library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
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## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.1 ✔ stringr 1.4.1
## ✔ readr 2.1.3 ✔ forcats 0.5.2
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## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()getwd()## [1] "C:/Users/Jerome/Documents/0000_Work_Files/R_Work/221105"source("http://www.openintro.org/stat/data/cdc.R")
colSums(is.na(cdc))## genhlth exerany hlthplan smoke100 height weight wtdesire age
## 0 0 0 0 0 0 0 0
## gender
## 0write.csv(cdc, "cdc.csv")colnames(cdc)## [1] "genhlth" "exerany" "hlthplan" "smoke100" "height" "weight" "wtdesire"
## [8] "age" "gender"colSums(subset(cdc, select = -c(genhlth, gender)))## exerany hlthplan smoke100 height weight wtdesire age
## 14914 17476 9441 1343658 3393659 3101877 901365#colSums(select(cdc, -genhlth, -gender))
#colSums(select(cdc, -c(genhlth, gender)))colSums(select(cdc, -genhlth, -gender))## exerany hlthplan smoke100 height weight wtdesire age
## 14914 17476 9441 1343658 3393659 3101877 901365colSums(select(cdc, -c(genhlth, gender)))## exerany hlthplan smoke100 height weight wtdesire age
## 14914 17476 9441 1343658 3393659 3101877 901365str(cdc)## 'data.frame': 20000 obs. of 9 variables:
## $ genhlth : Factor w/ 5 levels "excellent","very good",..: 3 3 3 3 2 2 2 2 3 3 ...
## $ exerany : num 0 0 1 1 0 1 1 0 0 1 ...
## $ hlthplan: num 1 1 1 1 1 1 1 1 1 1 ...
## $ smoke100: num 0 1 1 0 0 0 0 0 1 0 ...
## $ height : num 70 64 60 66 61 64 71 67 65 70 ...
## $ weight : int 175 125 105 132 150 114 194 170 150 180 ...
## $ wtdesire: int 175 115 105 124 130 114 185 160 130 170 ...
## $ age : int 77 33 49 42 55 55 31 45 27 44 ...
## $ gender : Factor w/ 2 levels "m","f": 1 2 2 2 2 2 1 1 2 1 ...na.omit(cdc)## genhlth exerany hlthplan smoke100 height weight wtdesire age gender
## 1 good 0 1 0 70 175 175 77 m
## 2 good 0 1 1 64 125 115 33 f
## 3 good 1 1 1 60 105 105 49 f
## 4 good 1 1 0 66 132 124 42 f
## 5 very good 0 1 0 61 150 130 55 f
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## 8 very good 0 1 0 67 170 160 45 m
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## 18 fair 0 1 1 71 185 185 76 m
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## 20 very good 1 1 0 67 125 120 33 f
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## 27 excellent 1 0 1 67 190 165 44 f
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## 29 very good 1 1 0 61 115 105 32 f
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## [ reached 'max' / getOption("max.print") -- omitted 8889 rows ]cor( cdc$smoke100,cdc$exerany)## [1] -0.03269509table(cdc$smoke100, cdc$gender)##
## m f
## 0 4547 6012
## 1 5022 4419table(cdc$exerany,cdc$smoke100)##
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