Description
Book 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: 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
Read more
Details
The Python Data Science Handbook is the ultimate tool for data researchers and scientists who want to unlock the full potential of Python. Packed with essential tools for working with data, this handbook offers a comprehensive reference for manipulating, transforming, and analyzing data. With its wide range of libraries such as IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and more, you'll have everything you need to gain valuable insights from your data.
Why settle for individual resources when you can have it all? The Python Data Science Handbook brings together all the necessary components of a complete data science stack. Whether you're a working scientist or a data cruncher, this desk reference will be your go-to resource for solving day-to-day data challenges. From data manipulation to visualization and building statistical or machine learning models, this handbook covers it all.
Don't waste precious time searching for disjointed resources. By having the Python Data Science Handbook, you'll save yourself hours of frustration trying to piece together different tools. With IPython and Jupyter providing computational environments, NumPy and Pandas for efficient data storage and manipulation, and Matplotlib for stunning visualizations, you'll be equipped to handle any data analysis task.
Unleash the power of Python for scientific computing with the Python Data Science Handbook. With Scikit-Learn's clean and efficient machine learning implementations, you'll be able to develop accurate models and make informed decisions based on your data. Make this comprehensive reference your must-have tool for scientific computing in Python and take your data analysis skills to the next level.
Discover More Best Sellers in Databases & Big Data
Shop Databases & Big Data
Think Bayes: Bayesian Statistics in Python (O'reilly)
$30.99
Databases & Big Data - Think Bayes: Bayesian Statistics in Python (O'reilly)
$4.97
Databases & Big Data - EXCEL 2023: From Beginner to Expert | The Illustrative Guide to Master All The Essential Functions and Formulas in Just 7 Days With Step-by-Step Tutorials, Practical Examples, Tips & Tricks
Advanced Algorithms and Data Structures
$25.99
Databases & Big Data - Advanced Algorithms and Data Structures
Grokking Algorithms: An illustrated guide for programmers and other curious people
$34.99
Databases & Big Data - Grokking Algorithms: An illustrated guide for programmers and other curious people
Using SQLite: Small. Fast. Reliable. Choose Any Three.
$0.00
Databases & Big Data - Using SQLite: Small. Fast. Reliable. Choose Any Three.
Python in a Nutshell: A Desktop Quick Reference
$45.72
Databases & Big Data - Python in a Nutshell: A Desktop Quick Reference
