Python Data Analysis Learn How To Apply Powerful Data Analysis Techniques With Popular Open Source Python Modules(1st Edition)
Authors:
Ivan Idris
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ISBN: 1783553359, 978-1783553358
Book publisher: Packt Publishing
Python Data Analysis Learn How To Apply Powerful Data Analysis Techniques With Popular Open Source Python Modules 1st Edition Summary: Learn how to apply powerful data analysis techniques with popular open source Python modulesAbout This BookLearn how to find, manipulate, and analyze data using PythonPerform advanced, high performance linear algebra and mathematical calculations with clean and efficient Python codeAn easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projectsWho This Book Is ForThis book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.What You Will LearnInstall open source Python modules on various platformsGet to know about the fundamentals of NumPy including arraysManipulate data with pandasRetrieve, process, store, and visualize dataUnderstand signal processing and time-series data analysisWork with relational and NoSQL databasesDiscover more about data modeling and machine learningGet to grips with interoperability and cloud computingIn DetailPython is a multi-paradigm programming language well suited for both object-oriented application development as well as functional design patterns. Python has become the language of choice for data scientists for data analysis, visualization, and machine learning. It will give you velocity and promote high productivity.This book will teach novices about data analysis with Python in the broadest sense possible, covering everything from data retrieval, cleaning, manipulation, visualization, and storage to complex analysis and modeling. It focuses on a plethora of open source Python modules such as NumPy, SciPy, matplotlib, pandas, IPython, Cython, scikit-learn, and NLTK. In later chapters, the book covers topics such as data visualization, signal processing, and time-series analysis, databases, predictive analytics and machine learning. This book will turn you into an ace data analyst in no time.
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