing to those who benefit from visual aids. This approach helps demystify data science, making it more approachable for students and professionals alike.

Where can I buy 'Ultimate Data Science Programming in Python'?

You can purchase 'Ultimate Data Science Programming in Python: Master data science libraries with 300 programs, 2 projects, and EDA GUI tools English Edition' on Ubuy. Ubuy is a reliable online platform offering a range of products, and it provides easy access to this insightful book tailored for both aspiring and experienced data scientists in Brazil.

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Ultimate Data Science Programming in Python: Master data science libraries with 300+ programs, 2 projects, and EDA GUI tools (English Edition)

This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization.

Número do item: 114772826

Ultimate Data Science Programming in Python: Master data science libraries with 300+ programs, 2 projects, and EDA GUI tools (English Edition)

87% of respondents would recommend this to a friend

Número do item: 114772826

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Comprehensive Coverage

Offers 300+ programs and 2 hands-on projects, ensuring deep mastery of data science libraries for learners, from beginners to advanced users.

Practical Learning

Includes real-world applications and EDA GUI tools that facilitate practical learning, enabling users to apply concepts effectively in data science projects.

User-Friendly Format

Designed in an easy-to-follow format, making complex data science concepts accessible and engaging for all levels of expertise, enhancing learning experience.

Detalhes do produto

DescriptionIn today's data-driven world, the ability to extract meaningful insights from vast datasets is crucial for success in various fields. This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization.Discover how to use Python libraries like NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization. This book also covers scientific computing with SciPy and integrates ChatGPT to boost your data science workflow. Designed for data scientists, analysts, and beginners, it offers a practical, hands-on approach to mastering data science fundamentals. With real-world applications and exercises, you will turn raw data into actionable insights, gaining a competitive edge. This book covers everything you need, including open-source libraries, Visual Explorer tools, and ChatGPT, making it a one-stop resource for Python-based data science.Readers will gain confidence after going through this book and we assure you that all the minute details have been taken into consideration while delivering the content. After reading, learning, and practicing from this book, we are sure that all IT professionals, novices, or job seekers will be able to work on data science projects thus proving their mettle.Key Features● Master key Python libraries like NumPy, Pandas, and Seaborn for effective data analysis and visualization.● Understand complex data science concepts through simple explanations and practical examples.● Get hands-on experience with 300+ solved examples to solidify your Python data science skills.What you will learn● Learn to work with popular IDEs like VS Code and Jupyter Notebook for efficient Python development.● Master open-source libraries such as NumPy, SciPy, Matplotlib, and Pandas through advanced, real-world examples.● Utilize automated EDA tools like PyGWalker and AutoViz to simplify complex data analysis.● Create sophisticated visualizations like heatmaps, FacetGrid, and box plots using Matplotlib and Seaborn.● Efficiently handle missing data, outliers, and perform filtering, sorting, grouping, and aggregation using Pandas and Polars.Who this book is forThis book is ideal for diploma, undergraduate, and postgraduate students from engineering and science fields to programming and software professionals. It is also perfect for data science, ML, and AI engineers looking to expand their expertise in cutting-edge technologies.Table of Contents1. Environmental Setup for Using Data Science Libraries in Python2. Exploring Numpy Library for Data Science in Python3. Exploring Array Manipulations in Numpy4. Exploring Scipy Library for Data Science in Python5. Line Plot exploration with Matplotlib Library6. Charting Data With Various Visuals Using Matplotlib7. Exploring Pandas Series for Data Science in Python8. Exploring Pandas Dataframe for Data Science in Python9. Advanced Dataframe Filtering Techniques10. Exploring Polars Library for Data Science in Python11. Exploring Expressions in Polars12. Exploring Seaborn Library for Data Science in Python13. Crafting Seaborn Plots: KDE, Line, Violin and Facets14. Integrating Data Science Libraries with ChatGPT Prompts15. Exploring Automated EDA Libraries for Machine Learning16. Case Study Using Python Data Science Libraries

Publisher	BPB Publications
Publication date	September 25, 2024
Language	English
Print length	556 pages
ISBN-10	9365895669
ISBN-13	978-9365895667
Item Weight	1.95 pounds (880 grams)
Dimensions	7.5 x 1.26 x 9.25 inches (19.1 x 3.2 x 23.5 cm)

Para quem é indicado?

Aspiring Data Scientists
Those looking to build a strong foundation in data science programming and practical application using Python.
Intermediate Programmers
Programmers familiar with Python who want to delve deeper into data science libraries and their functionalities.
Self-learners
Individuals interested in self-paced learning through hands-on projects and extensive example codes provided in the product.

Complete Beginners
Beginners with no programming skills may find the content overwhelming without prior knowledge in Python.

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Extensive library coverage
Hands-on projects included
User-friendly EDA tools
Clear and concise explanations
Great for beginners and advanced

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Some examples may feel repetitive.

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Master essential Python libraries like NumPy, Pandas, and Matplotlib.
Learn data manipulation, analysis, and visualization with hands-on exercises.
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Suitable for beginners, data scientists, and analysts looking to excel.
Includes real-world applications to turn raw data into actionable insights.
Complete resource covering everything needed for Python-based data science.

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Ultimate Data Science Programming in Python: Master data science libraries with 300+ programs, 2 projects, and EDA GUI tools (English Edition)