Abhijit Dasgupta ARAASTAT @webbedfeet Graphics and data visualizations to enhance storytelling: Revealing rather than obfuscating Abhijit Dasgupta ARAASTAT @webbedfeet

Context “Academic” consulting (with NIH) Healthcare sensor startup Business intelligence consulting Member of the DC data community and a meet up organizer

“Insights” Exploration Contextual understanding Reporting Data Information Evaluation / Action

“Insights” Processes are complex Evaluating actions of multiple factors on an outcome Subgroups, interactions

Visualizations Takes advantage of our human capability to understand patterns quickly and, often, intuitively Can be a gateway to interpreting what the data is saying

Visualizations Can enable information compression as well as information dissemination We can look at different aspects of the data in a single visualization GO WILD!! Lines, shapes, colors, sizes

Mental gymnastics should not be required

no Mental gymnastics The consumer of a visualization should not require too much effort to understand it Context should be clear (labels, axes, and so on) The interpretation should be “obvious” The “punch line” should be clear

no Mental gymnastics Sometimes a visualization is not the right tool A table or textual display might be simpler Sometimes hard to resist the temptation to create graphics

The task at hand

Exploring data Really value flexible ways to visualize data Small multiples and trellis graphics Linked graphs Interactivity Rendering speed Ability to hone in

Presenting information Visualizations need to be clear & uncluttered make the point provide easy access to underlying data “talking points” and metadata allow the consumer to explore a bit and think be geared towards what the consumer wants

Toolsets

Tools for visualization Ability to create static graphs has been around Grammar of Graphics & ggplot Conceptually easier (for me) to create layered, thematically consistent, graphics

Tools for Visualization Javascript-based graphics D3.js Leaflet Various others

Tools for Visualization Javascript-based graphics Potential for interaction Linking graphs Fast Additional information through popouts

Tools for Visualization Javascript-based graphics Good wrappers in R and Python Don’t actually need to know Javascript per se R Python plotly, rbokeh, highcharts, r2d3, htmlwidgets plotly, bokeh, altair,

Keeping the consumer in mind

Client/consumer focus What’s important to the consumer? Often not what’s important to the analyst We may have a perfectly clear graphic…. which is not what the consumer wants and not what (s)he needs

Client/consumer focus “Instead of a version of data science that is narrowly focused on researching new statistical models or building better data visualizations, a design-thinking approach recognizes data scientists as creative problem solvers.”

Examples

26th August, 2015

Meta-analysis of 129 studies published between 1955 and 2016 Retrospective or prospective designs Developing and developed countries Adults and children Objective is to understand patterns in SLE-related mortality over time (in 5 year intervals) Looking at 5 year intervals to estimate mortality

Temptation is of course to add more information to the graph

Data compression vs mental gymnastics This is the big balancing act You can add more “information”, but you make it harder to read In retrospect, we might have kept a simpler graphic

Caveat emptor I don’t play a data visualization expert on TV, or in real life for that matter I’m sharing thoughts I’ve had through many interactions with clients and colleagues, and my own narrow experiences There are GREAT resources out there. Use them Would love to hear and see better ideas

No snores? Perfect!! @webbedfeet webbedfeet.netlify.com #datadc