EXPLORING THE PLOTLY USING BREAST CANCER DATA

OLUWADARE MARGARET
30TH SEPTEMBER, 2020

INTRODUCTION

Dr. William H. Wolberg of the University of Wisconsin pioneered the Wisconsin Breast Cancer Data in 1990. His goal of collecting the data was to identify whether a tumor biopsy was malignant or benign. His team collected the samples using Fine Needle Aspiration (FNA). Our aim here is to demonstrate the use of plotly in plotting this data set.

To do this we will access the Mass library and read in the data called biospy. The following till be carried out:

  • Read in the data
  • Relabel varaiable names
  • Perform some data cleaning and exploration
  • Plot the data using plotly

PREPARE THE ENVIRONMENT

The following library will be used and the biospy data set from the MASS library will be used. 

library(MASS); library(corrplot); library(ggplot2); library(tidyverse);
library(plotly)
library(rgl); library(rglwidget)
data(biopsy)

We perform some cleaning by removing the id variable, renaming the varaible and ommiting na's.

bc <- biopsy[-1]
names(bc) <- c("age", "mnp", "ts", "inv", "ndc", "deM", "breast", "brtq", "irat", "class" )
bc = na.omit(bc)
str(bc)

'data.frame':   683 obs. of  10 variables:
 $ age   : int  5 5 3 6 4 8 1 2 2 4 ...
 $ mnp   : int  1 4 1 8 1 10 1 1 1 2 ...
 $ ts    : int  1 4 1 8 1 10 1 2 1 1 ...
 $ inv   : int  1 5 1 1 3 8 1 1 1 1 ...
 $ ndc   : int  2 7 2 3 2 7 2 2 2 2 ...
 $ deM   : int  1 10 2 4 1 10 10 1 1 1 ...
 $ breast: int  3 3 3 3 3 9 3 3 1 2 ...
 $ brtq  : int  1 2 1 7 1 7 1 1 1 1 ...
 $ irat  : int  1 1 1 1 1 1 1 1 5 1 ...
 $ class : Factor w/ 2 levels "benign","malignant": 1 1 1 1 1 2 1 1 1 1 ...
 - attr(*, "na.action")= 'omit' Named int [1:16] 24 41 140 146 159 165 236 250 276 293 ...
  ..- attr(*, "names")= chr [1:16] "24" "41" "140" "146" ...

PLOT OF DATA

# Point colors
marker <- list(color = ~class, colorscale = c('#FFE1A1', '#683531'), 
               showscale = TRUE)
# Create the plot
p <- plot_ly(bc, x = ~age, y = ~mnp, z = ~brtq, marker = marker) %>%
  add_markers() %>%
  layout(
    scene = list(xaxis = list(title = 'age'),
                 yaxis = list(title = 'menopause'),
                 zaxis = list(title = 'breast quarter'), 
                 title = "Breast cancer Data")
  )
p

plot of chunk Plot