We will read a breast cancer data set available at http://www.araastat.com/BIOF339_PracticalR/Lectures/lecture2_files/BreastCancer.xlsx. This is an Microsoft Excel file of 569 subjects with breast tumor biopsies. The objective of this data set and study was to predict the class of tumor (malignant/benign) from several tumor characteristics.
download.file to download this file to your computer, specifying where you save it.download.file('http://www.araastat.com/BIOF339_PracticalR/Lectures/lecture2_files/BreastCancer.xlsx', 'BreastCancer.xlsx')readxl from your favorite CRAN mirrorinstall.packages('readxl', repos='http://cran.rstudio.com')read_excel function from the readxl package.library(readxl)
dat <- read_excel('BreastCancer.xlsx')
dat <- data.frame(dat, stringsAsFactors = F) # Convert file to a data frame, remove spaces from namesstr(dat)## 'data.frame': 569 obs. of 31 variables:
## $ mean.radius : num 18 20.6 19.7 11.4 20.3 ...
## $ mean.texture : num 10.4 17.8 21.2 20.4 14.3 ...
## $ mean.perimeter : num 122.8 132.9 130 77.6 135.1 ...
## $ mean.area : num 1001 1326 1203 386 1297 ...
## $ mean.smoothness : num 0.1184 0.0847 0.1096 0.1425 0.1003 ...
## $ mean.compactness : num 0.2776 0.0786 0.1599 0.2839 0.1328 ...
## $ mean.concavity : num 0.3001 0.0869 0.1974 0.2414 0.198 ...
## $ mean.concave.points : num 0.1471 0.0702 0.1279 0.1052 0.1043 ...
## $ mean.symmetry : num 0.242 0.181 0.207 0.26 0.181 ...
## $ mean.fractal.dimension : num 0.0787 0.0567 0.06 0.0974 0.0588 ...
## $ radius.error : num 1.095 0.543 0.746 0.496 0.757 ...
## $ texture.error : num 0.905 0.734 0.787 1.156 0.781 ...
## $ perimeter.error : num 8.59 3.4 4.58 3.44 5.44 ...
## $ area.error : num 153.4 74.1 94 27.2 94.4 ...
## $ smoothness.error : num 0.0064 0.00522 0.00615 0.00911 0.01149 ...
## $ compactness.error : num 0.049 0.0131 0.0401 0.0746 0.0246 ...
## $ concavity.error : num 0.0537 0.0186 0.0383 0.0566 0.0569 ...
## $ concave.points.error : num 0.0159 0.0134 0.0206 0.0187 0.0188 ...
## $ symmetry.error : num 0.03 0.0139 0.0225 0.0596 0.0176 ...
## $ fractal.dimension.error: num 0.00619 0.00353 0.00457 0.00921 0.00511 ...
## $ worst.radius : num 25.4 25 23.6 14.9 22.5 ...
## $ worst.texture : num 17.3 23.4 25.5 26.5 16.7 ...
## $ worst.perimeter : num 184.6 158.8 152.5 98.9 152.2 ...
## $ worst.area : num 2019 1956 1709 568 1575 ...
## $ worst.smoothness : num 0.162 0.124 0.144 0.21 0.137 ...
## $ worst.compactness : num 0.666 0.187 0.424 0.866 0.205 ...
## $ worst.concavity : num 0.712 0.242 0.45 0.687 0.4 ...
## $ worst.concave.points : num 0.265 0.186 0.243 0.258 0.163 ...
## $ worst.symmetry : num 0.46 0.275 0.361 0.664 0.236 ...
## $ worst.fractal.dimension: num 0.1189 0.089 0.0876 0.173 0.0768 ...
## $ Status : chr "benign" "benign" "benign" "benign" ...dim(dat)## [1] 569 31names(dat)## [1] "mean.radius" "mean.texture"
## [3] "mean.perimeter" "mean.area"
## [5] "mean.smoothness" "mean.compactness"
## [7] "mean.concavity" "mean.concave.points"
## [9] "mean.symmetry" "mean.fractal.dimension"
## [11] "radius.error" "texture.error"
## [13] "perimeter.error" "area.error"
## [15] "smoothness.error" "compactness.error"
## [17] "concavity.error" "concave.points.error"
## [19] "symmetry.error" "fractal.dimension.error"
## [21] "worst.radius" "worst.texture"
## [23] "worst.perimeter" "worst.area"
## [25] "worst.smoothness" "worst.compactness"
## [27] "worst.concavity" "worst.concave.points"
## [29] "worst.symmetry" "worst.fractal.dimension"
## [31] "Status"dat[,'diff.radius'] <- dat[,'worst.radius'] - dat[,'mean.radius']dat_malignant <- dat[dat$Status=='malignant',]
dat_benign <- dat[dat$Status=='benign',]summary(dat_malignant[,1:9])## mean.radius mean.texture mean.perimeter mean.area
