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Practical Data Analysis Using Jupyter Notebook

You're reading from   Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838826031
Length 322 pages
Edition 1st Edition
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Author (1):
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Marc Wintjen Marc Wintjen
Author Profile Icon Marc Wintjen
Marc Wintjen
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Analysis Essentials
2. Fundamentals of Data Analysis FREE CHAPTER 3. Overview of Python and Installing Jupyter Notebook 4. Getting Started with NumPy 5. Creating Your First pandas DataFrame 6. Gathering and Loading Data in Python 7. Section 2: Solutions for Data Discovery
8. Visualizing and Working with Time Series Data 9. Exploring, Cleaning, Refining, and Blending Datasets 10. Understanding Joins, Relationships, and Aggregates 11. Plotting, Visualization, and Storytelling 12. Section 3: Working with Unstructured Big Data
13. Exploring Text Data and Unstructured Data 14. Practical Sentiment Analysis 15. Bringing It All Together 16. Works Cited
17. Other Books You May Enjoy

The shape of the curve

We will now dive into creating visualizations from data using a new library named matplotlib, which was installed when you used Anaconda for the first time. According to the history page from matplotlib.org, this library evolved from MATLAB graphics and was created by John D. Hunter with the philosophy that you should be able to create simple plots with just a few commands, or just one!

Like many of the libraries we've introduced, there is a multitude of features and capabilities available to help you create charts and data visualizations.The matplotlib library has an ecosystem that you can apply to different use cases that nicely compliment the libraries of pandas and numpy.

There are many tutorials and additional resources available to help you learn the library. I have added the necessary links in the Further reading section for your reference.

In this example, we are going to load a CSV file that contains stock price details...

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