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Python Data Science Handbook: Essential Tools For Working With Data By
Jake VanderPlas (Paperback, 2016)

For many researchers Python is a first-class 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 all-IPython NumPy Pandas Matplotlib Scikit-Learn 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 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 With this handbook you'll 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 labeledcolumnar data in Python Matplotlib includes capabilities for a flexible range of data visualizations in Python Scikit-Learn for efficient and clean Python implementations of the most important and established machine learning algorithms
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For many researchers Python is a first-class tool mainly because of its libraries for storing manipulating & 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 all-IPython Num Py Pandas Matplotlib Scikit-Learn & other related tools Working scientists & data crunchers familiar with reading & writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues manipulating transforming & cleaning data; visualizing different types of data; & using data to build statistical or machine learning models Quite simply this is the must-have reference for scientific computing in Python With this handbook you'll learn how to use IPython & Jupyter provide computational environments for data scientists using Python Num Py

Includes::
the ndarray for efficient storage & manipulation of dense data arrays in Python Pandas features the Data Frame for efficient storage & manipulation of labeledcolumnar data in Python Matplotlib

Includes::
capabilities for a flexible range of data visualizations in Python Scikit-Learn for efficient & clean Python implementations of the most important & established machine learning algorithms

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