Verba rename

Manipulasi Data dengan dplyr

James Chapman

Curriculum Manager, DataCamp

Pilih kolom

counties_selected <- counties %>%
  select(state, county, population, unemployment)

counties_selected

# A tibble: 3,138 x 4
   state   county   population unemployment
   <chr>   <chr>         <dbl>        <dbl>
 1 Alabama Autauga       55221          7.6
 2 Alabama Baldwin      195121          7.5
 3 Alabama Barbour       26932         17.6
 4 Alabama Bibb          22604          8.3
 5 Alabama Blount        57710          7.7
 6 Alabama Bullock       10678         18  
 7 Alabama Butler        20354          10.9
 8 Alabama Calhoun      116648          12.3
 9 Alabama Chambers      34079           8.9
10 Alabama Cherokee      26008           7.9
# … with 3,128 more rows

Ubah nama kolom

counties_selected %>%
  rename(unemployment_rate = unemployment)

# A tibble: 3,138 x 4
   state   county   population unemployment_rate
   <chr>   <chr>         <dbl>             <dbl>
 1 Alabama Autauga       55221               7.6
 2 Alabama Baldwin      195121               7.5
 3 Alabama Barbour       26932              17.6
 4 Alabama Bibb          22604               8.3
 5 Alabama Blount        57710               7.7
 6 Alabama Bullock       10678              18  
 7 Alabama Butler        20354              10.9
 8 Alabama Calhoun      116648              12.3
 9 Alabama Chambers      34079               8.9
10 Alabama Cherokee      26008               7.9
# … with 3,128 more rows

Gabungkan verba

counties_selected %>%
  select(state, county, population, unemployment_rate = unemployment)

# A tibble: 3,138 x 4
   state   county   population unemployment_rate
   <chr>   <chr>         <dbl>             <dbl>
 1 Alabama Autauga       55221               7.6
 2 Alabama Baldwin      195121               7.5
 3 Alabama Barbour       26932              17.6
 4 Alabama Bibb          22604               8.3
 5 Alabama Blount        57710               7.7
 6 Alabama Bullock       10678              18  
 7 Alabama Butler        20354              10.9
 8 Alabama Calhoun      116648              12.3
 9 Alabama Chambers      34079               8.9
10 Alabama Cherokee      26008               7.9
# … with 3,128 more rows

Bandingkan verba

Select

counties %>%
  select(state, county, population, unemployment_rate = unemployment)

Rename

counties %>%
  select(state, county, population, unemployment) %>%
  rename(unemployment_rate = unemployment)

Ayo berlatih!

Manipulasi Data dengan dplyr