The objective is to create dynamic reports using R Marksdown and generate the output in an HTML document.
To learn how to manipulate a given dataset using the package dplyr
knitr Global Options
# for development
knitr::opts_chunk$set(echo=TRUE, eval=TRUE, error=TRUE, warning=TRUE, message=TRUE, cache=FALSE, tidy=FALSE, fig.path='figures/')
# for production
#knitr::opts_chunk$set(echo=TRUE, eval=TRUE, error=FALSE, warning=FALSE, message=FALSE, cache=FALSE, tidy=FALSE, fig.path='figures/')Load Libraries
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionRead Data
dfr <- read.csv("./data/patient-data.csv", header=T, stringsAsFactors=F)
head(dfr)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/001 Demetrius White Male False 182.87 76.57
## 2 AC/AH/017 Rosario White Male False 179.12 80.43
## 3 AC/AH/020 Julio Black Male False 169.15 75.48
## 4 AC/AH/022 Lupe White Male False 175.66 94.54
## 5 AC/AH/029 Lavern White Female False 164.47 71.78
## 6 AC/AH/033 Bernie Dog Female True 158.27 69.90
## BirthDate State Pet HealthGrade Died RecordDate
## 1 31-01-1972 Georgia,xxx Dog 2 False 25-11-2015
## 2 09-06-1972 Missouri Dog 2 False 25-11-2015
## 3 03-07-1972 Pennsylvania None 2 False 25-11-2015
## 4 11-08-1972 Florida Cat 1 False 25-11-2015
## 5 06-06-1973 Iowa NULL 2 True 25-11-2015
## 6 25-06-1973 Maryland Dog 2 False 25-11-2015Adding new column BMIValue
dfr <- mutate(dfr,BMIValue=(WeightInKgs*(10^4)/(HeightInCms)^2))
head(dfr)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/001 Demetrius White Male False 182.87 76.57
## 2 AC/AH/017 Rosario White Male False 179.12 80.43
## 3 AC/AH/020 Julio Black Male False 169.15 75.48
## 4 AC/AH/022 Lupe White Male False 175.66 94.54
## 5 AC/AH/029 Lavern White Female False 164.47 71.78
## 6 AC/AH/033 Bernie Dog Female True 158.27 69.90
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 31-01-1972 Georgia,xxx Dog 2 False 25-11-2015 22.89674
## 2 09-06-1972 Missouri Dog 2 False 25-11-2015 25.06859
## 3 03-07-1972 Pennsylvania None 2 False 25-11-2015 26.38080
## 4 11-08-1972 Florida Cat 1 False 25-11-2015 30.63867
## 5 06-06-1973 Iowa NULL 2 True 25-11-2015 26.53567
## 6 25-06-1973 Maryland Dog 2 False 25-11-2015 27.90487Adding new column BMILabel
dfr <- mutate(dfr, BMILabel= ifelse(BMIValue < 18.5,"Underweight",
ifelse(BMIValue > 18.5 & BMIValue < 25, "Normal",
ifelse(BMIValue > 25 & BMIValue < 30, "Overweight",
ifelse(BMIValue > 30, "Obese",NA)))))
head(dfr)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/001 Demetrius White Male False 182.87 76.57
## 2 AC/AH/017 Rosario White Male False 179.12 80.43
## 3 AC/AH/020 Julio Black Male False 169.15 75.48
## 4 AC/AH/022 Lupe White Male False 175.66 94.54
## 5 AC/AH/029 Lavern White Female False 164.47 71.78
## 6 AC/AH/033 Bernie Dog Female True 158.27 69.90
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 31-01-1972 Georgia,xxx Dog 2 False 25-11-2015 22.89674
