Exploring the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database
Marisa Souza
April 18, 2017
Synopsis
This report involves exploring the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database.
This database tracks the characteristics of major storms and weather events in the United States, including when and where they occur. The events in the database start in the year 1950 and end in November 2011.
This analysis address the following questions:
Across the United States, which types of events are most harmful with respect to population health?
Across the United States, which types of events have the greatest economic consequences?
Data Processing
Loading the library
library(plyr)Loading data from the web site
download.file("https://d396qusza40orc.cloudfront.net/repdata%2Fdata%2FStormData.csv.bz2", destfile = "stormdata.bz2")Reading the file created above and putting the values in the “storm” variable
storm = read.csv("stormdata.bz2", header = T, sep = ",")Now, We can see the data and the variables
head(storm)## STATE__ BGN_DATE BGN_TIME TIME_ZONE COUNTY COUNTYNAME STATE
## 1 1 4/18/1950 0:00:00 0130 CST 97 MOBILE AL
## 2 1 4/18/1950 0:00:00 0145 CST 3 BALDWIN AL
## 3 1 2/20/1951 0:00:00 1600 CST 57 FAYETTE AL
## 4 1 6/8/1951 0:00:00 0900 CST 89 MADISON AL
## 5 1 11/15/1951 0:00:00 1500 CST 43 CULLMAN AL
## 6 1 11/15/1951 0:00:00 2000 CST 77 LAUDERDALE AL
## EVTYPE BGN_RANGE BGN_AZI BGN_LOCATI END_DATE END_TIME COUNTY_END
## 1 TORNADO 0 0
## 2 TORNADO 0 0
## 3 TORNADO 0 0
## 4 TORNADO 0 0
## 5 TORNADO 0 0
## 6 TORNADO 0 0
## COUNTYENDN END_RANGE END_AZI END_LOCATI LENGTH WIDTH F MAG FATALITIES
## 1 NA 0 14.0 100 3 0 0
## 2 NA 0 2.0 150 2 0 0
## 3 NA 0 0.1 123 2 0 0
## 4 NA 0 0.0 100 2 0 0
## 5 NA 0 0.0 150 2 0 0
## 6 NA 0 1.5 177 2 0 0
## INJURIES PROPDMG PROPDMGEXP CROPDMG CROPDMGEXP WFO STATEOFFIC ZONENAMES
## 1 15 25.0 K 0
## 2 0 2.5 K 0
## 3 2 25.0 K 0
## 4 2 2.5 K 0
## 5 2 2.5 K 0
## 6 6 2.5 K 0
## LATITUDE LONGITUDE LATITUDE_E LONGITUDE_ REMARKS REFNUM
## 1 3040 8812 3051 8806 1
## 2 3042 8755 0 0 2
## 3 3340 8742 0 0 3
## 4 3458 8626 0 0 4
## 5 3412 8642 0 0 5
## 6 3450 8748 0 0 6colnames(storm)## [1] "STATE__" "BGN_DATE" "BGN_TIME" "TIME_ZONE" "COUNTY"
## [6] "COUNTYNAME" "STATE" "EVTYPE" "BGN_RANGE" "BGN_AZI"
## [11] "BGN_LOCATI" "END_DATE" "END_TIME" "COUNTY_END" "COUNTYENDN"
## [16] "END_RANGE" "END_AZI" "END_LOCATI" "LENGTH" "WIDTH"
## [21] "F" "MAG" "FATALITIES" "INJURIES" "PROPDMG"
## [26] "PROPDMGEXP" "CROPDMG" "CROPDMGEXP" "WFO" "STATEOFFIC"
## [31] "ZONENAMES" "LATITUDE" "LONGITUDE" "LATITUDE_E" "LONGITUDE_"
## [36] "REMARKS" "REFNUM"Analysis
Initially the analysis will cover the issue below:
Across the United States, which types of events are most harmful with respect to population health?
