This is the git repository for a half day class that will get students up and running in the Python language.
- Install Anaconda Python
Download the latest distribution for your OS. It currently supports Windows, Mac OS and Linux. The key difference between Anaconda and default python is the packages that come with it. Anaconda will automatically install more libraries that can be of use to you. Anaconda is known for being data science focused.
WARNING!!
I recently had trouble installing the latest version of Anaconda on a Windows 10 laptop. The last few versions failed to install correctly for me.
- Install Jupyter Lab
Once Anaconda Python is installed and running, you will also need to install Jupyter Lab. There are 2 main methods of installation. The first is with conda, which is a package management tool for Anaconda Python. The second is with pip, which is the generic python package manager.
Test out if this worked by starting jupyter lab. To do this you will need to open a command prompt on your PC. For Mac OS/Linux it is a shell and for Windows it is the command prompt. From there you will need to type the following:
jupyter lab
This will start the webserver that acts as our development environment.
This is a 2 hour 45 minute hour class. It is broken up into 3 parts. Each part will be about 30-45 minutes followed by a short lab to try out the topics just covered. Hands on trying out of code is critical to learning. Lab instructions and solutions will be provided.
- Installation and Basics
We will start with installation if this was not done before the class started. Students need both anaconda python and jupyter labs. Once installed, this part of the lecture will cover:
1. Numeric types
2. Strings
3. Lists
4. Dictionaries
- Program Flow
This part of the course will cover programming syntax. The topics will include
1. If/else
2. For loops
3. Try/Except
4. Functions
5. File Handling
- Additional Code
This part of the course will introduce students to using both built in and external 3rd party code.
1. import
2. Try out Pandas, Numpy and Matplotlib together
By the end of this class students should be familiar with the basics of using the python language through the Jupyter Labs interface.