## 2 09-06-1972 Missouri Dog 2 False 25-11-2015 25.06859
## 3 03-07-1972 Pennsylvania None 2 False 25-11-2015 26.38080
## 4 11-08-1972 Florida Cat 1 False 25-11-2015 30.63867
## 5 06-06-1973 Iowa NULL 2 True 25-11-2015 26.53567
## 6 25-06-1973 Maryland Dog 2 False 25-11-2015 27.90487
## BMILabel
## 1 Normal
## 2 Overweight
## 3 Overweight
## 4 Obese
## 5 Overweight
## 6 OverweightData Cleaning
# converting yes or no to true or false
dfr$Smokes <- gsub("Yes","True", gsub("No","False", dfr$Smokes))
# removing white spaces
dfr$Gender <- trimws(dfr$Gender)
# converting wrong values to invalid
dfr$Race <- ifelse(!dfr$Race=="White" & !dfr$Race=="Black" & !dfr$Race=="Hispanic" & !dfr$Race=="Asian" &
!dfr$Race=="Bi-Racial", NA, dfr$Race)
head(dfr)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/001 Demetrius White Male False 182.87 76.57
## 2 AC/AH/017 Rosario White Male False 179.12 80.43
## 3 AC/AH/020 Julio Black Male False 169.15 75.48
## 4 AC/AH/022 Lupe White Male False 175.66 94.54
## 5 AC/AH/029 Lavern White Female False 164.47 71.78
## 6 AC/AH/033 Bernie <NA> Female True 158.27 69.90
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 31-01-1972 Georgia,xxx Dog 2 False 25-11-2015 22.89674
## 2 09-06-1972 Missouri Dog 2 False 25-11-2015 25.06859
## 3 03-07-1972 Pennsylvania None 2 False 25-11-2015 26.38080
## 4 11-08-1972 Florida Cat 1 False 25-11-2015 30.63867
## 5 06-06-1973 Iowa NULL 2 True 25-11-2015 26.53567
## 6 25-06-1973 Maryland Dog 2 False 25-11-2015 27.90487
## BMILabel
## 1 Normal
## 2 Overweight
## 3 Overweight
## 4 Obese
## 5 Overweight
## 6 OverweightConvert Health Grade
dfr$HealthGrade <- ifelse(dfr$HealthGrade==1,"Good Heath",
ifelse(dfr$HealthGrade==2, "Normal",
ifelse(dfr$HealthGrade==3,"Bad Health",NA)))
head(dfr)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/001 Demetrius White Male False 182.87 76.57
## 2 AC/AH/017 Rosario White Male False 179.12 80.43
## 3 AC/AH/020 Julio Black Male False 169.15 75.48
## 4 AC/AH/022 Lupe White Male False 175.66 94.54
## 5 AC/AH/029 Lavern White Female False 164.47 71.78
## 6 AC/AH/033 Bernie <NA> Female True 158.27 69.90
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 31-01-1972 Georgia,xxx Dog Normal False 25-11-2015 22.89674
## 2 09-06-1972 Missouri Dog Normal False 25-11-2015 25.06859
## 3 03-07-1972 Pennsylvania None Normal False 25-11-2015 26.38080
## 4 11-08-1972 Florida Cat Good Heath False 25-11-2015 30.63867
## 5 06-06-1973 Iowa NULL Normal True 25-11-2015 26.53567
## 6 25-06-1973 Maryland Dog Normal False 25-11-2015 27.90487
## BMILabel
## 1 Normal
## 2 Overweight
## 3 Overweight
## 4 Obese
## 5 Overweight
## 6 OverweightDisplay top 10 records on BMIValue
dfr <- arrange(dfr, desc(BMIValue))
head(dfr, 10)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/SG/009 Sammy White Male False 166.84 88.25
## 2 AC/SG/064 Jon White Male False 169.16 90.08
## 3 AC/AH/076 Albert White Male False 176.22 97.67
## 4 AC/AH/104 Jeremy White Male True 169.85 90.63
## 5 AC/AH/022 Lupe White Male False 175.66 94.54
## 6 AC/AH/248 Andrea White Male False 178.64 97.05
## 7 AC/SG/067 Thomas White Male False 167.51 84.15
## 8 AC/AH/052 Courtney White Male True 175.39 92.22
## 9 AC/AH/159 Edward White Male False 181.64 96.91
## 10 AC/AH/127 Jame White Male False 167.75 82.06
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 04-03-1972 Vermont Dog Good Heath False 25-06-2016 31.70402
