This introduction to Jupyter Notebooks (JNBs) is an outcome of a year of learning, creating, and classroom testing JNBs in a variety of settings: a sabbatical with an urban violence reduction organization; an after school distance learning program for low to middle income high school students in Chicago; a general education computer-lab based math course; and finally two upper division courses for applied math majors at a liberal arts college. The examples include line graphs, histograms, and a pie chart of violent crime data created for a community organization, a high school/general education lab on computer music, a visualization of volumes computable by triple integrals, and creation of a .gif animation of a numerical solution to a 2 -Dimensional PDE. In addition to executing and displaying output of computer code, JNBs can import data from files and external websites, interpret equations written in LaTeX, display PowerPoints in pdf format, and show videos posted on other websites. JNBs can also save output data, figures, and animations to files in a variety of formats. At a general education level, JNBs can enrich student learning experience by helping students overcome math anxiety through inclusion of the arts. At the undergraduate math major level, JNBs can create interesting visualizations/animations and support service learning projects. The appendix explains how to get started using JNBs. The learning curve for creating the JNBs described in this article is not that steep, and the low-hanging fruit from using JNBs for a wide-range of teaching contexts and for community service learning projects is plentiful.