Setting up Python
In the next sections, we’ll go through setting up a Python environment in Docker and Conda, two popular tools for setting up and maintaining environments. We’ll then cover how to use pip to install additional libraries into these environments.
Docker
Docker is a tool that lets you run a container within a given operating system. A container is a kind of virtual machine, but it shares the kernel with the host machine. The advantage of using a container is that it’s much lighter than a virtual machine, because it doesn’t need to boot a full operating system.
Docker is useful for data science because you can use it to create a reproducible environment for your data science project. That is, you can use Docker to create an environment with all the libraries and tools you need for your project, and share that environment with others.
To install Docker, follow the instructions on the Docker website.
Once you have Docker installed, you can use it...