## 2 04-10-1972 Illinois Cat Normal True 25-07-2016 31.47988
## 3 08-04-1973 Louisiana Cat Normal False 25-12-2015 31.45218
## 4 12-04-1972 Kentucky None Good Heath True 25-12-2015 31.41528
## 5 11-08-1972 Florida Cat Good Heath False 25-11-2015 30.63867
## 6 12-01-1973 Indiana Cat Good Heath True 25-05-2016 30.41152
## 7 19-07-1972 Pennsylvania Bird Normal True 25-07-2016 29.98974
## 8 16-03-1972 Indiana Bird Bad Health False 25-12-2015 29.97888
## 9 04-12-1972 Connecticut Cat Normal False 25-02-2016 29.37282
## 10 29-10-1972 Texas Dog Good Heath True 25-01-2016 29.16127
## BMILabel
## 1 Obese
## 2 Obese
## 3 Obese
## 4 Obese
## 5 Obese
## 6 Obese
## 7 Overweight
## 8 Overweight
## 9 Overweight
## 10 OverweightDisplay bottom 10 records on BMIValue
dfr <- arrange(dfr, BMIValue)
head(dfr, 10)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/SG/193 Ronnie White Male True 185.43 73.63
## 2 AC/AH/061 Lester Black Male False 181.13 72.33
## 3 AC/SG/099 Leslie Asian Male False 172.72 67.62
## 4 AC/AH/001 Demetrius White Male False 182.87 76.57
## 5 AC/AH/210 Keith Hispanic Female True 170.03 66.68
## 6 AC/AH/086 Kyle Black Male True 180.11 75.72
## 7 AC/AH/045 Shirley White Male False 181.32 76.90
## 8 AC/AH/089 Dong White Male False 179.24 75.54
## 9 AC/AH/164 Shane Hispanic Male True 177.03 74.04
## 10 AC/AH/114 Kris Hispanic Male False 177.75 74.84
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 05-06-1973 Iowa Dog Bad Health False 25-09-2016 21.41385
## 2 16-11-1972 Wisconsin Dog <NA> True 25-12-2015 22.04640
## 3 04-02-1972 Ohio Cat Good Heath False 25-07-2016 22.66678
## 4 31-01-1972 Georgia,xxx Dog Normal False 25-11-2015 22.89674
## 5 28-08-1972 New York Dog <NA> False 25-03-2016 23.06452
## 6 12-05-1973 Georgia Cat Bad Health False 25-12-2015 23.34183
## 7 25-12-1971 Louisiana Dog Good Heath False 25-11-2015 23.39025
## 8 11-03-1972 California None Normal True 25-12-2015 23.51295
## 9 18-02-1972 Florida None Normal False 25-02-2016 23.62505
## 10 19-11-1972 Pennsylvania Bird Bad Health False 25-01-2016 23.68725
## BMILabel
## 1 Normal
## 2 Normal
## 3 Normal
## 4 Normal
## 5 Normal
## 6 Normal
## 7 Normal
## 8 Normal
## 9 Normal
## 10 NormalDisplay Frequency of Gender > Race
summarise(group_by(dfr, Gender, Race), n())## Source: local data frame [10 x 3]
## Groups: Gender [?]
##
## Gender Race `n()`
## <chr> <chr> <int>
## 1 Female Asian 3
## 2 Female Black 3
## 3 Female Hispanic 7
## 4 Female White 41
## 5 Female <NA> 1
## 6 Male Asian 2
## 7 Male Bi-Racial 1
## 8 Male Black 5
## 9 Male Hispanic 10
## 10 Male White 27Display Max, Min & Avg of BMIValues for Race > Gender
summarise(group_by(dfr, Race , Gender), max(BMIValue), min(BMIValue), mean(BMIValue))## Source: local data frame [10 x 5]
