{"product_id":"python-data-science-handbook-essential-tools-for-working-with-data-9781098121228","title":"Python Data Science Handbook: Essential Tools for Working with Data","description":"\u003cp\u003ePython is a first-class tool for many researchers, primarily 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 new edition of \u003ci\u003ePython Data Science Handbook\u003c\/i\u003e do you get them all--IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools. \u003c\/p\u003e\u003cp\u003e Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day 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 must-have reference for scientific computing in Python. \u003c\/p\u003e\u003cp\u003e With this handbook, you'll learn how: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eIPython and Jupyter provide computational environments for scientists using Python \u003c\/li\u003e\n\u003cli\u003eNumPy includes the ndarray for efficient storage and manipulation of dense data arrays \u003c\/li\u003e\n\u003cli\u003ePandas contains the DataFrame for efficient storage and manipulation of labeled\/columnar data \u003c\/li\u003e\n\u003cli\u003eMatplotlib includes capabilities for a flexible range of data visualizations \u003c\/li\u003e\n\u003cli\u003eScikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms \u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eJake VanderPlas is a software engineer at Google Research, working on tools that support data-intensive research. He maintains a technical blog, Pythonic Perambulations, \u003c\/p\u003e\u003cp\u003eto share tutorials and opinions related to statistics, open software, and scientific computing in Python. He creates and develops Python tools for use in data-intensive science, including packages like Scikit-Learn, SciPy, AstroPy, Altair, JAX, and many others. He participates in the broader data science community, developing and presenting talks and tutorials on scientific computing topics at various conferences in the data science world.\u003c\/p\u003e\u003cbr\u003e","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":50608435003666,"sku":"9781098121228","price":57.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_ef5e002a-8d57-49d7-afef-f76b5d47dd01.jpg?v=1732321425","url":"https:\/\/surprise-castle.myshopify.com\/products\/python-data-science-handbook-essential-tools-for-working-with-data-9781098121228","provider":"Surprise Castle","version":"1.0","type":"link"}