Data Manipulation with dplyr
James Chapman
Curriculum Manager, DataCamp
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
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
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
Select
counties %>%
select(state, county, population, unemployment_rate = unemployment)
Rename
counties %>%
select(state, county, population, unemployment) %>%
rename(unemployment_rate = unemployment)
Data Manipulation with dplyr