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Jupyter for Data Science

You're reading from   Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781785880070
Length 242 pages
Edition 1st Edition
Languages
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (11) Chapters Close

Preface 1. Jupyter and Data Science FREE CHAPTER 2. Working with Analytical Data on Jupyter 3. Data Visualization and Prediction 4. Data Mining and SQL Queries 5. R with Jupyter 6. Data Wrangling 7. Jupyter Dashboards 8. Statistical Modeling 9. Machine Learning Using Jupyter 10. Optimizing Jupyter Notebooks

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning. Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "Similarly, the preceding describe statement gives us some quick statistics on the data frame."

A block of code is set as follows:

plt.xlabel("Actual Price")
plt.ylabel("Predicted Price")
plt.title("Actual Price vs Predicted Price")

New terms and important words are shown in bold.

Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "The Running tab lists the notebooks that have been started."

Warnings or important notes appear like this.
Tips and tricks appear like this.
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