Statistics and Data Visualisation with Python

554 Pages·14.312 MB·english

by  Jesús Rogel-Salazar

Statistics and Data
Visualisation with Python
This book is intended to serve as a bridge in statistics for graduates and business practitioners interested
in using their skills in the area of data science and analytics as well as statistical analysis in general. On the
one hand, the book is intended to be a refresher for readers who have taken some courses in statistics, but
who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable
for readers interested in the subject as a first encounter with statistical work in Python. Statistics and
Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the
reader to understand the ideas behind inferential statistics and begin to formulate hypotheses that form
the foundations for the applications and algorithms in statistical analysis, business analytics, machine
learning, and applied machine learning. This book begins with the basics of programming in Python and
data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are use-
ful in many modern applications.
Chapman & Hall/CRC
The Python Series
About the Series
Python has been ranked as the most popular programming language, and it is widely used in education and industry.
This book series will offer a wide range of books on Python for students and professionals. Titles in the series will
help users learn the language at an introductory and advanced level, and explore its many applications in data sci-
ence, AI, and machine learning. Series titles can also be supplemented with Jupyter notebooks.
Image Processing and Acquisition using Python, Second Edition
Ravishankar Chityala, Sridevi Pudipeddi
Python Packages
Tomas Beuzen and Tiffany-Anne Timbers
Statistics and Data Visualisation with Python
Jesús Rogel-Salazar
For more information about this series please visit: https://www.crcpress.com/Chapman--
HallCRC/book-series/PYTH
Statistics and Data
Visualisation with Python
Jesús Rogel-Salazar
First edition published 2023
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742
and by CRC Press
4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 Taylor & Francis Group, LLC
Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume respon-
sibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the
copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this
form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify
in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any
form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and
recording, or in any information storage or retrieval system, without written permission from the publishers.
For permission to photocopy or use material electronically from this work, access www. copyright.com
or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. For works that
are not available on CCC please contact [e-mail]
Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification
and explanation without intent to infringe.
Library of Congress Cataloging-in-Publication Data
Names: Rogel-Salazar, Jesus, author.
Title: Statistics and data visualisation with Python / Dr. Jesús
Rogel-Salazar.
Description: First edition. | Boca Raton, FL : CRC Press, 2023. | Series:
Chapman & Hall/CRC Press the python series | Includes bibliographical
references and index. | Identifiers: LCCN 2022026521 (print) | LCCN 2022026522 (ebook) | ISBN
9780367749361 (hbk) | ISBN 9780367744519 (pbk) | ISBN 9781003160359
(ebk)
Subjects: LCSH: Mathematical statistics--Data processing. | Python
(Computer program language) | Information visualization.
Classification: LCC QA276.45.P98 R64 2023 (print) | LCC QA276.45.P98
(ebook) | DDC 519.50285/5133--dc23/eng20221026
LC record available at https://lccn.loc.gov/2022026521
LC ebook record available at https://lccn.loc.gov/2022026522
ISBN: 978-0-367-74936-1 (hbk)
ISBN: 978-0-367-74451-9 (pbk)
ISBN: 978-1-003-16035-9 (ebk)
DOI: 10.1201/9781003160359
Typeset in URWPalladioL-Roman
by KnowledgeWorks Global Ltd.
Publisher’s note: This book has been prepared from camera-ready copy provided by the author.
To Luceli, Rosario and Gabriela
Thanks and lots of love!
Taylor & Francis
Taylor & Francis Group
http://taylorandfrancis.com
Contents
1
1 Data, Stats and Stories – An Introduction
2
1.1 From Small to Big Data
10
1.2 Numbers, Facts and Stats
14
1.3 A Sampled History of Statistics
22
1.4 Statistics Today
25
1.5 Asking Questions and Getting Answers
30
1.6 Presenting Answers Visually
33
2 Python Programming Primer
35
2.1 Talking to Python
2.1.1 Scripting and Interacting 38
2.1.2 Jupyter Notebook 41
42
2.2 Starting Up with Python
2.2.1 Types in Python 43
viii j. rogel-salazar
2.2.2 Numbers: Integers and Floats 43
2.2.3 Strings 46
2.2.4 Complex Numbers 49
51
2.3 Collections in Python
2.3.1 Lists 52
2.3.2 List Comprehension 60
2.3.3 Tuples 61
2.3.4 Dictionaries 66
2.3.5 Sets 72
80
2.4 The Beginning of Wisdom: Logic & Control Flow
2.4.1 Booleans and Logical Operators 80
2.4.2 Conditional Statements 82
2.4.3 While Loop 85
2.4.4 For Loop 87
89
2.5 Functions
94
2.6 Scripts and Modules
3 Snakes, Bears & Other Numerical Beasts: NumPy, SciPy & pandas
99
100
3.1 Numerical Python – NumPy
3.1.1 Matrices and Vectors 101
3.1.2 N-Dimensional Arrays 102
statistics and data visualisation with python ix
3.1.3 N-Dimensional Matrices 104
3.1.4 Indexing and Slicing 107
3.1.5 Descriptive Statistics 109
112
3.2 Scientific Python – SciPy
3.2.1 Matrix Algebra 114
3.2.2 Numerical Integration 116
3.2.3 Numerical Optimisation 117
3.2.4 Statistics 118
121
3.3 Panel Data = pandas
3.3.1 Series and Dataframes 122
3.3.2 Data Exploration with pandas 124
3.3.3 Pandas Data Types 125
3.3.4 Data Manipulation with pandas 126
3.3.5 Loading Data to pandas 130
3.3.6 Data Grouping 136
141
4 The Measure of All Things – Statistics
144
4.1 Descriptive Statistics
145
4.2 Measures of Central Tendency and Dispersion
146
4.3 Central Tendency
4.3.1 Mode 147
4.3.2 Median 150