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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Plot.ly


Plot.ly is a website currently in the beta stage, which provides online data visualization tools and a related Python library to be used on a user's machine. We can import and analyze data via the web interface or work entirely in a local environment and publish the end result on the Plot.ly website. Plots can be easily shared on the website within a team, allowing for collaboration, which is really the point of the website in the first place. In this section, we will give an example of how to plot a box plot with the Python API.

A box plot is a special way of visualizing a dataset using quartiles. If we split a sorted dataset into four equal parts, the first quartile will be the largest value of the part with the smallest numbers. The second quartile will be the value in the middle of the dataset, which is also called the median. The third quartile will be the value in the middle between the median and the highest value. The bottom and the top of the box plot are formed by the first...

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