Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python’s Scientific Libraries

Title Page
Copyright Page
Dedication
About the Author
About the Technical Reviewer
BRIEF CONTENTS
CONTENTS IN DETAIL
ACKNOWLEDGMENTS
INTRODUCTION
	Why Python?
	Navigating This Book
		Part I: Setting Up Your Scientific Coding Environment
		Part II: A Python Primer
		Part III: The Anaconda Ecosystem
		Part IV: The Essential Libraries
		Appendix
	Updates and Errata
	Leaving Reviews
PART I: SETTING UP YOUR SCIENTIFIC CODING ENVIRONMENT
1 INSTALLING AND LAUNCHING ANACONDA
	About Anaconda
	Installing Anaconda on Windows
	Installing Anaconda on macOS
	Installing Anaconda on Linux
	Getting to Know Anaconda Navigator
		Launching Navigator
		The Home Tab
		The Environments Tab
		The Learning Tab
		The Community Tab
		File Menu
	Summary
2 KEEPING ORGANIZED WITH CONDA ENVIRONMENTS
	Understanding Conda Environments
	Working with Conda Environments Using Navigator
		Launching Navigator
		Creating a New Environment
		Managing Packages
		Duplicating Environments
		Backing Up Environments
		Removing Environments
	Working with Conda Environments Using the Command Line Interface
		Launching the Command Line Interface
		Creating a New Environment
		Specifying an Environment’s Location
		Managing Packages
		Duplicating and Sharing Environments
		Restoring Environments
		Removing Environments
		Cleaning the Package Cache
	Summary
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
		Choosing a Syntax Style
		Using Keyboard Shortcuts
		Using Tabs and Kernels
		Printing and Saving
		Multiline Editing
	Summary
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
		The Naive Approach
		The Modular Approach
	Using Project Files and Folders
		Creating a Project in a New Directory
		Creating a Project in an Existing Directory
		Using the Project Pane
	The Help Pane
	The IPython Console
		Using the Console for Output and Plotting
		Using Kernels with the Console
		Clearing the Namespace
		The History Pane
		Special Consoles
	The Editor Pane
		Writing a Program Using the Editor
		Defining Code Cells
		Setting the Run Configuration
		Autocompleting Text
	The Code Analysis Pane
	The Variable Explorer Pane
	The Profiler Pane
	The Debugger Pane
	Summary
5 JUPYTER NOTEBOOK: AN INTERACTIVE JOURNAL FOR COMPUTATIONAL RESEARCH
	Installing Jupyter Notebook
		The Naive Approach
		The Modular Approach
	Your First Jupyter Notebook
		Creating Dedicated Project Folders
		Navigating the Notebook Dashboard and User Interface
		Naming a Notebook
		Adding Text with a Markdown Cell
		Adding Code and Making Plots with a Code Cell
		Working with Output Cells
		Adding an Image with a Markdown Cell
		Saving the Notebook
		Closing the Notebook
	Getting Help
		Keyboard Shortcuts
		The Command Palette
	Using Notebook Extensions
		Installing Extensions
		Enabling Extensions
	Working with Widgets
		Installing ipywidgets
		Creating Widgets with Interact
		Creating Widgets with Interactive
		Manually Creating Widgets
		Handling Events
		Customizing Widgets
		Embedding Widgets in Other Formats
	Sharing Notebooks
		Checking and Running Notebooks with the Kernel Menu
		Downloading Notebooks
		Sharing Notebooks via GitHub and Gist
		Sharing Notebooks via Jupyter Notebook Viewer
		Sharing Notebooks via Binder
		Other Sharing Options
		Trusting Notebooks
	Turning Notebooks into Slideshows
		Installing the RISE Extension
		Creating a Slideshow
		Using Speaker Notes
	Summary
6 JUPYTERLAB: YOUR CENTER FOR SCIENCE
	When to Use JupyterLab Instead of Notebook?
