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Python Data Science Handbook: Essential Tools for Working with Data,Used
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For many researchers, Python is a firstclass tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allIPython, NumPy, Pandas, Matplotlib, ScikitLearn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling daytoday issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the musthave reference for scientific computing in Python.With this handbook, youll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python ScikitLearn: for efficient and clean Python implementations of the most important and established machine learning algorithms
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- Q: What is the main focus of the Python Data Science Handbook? A: The Python Data Science Handbook focuses on essential tools for data science, including libraries like IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn, providing a comprehensive guide for manipulating, analyzing, and visualizing data.
- Q: Who is the author of the Python Data Science Handbook? A: The author of the Python Data Science Handbook is Jake VanderPlas, who is known for his contributions to the field of data science and Python programming.
- Q: Is the Python Data Science Handbook suitable for beginners? A: While the Python Data Science Handbook is ideal for those with some familiarity in Python, it serves as a comprehensive reference that can also benefit beginners who are eager to learn the essential tools of data science.
- Q: What type of binding does this book have? A: The Python Data Science Handbook is available in paperback binding, making it durable and easy to handle for both reading and reference.
- Q: How many pages are included in the Python Data Science Handbook? A: The Python Data Science Handbook contains a total of 546 pages, packed with valuable information and tutorials on data science tools.
- Q: When was the Python Data Science Handbook published? A: The Python Data Science Handbook was published on January 3, 2017.
- Q: What topics are covered in the Python Data Science Handbook? A: The book covers a range of topics including data manipulation with Pandas, data visualization with Matplotlib, and machine learning with Scikit-Learn, among others.
- Q: Can this book help with machine learning concepts? A: Yes, the Python Data Science Handbook includes guidance on using Scikit-Learn, which is a popular library for implementing machine learning algorithms in Python.
- Q: Is the Python Data Science Handbook a good reference for scientific computing? A: Absolutely, the Python Data Science Handbook is considered a must-have reference for scientific computing in Python, providing practical insights for working with data.
- Q: What is the condition of the book listed? A: The book is listed in good condition, indicating that it is well-maintained and suitable for use.