To answer this question the code bellow aggregate the events and adding fatalities and injuries, because these two variables indicate which events are most harmful with respect to population health
h = aggregate(storm$FATALITIES+storm$INJURIES ~ storm$EVTYPE, sum, data = storm)
colnames(h) = c("EVTYPE", "SUM_ESTIMATES")
head(h)## EVTYPE SUM_ESTIMATES
## 1 HIGH SURF ADVISORY 0
## 2 COASTAL FLOOD 0
## 3 FLASH FLOOD 0
## 4 LIGHTNING 0
## 5 TSTM WIND 0
## 6 TSTM WIND (G45) 0Now the code below orders the data and sets the 10 most harmful events
h = head(h[order(h$SUM_ESTIMATES, decreasing = T),],10)
h## EVTYPE SUM_ESTIMATES
## 834 TORNADO 96979
## 130 EXCESSIVE HEAT 8428
## 856 TSTM WIND 7461
## 170 FLOOD 7259
## 464 LIGHTNING 6046
## 275 HEAT 3037
## 153 FLASH FLOOD 2755
## 427 ICE STORM 2064
## 760 THUNDERSTORM WIND 1621
## 972 WINTER STORM 1527The code below creates a barplot with the most harmful events
barplot(h$SUM_ESTIMATES,
names.arg = h$EVTYPE,
cex.names = 0.4,
main = "Events are most harmful with respect to population health",
xlab = "Type of Event",
ylab = "Sum of Injuries and Fatalities")
Now the analysis will cover the issue below:
Across the United States, which types of events have the greatest economic consequences?
To answer this question the variables PROPDMG, CROPDMG, PROPDMGEXP and CROPDMGEXP were used.
The variables PROPDMG and CROPDMG indicate the value of damages in the events.
The variables PROPDMGEXP and CROPDMGEXP indicate alphabetical characters used to signify magnitude.
include “K” for thousands, “M” for millions, and “B” for billions.
Therefore, the PROPDMG and CROPDMG variables will be multiplied accordingly with, “M”, “K”, “B” which mean 1000000, 1000, 1000000000 respectively.
storm$PROPDMGEXP_NEW = ifelse(storm$PROPDMGEXP== "K", 1000,
ifelse(storm$PROPDMGEXP== "M", 1000000,
ifelse(storm$PROPDMGEXP == "B", 1000000000, 1)
)
)
storm$CROPDMGEXP_NEW = ifelse(storm$CROPDMGEXP== "K", 1000,
ifelse(storm$CROPDMGEXP== "M", 1000000,
ifelse(storm$CROPDMGEXP == "B", 1000000000, 1)
)
)
storm$PROPTOTALDMG = as.numeric(storm$PROPDMGEXP_NEW) * storm$PROPDMG
storm$CROPTOTALDMG = as.numeric(storm$CROPDMGEXP_NEW) * storm$CROPDMGLastly, the variables PROPTOTALDMG and CROPTOTALDMG were add to obtain the total sum of the damages.
storm$TOTALDMG = storm$PROPTOTALDMG + storm$CROPTOTALDMGNow the code below aggregates the events and sum of damage
h = aggregate(storm$TOTALDMG~storm$EVTYPE , sum, data = storm)
colnames(h) = c("EVTYPE", "SUM_TOTALDMG")
head(h)## EVTYPE SUM_TOTALDMG
## 1 HIGH SURF ADVISORY 200000
## 2 COASTAL FLOOD 0
## 3 FLASH FLOOD 50000
## 4 LIGHTNING 0
## 5 TSTM WIND 8100000
## 6 TSTM WIND (G45) 8000The code below orders the data and sets the 10 events with the greatest economic consequences
h = head(h[order(h$SUM_TOTALDMG, decreasing = T),],10)
h## EVTYPE SUM_TOTALDMG
## 170 FLOOD 150319678257
## 411 HURRICANE/TYPHOON 71913712800
## 834 TORNADO 57340614060
## 670 STORM SURGE 43323541000
## 244 HAIL 18752904943
## 153 FLASH FLOOD 17562129167
## 95 DROUGHT 15018672000
## 402 HURRICANE 14610229010
## 590 RIVER FLOOD 10148404500
## 427 ICE STORM 8967041360Now the code below creates a barplot with the greatest economic consequences
barplot(h$SUM_TOTALDMG,
names.arg = h$EVTYPE,
cex.names = 0.4,
main = "Events with the greatest economic consequences",
xlab = "Type of Event",
ylab = "Sum of damage ($USD)")
Results
Across the United States, which types of events are most harmful with respect to population health?
We can see in the first chart above that the most harmful event is the Tornado event.
Across the United States, which types of events have the greatest economic consequences?
We can see in the second chart above that the event with the greatest economic consequences is the Flood event