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Beginning Data Science with Python and Jupyter

You're reading from   Beginning Data Science with Python and Jupyter Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data

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Product type Paperback
Published in Jun 2018
Publisher
ISBN-13 9781789532029
Length 194 pages
Edition 1st Edition
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Author (1):
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Alex Galea Alex Galea
Author Profile Icon Alex Galea
Alex Galea
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Toc

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 and Python language keywords in text are shown as follows: "With the newly created blank Notebook, click in the top cell and type print('hello world')"

Folder names, filenames, file extensions, pathnames, include file names in text are shown as follows: "The header file boost/asio.hpp includes most of the types and functions required for using the Asio library".

A block of code is set as follows:

y = df['MEDV'].copy()
del df['MEDV']
df = pd.concat((y, df), axis=1)

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: "Click on New in the upper-right corner and select a kernel from the drop-down menu."

Important new programming terms are shown in bold. Conceptual terms are shown in italics.

Note

Important additional details about a topic appear like this, as in a sidebar.

Tip

Important notes, tips, and tricks appear like this.

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