Module 11: Apply it to your data 10
Jameson Bourque
Import your data
data <-read.csv("../00_data/Salaries.csv")Chapter 15
Create a factor
Modify factor order
Make two bar charts here - one before ordering another after
data %>%
distinct(rank)## rank
## 1 Prof
## 2 AsstProf
## 3 AssocProfdata %>%
distinct(yrs.since.phd)## yrs.since.phd
## 1 19
## 2 20
## 3 4
## 4 45
## 5 40
## 6 6
## 7 30
## 8 21
## 9 18
## 10 12
## 11 7
## 12 1
## 13 2
## 14 38
## 15 37
## 16 39
## 17 31
## 18 36
## 19 34
## 20 24
## 21 13
## 22 35
## 23 5
## 24 11
## 25 22
## 26 41
## 27 9
## 28 23
## 29 25
## 30 28
## 31 16
## 32 14
## 33 10
## 34 8
## 35 3
## 36 33
## 37 17
## 38 29
## 39 26
## 40 43
## 41 15
## 42 42
## 43 32
## 44 54
## 45 56
## 46 27
## 47 48
## 48 46
## 49 47
## 50 52
## 51 51
## 52 49
## 53 44data %>%
ggplot(aes(x = rank, y = yrs.since.phd))+
geom_point()
Modify factor levels
Show examples of three functions:
- fct_recode
data %>%
mutate(rank_rev = fct_recode(rank,"AssociateP" = "AssocProf")) %>%
select(rank, rank_rev) %>%
filter(rank == "AssocProf")## rank rank_rev
## 1 AssocProf AssociateP
## 2 AssocProf AssociateP
## 3 AssocProf AssociateP
## 4 AssocProf AssociateP
## 5 AssocProf AssociateP
## 6 AssocProf AssociateP
## 7 AssocProf AssociateP
## 8 AssocProf AssociateP
## 9 AssocProf AssociateP
## 10 AssocProf AssociateP
## 11 AssocProf AssociateP
## 12 AssocProf AssociateP
## 13 AssocProf AssociateP
## 14 AssocProf AssociateP
## 15 AssocProf AssociateP
## 16 AssocProf AssociateP
## 17 AssocProf AssociateP
## 18 AssocProf AssociateP
## 19 AssocProf AssociateP
## 20 AssocProf AssociateP
## 21 AssocProf AssociateP
## 22 AssocProf AssociateP
## 23 AssocProf AssociateP
## 24 AssocProf AssociateP
## 25 AssocProf AssociateP
## 26 AssocProf AssociateP
## 27 AssocProf AssociateP
## 28 AssocProf AssociateP
## 29 AssocProf AssociateP
## 30 AssocProf AssociateP
## 31 AssocProf AssociateP
## 32 AssocProf AssociateP
## 33 AssocProf AssociateP
## 34 AssocProf AssociateP
## 35 AssocProf AssociateP
## 36 AssocProf AssociateP
## 37 AssocProf AssociateP
## 38 AssocProf AssociateP
## 39 AssocProf AssociateP
## 40 AssocProf AssociateP
## 41 AssocProf AssociateP
## 42 AssocProf AssociateP
## 43 AssocProf AssociateP
## 44 AssocProf AssociateP
## 45 AssocProf AssociateP
## 46 AssocProf AssociateP
## 47 AssocProf AssociateP
## 48 AssocProf AssociateP
## 49 AssocProf AssociateP
## 50 AssocProf AssociateP
## 51 AssocProf AssociateP
## 52 AssocProf AssociateP
## 53 AssocProf AssociateP
## 54 AssocProf AssociateP
## 55 AssocProf AssociateP
## 56 AssocProf AssociateP
## 57 AssocProf AssociateP
## 58 AssocProf AssociateP
## 59 AssocProf AssociateP
## 60 AssocProf AssociateP
## 61 AssocProf AssociateP
## 62 AssocProf AssociateP
## 63 AssocProf AssociateP
## 64 AssocProf AssociateP- fct_collapse
data %>%
mutate(rank_col = fct_collapse(rank, "Prof" = c("AssocProf","AsstProf"))) %>%
select(rank, rank_col) %>%
filter(rank != "Prof")## rank rank_col
