Introduction to Python for Biology

Day 1

Introduction to Python

• Overview of Python as a programming language
• Understand why we use Python for scientific computing
• Differentiate between tasks that Python is suitable for and not
• Become familiar with Python syntax and formatting
• Installing Python
• Setting up your environment
• Differentiate between a Python script and a Jupyter Notebook
• Edit and run simple Python scripts using the command line
• Use Jupyter Notebooks to create and run both Markdown and Python cells
• How to read the documentation to get help

Variables and Assignment

• Assign values to variables
• Perform calculations with variables
• Differentiate between different Python variable types
• Use built-in functions to convert between Python variable types
• Import a Python library and use the functions it contains.
• Read tabular data from a file into a program.
• Select individual values and subsections from data.
• Perform operations on arrays of data
• Use comments to annotate code
• Plot simple graphs from data.

Looping and Repeating Actions

• Understand what a for loop does
• Understand what a while loop does and when to use it
• Write for loops to repeat calculations
• Trace changes to both the loop variable and other variables as a loop runs

Lists and Dictionaries

• Create and index a list of values
• Change the values of a list
• Add values to an existing list
• Reorder lists
• Slice list elements
• Create and manipulate nested lists
• Store paired data in dictionaries
• Iterate over dictionaries

Control Flow

• Write conditional statements using if, else, and elif branches
• Use Boolean operations to test conditions
• Evaluate complex conditionals using and, not, and or

Day 2

Manipulating Text

• Dealing with special characters in Python
• Use Python’s in-built string manipulation tools

Reading Text from a File

• Opening files for reading text
• Opening files for writing text
• Closing files
• Understanding paths and folders

Libraries

• Explain what software libraries are and why programmers create and use them
• Write programs that import and use libraries from Python’s standard library
• Find and read the documentation for standard libraries both interactively and online

Working with Files in Pandas

• Use Pandas to load tabular data sets
• Get basic information about the Pandas DataFrame
• Select individual values from a Pandas dataframe
• Select entire or a subset of rows or columns from a dataframe
• Create dataframes
• Filter and sort dataframes
• Handling missing values
• Split-apply-combine methods with Pandas

File Contents and Manipulation

• Delete files and folders
• List folder contents
• Run external programs
• Add flexibility to programs by taking user input
• Use command-line arguments in a program
• Handle flags and files separately in a command-line program
• Read data from standard input in a program so that it can be used in a pipeline

Day 3

Functions

• Explain the purpose of functions
• Differentiate between defining functions and calling functions
• Define functions that take parameters
• Return values from functions
• Identify local and global variable scope
• Test and debug functions
• Set default values for function parameters
• Discuss best practices on how to divide programs into small, single-purpose functions

Error-Handling

• Read a traceback, determine where an error took place, and identify the type of error that took place
• Describe the situations in which syntax errors, indentation errors, name errors, index errors, and missing file errors occur

Defensive Programming

• Understand what an assertion is
• Add assertions to check whether or not a program’s state is correct
• Add pre- and post-condition assertions to functions
• Understand test-driven development and use it when creating functions

Debugging

• Debug code with errors using systematic processes
• Discuss ways of making code less error-prone and more easily tested

Style

• Understand the reasoning behind the basic rules of coding style
• Refactor programs to make them more readable
• Use Python community coding standards (PEP-8)

Day 4

Plotting in Python

• Choose appropriate plots for different purposes
• Understand the Matplotlib library basic plotting formula
• Understand Matplotlib object hierarchy
• Create line plots, scatter plots, histograms, box plots, and bar charts using the Matplotlib library
• Combine multiple plots
• Use Pandas to do basic plotting on dataframes
• Use Seaborn to create higher-level Python plots

Day 5

Regular Expressions

• Identify instances when regular expressions will speed up workflow
• Understand what a regular expression is and how it is used
• Use the re library methods in Python
• Search for patterns in strings using regular expression operators
• Extract matched patterns in strings as groups