Python Pandas Workshop, first run for PyLadies NYC at Flatiron Health (May 2019).
A mix of Pandas and "how to get started with data analysis" using realistic healthcare data.
In this PyLadies class, we will be using a Jupyter notebook and the Pandas library to explore oncology treatment data. You will not only get an introduction to data analysis using Pandas, but also get a glimpse of the kind of healthcare data that engineers at Flatiron wrangle on a daily basis. (Note that the data used in the workshop is of course fake and not based on any real patient data we handle at Flatiron!)
We expect a working knowledge of Python in order to be able to follow along with the workshop. If you are an absolute beginner in Python and aren't familiar with Python syntax, this workshop might not be suited for you.
Binder is a web-based hub for Jupyter notebook. If your local setup does not work or if you prefer not to install anything locally, you can use the link here to work in a notebook on Binder. Please note that Binder will not save your notebook. You can download the notebook to your local machine at the end to have your own copy.
We strongly recommend using a machine with up-to-date versions of the libraries we use.
Either Python 2.7.12 and upwards, or any Python 3.
Install these libraries by running pip install on your laptop:
Ideal - the versions I run locally:
- Pandas 0.24.x and above
- Seaborn 0.9.x and above
- Matplotlib 3.0.x and above
- Jupyter 1.0.x and above
Works for most of the tutorial:
- Pandas 0.12.x and above
- Seaborn 0.5.x and above
- Matplotlib 2.1.x and above
- Jupyter 1.0.x and above
- Run in a terminal:
jupyter notebook - This should open a browser window, or go to http://localhost:8888/notebooks/
- Create a new notebook
- Try importing the newly installed libraries in a cell and execute the cell to test
- Please debug any issues that occur so you're ready to start the workshop!
Download the mock_treatment_starts_2016.csv file from this repo. NOTE The data is entirely made up and is in no way related to any real patient data we use at Flatiron.