	Installing JupyterLab
		The Naive Approach
		The Modular Approach
	Building a 3D Astronomical Simulation
		Using Dedicated Project Folders
		The JupyterLab Interface
		The Menu Bar
		The Left Sidebar
		Creating a New Notebook
		Naming the Notebook
		Using Markdown Cells
		Adding Code and Making Plots
		Adding a Console
		Displaying an Image File
		Exploring the Simulation
		Opening Multiple Notebooks
		Saving the Workspace
		Clearing the Workspace
		Closing the Workspace
	Taking Advantage of the JupyterLab Interface
		Creating Synchronized Views
		Copying Cells Between Notebooks
		Staying Focused by Using Single Document Mode
	Using the Text Editor
		Running a Script in a Terminal
		Running a Script in a Notebook
		Simultaneously Writing and Documenting Code
	Using JupyterLab Extensions
		Installing and Managing Extensions with the Extension Manager
		Installing and Managing Extensions Using the CLI
		Installing ipywidgets for JupyterLab
		Creating Custom Extensions
	Sharing
	Summary
PART II: A PYTHON PRIMER
7 INTEGERS, FLOATS, AND STRINGS
	Mathematical Expressions
		Mathematical Operators
		The Assignment Operator
		Augmented Assignment Operators
		Precedence
		The math Module
	Error Messages
	Data Types
		Accessing the Data Type
		Integers
		Floats
		Strings
	Summary
8 VARIABLES
	Variables Have Identities
	Assigning Variables
		Using Expressions
		Operator Overloading
		Using Functions
		Chained Assignment and Internment
		Using f-Strings
	Naming Variables
		Reserved Keywords
		Variables Are Case Sensitive
		Best Practices for Naming Variables
		Managing Dynamic Typing Issues
		Handling Insignificant Variables
	Getting User Input
	Using Comparison Operators
	Summary
9 THE CONTAINER DATA TYPES
	Tuples
		Creating Tuples
		Converting Other Types to Tuples
		Working with Tuples
	Lists
		Creating Lists
		Working with Lists
	Sets
		Creating Sets
		Working with Sets
		Creating Frozensets
	Dictionaries
		Creating Dictionaries
		Combining Two Sequences into a Dictionary
		Creating Empty Dictionaries and Values
		Working with Dictionaries
	Summary
10 FLOW CONTROL
	The if Statement
		Working with Code Blocks
		Using the else and elif Clauses
		Using Ternary Expressions
		Using Boolean Operators
	Loops
		The while Statement
		The for Statement
		Loop Control Statements
		Replacing Loops with Comprehensions
	Handling Exceptions
		Using try and except
		Forcing Exceptions with the raise Keyword
		Ignoring Errors
	Tracing Execution with Logging
	Summary
11 FUNCTIONS AND MODULES
	Defining Functions
		Using Parameters and Arguments
		Positional and Keyword Arguments
		Using Default Values
		Returning Values
		Naming Functions
		Built-in Functions
	Functions and the Flow of Execution
		Using Namespaces and Scopes
		Using Global Variables
		Using a main() Function
	Advanced Function Topics
		Recursion
		Designing Functions
		Lambda Functions
		Generators
	Modules
		Importing Modules
		Inspecting Modules
		Writing Your Own Modules
		Naming Modules
		Writing Modules That Work in Stand-Alone Mode
		Built-in Modules
	Summary
12 FILES AND FOLDERS
	Creating a New Spyder Project
	Working with Directory Paths
		The Operating System Module
		Absolute vs. Relative Paths
		The pathlib Module
		The Shell Utilities Module
	Working with Text Files
		Reading a Text File
		Closing Files Using the with Statement
		Writing to a Text File
		Reading and Writing Text Files Using pathlib
	Working with Complex Data
		Pickling Data
		Shelving Pickled Data
		Storing Data with JSON
		Catching Exceptions When Opening Files
		Other Storage Solutions
	Summary
13 OBJECT-ORIENTED PROGRAMMING
	When to Use OOP
	Creating a New Spyder Project
	Defining the Frigate Class
		Defining Instance Methods
		Instantiating Objects and Calling Instance Methods
	Defining a Guided-Missile Frigate Class Using Inheritance
