If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you’ll learn the entire process of exploratory data analysis—from wrangling data and generating statistics to identifying patterns and testing hypotheses.
Whether you’re a data scientist, software engineer, or data enthusiast, you’ll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You’ll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.
Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks
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ASIN : B0F3VD2567
Publisher : O’Reilly Media
Accessibility : Learn more
Publication date : April 4, 2025
Edition : 3rd
Language : English
File size : 9.1 MB
Simultaneous device usage : Unlimited
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 506 pages
ISBN-13 : 978-1098190224
Page Flip : Enabled
Best Sellers Rank: #900,470 in Kindle Store (See Top 100 in Kindle Store) #65 in Mathematical & Statistical #170 in Data Modeling & Design (Kindle Store) #186 in Data Modeling & Design (Books)