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Key benefits

Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types

Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning

Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books

Description

Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios.

What you will learn

Set up reproducible data analysis

Clean and transform data

Apply advanced statistical analysis

Create attractive data visualizations

Web scrape and work with databases, Hadoop, and Spark

Analyze images and time series data

Mine text and analyze social networks

Use machine learning and evaluate the results

Take advantage of parallelism and concurrency

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

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Total S$ 235.97

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Dimitri Shvorob Oct 31, 2016

The author has kindly made the code in the book publicly available - I will ungratefully advise interested readers to get the code and skip the book. (Python beginners should skip both). "Python Data Analysis Cookbook" is a typical low-quality Packt "book product" - I don't want to call these things "books" - which packages, but does not add much value to, a ragtag but large collection of Python code. The considerable page count should be heavily discounted - first, because a Packt page, ahem, packs less text than a page in a book from a regular publisher; second, because the author supplies a self-contained code sample, with a 2-by-2 plot visualization, for most of his "recipes". (It might take a single line to calculate a correlation coefficient, but the code will take a page, and the large chart will take another). Even so, you get a whole lot of code, doing all sorts of things, from Fourier transforms to manipulating database tables. (And, consistently, plotting - but using the author's own "dalib" Python package. This means that you will have to stick with "dalib" as well). This scattershot approach is a double-edged sword: it is likely that you will find *something* useful, but it is also likely that *most* of the book will be a dead weight. And then you ask how well that useful something is explained, and how easy would it be to find something similar online... A "pass" from me; review the table of contents to make up your mind.

Amazon Verified review

Tseliso Nov 03, 2016

Not as good as one expected.

Python Data Analysis Cookbook: Clean, scrape, analyze, and visualize data with the power of Python!

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