Module 6: Apply 5

Import data

# excel file
fires <- read_excel("myData.xlsx")
data

Filter rows

fires3 <- filter(fires, YEAR == 2)

Arrange rows

arrange(fires, desc(YEAR))

Select columns

select(fires, YEAR:DAMAGE_COSTS)
select(fires, ACRES_BURNED, DAMAGE_COSTS)
select(fires, YEAR, contains("Acre"))

Add columns

transmute(fires,
          gain = DAMAGE_COSTS/ACRES_BURNED)

# lag()
select(fires, DAMAGE_COSTS) %>%
    
    mutate(DMAAGE_COSTS_lag1 = lag(DAMAGE_COSTS))

Summarize by groups

fires %>%
    group_by(YEAR) %>%
    summarise(count = n(),
              dam = mean(DAMAGE_COSTS, na.rm = TRUE),
              acre = mean(ACRES_BURNED, na.rm = TRUE)) %>%
    
    # Plot
    ggplot(mapping = aes(x = dam, y = acre)) +
    geom_point()