Geo-Python
2019
Course information
General info
Course meetings in Period I
Instructors
Lecturers
Course assistants
Course websites
Learning goals
Grading
General grading breakdown
Installing Python
Install Python on Windows
Install Python on macOS
Install Python on Linux
Installing packages using Conda
The easiest way
Installing Jupyter Lab using conda
Alternative way to install packages if typical doesn’t work
Vocabulary - Basic terms
Python vocabulary
Basic vocabulary of Version Control
Resources
Books
Python tutorials
Git + Github tutorials
License and terms of usage
Instructional materials
you are free to
Under the following terms
Notices
Code snippets / software
Lesson 1
Motivation for the course
Effective data visualization
Lesson overview
Learning goals
Lecture video
Lecture slides
Course environment
JupyterLab
Cloud computing environments
Binder
CSC Notebooks
Using your own computer
Git and GitHub
Slack
Voting and polling
Page summary
Communicating with Slack
Accessing the workspace in Slack
Overview of Slack
Basic usage of Slack
Notifying a user
Using threads
General guidelines for communication
A taste of Python
General information
Sources
About this document
Getting started
Variables, math and functions
Simple Python math
Functions
Math operations
Check your understanding
Combining functions
Variables
Check your understanding
Updating variables
Variable values
Data types
Check your understanding
Character input
Good coding practices - Selecting “good” variable names
Some “not-so-good” variable names
Selecting “good” variable names
Formatting “good” variable names
Exercise 1
Part 1 - Creating a GitHub.com account and using Slack
Part 2 - Cooking up some Python
Summary (what to submit)
Lesson 2
Lesson overview
Learning goals
Lecture video
Basic elements of Python
Sources
Data types revisited
Let’s start with some data
Reminder: Data types and their compatibility
Converting data from one type to another
Combining text and numbers
Lists and indices
Creating a list
Index values
A useful analog - Bill the vending machine
Number of items in a list
Index value tips
Modifying list values
Data types in lists
Adding and removing values from lists
Appending to an integer? Not so fast…
Some other useful list methods
Reversing a list
Sorting a list
Good coding practices - Describing your code
Do I need to describe my code?
But seriously, the Internet says I shouldn’t comment my code
Code comments
Line comments
Block comments
Markdown text
Data source
Introduction to Version Control
Familiar?
What is version control?
What is Git?
What is GitHub?
Relies on Git
Social (collaborative) network
Open source / science
Documentation
Online tools
Issue tracking
Basic vocabulary
Resources
Meet Git
Overview and preparations
Key concepts and tools
Using Git from the command line
Configuration
Clone a repository from GitHub
Add changes to the staging area
Commit changes
Publish your local commits to GitHub
Using the JupyterLab Git plugin
Preparations in the Terminal
Stage changes in the plugin
Commit changes in the plugin
Pull and push using the plugin
If everything else fails…
Using Classroom for Github
Classroom for GitHub
Exercise 2
Cloud computing environments
Exercise 2 hints
Git
List methods
Indentation woes
Lesson 3
Lesson overview
Learning goals
Lecture
for loops
Sources
Basics of for loops
A (bad) example
Introducing the for loop
for loop format
Your daily for loop
for loop variables
for loops and the range() function
Poll question pause
Looping over the length of lists using index values
Why bother looping over a list by the index value?
Poll question pause
Conditional statements
Sources
Basics of conditional statements
A simple conditional statement
Comparison operators and boolean values
if, elif and else
Combining conditions
Combining for-loops and conditional statements
Good coding practices - writing readable code
Working code vs readable code
PEP 8 Style Guide
Maximum line length
Indentation
Whitespace and binary operators
Avoid extraneous whitespace
Write one statement per line
Exercise 3
Cloud computing environments
Exercise 3 hints
General tips
Tests
Combining strings
Nested if statements
Lesson 4
Lesson overview
Learning goals
Lecture
Lecture
Functions
Sources
What is a function?
