Module 11: Apply it to your data 10

Import your data

dog <- read_excel("../01_module4/data/myData.xlsx") %>% filter(!Length %>% str_detect("Hounds"))

Chapter 15

Create a factor

dog %>% count(Length)

## # A tibble: 3 × 2
##   Length     n
##   <chr>  <int>
## 1 Long      29
## 2 Medium    79
## 3 Short     86

length_hair <- c("Short", "Medium", "Long")

dog_rev <- dog %>%
    mutate(Length = Length %>% factor(levels = length_hair))

Modify factor order

Make two bar charts here - one before ordering another after

dog_summary <- dog_rev %>%
  group_by(Length) %>%
  summarise(
    shed = mean(`Shedding Level`, na.rm = TRUE),
  )

dog_summary

## # A tibble: 3 × 2
##   Length  shed
##   <fct>  <dbl>
## 1 Short   2.73
## 2 Medium  2.68
## 3 Long    2

ggplot(dog_summary, aes(shed, Length)) + geom_point()

ggplot(dog_summary, aes(shed, fct_reorder(Length, shed))) + geom_point()

Modify factor levels

Show examples of three functions:

• fct_recode

dog_rev %>%
    mutate(Length = fct_recode(Length,
                               "Sm" = "Short",
                               "Med" = "Medium",
                               "Lg" = "Long")) %>%
    count(Length)

## # A tibble: 3 × 2
##   Length     n
##   <fct>  <int>
## 1 Sm        86
## 2 Med       79
## 3 Lg        29

• fct_collapse

dog_rev %>%
    mutate(Length = fct_collapse(Length,
                                 Sm = "Short",
                                 Other = c("Medium", "Long"))) %>%
    count(Length)

## # A tibble: 2 × 2
##   Length     n
##   <fct>  <int>
## 1 Sm        86
## 2 Other    108

• fct_lump

dog %>%
    mutate(Length_rev = Length %>% fct_lump_n(1)) %>% 
    count(Length_rev)

## # A tibble: 2 × 2
##   Length_rev     n
##   <fct>      <int>
## 1 Short         86
## 2 Other        108

Chapter 16

No need to do anything here.