Synopsis

The following work explores the impact of natural disasters in several ways by looking at the amount of injuries/fatalities, and at the amount of property/crop damage. Collapsing many of the categories into broader consistent themes, we were able to isolate which ones had the largest impacts in different areas of the country. Where in many cases the cost impact of several of the broader categories was felt consistently across the nation, when isolating the actual injuries/fatalities each thematic category had substantially more standpoint states. This information is potentially relevant for risk and safety planning and budgeting within these regions, given the cost to human capital.

Processing the Data

Initial Processing

Here working from the original CSV file we subset the data for the sections relevant to our two main questions: 1) Across the United States, which types of events (as indicated in the EVTYPE variable) are most harmful with respect to population health? 2) Across the United States, which types of events have the greatest economic consequences?

library(ggplot2)
library(maps)
 
download.file("https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2","repdata%2Fdata%2FStormData.csv.bz2")
stormd <- read.csv("repdata%2Fdata%2FStormData.csv.bz2")
hurt <- stormd[(stormd$INJURIES>0|stormd$FATALITIES>0),]
cost <- stormd[(stormd$PROPDMG>0|stormd$CROPDMG>0),]
hurt$EVTYPE <- as.character(hurt$EVTYPE)
cost$EVTYPE <- as.character(cost$EVTYPE)
hurt$EVCAT <- 0
cost$EVCAT <- 0

Creating the “Buckets”

Even with the data subsetted, we were dealing with many disparate “EVTYPEs” and it was necessary to then gather them into larget buckets. which the following code takes care of:

#Hurt Categories
 
hurt[hurt$EVTYPE%in%c("DROUGHT","UNSEASONABLY WARM","UNSEASONABLY WARM AND DRY","WARM WEATHER","DRY MICROBURST"),"EVCAT"] <- "Dry"
 
hurt[hurt$EVTYPE%in%c("BRUSH FIRE","WILD FIRES","WILD/FOREST FIRE","WILDFIRE"),"EVCAT"] <- "Fire"
 
hurt[hurt$EVTYPE%in%c("COASTAL FLOOD","Coastal Flooding","COASTAL FLOODING","COASTAL FLOODING/EROSION","FLASH FLOOD","FLASH FLOOD/FLOOD","FLASH FLOODING","FLASH FLOODING/FLOOD","FLASH FLOODS","FLOOD","FLOOD & HEAVY RAIN","FLOOD/FLASH FLOOD","FLOOD/RIVER FLOOD","FLOODING","MINOR FLOODING","RAPIDLY RISING WATER","RIVER FLOOD","River Flooding","RIVER FLOODING","TIDAL FLOODING","URBAN AND SMALL STREAM FLOODIN","URBAN/SML STREAM FLD"),"EVCAT"] <- "Flood"
 
hurt[hurt$EVTYPE%in%c("LANDSLIDE","LANDSLIDES","Mudslide","Mudslides"),"EVCAT"] <-"Ground"
 
hurt[hurt$EVTYPE%in%c("DROUGHT/EXCESSIVE HEAT","EXCESSIVE HEAT","EXTREME HEAT","HEAT","Heat Wave","HEAT WAVE","HEAT WAVE DROUGHT","HEAT WAVES","RECORD HEAT","RECORD/EXCESSIVE HEAT"),"EVCAT"] <-"Heat"
 
hurt[hurt$EVTYPE%in%c("OTHER"),"EVCAT"] <-"Other"
 
hurt[hurt$EVTYPE%in%c("Coastal Storm","COASTAL STORM","COASTALSTORM","DUST STORM","HURRICANE","Hurricane Edouard","HURRICANE EMILY","HURRICANE ERIN","HURRICANE FELIX","HURRICANE OPAL","HURRICANE OPAL/HIGH WINDS","HURRICANE/TYPHOON","HURRICANE-GENERATED SWELLS","LIGHTNING","LIGHTNING AND THUNDERSTORM WIN","LIGHTNING INJURY","LIGHTNING.","MIXED PRECIP","STORM SURGE","STORM SURGE/TIDE","THUNDERSTORM","THUNDERSTORMW","TROPICAL STORM","TROPICAL STORM GORDON","TSUNAMI","TYPHOON","WINTER STORM","WINTER STORM HIGH WINDS","WINTER STORMS","Dust Devil","DUST DEVIL"),"EVCAT"] <-"Storm"
 
