Frederick Kaefer, Paul Kaefer
Introduction to Python Programming for Business and Social Science Applications
Frederick Kaefer, Paul Kaefer
Introduction to Python Programming for Business and Social Science Applications
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Introduction to Python Programming for Business and Social Science Applications shows you how to gather and analyze big data sets, and visualize the output, all in one program. Written for those with no programming background, this book will teach you how to use Python for your research and data analysis.
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Introduction to Python Programming for Business and Social Science Applications shows you how to gather and analyze big data sets, and visualize the output, all in one program. Written for those with no programming background, this book will teach you how to use Python for your research and data analysis.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Sage Publications
- Seitenzahl: 392
- Erscheinungstermin: 8. September 2020
- Englisch
- Abmessung: 254mm x 203mm x 18mm
- Gewicht: 816g
- ISBN-13: 9781544377445
- ISBN-10: 1544377444
- Artikelnr.: 58703153
- Verlag: Sage Publications
- Seitenzahl: 392
- Erscheinungstermin: 8. September 2020
- Englisch
- Abmessung: 254mm x 203mm x 18mm
- Gewicht: 816g
- ISBN-13: 9781544377445
- ISBN-10: 1544377444
- Artikelnr.: 58703153
Frederick Kaefer is an Associate Professor of Information Systems at the Loyola University Chicago Quinlan School of Business. After completing a Bachelors degree in Mathematics and Computer Science, he worked as a mainframe programmer for several years before earning an MBA with concentrations in Finance and Information Systems and a PhD in Management Information Systems. Professor Kaefer has taught computer programming and other information systems courses to business students for over 25 years. In addition to his interest in the Python programming language, Professor Kaefer has taught courses including Data Structures using C, and VBA Programming in MS Office.
Preface Figures and Tables in the Text Related to the GSS Data Set Figures and Tables in the Text Related to the Taxi Trips Data Set Python Modules and Packages Acknowledgments About the Authors Chapter 1
Introduction to Python Learning Objectives Introduction Brief Introduction to Python and Programming Setting Up a Python Development Environment Executing Python Code in the IDLE Shell Window Executing Python Code in Files Package Managers Data Sets Used Throughout the Book Chapter Summary Glossary End of Chapter Exercises References Chapter 2
Building Blocks of Programming Learning Objectives Introduction Good Programming Practice Basic Elements of Python Code Python Code Statements Errors Functions Using Modules of Python Code Chapter Summary Glossary End of Chapter Exercises References Chapter 3
Further Foundations of Python Programming Learning Objectives Introduction Compound Data Types Lists String Objects Sequence Operations Tuples Dictionaries Example Using Tuples and Dictionaries Chapter Summary Glossary End of Chapter Exercises References Chapter 4
Control Logic and Loops Learning Objectives Introduction Conditions Conditional Logic Loops Error Handling Chapter Summary Glossary End of Chapter Exercises References Chapter 5
Reading and Writing to Files Using Python Learning Objectives Introduction Data Input/Output: Using files CSV Files Exporting Our Results Working With Database Files Developing an Interactive Application Using a Database Chapter Summary Glossary End of Chapter Exercises Discussion Questions References Chapter 6
Preparing and Working With Data Using Pandas Learning Objectives Introduction NumPy Pandas Data Structures Creating Dummy Variables Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 7
Obtaining Data From the Web Using Python Learning Objectives Introduction HTML: The Language of the Web Using Python to Read From HTML Files Obtaining GSS Data From the Web: A More Complicated Process Ethical Issues: Inappropriate Use of Web Resources Beautiful Soup JSON: Obtaining Well-Structured Data REST API Queries: A Standardized Way to Access Well-Structured Data Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 8
Statistical Calculations Using Python Learning Objectives Introduction Ethical Issues: Considerations When Working With Statistics and Building Models Basic Statistics Using Statistical Modules Pandas Features SciPy Stats Module Statsmodels Module for Multiple Regression Statsmodels Module for Logistic Regression Chapter Summary Glossary End of Chapter Exercises References Chapter 9
Data Visualization Using Python Learning Objectives Introduction Data Visualization Matplotlib: A Python Library to Visualize Your Data Customizing Matplotlib Plots Creating 3D Plots Using Seaborn Package for Statistical Data Visualization Chapter Summary Glossary End of Chapter Exercises References Chapter 10
Machine Learning and Text Mining Learning Objectives Introduction Machine Learning Supervised Learning Unsupervised Learning Using Python for Text Mining Chapter Summary Glossary End of Chapter Exercises References Chapter 11
Developing Graphical User Interfaces With tkinter Learning Objectives Introduction tkinter Background tkinter Widgets tkinter Layout Manager Examples Placing Different Widgets Writing Python Code to Work With tkinter Widgets Example Program Using Three tkinter Windows GUI-Based Database Application Chapter Summary Glossary End of Chapter Exercises References Appendix A