## Groups: Race [?]
##
## Race Gender `max(BMIValue)` `min(BMIValue)` `mean(BMIValue)`
## <chr> <chr> <dbl> <dbl> <dbl>
## 1 Asian Female 28.19431 24.42511 26.06524
## 2 Asian Male 27.24885 22.66678 24.95782
## 3 Bi-Racial Male 24.83473 24.83473 24.83473
## 4 Black Female 26.71407 24.64441 25.52777
## 5 Black Male 26.60586 22.04640 24.43950
## 6 Hispanic Female 27.84206 23.06452 26.02787
## 7 Hispanic Male 28.78164 23.62505 26.29876
## 8 White Female 28.24834 24.21459 26.39055
## 9 White Male 31.70402 21.41385 27.67323
## 10 <NA> Female 27.90487 27.90487 27.90487Display records for Dead People
filter(dfr, Died == "True")## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/061 Lester Black Male False 181.13 72.33
## 2 AC/AH/089 Dong White Male False 179.24 75.54
## 3 AC/AH/150 Brett White Male True 181.56 79.54
## 4 AC/SG/056 Merrill Asian Female True 166.19 67.46
## 5 AC/SG/179 Logan White Male False 183.10 82.47
## 6 AC/AH/112 Pat Black Female False 160.57 63.54
## 7 AC/SG/182 Jamie Hispanic Male True 171.08 72.51
## 8 AC/AH/233 Marion White Female False 163.97 66.71
## 9 AC/SG/234 Luis Hispanic Female False 164.88 68.07
## 10 AC/AH/180 Drew White Female False 160.80 64.77
## 11 AC/AH/154 Tony White Female False 160.03 64.30
## 12 AC/SG/003 Walter White Female False 161.83 66.03
## 13 AC/SG/010 Theo Asian Female False 159.32 64.92
## 14 AC/AH/133 Clyde Hispanic Male False 181.15 83.93
## 15 AC/AH/192 Dominique White Male False 180.61 83.59
## 16 AC/AH/244 Sean White Female False 160.09 65.93
## 17 AC/SG/165 Elmer White Female False 162.18 67.81
## 18 AC/AH/221 Carlos White Female False 165.34 70.84
## 19 AC/SG/197 Stacy White Female False 159.44 66.21
## 20 AC/SG/134 Daryl White Female True 162.59 69.76
## 21 AC/AH/171 Devin White Female False 163.35 70.46
## 22 AC/SG/216 Alva White Female False 159.13 66.96
## 23 AC/SG/068 Valentine Hispanic Female False 160.47 68.20
## 24 AC/AH/029 Lavern White Female False 164.47 71.78
## 25 AC/SG/116 Connie Black Male False 184.34 90.41
## 26 AC/SG/084 Brian Hispanic Male False 174.25 80.93
## 27 AC/SG/016 Jimmie Black Female False 161.84 69.97
## 28 AC/AH/249 Jesus Hispanic Female True 159.78 68.31
## 29 AC/SG/008 Dana White Male True 169.66 77.30
## 30 AC/SG/065 Shayne White Female False 157.01 66.56
## 31 AC/AH/186 Christopher White Female False 157.95 67.41
## 32 AC/AH/176 Jerry Asian Male False 175.21 83.65
## 33 AC/AH/219 Jay White Female False 163.47 72.89
## 34 AC/SG/101 Jason White Female False 159.23 69.96
## 35 AC/SG/123 Darnell White Female True 162.32 72.72
## 36 AC/SG/167 Jimmy White Female False 159.38 70.37
## 37 AC/SG/217 Dean White Female False 160.58 71.49
## 38 AC/AH/185 Ronald White Male False 166.46 76.83
## 39 AC/SG/155 Raymond White Female False 158.35 69.72
## 40 AC/SG/046 Carl Hispanic Male False 171.41 81.70
## 41 AC/SG/191 Lacy Hispanic Female False 159.33 70.68
## 42 AC/AH/156 George White Male False 165.62 76.72
## 43 AC/AH/160 Rory Asian Female False 159.67 71.88
## 44 AC/AH/211 Son White Female False 157.16 69.64
## 45 AC/AH/049 Martin White Female False 160.06 72.37
## 46 AC/SG/181 Terry Hispanic Male False 177.14 88.70
## 47 AC/SG/055 Evan White Male False 166.75 79.06
## 48 AC/SG/172 Whitney White Male False 171.45 84.29
## 49 AC/SG/015 Shaun White Male True 170.51 84.35
## 50 AC/AH/127 Jame White Male False 167.75 82.06
## 51 AC/SG/067 Thomas White Male False 167.51 84.15
## 52 AC/AH/248 Andrea White Male False 178.64 97.05
## 53 AC/AH/104 Jeremy White Male True 169.85 90.63
## 54 AC/SG/064 Jon White Male False 169.16 90.08
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 16-11-1972 Wisconsin Dog <NA> True 25-12-2015 22.04640
