Download PDF by Thomas Haslwanter: An Introduction to Statistics with Python: With Applications

By Thomas Haslwanter

ISBN-10: 3319283154

ISBN-13: 9783319283159

ISBN-10: 3319283162

ISBN-13: 9783319283166

This textbook offers an creation to the loose software program Python and its use for statistical info research. It covers universal statistical assessments for non-stop, discrete and specific facts, in addition to linear regression research and subject matters from survival research and Bayesian facts. operating code and knowledge for Python strategies for every try, including easy-to-follow Python examples, should be reproduced through the reader and toughen their speedy knowing of the subject. With fresh advances within the Python atmosphere, Python has develop into a favored language for clinical computing, providing a strong atmosphere for statistical facts research and an engaging substitute to R. The booklet is meant for grasp and PhD scholars, mostly from the lifestyles and scientific sciences, with a uncomplicated wisdom of records. because it additionally presents a few statistics historical past, the ebook can be utilized via a person who desires to practice a statistical information research.

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Additional info for An Introduction to Statistics with Python: With Applications in the Life Sciences

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Know lists, tuples, and dictionaries; also, know about numpy arrays and pandas DataFrames. 6. Use functions a lot, and understand the if __name__=='__main__': construct. 7. append('mydir') 8. If you are using non-ASCII characters, such as the German \"{o}\"{a}\"{u}{\ss} or the French \`{e}\'{e}, you have to let Python know, by adding # -*- coding: utf-8 -*- in the first or second line of your Python module. This has to be done, even if the non-ASCII characters only appear in the comments! This requirement arises from the fact that Python will default to ASCII as standard encoding if no other encoding hints are given.

The handling of DataFrames is somewhat different from the handling of numpy arrays. 5 Pandas: Data Structures for Statistics 37 Finally, sometimes you want to have direct access to the data, not to the DataFrame. values which returns a numpy array. b) Notes on Data Selection While pandas’ DataFrames are similar to numpy arrays, their philosophy is different, and I have wasted a lot of nerves addressing data correctly. Therefore I want to explicitly point out the differences here: numpy pandas handles “rows” first.

The following links are all recommendable sources of information if you are starting with Python: • Python Scientific Lecture Notes If you don’t read anything else, read this! com) • NumPy for Matlab Users Start here if you have Matlab experience. html) • Lectures on scientific computing with Python Great Jupyter Notebooks, from JR Johansson! com/jrjohansson/scientific-python-lectures) • The Python tutorial The official introduction. org/3/tutorial) In addition free Python books are available, for different levels of programming skills: • A Byte of Python A very good book, at the introductory level.

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An Introduction to Statistics with Python: With Applications in the Life Sciences by Thomas Haslwanter

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