Links to Other Resources Appendix B
Debugging Using IDLE Debug Mode Appendix C
Timing Code Execution Appendix D
Solutions to Stop, Code, and Understand! Exercises
Introduction to Python Learning Objectives Introduction Brief Introduction to Python and Programming Setting Up a Python Development Environment Executing Python Code in the IDLE Shell Window Executing Python Code in Files Package Managers Data Sets Used Throughout the Book Chapter Summary Glossary End of Chapter Exercises References Chapter 2
Building Blocks of Programming Learning Objectives Introduction Good Programming Practice Basic Elements of Python Code Python Code Statements Errors Functions Using Modules of Python Code Chapter Summary Glossary End of Chapter Exercises References Chapter 3
Further Foundations of Python Programming Learning Objectives Introduction Compound Data Types Lists String Objects Sequence Operations Tuples Dictionaries Example Using Tuples and Dictionaries Chapter Summary Glossary End of Chapter Exercises References Chapter 4
Control Logic and Loops Learning Objectives Introduction Conditions Conditional Logic Loops Error Handling Chapter Summary Glossary End of Chapter Exercises References Chapter 5
Reading and Writing to Files Using Python Learning Objectives Introduction Data Input/Output: Using files CSV Files Exporting Our Results Working With Database Files Developing an Interactive Application Using a Database Chapter Summary Glossary End of Chapter Exercises Discussion Questions References Chapter 6
Preparing and Working With Data Using Pandas Learning Objectives Introduction NumPy Pandas Data Structures Creating Dummy Variables Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 7
Obtaining Data From the Web Using Python Learning Objectives Introduction HTML: The Language of the Web Using Python to Read From HTML Files Obtaining GSS Data From the Web: A More Complicated Process Ethical Issues: Inappropriate Use of Web Resources Beautiful Soup JSON: Obtaining Well-Structured Data REST API Queries: A Standardized Way to Access Well-Structured Data Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 8
Statistical Calculations Using Python Learning Objectives Introduction Ethical Issues: Considerations When Working With Statistics and Building Models Basic Statistics Using Statistical Modules Pandas Features SciPy Stats Module Statsmodels Module for Multiple Regression Statsmodels Module for Logistic Regression Chapter Summary Glossary End of Chapter Exercises References Chapter 9
Data Visualization Using Python Learning Objectives Introduction Data Visualization Matplotlib: A Python Library to Visualize Your Data Customizing Matplotlib Plots Creating 3D Plots Using Seaborn Package for Statistical Data Visualization Chapter Summary Glossary End of Chapter Exercises References Chapter 10
Machine Learning and Text Mining Learning Objectives Introduction Machine Learning Supervised Learning Unsupervised Learning Using Python for Text Mining Chapter Summary Glossary End of Chapter Exercises References Chapter 11
Developing Graphical User Interfaces With tkinter Learning Objectives Introduction tkinter Background tkinter Widgets tkinter Layout Manager Examples Placing Different Widgets Writing Python Code to Work With tkinter Widgets Example Program Using Three tkinter Windows GUI-Based Database Application Chapter Summary Glossary End of Chapter Exercises References Appendix A
Links to Other Resources Appendix B
Debugging Using IDLE Debug Mode Appendix C
Timing Code Execution Appendix D
Solutions to Stop, Code, and Understand! Exercises
Preface Figures and Tables in the Text Related to the GSS Data Set Figures and Tables in the Text Related to the Taxi Trips Data Set Python Modules and Packages Acknowledgments About the Authors Chapter 1
Introduction to Python Learning Objectives Introduction Brief Introduction to Python and Programming Setting Up a Python Development Environment Executing Python Code in the IDLE Shell Window Executing Python Code in Files Package Managers Data Sets Used Throughout the Book Chapter Summary Glossary End of Chapter Exercises References Chapter 2
Building Blocks of Programming Learning Objectives Introduction Good Programming Practice Basic Elements of Python Code Python Code Statements Errors Functions Using Modules of Python Code Chapter Summary Glossary End of Chapter Exercises References Chapter 3
Further Foundations of Python Programming Learning Objectives Introduction Compound Data Types Lists String Objects Sequence Operations Tuples Dictionaries Example Using Tuples and Dictionaries Chapter Summary Glossary End of Chapter Exercises References Chapter 4
Control Logic and Loops Learning Objectives Introduction Conditions Conditional Logic Loops Error Handling Chapter Summary Glossary End of Chapter Exercises References Chapter 5
Reading and Writing to Files Using Python Learning Objectives Introduction Data Input/Output: Using files CSV Files Exporting Our Results Working With Database Files Developing an Interactive Application Using a Database Chapter Summary Glossary End of Chapter Exercises Discussion Questions References Chapter 6
Preparing and Working With Data Using Pandas Learning Objectives Introduction NumPy Pandas Data Structures Creating Dummy Variables Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 7
