فهرست مطالب

• Cover Page
• Title Page
• Copyright Page
• Dedication
• About the Author
• About the Technical Reviewer
• BRIEF CONTENTS
• CONTENTS IN DETAIL
• ACKNOWLEDGMENTS
• INTRODUCTION
• PART I: SETTING UP YOUR SCIENTIFIC CODING ENVIRONMENT
• Chapter 1. INSTALLING AND LAUNCHING ANACONDA
• About Anaconda
• Installing Anaconda on Windows
• Installing Anaconda on macOS
• Installing Anaconda on Linux
• Getting to Know Anaconda Navigator
• Summary
• Chapter 2. KEEPING ORGANIZED WITH CONDA ENVIRONMENTS
• Understanding Conda Environments
• Working with Conda Environments Using Navigator
• Working with Conda Environments Using the Command Line Interface
• Summary
• Chapter 3. SIMPLE SCRIPTING IN THE JUPYTER QT CONSOLE
• Installing seaborn
• Installing and Launching the Jupyter Qt Console Using Navigator
• Installing and Launching the Jupyter Qt Console Using the CLI
• The Qt Console Controls
• Summary
• Chapter 4. SERIOUS SCRIPTING WITH SPYDER
• Installing and Launching Spyder with Anaconda Navigator
• Installing and Launching Spyder Using the CLI
• Launching Spyder from the Start Menu
• Configuring the Spyder Interface
• Using Spyder with Environments and Packages
• Using Project Files and Folders
• The Help Pane
• The IPython Console
• The Editor Pane
• The Code Analysis Pane
• The Variable Explorer Pane
• The Profiler Pane
• The Debugger Pane
• Summary
• Chapter 5. JUPYTER NOTEBOOK: AN INTERACTIVE JOURNAL FOR COMPUTATIONAL RESEARCH
• Installing Jupyter Notebook
• Your First Jupyter Notebook
• Getting Help
• Using Notebook Extensions
• Working with Widgets
• Sharing Notebooks
• Turning Notebooks into Slideshows
• Summary
• Chapter 6. JUPYTERLAB: YOUR CENTER FOR SCIENCE
• When to Use JupyterLab Instead of Notebook?
• Installing JupyterLab
• Building a 3D Astronomical Simulation
• Taking Advantage of the JupyterLab Interface
• Using the Text Editor
• Using JupyterLab Extensions
• Sharing
• Summary
• PART II: A PYTHON PRIMER
• Chapter 7. INTEGERS, FLOATS, AND STRINGS
• Mathematical Expressions
• Error Messages
• Data Types
• Summary
• Chapter 8. VARIABLES
• Variables Have Identities
• Assigning Variables
• Naming Variables
• Getting User Input
• Using Comparison Operators
• Summary
• Chapter 9. THE CONTAINER DATA TYPES
• Tuples
• Lists
• Sets
• Dictionaries
• Summary
• Chapter 10. FLOW CONTROL
• The if Statement
• Loops
• Handling Exceptions
• Tracing Execution with Logging
• Summary
• Chapter 11. FUNCTIONS AND MODULES
• Defining Functions
• Functions and the Flow of Execution
• Advanced Function Topics
• Modules
• Summary
• Chapter 12. FILES AND FOLDERS
• Creating a New Spyder Project
• Working with Directory Paths
• Working with Text Files
• Working with Complex Data
• Summary
• Chapter 13. OBJECT-ORIENTED PROGRAMMING
• When to Use OOP
• Creating a New Spyder Project
• Defining the Frigate Class
• Defining a Guided-Missile Frigate Class Using Inheritance
• Objects Within Objects: Defining the Fleet Class
• Reducing Code Redundancy with Dataclasses
• Making a Class Module
• Summary
• Chapter 14. DOCUMENTING YOUR WORK
• Comments
• Docstrings
• Summary
• PART III: THE ANACONDA ECOSYSTEM
• Chapter 15. THE SCIENTIFIC LIBRARIES
• The SciPy Stack
• A General Machine Learning Library: scikit-learn
• The Deep Learning Frameworks
• The Computer Vision Libraries
• The Natural Language Processing Libraries
• The Helper Libraries
• Summary
• Chapter 16. THE INFOVIS, SCIVIS, AND DASHBOARDING LIBRARIES
• InfoVis and SciVis Libraries
• Dashboards
• Choosing a Plotting Library
• Summary
• Chapter 17. THE GEOVIS LIBRARIES
• The Geospatial Libraries
• Choosing a GeoVis Library
• Summary
• PART IV: THE ESSENTIAL LIBRARIES
• Chapter 18. NUMPY: NUMERICAL PYTHON
• Introducing the Array
• Manipulating Arrays
• Doing Math Using Arrays
• Reading and Writing Array Data
• Summary
• Chapter 19. DEMYSTIFYING MATPLOTLIB
• Anatomy of a Plot
• The pyplot and Object-Oriented Approaches
• Using the pyplot Approach
• Using the Object-Oriented Style
• Styling Plots
• Summary
• Chapter 20. PANDAS, SEABORN, AND SCIKIT-LEARN
• Introducing the pandas Series and DataFrame
• The Palmer Penguins Project
• Summary
• Chapter 21. MANAGING DATES AND TIMES WITH PYTHON AND PANDAS
• Python datetime Module
• Time Series and Date Functionality with pandas
• Summary
• APPENDIX. ANSWERS TO THE “TEST YOUR KNOWLEDGE” CHALLENGES
• INDEX