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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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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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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. The Pandas Primer 4. Statistics and Linear Algebra 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

Plot.ly


Plot.ly is Software as a Service (SaaS) cloud service for online data visualization tools. Plot.ly provides a related Python library to be used with python 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...

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