Consider the Breast Cancer data set (please check the File > dataset folder on Microsoft Teams). Please write a python code which do the following operations: 1. Import the data wet into a panda data frame (read the .cou file) 2. Show the type for each data set column (mumerical or categorical at- tributes) 3. Check for missing values (mull values). 4. Replace the missing values using the median approach 5. Show the correlation between the target the column diagnosis) and the other attributes. Please indicate which attributes (maximum three) are mostly correlated with the target value. 6. Split data set into train (70%) and test data (30%). 7. Handle the categorical attributes (convert these categories from text to numbers) 8. Normalize your data normalization is a re-scaling of the data from the original range so that all values are within the range of 0 and 1). Note: Please submit your assignment as Jupyter notebook file with (-ipynb file) Deadline is Sunday, May, 15.