tuong_group_basic_python

Basic template repository for python classroom for Tuong group students.

This repository holds the basic scripts/questions for basic python usage to prep you for advanced analysis in single-cell. The idea is that there are simple functions and objectives included in this repository for everyday python usage. However, I have written mistakes into the codes in the learn folder and it is your task to find the mistakes and suggest the solutions. Good luck and hope you learn something from this!

Instructions

Once you have accepted the assignment, open the repository on your webpage or on vscode. If you have GitHub desktop installed, you can do it locally on your computer. Just have to remember to push your commits. Check out https://github.com/tuonglab/github-starter-course for more information.

Anyway, to perform the assignment(s), you would need to:

1. checkout the feedback branch or click on the feedback branch.
2. Click on the learn folder and look at the code/scripts relevant to the assignment i.e. If the assignment was list, click the corresponding .py file that has the word list in it e.g. learn/learn_list.py
3. There are mistakes contained in the file and it's your goal to fix them . The expected outputs are in the tests folder.
4. make your commits to the scripts in the learn folder. This will save your changes/answers to the assignments and trigger the tests to check if you do it correctly. Remember, you should only do this on the feedback branch.
5. check if the tests passed in either the Pull requests tab or the Actions tab. The goal is to have the test(s) be successful (green).

If you are unsure about anything, post the questions on slack!

lists

The first assignment is on lists.

A list is a data structure in Python that is a mutable, or changeable, ordered sequence of elements. Each element or value that is inside of a list is called an item. Just as strings are defined as characters between quotes, lists are defined by having values between square brackets [] https://www.w3schools.com/python/python_lists.asp

The objective for this assignment is to learn the simplest way to interact with python which is storing items/elements in a list. There are many ways to manipulate a list so this is just an introduction. We use lists all the time for single-cell analysis, including for inserting new metadata, forming lists of items we want to plot etc. Imagine you have 80,000 cells and you want to colour them by treatment status and also by cell-type. How would you construct this information so that we can create the relevant treatment status + cell-type information for each cell e.g. "treated_B cell", "untreated_B cell"? You can achieve this creating a list that holds this information!

There are 4 simple functions written in learn/learn_list.py but the tests are failing for each of them. Can you fix them up so that the tests succeed?

dictionary

The second assignment is on dictionary.

Dictionaries are used to store data values in key:value pairs. Dictionaries are defined by having values between square brackets {} https://www.w3schools.com/python/python_dictionaries.asp

The objective of this assignment is to learn how to use dictionaries for matching/changing values to suit our needs, which is very relevant for single-cell analysis. Imagine you have 10 clusters that you identified but you want to give each of them a biologically meaningful name. How would you go about changing the individual names? You can achieve this using dictionaries!

There are 2 functions written in learn/learn_dict.py but the tests are failing for each of them. Can you fix them up so that the tests succeed?

data frames

The third assignment is on data frames. We use the popular pandas package to interact with data frames.

A pandas DataFrame is a 2 dimensional data structure, like a 2 dimensional array, or a table with rows and columns. https://www.w3schools.com/python/pandas/pandas_dataframes.asp#:~:text=What%20is%20a%20DataFrame%3F,table%20with%20rows%20and%20columns.

The objective of this assignment is to learn how to slice the DataFrame object so that we end up with the information that we want. This is very important for how we deal with single-cell data. Imagine that you have 10,000 cells but you only want to subset to just 2,000 of them as they are from the spleen and not any other organ. How would you go about doing this? You can achieve this by slicing the DataFrame to only contain the relevant cells!

There are 2 functions written in learn/learn_pandas.py but the tests are failing for each of them. Can you fix them up so that the tests succeed?