Practical Statistics for Data Scientists: 50 Essential Concepts
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas,...
Python Data Analysis
Find, manipulate, and analyze your data using the Python 3.5 libraries
Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
An easy-to-follow guide with realistic examples that are frequently used in real-world data
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