## 2 11-03-1972 California None Normal True 25-12-2015 23.51295
## 3 03-05-1972 Kentucky Dog Good Heath True 25-02-2016 24.12933
## 4 27-11-1972 Indiana NULL Bad Health True 25-07-2016 24.42511
## 5 24-10-1972 Ohio Dog Bad Health True 25-09-2016 24.59910
## 6 26-06-1973 California <NA> <NA> True 25-01-2016 24.64441
## 7 25-03-1973 Louisiana None Bad Health True 25-09-2016 24.77419
## 8 23-12-1971 Ohio Cat Bad Health True 25-04-2016 24.81202
## 9 10-11-1971 Pennsylvania Cat Bad Health True 25-10-2016 25.03916
## 10 18-02-1973 Oregon CAT Good Heath True 25-03-2016 25.04966
## 11 30-08-1973 California DOG Good Heath True 25-02-2016 25.10777
## 12 11-07-1972 Oregon None Normal True 25-05-2016 25.21292
## 13 29-01-1973 New York Cat Normal True 25-06-2016 25.57631
## 14 13-10-1973 Washington Cat Bad Health True 25-02-2016 25.57647
## 15 24-03-1972 Michigan None Bad Health True 25-03-2016 25.62541
## 16 25-01-1973 Maryland None <NA> True 25-05-2016 25.72496
## 17 25-03-1972 Washington Bird Good Heath True 25-08-2016 25.78096
## 18 01-02-1972 Michigan Dog <NA> True 25-04-2016 25.91330
## 19 08-11-1972 New York Cat Good Heath True 25-10-2016 26.04528
## 20 28-05-1972 Texas CAT Normal True 25-08-2016 26.38875
## 21 16-04-1973 California Bird Bad Health True 25-03-2016 26.40611
## 22 19-06-1972 Alabama None Good Heath True 25-10-2016 26.44304
## 23 15-04-1972 Tennessee Cat Bad Health True 25-07-2016 26.48480
## 24 06-06-1973 Iowa NULL Normal True 25-11-2015 26.53567
## 25 05-06-1972 Florida None Bad Health True 25-08-2016 26.60586
## 26 06-03-1972 Virginia DOG Normal True 25-07-2016 26.65410
## 27 03-04-1972 Arizona Cat Bad Health True 25-06-2016 26.71407
## 28 23-04-1972 Alabama Cat Normal True 25-05-2016 26.75713
## 29 26-05-1973 Nevada Dog Good Heath True 25-05-2016 26.85472
## 30 05-04-1972 California Dog Bad Health True 25-07-2016 26.99968
## 31 06-05-1972 New Jersey Dog Bad Health True 25-03-2016 27.01998
## 32 01-05-1973 Virginia Dog Bad Health True 25-03-2016 27.24885
## 33 07-04-1972 North Carolina Bird Good Heath True 25-04-2016 27.27670
## 34 28-09-1973 Michigan Dog Normal True 25-07-2016 27.59307
## 35 03-09-1972 North Carolina Bird Good Heath True 25-08-2016 27.60005
## 36 30-09-1973 Washington None Normal True 25-09-2016 27.70256
## 37 11-11-1972 Ohio None Good Heath True 25-10-2016 27.72441
## 38 17-08-1972 Colorado None <NA> True 25-03-2016 27.72752
## 39 02-06-1972 California Cat Bad Health True 25-08-2016 27.80489
## 40 05-08-1973 Mississippi Bird Normal True 25-06-2016 27.80672
## 41 21-06-1973 Texas None Bad Health True 25-09-2016 27.84206
## 42 09-07-1972 California Dog Good Heath True 25-02-2016 27.96939
## 43 22-09-1973 Florida Cat Normal True 25-02-2016 28.19431
## 44 14-07-1973 California Cat Normal True 25-04-2016 28.19517
## 45 28-04-1972 California Horse Normal True 25-12-2015 28.24834
## 46 24-11-1971 Indiana CAT Bad Health True 25-09-2016 28.26769
## 47 24-02-1972 Illinois Bird Bad Health True 25-07-2016 28.43316
## 48 25-02-1972 Florida Dog Normal True 25-09-2016 28.67484
## 49 09-11-1972 New Jersey DOG Bad Health True 25-06-2016 29.01252
## 50 29-10-1972 Texas Dog Good Heath True 25-01-2016 29.16127
## 51 19-07-1972 