I made this after quite a lot of thought. There are a ton of pandas tutorials out there and the maintainers of pandas themselves have tutorials. But I think these tutorials have one of two flavors:
- Intro: you barely get into details.
- Reference: just the details
I wanted to let people know what are the important and advanced pandas functions that a data scientist uses on a day to day basis. And I could not find it.
Thus this.
This tutorial is an opinionated guide to pandas. I'll let you know which functions I think are not worth learning and which are. This is not an intro to pandas. This is pandas for data scientists, and I hope you enjoy.
The first step to get running with these tutorials is to install virtualenv. Fortunately there is a great tutorial on hitchhiker's guide to python. Please follow the steps in the guide.
Once you have installed virtualenv let's make an enviornment with the following command:
virtualenv -p python3 env
Notice that we are using python 3. Pandas has announced that they will stop supporting python 2 after 2019. You will then need to activate your env. Again the tutorial is a great resource on showing you how to do this on both windows and mac:
The next step is that we will need to install all the requirements:
pip install -r requirements.txt
Finally the last step is to run an ipython notebook from within the env and then we are ready to go:
ipython notebook
Pandas itself has some good resources on installation that you can find here
The recommended order is:
- Pandas Intro to Data Structures
- Indexing and Selecting
- Group Operations
- Row-Column Transformations
- Combining DataFrames
- Misc Functions
If you are like me you will also find using some of these techniques in exercises to be quite useful as well. And fortunately pandas has some great exercises listed on their site. If y'all would like and these tutorials/videos get enough support, I'd be happy to video the solutions to those exercises as well.