June 2016
Beginner to intermediate
284 pages
6h 22m
English
Content preview from Mastering Python Data AnalysisBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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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: "This code has the effect of selecting matplotlib stylesheet mystyle.mplstyle."
A block of code is set as follows:
gss_data = pd.read_stata('data/GSS2012merged_R5.dta',
convert_categoricals=False)
gss_data.head()Any command-line input or output is written as follows:
python -c 'import numpy'
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus ...
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