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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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Tools
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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 2. NumPy Arrays FREE CHAPTER 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

Working with Wakari

The Cloud service on https://wakari.io/ is similar to the PythonAnywhere website. The team behind Wakari has people on board who have actively contributed to SciPy and NumPy in the past. Once we have logged in, we are presented with the Wakari workspace. On the left in this workspace, we have a file browser that can also be used to upload files. On the right, we can open the Bash, Python, or IPython consoles.

You can clearly see the file browser in the following screenshot. Use the file browser to upload the r_demo.py file again.

Working with Wakari

Run the program in a Python 2.7 console. Refer to the following screenshot for the end result:

Working with Wakari

As we can see, the matplotlib show() function causes an exception to be thrown this time.

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