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.
# Load package
library(tidyverse)
# Import data
data(starwars)
starwarsselect Keep the variables name, eye_color, and films.select(starwars, name, eye_color, films)## # A tibble: 87 x 3
## name eye_color films
## <chr> <chr> <list>
## 1 Luke Skywalker blue <chr [5]>
## 2 C-3PO yellow <chr [6]>
## 3 R2-D2 red <chr [7]>
## 4 Darth Vader yellow <chr [4]>
## 5 Leia Organa brown <chr [5]>
## 6 Owen Lars blue <chr [3]>
## 7 Beru Whitesun lars blue <chr [3]>
## 8 R5-D4 red <chr [1]>
## 9 Biggs Darklighter brown <chr [1]>
## 10 Obi-Wan Kenobi blue-gray <chr [6]>
## # … with 77 more rowsfilter select blonds.filter(starwars, hair_color == "blond")## # A tibble: 3 x 13
## name height mass hair_color skin_color eye_color birth_year gender homeworld
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke… 172 77 blond fair blue 19 male Tatooine
## 2 Anak… 188 84 blond fair blue 41.9 male Tatooine
## 3 Fini… 170 NA blond fair blue 91 male Coruscant
## # … with 4 more variables: species <chr>, films <list>, vehicles <list>,
## # starships <list>filter select female blonds.filter(starwars, gender == "female" & hair_color == "blond")## # 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.
starwars <- mutate(starwars, height = height / 30.48)summarize Calculate mean height in feetsummarize(starwars, mean_ht = mean(height, na.rm=TRUE))## # A tibble: 1 x 1
## mean_ht
## <dbl>
## 1 5.72group_by and summarize Calculate mean height by gender.Hint: Use%>%, the pipe operator. Save the result under a new name, mean_height.
newdata <- group_by(starwars, gender)
newdata <- summarize(newdata,
mean_ht = mean(height, na.rm=TRUE))
newdata## # A tibble: 5 x 2
## gender mean_ht
## <chr> <dbl>
## 1 female 5.43
## 2 hermaphrodite 5.74
## 3 male 5.88
## 4 none 6.56
## 5 <NA> 3.94spread Convert the dataset, mean_height, to a wide dataset.wide_data <- spread(newdata, gender, mean_ht)
wide_data## # A tibble: 1 x 5
## female hermaphrodite male none `<NA>`
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 5.43 5.74 5.88 6.56 3.94gather(wide_data,
key="gender",
value="mean_ht",
female:`<NA>`)## # A tibble: 5 x 2
## gender mean_ht
## <chr> <dbl>
## 1 female 5.43
## 2 hermaphrodite 5.74
## 3 male 5.88
## 4 none 6.56
## 5 <NA> 3.94Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.