![]() ![]() ![]() ![]() by_vs #> # A tibble: 4 × 3 #> # Groups: vs #> vs am n #> #> 1 0 0 12 #> 2 0 1 6 #> 3 1 0 7 #> 4 1 1 7 by_vs %>% summarise (n = sum ( n ) ) #> # A tibble: 2 × 2 #> vs n #> #> 1 0 18 #> 2 1 14 # To removing grouping, use ungroup by_vs %>% ungroup ( ) %>% summarise (n = sum ( n ) ) #> # A tibble: 1 × 1 #> n #> #> 1 32 # By default, group_by() overrides existing grouping by_cyl %>% group_by ( vs, am ) %>% group_vars ( ) #> "vs" "am" # Use add = TRUE to instead append by_cyl %>% group_by ( vs, am. You can override using the #> `.groups` argument. ![]() 123 3.92 3.44 18.3 1 0 4 4 #> # ℹ 22 more rows # It changes how it acts with the other dplyr verbs: by_cyl %>% summarise ( disp = mean ( disp ), hp = mean ( hp ) ) #> # A tibble: 3 × 3 #> cyl disp hp #> #> 1 4 105. Library ( dplyr ) starwars %>% filter ( species = "Droid" ) #> # A tibble: 6 × 14 #> name height mass hair_color skin_color eye_color birth_year sex gender #> #> 1 C-3PO 167 75 gold yellow 112 none masculi… #> 2 R2-D2 96 32 white, blue red 33 none masculi… #> 3 R5-D4 97 32 white, red red NA none masculi… #> 4 IG-88 200 140 none metal red 15 none masculi… #> 5 R4-P17 96 NA none silver, red red, blue NA none feminine #> # ℹ 1 more row #> # ℹ 5 more variables: homeworld, species, films, #> # vehicles, starships starwars %>% select ( name, ends_with ( "color" ) ) #> # A tibble: 87 × 4 #> name hair_color skin_color eye_color #> #> 1 Luke Skywalker blond fair blue #> 2 C-3PO gold yellow #> 3 R2-D2 white, blue red #> 4 Darth Vader none white yellow #> 5 Leia Organa brown light brown #> # ℹ 82 more rows starwars %>% mutate ( name, bmi = mass / ( ( height / 100 ) ^ 2 ) ) %>% select ( name : mass, bmi ) #> # A tibble: 87 × 4 #> name height mass bmi #> #> 1 Luke Skywalker 172 77 26.0 #> 2 C-3PO 167 75 26.9 #> 3 R2-D2 96 32 34.7 #> 4 Darth Vader 202 136 33.3 #> 5 Leia Organa 150 49 21.8 #> # ℹ 82 more rows starwars %>% arrange ( desc ( mass ) ) #> # A tibble: 87 × 14 #> name height mass hair_color skin_color eye_color birth_year sex gender #> #> 1 Jabba De… 175 1358 green-tan… orange 600 herm… mascu… #> 2 Grievous 216 159 none brown, wh… green, y… NA male mascu… #> 3 IG-88 200 140 none metal red 15 none mascu… #> 4 Darth Va… 202 136 none white yellow 41.9 male mascu… #> 5 Tarfful 234 136 brown brown blue NA male mascu… #> # ℹ 82 more rows #> # ℹ 5 more variables: homeworld, species, films, #> # vehicles, starships starwars %>% group_by ( species ) %>% summarise ( n = n ( ), mass = mean ( mass, na.rm = TRUE ) ) %>% filter ( n > 1, mass > 50 ) #> # A tibble: 8 × 3 #> species n mass #> #> 1 Droid 6 69.8 #> 2 Gungan 3 74 #> 3 Human 35 82.8 #> 4 Kaminoan 2 88 #> 5 Mirialan 2 53.By_cyl % group_by ( cyl ) # grouping doesn't change how the data looks (apart from listing # how it's grouped): by_cyl #> # A tibble: 32 × 11 #> # Groups: cyl #> mpg cyl disp hp drat wt qsec vs am gear carb #> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. ![]()
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