Introduction to Research Programming (with Python)

Lesson 1: Introduction

Questions

• What is Python?
• Why learning Python?
• What's the Jupyter notebooks?
• How do we use Jupyter notebooks?

Objectives

• Recognise when using a notebook is useful.
• Use a notebook either by clicking or keyboard shortcuts.
• Generate different formatted text and code blocks.

Lesson 2: Example data analysis

Questions

• Why write software to manage your data and plots?
• Why do we need to import libraries?
• How do we write comments?
• Why are functions useful?
• What allows looping?

Objectives

• Identifying the elements of a program

Lesson 3: Variables

Questions

• What's a variable?
• What happens to a variable when it gets reassigned?
• How do you know the type of a variable?
• How do we read the errors?
• How the notebook keep track of the variables in cells?

Objectives

• Illustrate the concept of variable with labels and boxes.
• Recognise and test the different variables types.
• Predict the behaviour of variables through different cells.

Lesson 4: Using Functions

Questions

• How are functions used?
• What's a method?
• How can you get help on functions?

Objectives

• Recognise methods and functions.
• Use help and ? to read the documentation of functions.

Lesson 5: Types

Questions

• What's a type?
• What's the similarities between strings and lists?
• How we unpack the content of a sequence over multiple variables?

Objectives

• Identify types.
• Predict the output of type(x)
• Use appropriated methods over each type.
• Match properties of string with lists.
• Compare lists of lists with matrices.

Lesson 6: Containers

Questions

• When something is contained in an object?
• What is mutability?
• What other types of containers are available?
• What is Identity? What is equality?

Objectives

• Interpret the result of in and for what it can be used.
• Attribute to the data type the differences with memory handling.
• Use tuples and lists
• Predict when to use identity or equality.

Lesson 7: Dictionaries

Questions

• What's a dictionary?
• What are the parts of a dictionary?
• Which type can be used as keys?
• What's a set?

Objectives

• Identify a dictionary and a set.
• Recognise differences between them.
• Carry out binary operations on set.

Lesson 8: Data structures

Questions

• How can we create a complex data structure?

Objectives

• Implement a data structure.
• Distinguish different approaches.
• Judge which one is more readable, efficient, easier to use,..

Lesson 9: Control and Flow

Questions

• What's a Turing complete machine?
• How to make the program to take decisions?
• What comparison operators can we use?
• How do the variables evaluate?

Objectives

• exemplify the various levels of decision making on a program.
• recall the need of indentation.
• Execute comparisons between variables.

Lesson 10: Iteration

Questions

• What's a loop?
• What can we use to iterate over?
• How can we exit from a loop?

Objectives

• Understand why loops are useful.
• Recall the need of indentation.
• Implement a mix of loops and control flow to extract information from a data structure.

Lesson 11: Comprehensions

Questions

• What's comprehension?
• what kind of operations can we run over a list?
• What objects can we built using comprehension?

Objectives

• Translate a loop into a comprehension.
• Execute nested comprehensions.
• Integrate with a data structure.

Lesson 12: Defining Functions

Questions

• How do we create a function?
• What type of arguments can have?
• How can I provide help?

Objectives

• Infer the output of a simple function.
• Detect possible side effects.
• Construct a function.
• Write docstrings.

Lesson 13: Using libraries

Questions

• Why do we use libraries?
• How are they loaded and used?

Objectives

• Identify how to load a library.
• Recognise when overriding can happen.

Lesson 14: Working with files

Questions

• How can I read data stored in files?
• Why should we plan for different operative systems?
• What do we need to keep in mind when reading strings?
• How does working with files change when they are stored remotely (Internet)?
• Which format accommodate better our data?

Objectives

• Implement a reader with and without a context manager.
• Familiarise with the os module and generate readers that can work at different computers.
• Identify different type of strings python can handle.
• Recall the modules needed.
• Understand different properties for different file formats.

Lesson 15: Plotting

Questions

• How do I represent data visually?
• How can I show more than one plot at once

Objectives

• Carry out generation of simple plots.
• Recognise what are figures and axes.

Lesson 16: Numerical Python

Questions

• How do I operate and represent multi-dimensional arrays in python?
• What is broadcasting?
• How does numpy handles memory?

Objectives

• Recognise differences between numpy's arrays and other data structures in python and the operations available.
• Judge when and where np.newaxis is needed for operating matrices.
• Distinguish between copy and [:] views of an array.