Week 4: Apply 3

Import data

# excel file
data <- read_excel("data/myData (1).xlsx")
data

## # A tibble: 6,156 × 35
##    country     country_code  year `Cardiovascular diseases (%)` `Cancers (%)`
##    <chr>       <chr>        <dbl>                         <dbl>         <dbl>
##  1 Afghanistan AFG           1990                          17.6          4.03
##  2 Afghanistan AFG           1991                          17.8          4.05
##  3 Afghanistan AFG           1992                          18.4          4.17
##  4 Afghanistan AFG           1993                          19.0          4.27
##  5 Afghanistan AFG           1994                          19.1          4.26
##  6 Afghanistan AFG           1995                          19.9          4.39
##  7 Afghanistan AFG           1996                          20.4          4.48
##  8 Afghanistan AFG           1997                          20.4          4.45
##  9 Afghanistan AFG           1998                          19.6          4.26
## 10 Afghanistan AFG           1999                          21.1          4.57
## # ℹ 6,146 more rows
## # ℹ 30 more variables: `Respiratory diseases (%)` <dbl>, `Diabetes (%)` <dbl>,
## #   `Dementia (%)` <dbl>, `Lower respiratory infections (%)` <dbl>,
## #   `Neonatal deaths (%)` <dbl>, `Diarrheal diseases (%)` <dbl>,
## #   `Road accidents (%)` <dbl>, `Liver disease (%)` <dbl>,
## #   `Tuberculosis (%)` <dbl>, `Kidney disease (%)` <dbl>,
## #   `Digestive diseases (%)` <dbl>, `HIV/AIDS (%)` <dbl>, …

Plot prices

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