Pennsylvania Bird Normal True 25-07-2016 29.98974
## 52 12-01-1973 Indiana Cat Good Heath True 25-05-2016 30.41152
## 53 12-04-1972 Kentucky None Good Heath True 25-12-2015 31.41528
## 54 04-10-1972 Illinois Cat Normal True 25-07-2016 31.47988
## BMILabel
## 1 Normal
## 2 Normal
## 3 Normal
## 4 Normal
## 5 Normal
## 6 Normal
## 7 Normal
## 8 Normal
## 9 Overweight
## 10 Overweight
## 11 Overweight
## 12 Overweight
## 13 Overweight
## 14 Overweight
## 15 Overweight
## 16 Overweight
## 17 Overweight
## 18 Overweight
## 19 Overweight
## 20 Overweight
## 21 Overweight
## 22 Overweight
## 23 Overweight
## 24 Overweight
## 25 Overweight
## 26 Overweight
## 27 Overweight
## 28 Overweight
## 29 Overweight
## 30 Overweight
## 31 Overweight
## 32 Overweight
## 33 Overweight
## 34 Overweight
## 35 Overweight
## 36 Overweight
## 37 Overweight
## 38 Overweight
## 39 Overweight
## 40 Overweight
## 41 Overweight
## 42 Overweight
## 43 Overweight
## 44 Overweight
## 45 Overweight
## 46 Overweight
## 47 Overweight
## 48 Overweight
## 49 Overweight
## 50 Overweight
## 51 Overweight
## 52 Obese
## 53 Obese
## 54 ObeseDisplay records for Hispanic Females
filter(dfr, Race == "Hispanic" & Gender == "Female")## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 1 AC/AH/210 Keith Hispanic Female True 170.03 66.68
## 2 AC/SG/234 Luis Hispanic Female False 164.88 68.07
## 3 AC/AH/208 Lawrence Hispanic Female False 165.80 71.77
## 4 AC/SG/068 Valentine Hispanic Female False 160.47 68.20
## 5 AC/AH/249 Jesus Hispanic Female True 159.78 68.31
## 6 AC/SG/122 Michal Hispanic Female False 160.09 68.94
## 7 AC/SG/191 Lacy Hispanic Female False 159.33 70.68
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 1 28-08-1972 New York Dog <NA> False 25-03-2016 23.06452
## 2 10-11-1971 Pennsylvania Cat Bad Health True 25-10-2016 25.03916
## 3 07-08-1973 Louisiana None Good Heath False 25-03-2016 26.10802
## 4 15-04-1972 Tennessee Cat Bad Health True 25-07-2016 26.48480
## 5 23-04-1972 Alabama Cat Normal True 25-05-2016 26.75713
## 6 16-12-1971 South Carolina DOG Good Heath False 25-08-2016 26.89942
## 7 21-06-1973 Texas None Bad Health True 25-09-2016 27.84206
## BMILabel
## 1 Normal
## 2 Overweight
## 3 Overweight
## 4 Overweight
## 5 Overweight
## 6 Overweight
## 7 OverweightDisplay 7 sample records
set.seed(707)
sample_n(dfr, 7)## ID Name Race Gender Smokes HeightInCms WeightInKgs
## 10 AC/AH/114 Kris Hispanic Male False 177.75 74.84
## 44 AC/SG/204 Anthony White Female False 164.11 70.66
## 27 AC/AH/154 Tony White Female False 160.03 64.30
## 52 AC/SG/121 Rudy White Female False 163.94 71.47
## 73 AC/SG/046 Carl Hispanic Male False 171.41 81.70
## 67 AC/SG/123 Darnell White Female True 162.32 72.72
## 83 AC/AH/241 Lindsay White Female False 161.38 73.55
## BirthDate State Pet HealthGrade Died RecordDate BMIValue
## 10 19-11-1972 Pennsylvania Bird Bad Health False 25-01-2016 23.68725
## 44 17-06-1972 California Dog Bad Health False 25-10-2016 26.23636
## 27 30-08-1973 California DOG Good Heath True 25-02-2016 25.10777
## 52 12-03-1973 Michigan Cat Bad Health False 25-08-2016 26.59218
## 73 05-08-1973 Mississippi Bird Normal True 25-06-2016 27.80672
## 67 03-09-1972 North Carolina Bird Good Heath True 25-08-2016 27.60005
## 83 08-02-1972 Florida Cat Bad Health False 25-05-2016 28.24121
## BMILabel
## 10 Normal
## 44 Overweight
## 27 Overweight
## 52 Overweight
## 73 Overweight
## 67 Overweight
## 83 Overweight