hurt[hurt$EVTYPE%in%c("AVALANCE","AVALANCHE","BLACK ICE","BLIZZARD","blowing snow","BLOWING SNOW","Cold","COLD","COLD AND SNOW","Cold Temperature","COLD WAVE","COLD WEATHER","EXCESSIVE SNOW","Extended Cold","Extreme Cold","EXTREME COLD","EXTREME COLD/WIND CHILL","FALLING SNOW/ICE","FOG AND COLD TEMPERATURES","FREEZE","FREEZING DRIZZLE","FREEZING RAIN","FREEZING RAIN/SNOW","Freezing Spray","FROST","GLAZE","GLAZE/ICE STORM","HAIL","HEAVY SNOW","HEAVY SNOW AND HIGH WINDS","Heavy snow shower","HEAVY SNOW/BLIZZARD/AVALANCHE","HEAVY SNOW/ICE","HYPERTHERMIA/EXPOSURE","HYPOTHERMIA","Hypothermia/Exposure","HYPOTHERMIA/EXPOSURE","ICE","ICE ON ROAD","ICE ROADS","ICE STORM","ICE STORM/FLASH FLOOD","ICY ROADS","LIGHT SNOW","LOW TEMPERATURE","RAIN/SNOW","RECORD COLD","SLEET","SMALL HAIL","Snow","SNOW","SNOW AND ICE","SNOW SQUALL","Snow Squalls","SNOW/ BITTER COLD","THUNDERSNOW","UNSEASONABLY COLD","WINTER WEATHER","WINTER WEATHER MIX","WINTER WEATHER/MIX","WINTRY MIX"),"EVCAT"] <-"Subzero"
 
hurt[hurt$EVTYPE%in%c("DROWNING","EXCESSIVE RAINFALL","HAZARDOUS SURF","HEAVY RAIN","HEAVY RAINS","HEAVY SEAS","Heavy Surf","HEAVY SURF","HEAVY SURF/HIGH SURF","HIGH","HIGH SEAS","High Surf","HIGH SURF","HIGH SWELLS","HIGH WATER","HIGH WAVES","Marine Accident","MARINE MISHAP","RIP CURRENT","RIP CURRENTS","RIP CURRENTS/HEAVY SURF","ROGUE WAVE","ROUGH SEAS","ROUGH SURF","Torrential Rainfall","WATERSPOUT"),"EVCAT"] <-"Water(Non-Flood)"
 
hurt[hurt$EVTYPE%in%c("COLD/WIND CHILL","COLD/WINDS","DENSE FOG","DRY MIRCOBURST WINDS","EXTREME WINDCHILL","FOG","FUNNEL CLOUD","GUSTY WIND","Gusty winds","Gusty Winds","GUSTY WINDS","Heavy surf and wind","HIGH WIND","HIGH WIND 48","HIGH WIND AND SEAS","HIGH WIND/HEAVY SNOW","HIGH WIND/SEAS","HIGH WINDS","HIGH WINDS/COLD","HIGH WINDS/SNOW","MARINE HIGH WIND","MARINE STRONG WIND","MARINE THUNDERSTORM WIND","MARINE TSTM WIND","NON TSTM WIND","NON-SEVERE WIND DAMAGE","RAIN/WIND","SNOW/HIGH WINDS","STRONG WIND","Strong Winds","STRONG WINDS","THUNDERSTORM WIND","THUNDERSTORM WIND (G40)","THUNDERSTORM WIND G52","THUNDERSTORM WINDS","THUNDERSTORM WINDS","THUNDERSTORM WINDS 13","THUNDERSTORM WINDS/HAIL","THUNDERSTORM WINDSS","THUNDERSTORMS WINDS","THUNDERTORM WINDS","TORNADO","TORNADO F2","TORNADO F3","TORNADOES, TSTM WIND, HAIL","TSTM WIND","TSTM WIND (G35)","TSTM WIND (G40)","TSTM WIND (G45)","TSTM WIND/HAIL","WATERSPOUT TORNADO","WATERSPOUT/TORNADO","Whirlwind","WIND","WIND STORM","WINDS","THUNDERSTORM  WINDS"),"EVCAT"] <-"Wind"
 
