Week 4: Apply 3

Import data

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

## # A tibble: 2,808 × 9
##    species date                geo_group region losses   dead discarded escaped
##    <chr>   <dttm>              <chr>     <chr>   <dbl>  <dbl>     <dbl>   <dbl>
##  1 salmon  2020-01-01 00:00:00 area      1       31425  28126      3299       0
##  2 salmon  2020-01-01 00:00:00 area      2      324116 277888     46113       0
##  3 salmon  2020-01-01 00:00:00 area      3      844829 776983     63770       0
##  4 salmon  2020-01-01 00:00:00 area      4      676852 623159     51823       0
##  5 salmon  2020-01-01 00:00:00 area      5      109269  97627     11424       0
##  6 salmon  2020-01-01 00:00:00 area      6      548921 531193     15710       0
##  7 salmon  2020-01-01 00:00:00 area      7      231487 228847      2640       0
##  8 salmon  2020-01-01 00:00:00 area      8      442659 431218     11228       0
##  9 salmon  2020-01-01 00:00:00 area      9      311127 308298      2212       0
## 10 salmon  2020-01-01 00:00:00 area      10     288849 281808      3120       0
## # ℹ 2,798 more rows
## # ℹ 1 more variable: other <dbl>

Plot prices

data %>%
    
    ggplot(aes(region)) +
    geom_bar()