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Key benefits

Clean, format, and explore data using graphical and numerical summaries

Leverage the IPython environment to efficiently analyze data with Python

Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data

Description

Python, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning. Ever imagined how to become an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? Well, look no further, this is the book you want! Through this comprehensive guide, you will explore data and present results and conclusions from statistical analysis in a meaningful way. You’ll be able to quickly and accurately perform the hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. You’ll start off by learning about the tools available for data analysis in Python and will then explore the statistical models that are used to identify patterns in data. Gradually, you’ll move on to review statistical inference using Python, Pandas, and SciPy. After that, we’ll focus on performing regression using computational tools and you’ll get to understand the problem of identifying clusters in data in an algorithmic way. Finally, we delve into advanced techniques to quantify cause and effect using Bayesian methods and you’ll discover how to use Python’s tools for supervised machine learning.

What you will learn

* Read, sort, and map various data into Python and Pandas

* Recognise patterns so you can understand and explore data

* Use statistical models to discover patterns in data

* Review classical statistical inference using Python, Pandas, and SciPy

* Detect similarities and differences in data with clustering

* Clean your data to make it useful

* Work in Jupyter Notebook to produce publication ready figures to be included in reports

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

Frequently bought together

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Total NZ$ 266.97

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Mher kazandjian Sep 18, 2016

A book that provides a comprehensive set tools and techniques for real life dataanalysis and lots of examples.Unlike many mainstream books that usually use synthetic data, the examples in thisbook use actual data that is publicly available. The examples and code samplesof the various algorithms and techniques run out of the box requiring minimalsetup.The book starts with a good introduction on statistical distributions followedby modelling techniques to assess the quality and the significance of the models.These are essential tools for any researcher or scientist or developer that wantto make sense of models in academia or industry.The second part of the book is really exciting connecting clustering techniquesto machine learning and time-series analysis that is at the core of big datanowadays.

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Mastering Python Data Analysis: Become an expert at using Python for advanced statistical analysis of data using real-world examples

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