## 1 AsstProf Prof
## 2 AssocProf Prof
## 3 AssocProf Prof
## 4 AsstProf Prof
## 5 AsstProf Prof
## 6 AsstProf Prof
## 7 AssocProf Prof
## 8 AsstProf Prof
## 9 AsstProf Prof
## 10 AsstProf Prof
## 11 AsstProf Prof
## 12 AsstProf Prof
## 13 AsstProf Prof
## 14 AsstProf Prof
## 15 AssocProf Prof
## 16 AssocProf Prof
## 17 AsstProf Prof
## 18 AsstProf Prof
## 19 AssocProf Prof
## 20 AssocProf Prof
## 21 AssocProf Prof
## 22 AssocProf Prof
## 23 AsstProf Prof
## 24 AssocProf Prof
## 25 AsstProf Prof
## 26 AssocProf Prof
## 27 AsstProf Prof
## 28 AssocProf Prof
## 29 AsstProf Prof
## 30 AsstProf Prof
## 31 AsstProf Prof
## 32 AsstProf Prof
## 33 AsstProf Prof
## 34 AssocProf Prof
## 35 AsstProf Prof
## 36 AssocProf Prof
## 37 AssocProf Prof
## 38 AsstProf Prof
## 39 AssocProf Prof
## 40 AssocProf Prof
## 41 AssocProf Prof
## 42 AssocProf Prof
## 43 AssocProf Prof
## 44 AssocProf Prof
## 45 AsstProf Prof
## 46 AsstProf Prof
## 47 AsstProf Prof
## 48 AssocProf Prof
## 49 AsstProf Prof
## 50 AsstProf Prof
## 51 AssocProf Prof
## 52 AssocProf Prof
## 53 AsstProf Prof
## 54 AssocProf Prof
## 55 AssocProf Prof
## 56 AssocProf Prof
## 57 AsstProf Prof
## 58 AsstProf Prof
## 59 AsstProf Prof
## 60 AsstProf Prof
## 61 AssocProf Prof
## 62 AsstProf Prof
## 63 AssocProf Prof
## 64 AsstProf Prof
## 65 AssocProf Prof
## 66 AsstProf Prof
## 67 AssocProf Prof
## 68 AsstProf Prof
## 69 AsstProf Prof
## 70 AssocProf Prof
## 71 AsstProf Prof
## 72 AssocProf Prof
## 73 AssocProf Prof
## 74 AssocProf Prof
## 75 AsstProf Prof
## 76 AssocProf Prof
## 77 AssocProf Prof
## 78 AssocProf Prof
## 79 AssocProf Prof
## 80 AssocProf Prof
## 81 AssocProf Prof
## 82 AsstProf Prof
## 83 AsstProf Prof
## 84 AsstProf Prof
## 85 AsstProf Prof
## 86 AsstProf Prof
## 87 AssocProf Prof
## 88 AssocProf Prof
## 89 AssocProf Prof
## 90 AssocProf Prof
## 91 AsstProf Prof
## 92 AssocProf Prof
## 93 AssocProf Prof
## 94 AsstProf Prof
## 95 AsstProf Prof
## 96 AsstProf Prof
## 97 AsstProf Prof
## 98 AssocProf Prof
## 99 AssocProf Prof
## 100 AsstProf Prof
## 101 AssocProf Prof
## 102 AsstProf Prof
## 103 AsstProf Prof
## 104 AsstProf Prof
## 105 AssocProf Prof
## 106 AssocProf Prof
## 107 AsstProf Prof
## 108 AsstProf Prof
## 109 AssocProf Prof
## 110 AssocProf Prof
## 111 AsstProf Prof
## 112 AsstProf Prof
## 113 AsstProf Prof
## 114 AssocProf Prof
## 115 AssocProf Prof
## 116 AssocProf Prof
## 117 AsstProf Prof
## 118 AssocProf Prof
## 119 AssocProf Prof
## 120 AsstProf Prof
## 121 AsstProf Prof
## 122 AsstProf Prof
## 123 AssocProf Prof
## 124 AssocProf Prof
## 125 AssocProf Prof
## 126 AsstProf Prof
## 127 AsstProf Prof
## 128 AssocProf Prof
## 129 AsstProf Prof
## 130 AssocProf Prof
## 131 AsstProf Prof- fct_lump
data %>% count(rank)## rank n
## 1 AssocProf 64
## 2 AsstProf 67
## 3 Prof 266data %>% mutate(rank_lump = fct_lump(rank)) %>% distinct(rank_lump)## rank_lump
## 1 Prof
## 2 OtherChapter 16
No need to do anything here.