#Cost Categories
 
cost[cost$EVTYPE%in%c("VOLCANIC ASH","BLOWING DUST","UNSEASONABLY WARM","DROUGHT","DRY MICROBURST" ),"EVCAT"] <-"Dry"
 
cost[cost$EVTYPE%in%c("LIGHTNING FIRE","WILD FIRES","WILD/FOREST FIRE","WILD/FOREST FIRES","WILDFIRE","WILDFIRES","BRUSH FIRE","FOREST FIRES","GRASS FIRES" ),"EVCAT"] <-"Fire"
 
cost[cost$EVTYPE%in%c("HEAVY SURF COASTAL FLOODING","HIGH WINDS/COASTAL FLOOD","LAKE FLOOD","LAKESHORE FLOOD","DAM BREAK","MAJOR FLOOD","MINOR FLOODING","MUD SLIDES URBAN FLOODING","RIVER AND STREAM FLOOD","RIVER FLOOD","River Flooding","RIVER FLOODING","RURAL FLOOD","SMALL STREAM FLOOD","Tidal Flooding","TIDAL FLOODING","URBAN AND SMALL","URBAN FLOOD","URBAN FLOODING","URBAN FLOODS","URBAN SMALL","URBAN/SMALL STREAM","URBAN/SMALL STREAM FLOOD","URBAN/SML STREAM FLD","FLASH FLOOD","BREAKUP FLOODING","COASTAL FLOODING/EROSION","Coastal Flood","COASTAL FLOOD","Coastal Flooding","COASTAL FLOODING","COASTAL FLOODING/EROSION","Erosion/Cstl Flood","FLASH FLOOD"," FLASH FLOOD","COASTAL  FLOODING/EROSION","FLASH FLOOD - HEAVY RAIN","FLASH FLOOD FROM ICE JAMS","FLASH FLOOD LANDSLIDES","FLASH FLOOD WINDS","FLASH FLOOD/","FLASH FLOOD/ STREET","FLASH FLOOD/FLOOD","FLASH FLOOD/LANDSLIDE","FLASH FLOODING","FLASH FLOODING/FLOOD","FLASH FLOODING/THUNDERSTORM WI","FLASH FLOODS","FLOOD","FLOOD & HEAVY RAIN","FLOOD FLASH","FLOOD/FLASH","FLOOD/FLASH FLOOD","FLOOD/FLASH/FLOOD","FLOOD/FLASHFLOOD","FLOOD/RAIN/WINDS","FLOOD/RIVER FLOOD","FLOODING","FLOODING/HEAVY RAIN","FLOODS","HEAVY RAINS/FLOODING" ),"EVCAT"] <-"Flood"
 
cost[cost$EVTYPE%in%c("LANDSLIDE","LANDSLIDES","MUD SLIDE","MUD SLIDES","MUDSLIDE","MUDSLIDES","ROCK SLIDE" ),"EVCAT"] <-"Ground"
 
cost[cost$EVTYPE%in%c("DROUGHT/EXCESSIVE HEAT","EXCESSIVE HEAT","EXTREME HEAT","HEAT","HEAT WAVE","HEAT WAVE DROUGHT" ),"EVCAT"] <-"Heat"
 
cost[cost$EVTYPE%in%c("?","APACHE COUNTY","Other","OTHER" ),"EVCAT"] <-"Other"
 
