Getting Started With Python Data Analysis [Paperback]

Learn to use powerful Python libraries for effective data processing and analysis

About This Book

• Learn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and Matplotlib
• Create, manipulate, and analyze your data to extract useful information to optimize your system
• A hands-on guide to help you learn data analysis using Python

Who This Book Is For

If you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.

What You Will Learn

• Understand the importance of data analysis and get familiar with its processing steps
• Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis
• Create effective visualizations to present your data using Matplotlib
• Process and analyze data using the time series capabilities of Pandas
• Interact with different kind of database systems, such as file, disk format, Mongo, and Redis
• Apply the supported Python package to data analysis applications through examples
• Explore predictive analytics and machine learning algorithms using Scikit-learn, a Python library

In Detail

Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It's often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis.

With this book, we will get you started with Python data analysis and show you what its advantages are.

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