# Hurricanes and Data Visualisation: Part II(b) – Ooops!

In addendum to my second article on hurricanes and data visualisation, I examine a rather epic fail relating to Hurricane Ophelia.

# Hurricanes and Data Visualisation: Part II – Map Reading

The second in a series on Data Visualisation and Hurricanes. Here we grapple with hurricane prediction and cover some issues with data visualisations that are intended to convey safety information to the public.

# Hurricanes and Data Visualisation: Part I(b) – The Mona Lisa

A robust argument against rainbow colourmaps using the Mona Lisa as a case study. Inspired by a Quora post by Hyunjun Ji.

# Hurricanes and Data Visualisation: Part I – Rainbow’s Gravity

The first of two articles looking at how data about hurricanes is displayed and communicated. This includes a worked example illustrating some of the issues that can arise when adopting a rainbow colour palette in data visualisation, specifically with respect to rainfall contour maps.

# A Picture Paints a Thousand Numbers

An expanded and illustrated version of The Data & Analytics Dictionary’s entry about Charts, featuring many of the commonly used types.

# The Latest from the Maths & Science Section

Three selected articles from the new peterjamesthomas.com Maths & Science Section, focussing on Euler’s Number, e, that staple of mystical quasi-mathematics, π and their relationship to each other.

# As Nice as Pie

A review of the humble Pie Chart, what it is good at, where it presents problems and some alternatives.

# Draining the Swamp

A review of some of the problems that can beset Data Lakes, together with some ideas about what to do to fix these from Dan Woods (Forbes), Paul Barth (Podium Data) and Dave Wells (Eckerson Group).

# A Retrospective of 2017’s Articles

A retrospective of the 35 articles published on peterjamesthomas.com during the course of 2017, including the ones that the author enjoyed writing most.

# The Anatomy of a Data Function – Part II

Part two of three articles focussed on the structure and components of a Data Function, together with how they interact to support each other and business goals.