# this is an example of an untidy data
library(readxl)
deerkill <- read_excel("~/wfed540/classmeeting 4/classmeeting 4/deer kil.xlsx")
deerkill
## # A tibble: 10 x 3
## Counties `2016` `2015`
## <chr> <dbl> <dbl>
## 1 Tioga 236 225
## 2 Mifflin 175 159
## 3 Lycoming 166 217
## 4 Potter 317 298
## 5 Franklin 125 186
## 6 Dauphin 137 156
## 7 Carbon 203 175
## 8 Pike 96 111
## 9 Bradford 245 275
## 10 Lancaster 158 143
###########################################
#This is an example of tidy data
library(readxl)
deerkill2 <- read_excel("~/wfed540/classmeeting 4/derrkill2.xlsx")
deerkill2
## # A tibble: 20 x 3
## Counties year deer
## <chr> <dbl> <dbl>
## 1 Tioga 2016 236
## 2 Tioga 2015 225
## 3 Mifflin 2016 175
## 4 Mifflin 2015 159
## 5 Lycoming 2016 166
## 6 Lycoming 2015 217
## 7 Potter 2016 317
## 8 Potter 2015 298
## 9 Franklin 2016 125
## 10 Franklin 2015 186
## 11 Dauphin 2016 137
## 12 Dauphin 2015 156
## 13 Carbon 2016 203
## 14 Carbon 2015 175
## 15 Pike 2016 96
## 16 Pike 2015 111
## 17 Bradford 2016 245
## 18 Bradford 2015 275
## 19 Lancaster 2016 158
## 20 Lancaster 2015 143
########################################
#This is an example of income and religion (Nominal Data)
library(readxl)
religion2 <- read_excel("~/wfed540/classmeeting 4/classmeeting 4/religion2.xlsx")
religion2
## # A tibble: 10 x 3
## Religion `$10-50k` `$50-100k`
## <chr> <dbl> <dbl>
## 1 Agnostic 36 25
## 2 Atheist 15 6
## 3 Buddhist 26 78
## 4 Catholic 123 234
## 5 Brethren 230 301
## 6 Buddhism 27 59
## 7 Methodist 46 79
## 8 Lutheran 179 124
## 9 Mormon 89 67
## 10 Mennonite 47 47
#######################################
# this is an example of people who have middle names (Nominal)
library(readxl)
middle_names <- read_excel("~/wfed540/classmeeting 4/middle names.xlsx")
middle_names
## # A tibble: 14 x 3
## Name middle_name no_middlename
## <chr> <chr> <chr>
## 1 Joe yes <NA>
## 2 Bob yes <NA>
## 3 Cindy <NA> no
## 4 Jim <NA> no
## 5 Maria yes <NA>
## 6 Gary <NA> no
## 7 Steve <NA> no
## 8 Leila yes <NA>
## 9 Sonja yes <NA>
## 10 Noda yes <NA>
## 11 David <NA> no
## 12 Olga yes <NA>
## 13 Ted <NA> no
## 14 Ray <NA> no
######################################
#This ia an example of who wears glasses
library(readxl)
glasses <- read_excel("~/wfed540/classmeeting 4/classmeeting 4/glasses.xlsx")
glasses
## # A tibble: 10 x 3
## names glasses no_glasses
## <chr> <dbl> <dbl>
## 1 ashley 1 NA
## 2 sue NA 1
## 3 judy NA 1
## 4 ben 1 NA
## 5 dan NA 1
## 6 deb 1 NA
## 7 sam 1 NA
## 8 ann 1 NA
## 9 ted NA 1
## 10 niki 1 NA