Objective: Build a dashboard and/or perform an analysis of Housing data that con

Objective: Build a dashboard and/or perform an analysis of Housing data that conveys to the user interesting information around homes in Boston. Explore and communicate patterns in the data using excels functionality.
Feature Explanation:
CRIM: Per capita crime rate by town.
ZN: Proportion of residential land zoned for large lots (over 25,000 sq. ft.).
INDUS: Proportion of non-retail business acres per town.
CHAS: Charles River dummy variable (1 if tract bounds river; 0 otherwise).
NOX: Nitric oxides concentration (parts per 10 million).
RM: Average number of rooms per dwelling.
AGE: Proportion of owner-occupied units built prior to 1940.
DIS: Weighted distances to five Boston employment centers.
RAD: Index of accessibility to radial highways.
TAX: Full-value property tax rate per $10,000.
PTRATIO: Pupil-teacher ratio by town.
B: 1000(Bk – 0.63)^2 where Bk is the proportion of Black residents by town.
LSTAT: Percentage of lower status of the population.
MEDV: Median value of owner-occupied homes in $1000s.
Scatter Plot:
Create a scatter plot to visualize the relationship between the average number of rooms (RM) and the median home value (MEDV). What insights can be drawn from the plot?
Crime Rate and Price Relationship:
Develop a scatter plot or another suitable chart to illustrate the relationship between the per capita crime rate (CRIM) and the median home value (MEDV). What conclusions can be made from this visualization?
Neighborhood Crime Distribution:
Construct a bar chart to display the distribution of crime rates (CRIM) across different neighborhoods. Are there any specific neighborhoods with notably high or low crime rates?
Key Metrics Display:
Design a section in the dashboard to display key metrics such as the average room count, crime rate, and median home value. How do these metrics vary across the dataset?
Discovering Patterns:
Identify and visualize an interesting pattern or trend in the data that you believe may influence the median home value (MEDV). This could be a variable not explicitly mentioned in the instructions. Provide a brief explanation of why you find this pattern noteworthy
What variable do you believe has the greatest impact on MEDV?