This repository contains supplemental material for the guest lecture on data validation at the REMLA course.
Please follow the instructions below to setup your local environment prior to the lecture on 2022-05-16 Mon as it takes considerable amount of time to build the docker image.
I assume basic familiarly with python and the pandas package. If you are not familiar with pandas, please take a look at the documentation. In particular, you can look at the 10 minutes with pandas tutorial to grasp the basics.
We will primarily be working within a computatial notebook enviroment such as the one provided by Jupyter. Once again, if you are not familiar with a notebook style workflow, I would encourage you to checkout the documentation & tutorials.
Follow the steps below to setup your local environment.
Fork this repository & clone it to your local machine (you should know how to do this already!).
Build the image using the provided Dockerfile, we will call it tfdv for convenience.
# NOTE this step will take some time
docker build -t tfdv .
Start a container from the built image.
docker run -it --rm -v "$(pwd):/app" -p 8888:8888 tfdv
If all went well, then you should see some output (from Jupyter notebooks) in your terminal. Visit the url and make sure that Jupyter is working properly.
Download the cancer dataset from Kaggle and save it under the data directory.