This is part of the data

C F H. CellSize CellShape Adhesion EpithelialSize BareNuclei BlandChrom: NormalNucle Mitoses w w 5 1. w w Hamnooo: w A B sample Iclump 1000025 1002945 1015425 1016277 1017023 1017122 1018099 1018561 1033078 ? 1033078 1035283 1036172 PPPPNPOPO PAP NPNNNNNNN Class 1 benign 1 benign 1 benign 1 benign 1 benign 1 malignant 1 benign 1 benign 5 benign 1 benign 1 benign 1 benign 1 PPPPPO OHNE 1 NW NP w w 12 13 Write R code to perform the following tasks. (1) (3) Read the file to a data frame and figure out if there are missing values. If there are missing values, figure out which columns have missing values. Remove rows that contain any missing values. 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. Use logical sub setting to separate the two groups: benign and malignant. 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. (5) clump Cells CellShape LJ. LILILI Adhesion Epithelial Size BareNuclel count Class benign malignant BlandChromatin NormalNudeli 1 .-. .- - - - 50 - - 75 - 10.0 R 25 50 75 10.0 0.0 25 5.0 value is 10.0 0.0 25 (6) Write a few lines to describe what inferences you can make from this analysis