Data Science Docker Environment

Problem

Bootstrapping a new analyst on a Python + R data-science stack — Jupyter, scikit-learn, pandas, RStudio kernel, common viz libs — eats a day every time. The exact versions that worked last quarter rarely work today.

Approach

• One Dockerfile that pins Python + R + library versions.
• docker-compose wires up a notebook server with a sane volume mount, port mapping, and an opinionated default working directory.
• A small Makefile of common operations (build, start, shell, kill) so day-zero is one command.

Used as a teaching environment and as the base image for several internal analytics setups.

Links

• Repo: github.com/nilesh-patil/datascience-environment — 18 GitHub stars