there are some differences between the benign and malignant samples based on the sample characteristic represented by the column

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Description: You are given a breast cancer data text file (breast_cancer.csv) from the University of Wisconsin Hospitals, Madison from Dr. William H. Wolberg. Each row in the file represents a test performed on potential breast cancer sample. All missing Values are marked as “?”. The columns in the file are described below. Column # possible values -- ----------------------------------------- 1. Sample code number id number 2. Clump Thickness 1 - 10 3. Uniformity of Cell Size 1 - 10 4. Uniformity of Cell Shape 1 - 10 5. Marginal Adhesion 1 - 10 6. Single Epithelial Cell Size 1 - 10 7. Bare Nuclei 1 - 10 8. Bland Chromatin 1 - 10 9. Normal Nucleoli 1 - 10 10. Mitoses 1 - 10 11. Class: (benign, malignant) Write R code to perform the following tasks. Tasks 1, 2, 3, 5, 6: each is worth 5 points Task 6 is worth 15 points. (1) Read the file to a data frame and figure out if there are missing values. (2) If there are missing values, figure out which columns have missing values. (3) Remove rows that contain any missing values(use complete.cases function in R). (4) Compute the average value of each column (column 2 to column 10) for benign and malignant samples separately. This will give you an idea if there are some differences between the benign and malignant samples based on the sample characteristic represented by the column. For this code, you cannot use R functionalities such as “aggregate”, “apply” etc or dplyr package. Use logical sub setting to separate the two groups: benign and malignant. (5) Using ggplot2, generate a histogram plot (binsize = 1) that looks like below. Use facet wrap to separate the plots for the different columns. You will need to use melt function from reshape2 package (covered in lecture notes and video) to prepare the data frame in a usable input format for ggplot2. 

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