Why an Interactive User Interface to analyze the storm data
author: Pablo Adames date: April 2, 2017 autosize: true
The App Vs. The Data
<https://padames.shinyapps.io/analysis_of_storm_data_from_naoo_data/>
STATE EVTYPE FATALITIES INJURIES LATITUDE LONGITUDE
55 AL HAIL 0 0 3435 8700
1456 AL HIGH WIND 0 0 3203 8613
210826 MN LIGHTNING 0 0 0 0
EVT_TYPE DATE
55 Snow/Hail/Rain/Ice 1955-04-03 00:25:00
1456 Hurricanes/Tornados/Thunderstorms 1975-04-01 00:10:00
210826 Fires/Lightning 1994-04-06 00:16:00The Data
- 902297 entries in the data set
- Spanning 5 decades
- Same seven categories for the storm events (as in previous work)
- Two types of effects on population
- Instructions in the App
Geolocating events and documenting the effects
One of the barriers to making sense of the data is understanding where and how often it happens.
R plus the Leaflet library and shiny offer a powerful visualization tool for complex data sets
The effects can be seen in detail at the higher zoom levels (right image).
Insight into the data
It is easy to get distracted or fail to identify the trends in complex ata sets.
This data set is one such complex set but thanks to this App it can be explored to identify those features of the data that oftentimes remain hidden under the shear volume of the information.
Visit <https://padames.shinyapps.io/analysis_of_storm_data_from_naoo_data/>
To download orignal data visit: ftp://ftp.ncdc.noaa.gov/pub/data/swdi/stormevents/csvfiles/>.
The format changed in 2014 making the data easier to understand and to process. However it’s still quite challenging to explore whitout an app.