Data Science FACENS - Data Visualization
Associated examples and material of the discipline Data Visualization -- Data Science Specialization Program -- FACENS.
Table of contents
- Running Examples & Exercises
Running Examples & Exercises
Examples and exercises are presented as Jupyter Notebooks. Get started by cloning this repository within your own Jupyter environment or by launching a Jupyter environment from cloud services.
Please follow these instructions for installing and running Jupyter using Anaconda.
Please follow these instructions for installing and running Jupyter using pip.
Alternatively, you may install Jupyter Lab by following these instructions.
You can run a containerized instance of Jupyter Lab from our own Docker image. Try:
docker run -it -p 8888:8888 matheusmota/facens-dataviz
Alternatively, you can map you local home folder into the container:
docker run -it -v `pwd`:/jupyter/data/ -p 8888:8888 matheusmota/facens-dataviz
Access the Jupyter Lab server by going to http://0.0.0.0:8888.
The Dockerfile used to build the image can be found here.
Alternative #3: repo2docker
repo2docker -p 8888:8888 -v `pwd`:`pwd` https://github.com/matheusmota/facens-dataviz jupyter-lab --ip 0.0.0.0 --NotebookApp.token=''
Access the Jupyter Lab server by going to http://0.0.0.0:8888/lab.
- Feel free to use images from this library of ready-to-run Docker images containing Jupyter. Do not forget to install dependencies (see the binder folder).