Le verbe rename

Manipulation de données avec dplyr

James Chapman

Curriculum Manager, DataCamp

Sélectionner des colonnes

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
Manipulation de données avec dplyr

Renommer une colonne

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
Manipulation de données avec dplyr

Combiner des verbes

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
Manipulation de données avec dplyr

Comparer les verbes

Select

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

Rename

counties %>%
  select(state, county, population, unemployment) %>%
  rename(unemployment_rate = unemployment)
Manipulation de données avec dplyr

Passons à la pratique !

Manipulation de données avec dplyr

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