In this talk, we will demonstrate Vaex, an open-source DataFrame library that embodies these concepts. Using data from the New York City YellowCab taxi service comprising 1.1 billion samples and taking up over 170 GB on disk, we will showcase how one can conduct an exploratory data analysis, complete with filtering, grouping, calculations of statistics and interactive visualisations on a single laptop in real time. Finally we will show an example of how one can automatically build a machine learning pipeline as a by-product of the exploratory data analysis using the computational graphs in Vaex.