Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
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Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
Python for Data Science: A Hands-On Introduction
Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities.
Python for Data Science: A Hands-On Introduction
Artikelnr.: 52380517

Python for Data Science: A Hands-On Introduction

Artikelnr.: 52380517

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Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities.
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Besondere Merkmale

Practical Learning
Engages users with hands-on projects that reinforce data science concepts, allowing learners to apply Python in real-world scenarios effectively.
Comprehensive Coverage
Covers essential data science tools and libraries, ensuring a strong foundational understanding for beginners while addressing common user challenges.
User-Friendly Format
Designed for easy navigation and understanding, making complex topics accessible and enjoyable for readers with varying experience levels.

Produktdetails

Shop Python for Data Science: A Hands-On Introduction online at a best price in Germany. 1718502206
  • A hands-on, real-world introduction to data analysis with the Python programming language, loaded with wide-ranging examples.Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds. Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities. You’ll learn how to write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques for use cases in business management, marketing, and decision support.You will discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.
Verleger No Starch Press
VeröffentlichungsdatumAugust 2, 2022
Sprache Englisch
Drucklänge 240 pages
ISBN-10 1718502206
ISBN-13 978-1718502208
Artikelgewicht15.2 ounces (430.92 grams)
Abmessungen7.05 x 0.71 x 9.25 inches (17.9 x 1.8 x 23.5 cm)

Für wen ist das Produkt geeignet?

Suitable For
  • Beginners in Python

    Ideal for newcomers to programming who want to learn Python while focusing on data science applications.

  • Data Science Enthusiasts

    Perfect for individuals interested in data science who wish to gain practical experience with real-world datasets.

  • Professionals Upskilling

    Great for professionals looking to enhance their skill set in data analysis and Python programming for career advancement.

Not Suitable For
  • Experienced Programmers

    Not suitable for seasoned programmers who may find the content too basic and lacking in advanced topics.

  • Advanced Data Scientists

    May not meet the needs of data scientists seeking in-depth methodologies and complex analytical techniques.

  • Theory-Focused Learners

    Less ideal for those who prefer theoretical knowledge over hands-on experience and practical application.

PRODUKTBESCHREIBUNG

Haben Sie eine Frage? Mit uns chatten

Kunden Fragen und Antworten

  • Frage: What is 'Python for Data Science: A Hands-On Introduction' about?

    Antworten: 'Python for Data Science: A Hands-On Introduction' is an educational resource designed to teach the fundamentals of Python programming specifically for data science applications. It covers essential topics such as data manipulation, analysis, and visualization using practical examples.
    Kategorien: overview
    Confidence: Mittel
  • Frage: What do I need to get started with this book?

    Antworten: To get started with 'Python for Data Science: A Hands-On Introduction', you will need a basic understanding of programming concepts and access to a computer with Python installed. Familiarity with data science concepts can be beneficial but is not mandatory.
    Kategorien: setup
    Confidence: Mittel
  • Frage: What are the key topics covered in this book?

    Antworten: The book covers key topics such as data analysis libraries (like Pandas and NumPy), data visualization techniques with Matplotlib and Seaborn, and an introduction to machine learning principles. Each topic is supported with hands-on exercises.
    Kategorien: usage
    Confidence: Mittel
  • Frage: What are the prerequisites for this book?

    Antworten: While 'Python for Data Science: A Hands-On Introduction' primarily targets beginners, some familiarity with basic programming and statistics may enhance understanding. However, the book is structured to build knowledge from the ground up.
    Kategorien: setup
    Confidence: Mittel
  • Frage: Is this book suitable for beginners?

    Antworten: Yes, this book is designed for beginners who want to learn Python and its application in data science. It provides step-by-step guidance and practical tasks to help readers build their skills.
    Kategorien: overview
    Confidence: high
  • Frage: What kind of projects are included in the book?

    Antworten: The book includes practical projects that range from simple data analysis tasks to more complex data visualization and machine learning applications, allowing readers to apply what they've learned in real-world scenarios.
    Kategorien: usage
    Confidence: Mittel
  • Frage: What tools or software do I need while using this book?

    Antworten: Readers should have Python installed on their computer, along with libraries such as Pandas, NumPy, Matplotlib, and Seaborn. Instructions for setup are typically provided within the book.
    Kategorien: setup
    Confidence: Mittel
  • Frage: How is this book structured?

    Antworten: The book is structured into chapters that cover distinct topics in Python programming and data science methodologies, with each chapter containing theoretical explanations followed by hands-on exercises to reinforce learning.
    Kategorien: overview
    Confidence: Mittel
  • Frage: Can I find online resources to supplement this book?

    Antworten: Yes, many readers complement their learning with online resources such as coding videos, interactive coding platforms, and forums related to Python and data science.
    Kategorien: other
    Confidence: Mittel
  • Frage: Is there an accompanying workbook or online support for this book?

    Antworten: Typically, educational books may have supplementary online resources or workbooks. It is advisable to check the publisher's website or the book's official page for more details.
    Kategorien: Zubehör
    Confidence: low
  • Frage: What if I encounter issues while learning from this book?

    Antworten: If you encounter issues while learning, consider joining online forums, engaging with study groups, or seeking additional help through tutorials or Q&A platforms related to Python and data science.
    Kategorien: troubleshooting
    Confidence: Mittel
  • Frage: What is the release date of 'Python for Data Science: A Hands-On Introduction'?

    Antworten: The release date can vary based on the edition you are referring to. It's best to check online retailers or the publisher's website for specific release information.
    Kategorien: other
    Confidence: Mittel
  • Frage: Are there multiple editions of this book available?

    Antworten: Yes, there may be multiple editions of 'Python for Data Science: A Hands-On Introduction'. Each edition can differ in terms of updated content and additional resources, so it's advisable to check for the latest version.
    Kategorien: other
    Confidence: Mittel
  • Frage: What is the target audience for this book?

    Antworten: The target audience includes aspiring data scientists, students, and professionals looking to enhance their programming skills in Python for data analysis and visualization.
    Kategorien: overview
    Confidence: high
  • Frage: Can I return the book if I'm not satisfied?

    Antworten: Return policies may vary by retailer, but in general, most books can be returned within a specified period if they are in new condition. Always check the return policy of the store where you purchased it.
    Kategorien: returns
    Confidence: Mittel

Data Mining Editorial Review

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  • Effectively reduces wrinkles and fine lines
  • Pleasant and mild scent
  • Geeignet für empfindliche Haut
  • Visible results within a few weeks
  • Lightweight formula, non-greasy

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€ 50

€ 72

Bestellen Sie jetzt und erhalten Sie es am Monday, Juni 29

QTY:

Nur noch 5 Artikel auf Lager.
Gesicherte TransaktionGesicherte Transaktion

Ubuy ist bestrebt, Ihre Sicherheit und Privatsphäre zu schützen. Unser fortschrittliches Zahlungssicherheitssystem gewährleistet Vertraulichkeit, indem Ihre Daten während der Übertragung mit AES (Advanced Encryption Standards) und SSL (Secure Socket Layer) Protokollen verschlüsselt werden. Ihre Zahlungsdaten sind 100% sicher, da wir Ihre Zahlungsdaten nicht an Drittanbieter weitergeben.

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Merkmale und Vorteile

  • Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds.
  • Write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques
  • Discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science
  • Load data in various formats, streamline, group, and aggregate data sets, and create charts, maps, and visualizations
  • Real-world data applications including Taxi service, market basket analysis, and machine learning to predict stock prices