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2016 | OriginalPaper | Chapter

2. Python

Author: Thomas Haslwanter

Published in: An Introduction to Statistics with Python

Publisher: Springer International Publishing

Abstract

This chapter is a kick-start into Python. It shows how to install Python under Windows, Linux, or MacOS, and walks step-by-step through documented programming examples. The most important statistics packages for Python are introduced. Tips are given to help avoid some of the problems frequently encountered while learning Python.

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During the writing of this book, the former monolithic IPython was split into two separate projects: Jupyter is providing the front end (the notebook, the qtconsole, and the console), and IPython the computational kernel running the Python commands.

In my current Windows 10 environment, I have to change the path directly by using the command “regedit” to modify the variable “HKEY_CURRENT_USER — Environment”

More help on text-files can be found under http://support.smqueue.com/support/solutions/articles/31751-how-to-create-a-plain-text-file-on-a-mac-computer-for-bulk-uploads.

http://stackoverflow.com/questions/509211/explain-pythons-slice-notation.

https://github.com/thomas-haslwanter/statsintro_python/blob/master/ISP/Code_Quantlets/Utilities.

Harms, D., & McDonald, K. (2010). The quick python book (2nd ed.). Greenwich: Manning Publications Co.

Olson, R. (2012). Statistical analysis made easy in python. http://www.randalolson.com/2012/08/06/statistical-analysis-made-easy-in-python/

Pilon, C. D. (2015). Probabilistic programming and Bayesian methods for hackers. http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/

Scopatz, A., & Huff, K. D. (2015). Effective computation in physics. Sebastopol: O’Reilly Media.

Sheppard, K. (2015). Introduction to python for econometrics, statistics and data analysis. http://www.kevinsheppard.com/images/0/09/Python_introduction.pdf

Wilkinson, G. N., & Rogers, C. E. (1973). Symbolic description of factorial models for analysis of variance. Applied Statistics, 22:, 392–399. CrossRef

Title: Python
Author: Thomas Haslwanter
Publisher: Springer International Publishing
Book: An Introduction to Statistics with Python
Print ISBN: 978-3-319-28315-9

Electronic ISBN: 978-3-319-28316-6

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-319-28316-6_2

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