The purpose of this assignment is to help you not only understand why and how to do data visualization but also explore its benefits for business intelligence. This assignment requires you to answer all the questions with your own storytelling and relevant visualizations.

download the dataset, VA_SAMPLE_ACME_BANK.

VA_SAMPLE_ACME_BANK shows data related to some financial institutions across the US. Note: financial knowledge is not needed in this assignment.

1. Create a new variable, Unpaid Ratio Unpaid Ratio = _ / _

i) Create a Bar chart of Industry_Name.

What is the Unpaid Ratio of the Mining industry? [Put the answer as a comment in your script]

(Hint: Group_by each industry first; Then use summarise by calculating the unpaid_ratio for each industry using the above formular[sum(Outstanding_balance)/sum(Original_balance); Lastly, arrange in descending order]. Remember to remove NAs using na.rm = T)

2. Now, we want to explore the correlation relationships among Adverse_capital_ratio, Baseline_Capital_Ratio, Capital_ratio, Default_rate. Select these variables from data frame then save them into a new data frame corr_df.

i) Calculate the correlation matrix for Adverse_capital_ratio, Baseline_Capital_Ratio, Capital_ratio, and Default_rate

ii) What is the correlation index between Adverse_capital_ratio and Baseline_Capital_Ratio? [Put the answer as a comment in the script]

3. i)Create a Pie chart to show the percentage of different Loan_Type.

ii) In this visualization, the Term Loan occupies about what proportions of the entire pie? (e.g., , 1/3, 2/3, , etc... ) [Put the answer as a comment in your script]

4. Create a Treemap to show the percentage of different Loan_Type.

5. i) Create a Box Plot of Return_percent.

ii) Is the Return_percent distribution left-skewed or right-skewed? [Put the answer as a comment in your script]

Submit your R-script, including codes for generating the results as well as the answers of the questions as comments (followed by # in R) in the R script