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Foundations for Analytics with Python
If you’re like many of Excel’s 750 million users, you want to do more with your data—like repeating similar analyses over hundreds of files, or combining data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale the processing and analysis of data in... | | Python Data Analysis
Key Features
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Find, manipulate, and analyze your data using the Python 3.5 libraries
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Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
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An easy-to-follow guide with realistic examples that are frequently used in real-world data
... | | 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,... |
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| | | | Python Data Analysis Cookbook
Key Features
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Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types
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Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning
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Authored by Ivan Idris, expert in python programming and proud
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Python Data Science Handbook: Essential Tools for Working with Data
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,... | | Python for Data Mining Quick Syntax Reference
?Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.
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