		Instantiating a New Guided-Missile Frigate Object
		Using the super() Function for Inheritance
	Objects Within Objects: Defining the Fleet Class
	Reducing Code Redundancy with Dataclasses
		Using Decorators
		Defining the Ship Class
		Identifying Friend or Foe with Fields and Post-Init Processing
		Optimizing Dataclasses with __slots__
	Making a Class Module
	Summary
14 DOCUMENTING YOUR WORK
	Comments
		Single-Line Comments
		Multiline Comments
		Inline Comments
		Commenting-Out Code
	Docstrings
		Documenting Modules
		Documenting Classes
		Documenting Functions and Methods
		Keeping Docstrings Up to Date with doctest
		Checking Docstrings in the Spyder Code Analysis Pane
	Summary
PART III: THE ANACONDA ECOSYSTEM
15 THE SCIENTIFIC LIBRARIES
	The SciPy Stack
		NumPy
		SciPy
		SymPy
		pandas
	A General Machine Learning Library: scikit-learn
	The Deep Learning Frameworks
		TensorFlow
		Keras
		PyTorch
	The Computer Vision Libraries
		OpenCV
		scikit-image
		PIL/Pillow
	The Natural Language Processing Libraries
		NLTK
		spaCy
	The Helper Libraries
		Requests
		Beautiful Soup
		Regex
		Dask
	Summary
16 THE INFOVIS, SCIVIS, AND DASHBOARDING LIBRARIES
	InfoVis and SciVis Libraries
		Matplotlib
		seaborn
		The pandas Plotting API
		Altair
		Bokeh
		Plotly
		HoloViews
		Datashader
		Mayavi and ParaView
	Dashboards
		Dash
		Streamlit
		Voilà
		Panel
	Choosing a Plotting Library
		Size of Dataset
		Types of Plots
		Format
		Versatility
		Maturity
		Making the Final Choice
	Summary
17 THE GEOVIS LIBRARIES
	The Geospatial Libraries
		GeoPandas
		Cartopy
		Geoplot
		Plotly
		folium
		ipyleaflet
		GeoViews: The HoloViz Approach
		KeplerGL
		pydeck
		Bokeh
	Choosing a GeoVis Library
	Summary
PART IV: THE ESSENTIAL LIBRARIES
18 NUMPY: NUMERICAL PYTHON
	Introducing the Array
		Describing Arrays Using Dimension and Shape
		Creating Arrays
		Accessing Array Attributes
		Indexing and Slicing Arrays
	Manipulating Arrays
		Shaping and Transposing
		Joining Arrays
		Splitting Arrays
	Doing Math Using Arrays
		Vectorization
		Broadcasting
		The Matrix Dot Product
		Incrementing and Decrementing Arrays
		Using NumPy Functions
	Reading and Writing Array Data
	Summary
19 DEMYSTIFYING MATPLOTLIB
	Anatomy of a Plot
	The pyplot and Object-Oriented Approaches
	Using the pyplot Approach
		Creating and Manipulating Plots with pyplot Methods
		Working with Subplots
		Building Multipanel Displays Using GridSpec
	Using the Object-Oriented Style
		Creating and Manipulating Plots with the Object-Oriented Style
		Working with Subplots
		Building Multipanel Displays Using GridSpec
		Insetting Plots
		Plotting in 3D
		Animating Plots
	Styling Plots
		Changing Runtime Configuration Parameters
		Creating and Using a Style File
		Applying Style Sheets
	Summary
20 PANDAS, SEABORN, AND SCIKIT-LEARN
	Introducing the pandas Series and DataFrame
		The Series Data Structure
		The DataFrame Data Structure
	The Palmer Penguins Project
		The Project Outline
		Setting Up the Project
		Importing Packages and Setting Up the Display
		Loading the Dataset
		Displaying the DataFrame and Renaming Columns
		Checking for Duplicates
		Handling Missing Values
		Exploring the Dataset
		Predicting Penguin Species Using K-Nearest Neighbors
	Summary
21 MANAGING DATES AND TIMES WITH PYTHON AND PANDAS
	Python datetime Module
		Getting the Current Date and Time
		Assigning Timestamps and Calculating Time Delta
		Formatting Dates and Times
		Converting Strings to Dates and Times
		Plotting with datetime Objects
		Creating Naive vs. Aware Objects
	Time Series and Date Functionality with pandas
		Parsing Time Series Information
		Creating Date Ranges
		Creating Periods
		Creating Time Deltas
		Shifting Dates with Offsets
		Indexing and Slicing Time Series
		Resampling Time Series
	Summary
APPENDIX ANSWERS TO THE “TEST YOUR KNOWLEDGE” CHALLENGES
INDEX