ggplot(loans_full_schema, aes(loan_purpose))+
geom_bar()+
coord_flip()+
labs(title = "Distribution of Loan Purposes",
x = "Loan Purpose",
y = "Count") +
theme(plot.title = element_text(hjust = 0.5, size = rel(1.5), margin = margin(15,15,15,15)),
axis.title = element_text(size = rel(1.2)),
axis.title.x = element_text(margin = margin(10,5,5,5)),
axis.title.y = element_text(margin = margin(5,10,5,5)))
The most common loan purpose is for debt consolidation
ggplot(data = loans_full_schema) +
stat_summary(mapping = aes(x = factor(term), y = interest_rate, fill = loan_purpose) , fun = "mean", geom = "bar", position = "dodge") +
labs(title = "Mean Interest Rate by Term and Loan Purpose",
x = "Term",
y = "Mean Interest Rate",
fill = "Loan Purpose") +
theme(plot.title = element_text(hjust = 0.5, size = rel(1.5), margin = margin(15,15,15,15)),
axis.title = element_text(size = rel(1.2)),
axis.title.x = element_text(margin = margin(10,5,5,5)),
axis.title.y = element_text(margin = margin(5,10,5,5)),
axis.text = element_text(size = rel(1.2)))
The bar chart shows The average interenst rate by the Loan purposed. We can tell with longer term(60 months), the interest rate is higher than the shorter one (36 months). This might happen because for longer term, it increase the risk of longer repayment periods.
ggplot(data = loans_full_schema) +
stat_summary(mapping = aes(x = grade , y = interest_rate) , fun = "mean", geom = "bar", position = "dodge") +
labs(title = "Mean Interest Rate by Credit Grade",
x = "Grade",
y = " Mean Interest Rate") +
theme(plot.title = element_text(hjust = 0.5, size = rel(1.5), margin = margin(15,15,15,15)),
axis.title = element_text(size = rel(1.2)),
axis.title.x = element_text(margin = margin(10,5,5,5)),
axis.title.y = element_text(margin = margin(5,10,5,5)),
axis.text = element_text(size = rel(1.2)))
Based on the visualization, the lower grade would have higher interest
rate. This reflects risk-based pricing, where borrowers with lower
creditworthiness are charged higher interest rates.
ggplot(data = loans_full_schema) +
stat_summary(mapping = aes(x = loan_purpose , y = annual_income) , fun = "mean", geom = "bar", position = "dodge") +
coord_flip()+
labs(title = "Mean Anual Income by Loan Purpose",
x = "Loan Purpose",
y = " Mean Anual Income") +
theme(plot.title = element_text(hjust = 0.5, size = rel(1.5), margin = margin(15,15,15,15)),
axis.title = element_text(size = rel(1.2)),
axis.title.x = element_text(margin = margin(10,5,5,5)),
axis.title.y = element_text(margin = margin(5,10,5,5)))
Borrowers with higher annual income tend to take loans for large purchases, renewable energy investments, or major financial commitments, suggesting that higher-income individuals may use loans strategically rather than for debt consolidation