## Min. : 6.981 Min. : 9.71 Min. : 43.79 Min. :143.5
## 1st Qu.:11.080 1st Qu.:15.15 1st Qu.: 70.87 1st Qu.:378.2
## Median :12.200 Median :17.39 Median : 78.18 Median :458.4
## Mean :12.147 Mean :17.91 Mean : 78.08 Mean :462.8
## 3rd Qu.:13.370 3rd Qu.:19.76 3rd Qu.: 86.10 3rd Qu.:551.1
## Max. :17.850 Max. :33.81 Max. :114.60 Max. :992.1
## mean.smoothness mean.compactness mean.concavity mean.concave.points
## Min. :0.05263 Min. :0.01938 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.08306 1st Qu.:0.05562 1st Qu.:0.02031 1st Qu.:0.01502
## Median :0.09076 Median :0.07529 Median :0.03709 Median :0.02344
## Mean :0.09248 Mean :0.08008 Mean :0.04606 Mean :0.02572
## 3rd Qu.:0.10070 3rd Qu.:0.09755 3rd Qu.:0.05999 3rd Qu.:0.03251
## Max. :0.16340 Max. :0.22390 Max. :0.41080 Max. :0.08534
## mean.symmetry
## Min. :0.1060
## 1st Qu.:0.1580
## Median :0.1714
## Mean :0.1742
## 3rd Qu.:0.1890
## Max. :0.2743summary(dat_benign[,1:9])## mean.radius mean.texture mean.perimeter mean.area
## Min. :10.95 Min. :10.38 Min. : 71.90 Min. : 361.6
## 1st Qu.:15.07 1st Qu.:19.33 1st Qu.: 98.75 1st Qu.: 705.3
## Median :17.32 Median :21.46 Median :114.20 Median : 932.0
## Mean :17.46 Mean :21.60 Mean :115.37 Mean : 978.4
## 3rd Qu.:19.59 3rd Qu.:23.77 3rd Qu.:129.93 3rd Qu.:1203.8
## Max. :28.11 Max. :39.28 Max. :188.50 Max. :2501.0
## mean.smoothness mean.compactness mean.concavity mean.concave.points
## Min. :0.07371 Min. :0.04605 Min. :0.02398 Min. :0.02031
## 1st Qu.:0.09401 1st Qu.:0.10960 1st Qu.:0.10952 1st Qu.:0.06462
## Median :0.10220 Median :0.13235 Median :0.15135 Median :0.08628
## Mean :0.10290 Mean :0.14519 Mean :0.16077 Mean :0.08799
## 3rd Qu.:0.11092 3rd Qu.:0.17240 3rd Qu.:0.20305 3rd Qu.:0.10318
## Max. :0.14470 Max. :0.34540 Max. :0.42680 Max. :0.20120
## mean.symmetry
## Min. :0.1308
## 1st Qu.:0.1741
## Median :0.1899
## Mean :0.1929
## 3rd Qu.:0.2099
## Max. :0.3040library(stringr)
mean_vars = str_detect(names(dat_malignant),'mean') # Gets column names with "mean" in it (what structure is this?)
summary(dat_malignant[,mean_vars])## mean.radius mean.texture mean.perimeter mean.area
## Min. : 6.981 Min. : 9.71 Min. : 43.79 Min. :143.5
## 1st Qu.:11.080 1st Qu.:15.15 1st Qu.: 70.87 1st Qu.:378.2
## Median :12.200 Median :17.39 Median : 78.18 Median :458.4
## Mean :12.147 Mean :17.91 Mean : 78.08 Mean :462.8
## 3rd Qu.:13.370 3rd Qu.:19.76 3rd Qu.: 86.10 3rd Qu.:551.1
## Max. :17.850 Max. :33.81 Max. :114.60 Max. :992.1
## mean.smoothness mean.compactness mean.concavity mean.concave.points
## Min. :0.05263 Min. :0.01938 Min. :0.00000 Min. :0.00000
## 1st Qu.:0.08306 1st Qu.:0.05562 1st Qu.:0.02031 1st Qu.:0.01502
## Median :0.09076 Median :0.07529 Median :0.03709 Median :0.02344
## Mean :0.09248 Mean :0.08008 Mean :0.04606 Mean :0.02572
## 3rd Qu.:0.10070 3rd Qu.:0.09755 3rd Qu.:0.05999 3rd Qu.:0.03251
## Max. :0.16340 Max. :0.22390 Max. :0.41080 Max. :0.08534
## mean.symmetry mean.fractal.dimension
## Min. :0.1060 Min. :0.05185
## 1st Qu.:0.1580 1st Qu.:0.05853
## Median :0.1714 Median :0.06154
## Mean :0.1742 Mean :0.06287
## 3rd Qu.:0.1890 3rd Qu.:0.06576
## Max. :0.2743 Max. :0.09575haven package to load them into R. You may have to install it.