Impact of Severe Weather Events on Health and Economy

Impact of Severe Weather Events on Health and Economy

Synopsis

This analysis explores data from the NOAA Storm Database to identify severe weather events that are most harmful to human health and those causing the greatest economic damage. Tornadoes cause the highest fatalities and injuries, while floods result in substantial property damage. The data is cleaned, transformed, and summarized to provide insights into these impacts.

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Data Processing

Load Libraries

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.4.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.4.3

Load Data

setwd("C:/Users/Aaditya Sadangi/Downloads")
storm_data <- read.csv("repdata_data_StormData.csv.bz2")

Clean and Process Data

processed_data <- storm_data %>%
select(EVTYPE, FATALITIES, INJURIES, PROPDMG, CROPDMG) %>%
group_by(EVTYPE) %>%
summarise(
Total_Fatalities = sum(FATALITIES, na.rm = TRUE),
Total_Injuries = sum(INJURIES, na.rm = TRUE),
Total_Property_Damage = sum(PROPDMG, na.rm = TRUE),
Total_Crop_Damage = sum(CROPDMG, na.rm = TRUE)
) %>%
mutate(Total_Economic_Damage = Total_Property_Damage + Total_Crop_Damage) %>%
arrange(desc(Total_Fatalities))

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Results

Most Harmful Events to Population Health

###Top 10 events by fatalities

top_fatalities <- processed_data %>%
top_n(10, Total_Fatalities)

###Plot

ggplot(top_fatalities, aes(x = reorder(EVTYPE, -Total_Fatalities), y = Total_Fatalities)) +
geom_bar(stat = "identity", fill = "steelblue") +
coord_flip() +
labs(title = "Top 10 Events Most Harmful to Population Health",
x = "Event Type",
y = "Total Fatalities")

Events with Greatest Economic Consequences

###Top 10 events by economic damage

top_economic_damage <- processed_data %>%
top_n(10, Total_Economic_Damage)

###Plot

ggplot(top_economic_damage, aes(x = reorder(EVTYPE, -Total_Economic_Damage), y = Total_Economic_Damage)) +
geom_bar(stat = "identity", fill = "darkgreen") +
coord_flip() +
labs(title = "Top 10 Events with Greatest Economic Consequences",
x = "Event Type",
y = "Total Economic Damage")

Conclusion

This analysis demonstrates that tornadoes are the most harmful weather events to population health due to their high fatality and injury rates. On the other hand, floods have the greatest economic impact due to extensive property damage. These findings highlight the importance of disaster preparedness for minimizing human casualties and financial losses.