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
Numéro d'article: 52380517

Python for Data Science: A Hands-On Introduction

Numéro d'article: 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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Ce qui se démarque

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.

Détails du produit

Shop Python for Data Science: A Hands-On Introduction online at a best price in Mauritius. 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.
Publisher No Starch Press
Publication date August 2, 2022
Language English
Print length 240 pages
ISBN-10 1718502206
ISBN-13 978-1718502208
Item Weight 15.2 ounces (430.92 grams)
Dimensions 7.05 x 0.71 x 9.25 inches (17.9 x 1.8 x 23.5 cm)

À qui est-ce destiné ?

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.

DESCRIPTION DU PRODUIT

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Questions et réponses des clients

  • question: What is Python?

    répondre: Python is an interpreted, high-level, general-purpose programming language.
  • question: Is Python good for data science?

    répondre: Yes, Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds.
  • question: What are some real-world data applications covered?

    répondre: Real-world data applications include using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.

Data Mining Editorial Review

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Avantages

  • Effectively reduces wrinkles and fine lines
  • Pleasant and mild scent
  • Suitable for sensitive skin
  • Visible results within a few weeks
  • Lightweight formula, non-greasy

Les inconvénients

  • Some users may prefer a more hydrating formula

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