[80 Marks]: Solve all the questions using Python. Use Pandas, Seaborn, Sklearn, etc., libraries for all the analysis. Consider the data given in Excel file HW4_DataA. Consider the following data description:
Table 8.5.1: Data description
Field Description
age The age of the individual. The age of the individual.
gender The gender of the individual, either 'Male' or 'Female'.
occupation The occupation of the individual
education_level The highest level of education attained by the individual
marital_status The marital status of the individual, either 'Single' or 'Married'.
income The annual income of the individual in dollars.
credit_score The credit score of the individual, ranging from 300 to 850.
loan_status The target variable, indicating whether the loan application was 'Approved' or 'Denied'.
8.5.1: Topic 8 Coding Tasks
Do the following tasks (in exact sequence) using the "HW4_DataA" data:
B-1. [5 marks]: Read and display the data given in HW4_DataA. Describe both the numeric and categorical attributes. Refer to Table 8.5.2 for the data description.