Become an expert at using Python for advanced statistical analysis of data using real-world examples
If you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you. Familiarity with the basics of applying Python libraries to data sets is assumed.
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.
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Magnus Vilhelm Persson is a scientist with a passion for Python and open source software usage and development. He obtained his PhD in Physics/Astronomy from Copenhagen University's Centre for Star and Planet Formation (StarPlan) in 2013. Since then he has continued his research in Astronomy at various academic institutes across Europe. In his research he uses various types of data and analysis to gain insights into how stars are formed. He has participated in radio shows about Astronomy, and also organizes workshops and intensive courses about the use of Python for data analysis.
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