j6RfM *Python Data Science Handbook: Essential Tools for Working with Data [PDF/EPub] Book by Jake VanderPlas
1 view
Skip to first unread message
cark...@gmail.com
Dec 22, 2021, 9:05:06 AM12/22/21
to 8t...@googlegroups.com
Rj6RfM1PfV - Download and read Jake VanderPlas's book Python Data Science Handbook: Essential Tools for Working with Data in PDF, EPub, Mobi, Kindle online. Free book Python Data Science Handbook: Essential Tools for Working with Data by Jake VanderPlas.
Click to Continue
Synopsis: 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:includes the for efficient storage and manipulation of dense data arrays in PythonNumPy:ndarrayfeatures the DataFrame for efficient storage and manipulation of labeled/columnar data in PythonPandas:.
Click to Continue
Synopsis: 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:includes the for efficient storage and manipulation of dense data arrays in PythonNumPy:ndarrayfeatures the DataFrame for efficient storage and manipulation of labeled/columnar data in PythonPandas:.
Reply all
Reply to author
Forward
0 new messages