Shiny app to explore South Australia’s road accidents data. See details at https://github.com/asheshwor/crashsa
Group project for 2015 Unleashed SA Adelaide event. Team: Data Dingoes
Young Australians are often faced with the big decision whether to stay in the city they were raised in, or move interstate for employment opportunities or to be with a loved one. It’s a big life decision. But how do you decide? Should I stay or should I go?
Adelaide loses lots of young graduates. They may earn more interstate but what about housing affordability or lifestyle?
Our app pulls together relevant data points to help individuals reach a meaningful decision.
Hackerspace url: https://hackerspace.govhack.org/content/should-i-stay-or-should-i-go
Video url: https://vimeo.com/132623156
Code repository: https://github.com/Unleashed2015/BigDecisions
This is a simple implementation of Shiny dashboard to explore the Nepal earthquake data. The earthquake data used here is NOT real-time. The records were downloaded from USGS website (csv format) and placed in the data folder. To filter the quakes in the vicinity of Nepal, only the quakes within the bounding box of Nepal map are used.
Try the app at https://asheshwor.shinyapps.io/np-quake
Source code and brief documentation available here: https://github.com/asheshwor/np-quake
As a follow-up to world migration visualization, I used 2011 Australian census data to visualize the inter-state migration. I experimented with different styles to connect origin and destination points. It is easier to visualize the direction of movement using sine wave connector lines as outgoing and incoming will be on opposite directions.
Github repo: https://github.com/asheshwor/aumig/blob/master/aumig.R
I use my location history collected by google and myTracks to visualize where I’ve been using R. Github repo: https://github.com/asheshwor/mapping-location-history