Anatomy of a function
Our first function (aww…)
Calling functions
Using our new function
Let’s make another function
Using our second function
Check your understanding
Functions within a function (Yo dawg…)
Using our combined functions
An introduction to script files
The general concept of a .py script file
Getting started
Saving a text file as a Python file
Saving and loading functions
Saving functions in a script file
Calling functions from a script file
Making sure we’re in the right working directory
Binder users
CSC notebooks users
Changing the working directory
Binder users
CSC notebooks users
Importing our script functions
Using our script functions
Importing multiple functions
Importing all functions from a script
Temperature calculator (
optional, advanced topic
)
Defining the function
Adding some conditional statements
Returning the result
Adding a docstring
Testing the new function
Using the tempCalculator
Loading and using modules
Modules, packages and libraries?
Loading modules
Renaming imported modules
Importing a single function
Importing a submodule
Using module functions
What should I not do?
from X import *
Poor names when renaming on import
Extra: installing packages
Good coding practices - Writing our scripts the “right” way
Inline comments
Use line breaks wisely
Use a docstring
Advanced topics
Adding a license
Starting with a shebang
Page summary
Exercise 4
Cloud computing environments
Exercise 4 hints
Importing variables from a script
Counting values from a list
Lesson 5
Lesson overview
Learning goals
Lecture videos
What is Pandas?
Easy-to-use data structures
Combines functionalities from many Python modules
Supports data read/write from multiple formats
Exploring data using Pandas
Input data: weather statistics
Reading a data file with Pandas
DataFrame properties
Selecting columns
Descriptive statistics
Extra: Very basic plots
Extra: From lists to pandas objects
Processing data with Pandas
Basic calculations
Selecting rows and columns
Filtering and updating data
Dealing with missing data
Data type conversions
Unique values
Sorting data
Writing data to a file
Exercise 5
Exercise 5 hints for Pandas
Lesson 6
Lesson overview
Learning goals
Lesson videos
Data processing with Pandas, part 2
Motivation
Input data
Downloading the data
CSC Notebooks users
Users with Jupyter on their personal computers
Binder users
About the data
Reading the data
Renaming columns
Check dataframe properties
Using your own functions in pandas
Iterating over rows
Applying a function
Parsing dates
String slicing
datetime
Aggregating data in Pandas by grouping
Detecting warm months
Repeating the data analysis with larger dataset
Dealing with errors
Interpreting error messages
Reading error messages
Common errors and exceptions
IndexErrors
NameErrors
IndentationErrors
TypeErrors
Other kinds of errors
More information
Good coding practices - Using assertions
Assertions
Multiple assertions
A bad example
A better example
More information
Debugging your Python code
Source
Test your code with known outputs
Testing with a simplified data file
Make your code crash quickly and regularly
Make small changes and track them
Exercise 6
Cloud computing environments
Exercise 6 hints
Data format for problems 1-3
Reading in fixed-width text files
Skipping the second row of a file
Joining data from one DataFrame to another
Lesson 7
Lesson overview
Learning goals
Lesson videos
Plotting in Python
Anatomy of a plot
Common terms when doing plotting
Plotting with Pandas (…and Matplotlib…and Bokeh)
Input data
Downloading the data
Binder users
About the data
Getting started
Basic x-y plot
Selecting our plotted data
Basic plot formatting
Embiggening* the plot
Other common plot formatting operations
Adding text to the plot
Changing the axis ranges
Dealing with datetime axes
Bar plots in Pandas
Saving your plots as image files
Interactive plotting with Pandas-Bokeh
More advanced plotting with Pandas/Matplotlib
The data
Getting started
Loading the data
Preparing the data
Converting temperatures to Celsius
Using subplots
Extracting seasonal temperatures
Finding data bounds
Creating our first set of subplots
Exercise 7
Cloud computing environments
Hints for Exercise 7
Labels and legends
Using
enumerate()
Saving multiple plots into a directory
Settings for multiple subplots:
Preventing plot display
Creating an animation from multiple images
Creating the animation
NumPy-specific hints
Extracting seasonal dates and temperatures (in many years)
Finding seasonal average temperatures (by year)
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