2  inClass1

library(dplyr)

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

starwars %>%
  select(name, height, skin_color) %>%
  slice(1:20) %>%
  count(name)

# A tibble: 20 × 2
   name                      n
   <chr>                 <int>
 1 Anakin Skywalker          1
 2 Beru Whitesun lars        1
 3 Biggs Darklighter         1
 4 C-3PO                     1
 5 Chewbacca                 1
 6 Darth Vader               1
 7 Greedo                    1
 8 Han Solo                  1
 9 Jabba Desilijic Tiure     1
10 Jek Tono Porkins          1
11 Leia Organa               1
12 Luke Skywalker            1
13 Obi-Wan Kenobi            1
14 Owen Lars                 1
15 Palpatine                 1
16 R2-D2                     1
17 R5-D4                     1
18 Wedge Antilles            1
19 Wilhuff Tarkin            1
20 Yoda                      1

starwars

# A tibble: 87 × 14
   name     height  mass hair_color skin_color eye_color birth_year sex   gender
   <chr>     <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> <chr> 
 1 Luke Sk…    172    77 blond      fair       blue            19   male  mascu…
 2 C-3PO       167    75 <NA>       gold       yellow         112   none  mascu…
 3 R2-D2        96    32 <NA>       white, bl… red             33   none  mascu…
 4 Darth V…    202   136 none       white      yellow          41.9 male  mascu…
 5 Leia Or…    150    49 brown      light      brown           19   fema… femin…
 6 Owen La…    178   120 brown, gr… light      blue            52   male  mascu…
 7 Beru Wh…    165    75 brown      light      blue            47   fema… femin…
 8 R5-D4        97    32 <NA>       white, red red             NA   none  mascu…
 9 Biggs D…    183    84 black      light      brown           24   male  mascu…
10 Obi-Wan…    182    77 auburn, w… fair       blue-gray       57   male  mascu…
# ℹ 77 more rows
# ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
#   vehicles <list>, starships <list>

library(dplyr)
storms

# A tibble: 19,066 × 13
   name   year month   day  hour   lat  long status      category  wind pressure
   <chr> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <fct>          <dbl> <int>    <int>
 1 Amy    1975     6    27     0  27.5 -79   tropical d…       NA    25     1013
 2 Amy    1975     6    27     6  28.5 -79   tropical d…       NA    25     1013
 3 Amy    1975     6    27    12  29.5 -79   tropical d…       NA    25     1013
 4 Amy    1975     6    27    18  30.5 -79   tropical d…       NA    25     1013
 5 Amy    1975     6    28     0  31.5 -78.8 tropical d…       NA    25     1012
 6 Amy    1975     6    28     6  32.4 -78.7 tropical d…       NA    25     1012
 7 Amy    1975     6    28    12  33.3 -78   tropical d…       NA    25     1011
 8 Amy    1975     6    28    18  34   -77   tropical d…       NA    30     1006
 9 Amy    1975     6    29     0  34.4 -75.8 tropical s…       NA    35     1004
10 Amy    1975     6    29     6  34   -74.8 tropical s…       NA    40     1002
# ℹ 19,056 more rows
# ℹ 2 more variables: tropicalstorm_force_diameter <int>,
#   hurricane_force_diameter <int>