Week 4: Apply 3

Import data

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

## # A tibble: 2,557 × 29
##    spec_name            acc_genus acc_species palm_tribe palm_subfamily climbing
##    <chr>                <chr>     <chr>       <chr>      <chr>          <chr>   
##  1 Acanthophoenix crin… Acanthop… crinita     Areceae    Arecoideae     climbing
##  2 Acanthophoenix rous… Acanthop… rousselii   Areceae    Arecoideae     climbing
##  3 Acanthophoenix rubra Acanthop… rubra       Areceae    Arecoideae     climbing
##  4 Acoelorrhaphe wrigh… Acoelorr… wrightii    Trachycar… Coryphoideae   climbing
##  5 Acrocomia aculeata   Acrocomia aculeata    Cocoseae   Arecoideae     climbing
##  6 Acrocomia crispa     Acrocomia crispa      Cocoseae   Arecoideae     climbing
##  7 Acrocomia emensis    Acrocomia emensis     Cocoseae   Arecoideae     climbing
##  8 Acrocomia glaucesce… Acrocomia glaucescens Cocoseae   Arecoideae     climbing
##  9 Acrocomia hassleri   Acrocomia hassleri    Cocoseae   Arecoideae     climbing
## 10 Acrocomia intumesce… Acrocomia intumescens Cocoseae   Arecoideae     climbing
## # ℹ 2,547 more rows
## # ℹ 23 more variables: acaulescent <chr>, erect <chr>, stem_solitary <chr>,
## #   stem_armed <chr>, leaves_armed <chr>, max_stem_height_m <chr>,
## #   max_stem_dia_cm <chr>, understorey_canopy <chr>, max_leaf_number <chr>,
## #   max__blade__length_m <chr>, max__rachis__length_m <chr>,
## #   max__petiole_length_m <chr>, average_fruit_length_cm <chr>,
## #   min_fruit_length_cm <chr>, max_fruit_length_cm <chr>, …

Plot data

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