cost[cost$EVTYPE%in%c("HURRICANE","HURRICANE-GENERATED SWELLS","HURRICANE EMILY","HURRICANE ERIN","HURRICANE FELIX","HURRICANE GORDON","HURRICANE OPAL","HURRICANE OPAL/HIGH WINDS","HURRICANE/TYPHOON","Landslump","LIGHTNING","LANDSPOUT","LIGHTING","LIGHTNING WAUSEON","LIGHTNING AND HEAVY RAIN","LIGHTNING/HEAVY RAIN","LIGNTNING","MARINE HAIL","SEVERE THUNDERSTORM","SEVERE THUNDERSTORMS","SLEET/ICE STORM","THUNDERSTORM DAMAGE TO","THUNDERSTORM HAIL","THUNDERSTORMS","TROPICAL DEPRESSION","TROPICAL STORM ALBERTO","TROPICAL STORM DEAN","TROPICAL STORM JERRY","STORM SURGE","STORM SURGE/TIDE","THUNDERSTORM","DUST DEVIL WATERSPOUT","THUNDERSTORMW","TROPICAL STORM","TROPICAL STORM GORDON","TSUNAMI","TYPHOON","WATERSPOUT-","WATERSPOUT-TORNADO","WATERSPOUT/ TORNADO","WINTER STORM","WINTER STORM HIGH WINDS","WINTER STORMS","Coastal Storm","DUST STORM","HAIL 0.75","HAIL 075","HAIL 100","HAIL 125","HAIL 150","HAIL 175","HAIL 200","HAIL 275","HAIL 450","HAIL 75","HAIL DAMAGE","HAIL/WIND","HAIL/WINDS","HAILSTORM","LIGHTNING  WAUSEON" ),"EVCAT"] <-"Storm"
 
#Includes an escape vector for the one backslash in the pack
 
cost[cost$EVTYPE%in%c("ICE","ICE AND SNOW","ICE FLOES","ICE JAM","Ice jam flood (minor","ICE JAM FLOODING","ICE ROADS","ICE STORM","ICE/STRONG WINDS","ICY ROADS","LAKE-EFFECT SNOW","Lake Effect Snow","LAKE EFFECT SNOW","LATE SEASON SNOW","Light snow","Light Snow","LIGHT SNOW","Light Snowfall","RECORD COLD","RECORD SNOW","SMALL HAIL","Snow","SNOW","SNOW ACCUMULATION","SNOW AND HEAVY SNOW","SNOW AND ICE","SNOW AND ICE STORM","SNOW FREEZING RAIN","SNOW SQUALL","Snow Squalls","SNOW SQUALLS","SNOW/ BITTER COLD","SNOW/ ICE","SNOW/BLOWING SNOW","SNOW/COLD","SNOW/FREEZING RAIN","SNOW/HEAVY SNOW","SNOW/ICE","SNOW/ICE STORM","SNOW/SLEET","SNOW/SLEET/FREEZING RAIN","SNOWMELT FLOODING","THUNDERSNOW","Unseasonable Cold","AGRICULTURAL FREEZE","BLIZZARD/WINTER STORM","COLD AND WET CONDITIONS","COOL AND WET","Damaging Freeze","DAMAGING FREEZE","UNSEASONABLY COLD","Early Frost","FREEZING FOG","WINTER WEATHER","WINTER WEATHER MIX","WINTER WEATHER/MIX","Wintry Mix","WINTRY MIX","FREEZING RAIN/SLEET","Frost/Freeze","FROST/FREEZE","FROST\\FREEZE","GLAZE ICE","AVALANCHE","GROUND BLIZZARD","BLIZZARD","blowing snow","Cold","COLD","EXCESSIVE SNOW","Extended Cold","Extreme Cold","EXTREME COLD","EXTREME COLD/WIND CHILL","EXTREME WIND CHILL","Freeze","FREEZE","Freezing drizzle","Freezing Drizzle","FREEZING DRIZZLE","Freezing Rain","FREEZING RAIN","FREEZING RAIN/SNOW","FROST","Glaze","GLAZE","HAIL","HARD FREEZE","HEAVY LAKE SNOW","HEAVY RAIN/SNOW","HEAVY SNOW","HEAVY SNOW-SQUALLS","HEAVY SNOW AND STRONG WINDS","Heavy snow shower","HEAVY SNOW SQUALLS","HEAVY SNOW/BLIZZARD","HEAVY SNOW/BLIZZARD/AVALANCHE","HEAVY SNOW/FREEZING RAIN","HEAVY SNOW/HIGH WINDS & FLOOD","HEAVY SNOW/ICE","HEAVY SNOW/SQUALLS","HEAVY SNOW/WIND","HEAVY SNOW/WINTER STORM","HEAVY SNOWPACK"),"EVCAT"] <-"Subzero"
 
