The count verb

Data Manipulation with dplyr

James Chapman

Curriculum Manager, DataCamp

Count

counties %>%
  count()

# A tibble: 1 x 1
      n
  <int>
1  3138

Count variable

counties %>%
  count(state)

# A tibble: 50 x 2
   state           n
   <chr>       <int>
 1 Alabama        67
 2 Alaska         28
 3 Arizona        15
 4 Arkansas       75
 5 California     58
 6 Colorado       64
 7 Connecticut     8
 8 Delaware        3
 9 Florida        67
10 Georgia       159
# … with 40 more rows

Count and sort

counties %>%
  count(state, sort = TRUE)

# A tibble: 50 x 2
   state              n
   <chr>          <int>
 1 Texas            253
 2 Georgia          159
 3 Virginia         133
 4 Kentucky         120
 5 Missouri         115
 6 Kansas           105
 7 Illinois         102
 8 North Carolina   100
 9 Iowa              99
10 Tennessee         95
# … with 40 more rows

Count population

counties %>%
  select(state, county, population)

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

Add weight

counties %>%
  count(state, wt = population, sort = TRUE)

# A tibble: 50 x 2
   state                 n
   <chr>             <dbl>
 1 California     38421464
 2 Texas          26538497
 3 New York       19673174
 4 Florida        19645772
 5 Illinois       12873761
 6 Pennsylvania   12779559
 7 Ohio           11575977
 8 Georgia        10006693
 9 Michigan        9900571
10 North Carolina  9845333
# … with 40 more rows

Let's practice!

Data Manipulation with dplyr