X
Python Data Science Handbook: Essential Tools for
Python Data Science Handbook: Essential Tools for

Python Data Science Handbook: Essential Tools for Working with Data

Product ID : 16048952
4.6 out of 5 stars


Galleon Product ID 16048952
Shipping Weight 2.03 lbs
I think this is wrong?
Model
Manufacturer O'Reilly Media
Shipping Dimension 9.69 x 6.93 x 1.18 inches
I think this is wrong?
-
Save 12%
Before ₱ 6,650
5,869

*Price and Stocks may change without prior notice
*Packaging of actual item may differ from photo shown
  • Electrical items MAY be 110 volts.
  • 7 Day Return Policy
  • All products are genuine and original
  • Cash On Delivery/Cash Upon Pickup Available

Pay with

Python Data Science Handbook: Essential Tools for Features

  • Python Data Science Handbook


About Python Data Science Handbook: Essential Tools For

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 labeled/columnar 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