cost[cost$EVTYPE%in%c("Heavy Surf","HEAVY SURF","HEAVY SURF/HIGH SURF","HIGH SEAS","High Surf","HIGH SURF","HIGH SWELLS","HIGH WATER","HVY RAIN","Marine Accident","RIP CURRENT","RIP CURRENTS","ROUGH SURF","WATERSPOUT","WET MICROBURST","HIGH SURF ADVISORY","HEAVY SWELLS","HIGH TIDES","LIGHT FREEZING RAIN","Mixed Precipitation","MIXED PRECIPITATION","RAIN","RAINSTORM","RECORD RAINFALL","UNSEASONAL RAIN","ASTRONOMICAL HIGH TIDE","ASTRONOMICAL LOW TIDE","Beach Erosion","COASTAL EROSION","COASTAL SURGE","EXCESSIVE WETNESS","HEAVY MIX","HEAVY PRECIPITATION","HEAVY RAIN","HEAVY RAIN AND FLOOD","Heavy Rain/High Surf","HEAVY RAIN/LIGHTNING","HEAVY RAIN/SEVERE WEATHER","HEAVY RAIN/SMALL STREAM URBAN","HEAVY RAINS","HEAVY SHOWER","   HIGH SURF ADVISORY" ),"EVCAT"] <-"Water(Non-Flood)"
 
