select Keep the variables name, eye_color, and films.filter select blonds.filter select female blonds.mutate Convert height in centimeters to feet.summarize Calculate mean height in feetgroup_by and summarize Calculate mean height by gender.spread Convert the dataset, mean_height, to a wide dataset.In this exercise you will learn to clean data using the dplyr package. To this end, you will follow through the codes in one of our e-texts, Data Visualization with R. The given example code below is from Chapter 1.2 Cleaning data.
## # A tibble: 87 x 13
## name height mass hair_color skin_color eye_color birth_year gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr>
## 1 Luke… 172 77 blond fair blue 19 male
## 2 C-3PO 167 75 <NA> gold yellow 112 <NA>
## 3 R2-D2 96 32 <NA> white, bl… red 33 <NA>
## 4 Dart… 202 136 none white yellow 41.9 male
## 5 Leia… 150 49 brown light brown 19 female
## 6 Owen… 178 120 brown, gr… light blue 52 male
## 7 Beru… 165 75 brown light blue 47 female
## 8 R5-D4 97 32 <NA> white, red red NA <NA>
## 9 Bigg… 183 84 black light brown 24 male
## 10 Obi-… 182 77 auburn, w… fair blue-gray 57 male
## # … with 77 more rows, and 5 more variables: homeworld <chr>, species <chr>,
## # films <list>, vehicles <list>, starships <list>select Keep the variables name, eye_color, and films.filter select blonds.## # A tibble: 19 x 13
## name height mass hair_color skin_color eye_color birth_year gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr>
## 1 Leia… 150 49 brown light brown 19 female
## 2 Beru… 165 75 brown light blue 47 female
## 3 Mon … 150 NA auburn fair blue 48 female
## 4 Shmi… 163 NA black fair brown 72 female
## 5 Ayla… 178 55 none blue hazel 48 female
## 6 Adi … 184 50 none dark blue NA female
## 7 Cordé 157 NA brown light brown NA female
## 8 Lumi… 170 56.2 black yellow blue 58 female
## 9 Barr… 166 50 black yellow blue 40 female
## 10 Dormé 165 NA brown light brown NA female
## 11 Zam … 168 55 blonde fair, gre… yellow NA female
## 12 Taun… 213 NA none grey black NA female
## 13 Joca… 167 NA white fair blue NA female
## 14 R4-P… 96 NA none silver, r… red, blue NA female
## 15 Shaa… 178 57 none red, blue… black NA female
## 16 Sly … 178 48 none pale white NA female
## 17 Rey NA NA brown light hazel NA female
## 18 Capt… NA NA unknown unknown unknown NA female
## 19 Padm… 165 45 brown light brown 46 female
## # … with 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>filter select female blonds.## # A tibble: 0 x 13
## # … with 13 variables: name <chr>, height <int>, mass <dbl>, hair_color <chr>,
## # skin_color <chr>, eye_color <chr>, birth_year <dbl>, gender <chr>,
## # homeworld <chr>, species <chr>, films <list>, vehicles <list>,
## # starships <list>mutate Convert height in centimeters to feet.Hint: Divide the length value by 30.48.
summarize Calculate mean height in feetgroup_by and summarize Calculate mean height by gender.Hint: Use%>%, the pipe operator. Save the result under a new name, mean_height.
spread Convert the dataset, mean_height, to a wide dataset.## # A tibble: 5 x 6
## mean_wt female hermaphrodite male none `<NA>`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 46.3 NA NA NA NA 120
## 2 54.0 165. NA NA NA NA
## 3 81.0 NA NA 179. NA NA
## 4 140 NA NA NA 200 NA
## 5 1358 NA 175 NA NA NAHint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.