There are several tools for visualizing data such as Tableau, Qlik, Dygraphs, Kibana etc. The curve awakens the imagination.ĭata visualization plays a vital role in life of a Data Scientist. It is easier to visualize complex data and relationships than deciphering them from spreadsheets / tables. The profile of a curve reveals a whole situation in a flash – history of an epidemic, a panic or an era of prosperity. Lastly this tutorial helped with the maps.Įnjoy and feel free to comment below – would be good to receive feedback.There is magic in graphs. The example I created converts a CSV file to data tables, graphs and map of Australia using uses RStudio’s Shiny Dashboard =>Īustralia Government Disaster Events Dashboard Quick preview of what I achieved thanks to Shiny Dashboards:

Therefore chose data from to build my demo, as it is freely available. The Australian government provides public access to numerous data sets and encourages re-use. Study the Shiny Dashboard Instructions – my source code might help too.

Previously the tutorial comprised 3 parts, but now are presented in the single video lasting a bit of 2 hours 25 minutes. It is very comprehensive and the only requirement is Rstudio, naturally. As a currently archived course you can complete it self paced, although assessments are disabled.

My favourite course is MIT’s Analytics Edge. There are a ton of courses online, such as on Rstudio, EDX and Coursera.

First requirement is to have a fair understanding of R.

If you just want to see the demo first » CLICK HERE « Writing up my experiences as a way of introduction, in the hope it might help others to learn Shiny Server.” “Having studied Data Science since April 2014, felt it a good time to get to know Rstudio’s Shiny Server! So sourced ’s Disaster Events and built an interactive dashboard.

Rstudio shiny dashboard