Module 8
Asher Ireland
06/06/2023
Introduction
This report will work on basic usage of dplyr in conjuction with ggplot2 using R, RStudio and knitr. The goal of this report is to:
- Practice dplyr
- Continue practicing previous concepts
##Read in the data and convert Subject to a factor
library(dplyr)## Warning: package 'dplyr' was built under R version 4.2.3##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(ggplot2)## Warning: package 'ggplot2' was built under R version 4.2.3theoph <- read.csv("theoph.csv")
theoph$Subject = factor(theoph$Subject)##Create a data frame with only Subject ID, Time, and Concentration Variables
theoph %>%
select(Subject,Time,conc)## Subject Time conc
## 1 1 0.00 0.74
## 2 1 0.25 2.84
## 3 1 0.57 6.57
## 4 1 1.12 10.50
## 5 1 2.02 9.66
## 6 1 3.82 8.58
## 7 1 5.10 8.36
## 8 1 7.03 7.47
## 9 1 9.05 6.89
## 10 1 12.12 5.94
## 11 1 24.37 3.28
## 12 2 0.00 0.00
## 13 2 0.27 1.72
## 14 2 0.52 7.91
## 15 2 1.00 8.31
## 16 2 1.92 8.33
## 17 2 3.50 6.85
## 18 2 5.02 6.08
## 19 2 7.03 5.40
## 20 2 9.00 4.55
## 21 2 12.00 3.01
## 22 2 24.30 0.90
## 23 3 0.00 0.00
## 24 3 0.27 4.40
## 25 3 0.58 6.90
## 26 3 1.02 8.20
## 27 3 2.02 7.80
## 28 3 3.62 7.50
## 29 3 5.08 6.20
## 30 3 7.07 5.30
## 31 3 9.00 4.90
## 32 3 12.15 3.70
## 33 3 24.17 1.05
## 34 4 0.00 0.00
## 35 4 0.35 1.89
## 36 4 0.60 4.60
## 37 4 1.07 8.60
## 38 4 2.13 8.38
## 39 4 3.50 7.54
## 40 4 5.02 6.88
## 41 4 7.02 5.78
## 42 4 9.02 5.33
## 43 4 11.98 4.19
## 44 4 24.65 1.15
## 45 5 0.00 0.00
## 46 5 0.30 2.02
## 47 5 0.52 5.63
## 48 5 1.00 11.40
## 49 5 2.02 9.33
## 50 5 3.50 8.74
## 51 5 5.02 7.56
## 52 5 7.02 7.09
## 53 5 9.10 5.90
## 54 5 12.00 4.37
## 55 5 24.35 1.57
## 56 6 0.00 0.00
## 57 6 0.27 1.29
## 58 6 0.58 3.08
## 59 6 1.15 6.44
## 60 6 2.03 6.32
## 61 6 3.57 5.53
## 62 6 5.00 4.94
## 63 6 7.00 4.02
## 64 6 9.22 3.46
## 65 6 12.10 2.78
## 66 6 23.85 0.92
## 67 7 0.00 0.15
## 68 7 0.25 0.85
## 69 7 0.50 2.35
## 70 7 1.02 5.02
## 71 7 2.02 6.58
## 72 7 3.48 7.09
## 73 7 5.00 6.66
## 74 7 6.98 5.25
## 75 7 9.00 4.39
## 76 7 12.05 3.53
## 77 7 24.22 1.15
## 78 8 0.00 0.00
## 79 8 0.25 3.05
## 80 8 0.52 3.05
## 81 8 0.98 7.31
## 82 8 2.02 7.56
## 83 8 3.53 6.59
## 84 8 5.05 5.88
## 85 8 7.15 4.73
## 86 8 9.07 4.57
## 87 8 12.10 3.00
## 88 8 24.12 1.25
## 89 9 0.00 0.00
## 90 9 0.30 7.37
## 91 9 0.63 9.03
## 92 9 1.05 7.14
## 93 9 2.02 6.33
## 94 9 3.53 5.66
## 95 9 5.02 5.67
## 96 9 7.17 4.24
## 97 9 8.80 4.11
## 98 9 11.60 3.16
## 99 9 24.43 1.12
## 100 10 0.00 0.24
## 101 10 0.37 2.89
## 102 10 0.77 5.22
## 103 10 1.02 6.41
## 104 10 2.05 7.83
## 105 10 3.55 10.21
## 106 10 5.05 9.18
## 107 10 7.08 8.02
## 108 10 9.38 7.14
## 109 10 12.10 5.68
## 110 10 23.70 2.42
## 111 11 0.00 0.00
## 112 11 0.25 4.86
## 113 11 0.50 7.24
## 114 11 0.98 8.00
## 115 11 1.98 6.81
## 116 11 3.60 5.87
## 117 11 5.02 5.22
## 118 11 7.03 4.45
## 119 11 9.03 3.62
## 120 11 12.12 2.69
## 121 11 24.08 0.86
## 122 12 0.00 0.00
## 123 12 0.25 1.25
## 124 12 0.50 3.96
## 125 12 1.00 7.82
## 126 12 2.00 9.72
## 127 12 3.52 9.75
## 128 12 5.07 8.57
## 129 12 7.07 6.59
## 130 12 9.03 6.11
## 131 12 12.05 4.57
## 132 12 24.15 1.17##Create a data frame with a single row for each subject, with ID, weight, and dose
theoph %>%