Obtaining Data From the Web Using Python Learning Objectives Introduction HTML: The Language of the Web Using Python to Read From HTML Files Obtaining GSS Data From the Web: A More Complicated Process Ethical Issues: Inappropriate Use of Web Resources Beautiful Soup JSON: Obtaining Well-Structured Data REST API Queries: A Standardized Way to Access Well-Structured Data Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 8
Statistical Calculations Using Python Learning Objectives Introduction Ethical Issues: Considerations When Working With Statistics and Building Models Basic Statistics Using Statistical Modules Pandas Features SciPy Stats Module Statsmodels Module for Multiple Regression Statsmodels Module for Logistic Regression Chapter Summary Glossary End of Chapter Exercises References Chapter 9
Data Visualization Using Python Learning Objectives Introduction Data Visualization Matplotlib: A Python Library to Visualize Your Data Customizing Matplotlib Plots Creating 3D Plots Using Seaborn Package for Statistical Data Visualization Chapter Summary Glossary End of Chapter Exercises References Chapter 10
Machine Learning and Text Mining Learning Objectives Introduction Machine Learning Supervised Learning Unsupervised Learning Using Python for Text Mining Chapter Summary Glossary End of Chapter Exercises References Chapter 11
Developing Graphical User Interfaces With tkinter Learning Objectives Introduction tkinter Background tkinter Widgets tkinter Layout Manager Examples Placing Different Widgets Writing Python Code to Work With tkinter Widgets Example Program Using Three tkinter Windows GUI-Based Database Application Chapter Summary Glossary End of Chapter Exercises References Appendix A
Links to Other Resources Appendix B
Debugging Using IDLE Debug Mode Appendix C
Timing Code Execution Appendix D
Solutions to Stop, Code, and Understand! Exercises
Introduction to Python Learning Objectives Introduction Brief Introduction to Python and Programming Setting Up a Python Development Environment Executing Python Code in the IDLE Shell Window Executing Python Code in Files Package Managers Data Sets Used Throughout the Book Chapter Summary Glossary End of Chapter Exercises References Chapter 2
Building Blocks of Programming Learning Objectives Introduction Good Programming Practice Basic Elements of Python Code Python Code Statements Errors Functions Using Modules of Python Code Chapter Summary Glossary End of Chapter Exercises References Chapter 3
Further Foundations of Python Programming Learning Objectives Introduction Compound Data Types Lists String Objects Sequence Operations Tuples Dictionaries Example Using Tuples and Dictionaries Chapter Summary Glossary End of Chapter Exercises References Chapter 4
Control Logic and Loops Learning Objectives Introduction Conditions Conditional Logic Loops Error Handling Chapter Summary Glossary End of Chapter Exercises References Chapter 5
Reading and Writing to Files Using Python Learning Objectives Introduction Data Input/Output: Using files CSV Files Exporting Our Results Working With Database Files Developing an Interactive Application Using a Database Chapter Summary Glossary End of Chapter Exercises Discussion Questions References Chapter 6
Preparing and Working With Data Using Pandas Learning Objectives Introduction NumPy Pandas Data Structures Creating Dummy Variables Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 7
Obtaining Data From the Web Using Python Learning Objectives Introduction HTML: The Language of the Web Using Python to Read From HTML Files Obtaining GSS Data From the Web: A More Complicated Process Ethical Issues: Inappropriate Use of Web Resources Beautiful Soup JSON: Obtaining Well-Structured Data REST API Queries: A Standardized Way to Access Well-Structured Data Chapter Summary Glossary Discussion Questions End of Chapter Exercises References Chapter 8
Statistical Calculations Using Python Learning Objectives Introduction Ethical Issues: Considerations When Working With Statistics and Building Models Basic Statistics Using Statistical Modules Pandas Features SciPy Stats Module Statsmodels Module for Multiple Regression Statsmodels Module for Logistic Regression Chapter Summary Glossary End of Chapter Exercises References Chapter 9
Data Visualization Using Python Learning Objectives Introduction Data Visualization Matplotlib: A Python Library to Visualize Your Data Customizing Matplotlib Plots Creating 3D Plots Using Seaborn Package for Statistical Data Visualization Chapter Summary Glossary End of Chapter Exercises References Chapter 10
Machine Learning and Text Mining Learning Objectives Introduction Machine Learning Supervised Learning Unsupervised Learning Using Python for Text Mining Chapter Summary Glossary End of Chapter Exercises References Chapter 11
Developing Graphical User Interfaces With tkinter Learning Objectives Introduction tkinter Background tkinter Widgets tkinter Layout Manager Examples Placing Different Widgets Writing Python Code to Work With tkinter Widgets Example Program Using Three tkinter Windows GUI-Based Database Application Chapter Summary Glossary End of Chapter Exercises References Appendix A
Links to Other Resources Appendix B
Debugging Using IDLE Debug Mode Appendix C
Timing Code Execution Appendix D
Solutions to Stop, Code, and Understand! Exercises