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Getting Started with Python Data Analysis

You're reading from   Getting Started with Python Data Analysis Learn to use powerful Python libraries for effective data processing and analysis

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785285110
Length 188 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introducing Data Analysis and Libraries FREE CHAPTER 2. NumPy Arrays and Vectorized Computation 3. Data Analysis with Pandas 4. Data Visualization 5. Time Series 6. Interacting with Databases 7. Data Analysis Application Examples 8. Machine Learning Models with scikit-learn Index

Who this book is for

We assume you have been exposed to programming and Python and you want to broaden your horizons and get to know some key libraries in the data analysis field. We think that people with different backgrounds can benefit from this book. If you work in business, finance, in research and development at a lab or university, or if your work contains any data processing or analysis steps and you want know what Python has to offer, then this book can be of help. If you want to get started with basic data processing tasks or time series, then you can find lot of hands-on knowledge in the examples of this book. The strength of this book is its breadth. While we cannot dive very deep into a single package – although we will use Pandas extensively - we hope that we can convey a bigger picture: how the different parts of the Python data ecosystem work and can work together to form one of the most innovative and engaging programming environments.

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