Synopsis

This report analyzes the NOAA Storm Database to assess the impact of severe weather events on population health and economic consequences across the United States. The analysis identifies which types of events are most harmful with respect to population health and which have the greatest economic impact. The findings are intended to help in understanding the severity of different weather events and their consequences.

Data Processing

Data Cleaning

# Convert EVTYPE to uppercase for consistency
storm_data$EVTYPE <- toupper(storm_data$EVTYPE)

# Subset the relevant columns for health and economic analysis
health_data <- storm_data[, c("EVTYPE", "FATALITIES", "INJURIES")]
economic_data <- storm_data[, c("EVTYPE", "PROPDMG", "CROPDMG")]

# Summarize health data
health_impact <- aggregate(cbind(FATALITIES, INJURIES) ~ EVTYPE, data = health_data, sum)

# Summarize economic data
economic_impact <- aggregate(cbind(PROPDMG, CROPDMG) ~ EVTYPE, data = economic_data, sum)

Results

Most Harmful Events with Respect to Population Health

# Sort and select top 10 most harmful events
most_harmful_events <- health_impact %>%
  arrange(desc(FATALITIES), desc(INJURIES)) %>%
  head(10)

# Plot top 10 most harmful events
ggplot(most_harmful_events, aes(x = reorder(EVTYPE, FATALITIES), y = FATALITIES)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "Top 10 Most Harmful Events with Respect to Fatalities", x = "Event Type", y = "Fatalities")

Events with Greatest Economic Consequences

# Sort and select top 10 events with greatest economic consequences
most_damaging_events <- economic_impact %>%
  arrange(desc(PROPDMG), desc(CROPDMG)) %>%
  head(10)

# Plot top 10 events with greatest economic consequences
ggplot(most_damaging_events, aes(x = reorder(EVTYPE, PROPDMG), y = PROPDMG)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "Top 10 Events with Greatest Economic Consequences", x = "Event Type", y = "Property Damage")

Conclusion

The analysis identifies specific types of severe weather events that have the most significant impacts on both population health and economic resources. This information can be useful for understanding which events to prioritize for resource allocation and preparedness planning.