cost[cost$EVTYPE%in%c("HIGH WINDS","HIGH WIND","HIGH WIND (G40)","HIGH WIND 48","HIGH WIND AND SEAS","HIGH WIND DAMAGE","HIGH WIND/BLIZZARD","HIGH WIND/HEAVY SNOW","HIGH WIND/SEAS","HIGH WINDS","HIGH WINDS HEAVY RAINS","HIGH WINDS/","HIGH WINDS/COLD","HIGH WINDS/HEAVY RAIN","HIGH WINDS/SNOW","LIGHTNING THUNDERSTORM WINDS","MARINE HIGH WIND","MARINE STRONG WIND","MARINE THUNDERSTORM WIND","MARINE TSTM WIND","MICROBURST WINDS","NON-SEVERE WIND DAMAGE","NON-TSTM WIND","SEVERE THUNDERSTORM WINDS","SNOW/HIGH WINDS","STORM FORCE WINDS","Strong Wind","STRONG WIND","Strong Winds","STRONG WINDS","THUDERSTORM WINDS","THUNDEERSTORM WINDS","THUNDERESTORM WINDS","THUNDERSTORM WINDS","THUNDERSTORM WIND","THUNDERSTORM WIND 60 MPH","THUNDERSTORM WIND 65 MPH","THUNDERSTORM WIND 65MPH","THUNDERSTORM WIND 98 MPH","THUNDERSTORM WIND G50","THUNDERSTORM WIND G55","THUNDERSTORM WIND G60","THUNDERSTORM WIND TREES","THUNDERSTORM WIND.","THUNDERSTORM WIND/ TREE","THUNDERSTORM WIND/ TREES","THUNDERSTORM WIND/AWNING","THUNDERSTORM WIND/HAIL","THUNDERSTORM WIND/LIGHTNING","THUNDERSTORM WINDS","THUNDERSTORM WINDS 13","THUNDERSTORM WINDS 63 MPH","THUNDERSTORM WINDS AND","THUNDERSTORM WINDS G60","THUNDERSTORM WINDS HAIL","THUNDERSTORM WINDS LIGHTNING","THUNDERSTORM WINDS.","THUNDERSTORM WINDS/ FLOOD","THUNDERSTORM WINDS/FLOODING","THUNDERSTORM WINDS/FUNNEL CLOU","THUNDERSTORM WINDS/HAIL","THUNDERSTORM WINDS53","THUNDERSTORM WINDSHAIL","THUNDERSTORM WINDSS","THUNDERSTORM WINS","THUNDERSTORMS WIND","THUNDERSTORMS WINDS","THUNDERSTORMWINDS","THUNDERSTROM WIND","THUNDERTORM WINDS","THUNERSTORM WINDS","TORNADO","TORNADO F0","TORNADO F1","TORNADO F2","TORNADO F3","TORNADOES","TORNADOES, TSTM WIND, HAIL","TORNDAO","Tstm Wind","TSTM WIND","TSTM WIND (G45)","TSTM WIND (41)","TSTM WIND (G35)","TSTM WIND (G40)","TSTM WIND (G45)","TSTM WIND 40","TSTM WIND 45","TSTM WIND 55","TSTM WIND 65)","TSTM WIND AND LIGHTNING","TSTM WIND DAMAGE","TSTM WIND G45","TSTM WIND G58","TSTM WIND/HAIL","TSTM WINDS","TSTMW","TUNDERSTORM WIND","WATERSPOUT TORNADO","WATERSPOUT/TORNADO","Whirlwind","WHIRLWIND","Wind","WIND","WIND AND WAVE","Wind Damage","WIND DAMAGE","WIND STORM","WIND/HAIL","WINDS","TSTM WIND","TSTM WIND (G45)","COLD/WIND CHILL","DENSE FOG","Dust Devil","DUST DEVIL","DUST STORM/HIGH WINDS","EXTREME WINDCHILL","FOG","Microburst","MICROBURST","SEICHE","SEVERE TURBULENCE","COLD AIR TORNADO","FUNNEL CLOUD","DENSE SMOKE","gradient wind","Gradient wind","GRADIENT WIND","DOWNBURST","GUSTNADO","GUSTY WIND","GUSTY WIND/HAIL","GUSTY WIND/HVY RAIN","Gusty wind/rain","Gusty Winds","GUSTY WINDS","HIGH  WINDS", "THUNDERSTORM  WINDS","TSTM WIND  (G45)"," TSTM WIND (G45)"," TSTM WIND"," TSTM WIND"),"EVCAT"] <-"Wind"

Modifying and aggregating “Impact” values

Now that we had the subset, and every EVTYPE was collapsed into the following EVCAT(egories): Dry, Fire, Flood, Ground, Heat, Other, Storm, Subzero, Water(Non-Flood),Wind,

we have to prepare the actual cost data and the injury data for our analysis. hurt\(POPDMG <- hurt\)FATALITIES+hurt$INJURIES

The logic used for the multipliers in the cost fields comes from this particular proof: R Publication on Multipliers

hurt$POPDMG <- hurt$FATALITIES+hurt$INJURIES

cost$CROPMULTI <- 0
cost$PROPMULTI <- 0
 
cost[cost$CROPDMGEXP%in%c("?",""),"CROPMULTI"]<-0
cost[cost$CROPDMGEXP%in%c(2),"CROPMULTI"]<-10
cost[cost$CROPDMGEXP%in%c("B"),"CROPMULTI"]<-1000000000
cost[cost$CROPDMGEXP%in%c("k","K"),"CROPMULTI"]<-1000
cost[cost$CROPDMGEXP%in%c("m","M"),"CROPMULTI"]<-1000000
 