select(Subject,Wt,Dose) %>%
distinct(Subject, Wt, Dose)## Subject Wt Dose
## 1 1 79.6 4.02
## 2 2 72.4 4.40
## 3 3 70.5 4.53
## 4 4 72.7 4.40
## 5 5 54.6 5.86
## 6 6 80.0 4.00
## 7 7 64.6 4.95
## 8 8 70.5 4.53
## 9 9 86.4 3.10
## 10 10 58.2 5.50
## 11 11 65.0 4.92
## 12 12 60.5 5.30##Create a data frame with only the first subject
filter(theoph, Subject==1)## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58
## 7 1 79.6 4.02 5.10 8.36
## 8 1 79.6 4.02 7.03 7.47
## 9 1 79.6 4.02 9.05 6.89
## 10 1 79.6 4.02 12.12 5.94
## 11 1 79.6 4.02 24.37 3.28Create a data frame with only the first four subjects
filter(theoph, Subject %in% c("1","2","3","4"))## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58
## 7 1 79.6 4.02 5.10 8.36
## 8 1 79.6 4.02 7.03 7.47
## 9 1 79.6 4.02 9.05 6.89
## 10 1 79.6 4.02 12.12 5.94
## 11 1 79.6 4.02 24.37 3.28
## 12 2 72.4 4.40 0.00 0.00
## 13 2 72.4 4.40 0.27 1.72
## 14 2 72.4 4.40 0.52 7.91
## 15 2 72.4 4.40 1.00 8.31
## 16 2 72.4 4.40 1.92 8.33
## 17 2 72.4 4.40 3.50 6.85
## 18 2 72.4 4.40 5.02 6.08
## 19 2 72.4 4.40 7.03 5.40
## 20 2 72.4 4.40 9.00 4.55
## 21 2 72.4 4.40 12.00 3.01
## 22 2 72.4 4.40 24.30 0.90
## 23 3 70.5 4.53 0.00 0.00
## 24 3 70.5 4.53 0.27 4.40
## 25 3 70.5 4.53 0.58 6.90
## 26 3 70.5 4.53 1.02 8.20
## 27 3 70.5 4.53 2.02 7.80
## 28 3 70.5 4.53 3.62 7.50
## 29 3 70.5 4.53 5.08 6.20
## 30 3 70.5 4.53 7.07 5.30
## 31 3 70.5 4.53 9.00 4.90
## 32 3 70.5 4.53 12.15 3.70
## 33 3 70.5 4.53 24.17 1.05
## 34 4 72.7 4.40 0.00 0.00
## 35 4 72.7 4.40 0.35 1.89
## 36 4 72.7 4.40 0.60 4.60
## 37 4 72.7 4.40 1.07 8.60
## 38 4 72.7 4.40 2.13 8.38
## 39 4 72.7 4.40 3.50 7.54
## 40 4 72.7 4.40 5.02 6.88
## 41 4 72.7 4.40 7.02 5.78
## 42 4 72.7 4.40 9.02 5.33
## 43 4 72.7 4.40 11.98 4.19
## 44 4 72.7 4.40 24.65 1.15Calculate the average concentration per subject (across all times)
theoph %>%
group_by(Subject)%>%
summarise(avgConc=mean(conc))## # A tibble: 12 × 2
## Subject avgConc
## <fct> <dbl>
## 1 1 6.44
## 2 2 4.82
## 3 3 5.09
## 4 4 4.94
## 5 5 5.78
## 6 6 3.53
## 7 7 3.91
## 8 8 4.27
## 9 9 4.89
## 10 10 5.93
## 11 11 4.51
## 12 12 5.41Create a data fram with only the first subject and create a ggplot with Time and Conc
theoph%>%
filter(Subject==1) %>%
ggplot(aes(x=Time, y=conc))+geom_line()
Create a line plot with time and concentration for all subjects colored by subject
theoph%>%
select(Subject,Time,conc)%>%
ggplot(aes(x=Time, y=conc,color=Subject))+geom_line()
Create a line plot with time and concentration for all subjects faceted by subject ID
theoph%>%
select(Subject,Time,conc)%>%
ggplot(aes(x=Time, y=conc))+geom_line()+facet_wrap("Subject")