Using R studio solve Problem 1: Reshape us_rent_income (from the tidyr package) so that it has one line per state, and two new columns named estimate_income and estimate_rent that contain values from estimate. Create a dataframet from state.x77, available in R. Add to the above dataframe two column region=state.region and division=state.division. Merge the last dataframe with the reshaped us_rent_income, keep all rows. From the merged dataframe drop rows where any values are missing. Add a column with the proportion of income spent on rent (rent / income). Drop rows where Area is not greater than ten times Frost. Replace all spaces in all column names with dashes (e.g., HS Grad to HS-Grad). Without removing any rows, add a column with the population-weighted mean rent by geographic division. Which division has the highest mean rent? Save the resulting dataframe as a CSV file.