cost[cost$PROPDMGEXP%in%c("-","?",""),"PROPMULTI"]<-0
cost[cost$PROPDMGEXP%in%c("+"),"PROPMULTI"]<-1
cost[cost$PROPDMGEXP%in%c(1,2,3,4,5,6,7,8),"PROPMULTI"]<-10
cost[cost$PROPDMGEXP%in%c("B"),"PROPMULTI"]<-1000000000
cost[cost$PROPDMGEXP%in%c("h","H"),"PROPMULTI"]<-100
cost[cost$PROPDMGEXP%in%c("k","K"),"PROPMULTI"]<-1000
cost[cost$PROPDMGEXP%in%c("m","M"),"PROPMULTI"]<-1000000
 
cost$COSTTOT <- (cost$CROPDMG*cost$CROPMULTI)+(cost$PROPDMG*cost$PROPMULTI)

Preparing to Map

Using the maps package, instead of creating a scatterplot or barchart, one of the easiest ways to express this data in aggregate was a heatmap of the respective values. This required, however, a final bit of data processing to incorporate state information.

hurtagg <- aggregate(hurt$POPDMG,by=c(hurt["EVCAT"],hurt["STATE"]),FUN=sum)
costagg <- aggregate(cost$COSTTOT,by=c(cost["EVCAT"],cost["STATE"]),FUN=sum)
 
hurtagg <- hurtagg[hurtagg$STATE%in%c(state.abb),]
costagg <- costagg[costagg$STATE%in%c(state.abb),]
 
states <- data.frame(state.abb,state.name)
colnames(hurtagg)[2]<-"state.abb"
colnames(costagg)[2]<-"state.abb"
hurtmerge <- merge(states,hurtagg,by="state.abb",all=TRUE)
costmerge <- merge(states,costagg,by="state.abb",all=TRUE)
hurtmerge$state.name <- tolower(hurtmerge$state.name)
costmerge$state.name <- tolower(costmerge$state.name)
statedata<- map_data("state")
 
colnames(hurtmerge)[2]<-"region"
colnames(costmerge)[2]<-"region"

Results

Injuries/Fatalities

With respect to Flooding, Storms and Subzero category events we see a broad distribution of states where they have the most impact on the population’s health (with respect to injuries and fatalities).

Interestingly enough,whereas we’ll see substantially substantially less relative cost (to the other states), in the next group of graphs, with respect to deaths, Wisconsin outshines the other states by a lot with respect to injuries and deaths from “dry” problems.

ggplot() + geom_map(data=statedata, map=statedata,aes(x=long, y=lat, map_id=region),color="white")+geom_map(data=hurtmerge,map=statedata,aes(fill=hurtmerge$x, map_id=region),color="white")+scale_fill_continuous(name="Affected Pop.",low='blue', high='darkred',guide='colorbar')+facet_wrap(~EVCAT)+ggtitle("Total Population (Injuries+Fatalities) of Natural Disaster Categories")
## Warning: Ignoring unknown aesthetics: x, y

Property & Crop Damage

With a fairly consistent spread throughout the data, two areas of notes are the amount of “Dry” damage costs in West Virginia, meaning that drought (among other things) ends up being very expensive for the aggricultural space there.

A deeper dive analysis of whether this was property or crop damage would provide additional detail.

Conversely, the amount of mudslides, landslides and other issues create a lot of cost damage in Idaho, damage I would assume would be moreso related to property damage, but as mentioned should be explored further.

ggplot() + geom_map(data=statedata, map=statedata,aes(x=long, y=lat, map_id=region),color="white")+geom_map(data=costmerge,map=statedata,aes(fill=costmerge$x, map_id=region),color="white")+scale_fill_continuous(name="Total Cost($USD)",low='blue', high='darkred',guide='colorbar')+facet_wrap(~EVCAT)+ggtitle("Total Cost (Property+Crop Damage) of Natural Disaster Categories")
## Warning: Ignoring unknown aesthetics: x, y

Potential Next Steps

  1. Dive into the different between injuries and fatalities and see if there are any correlations between region and fatality rate (out of the entire affected population)

  2. Isolate particular categories defined in this report, and dive down into the specific “EVTYPEs” in the underlying dataset.