################# # Module 10 # Data Cleaning and Plotting ############## ## Read the property taxes dataset from yesterday # 1. Make boxplots using a) default and b) ggplot2 graphics showing cityTax # by whether the property is a principal residence or not. # 2. Subset the data to only retain those houses that are principal residences. # a) How many such houses are there? # b) Describe the distribution of property taxes on these residences. # 3. Convert the 'lotSize' variable to a numeric square feet variable. # Tips: - Assume hyphens represent decimal places within measurements. # - 1 acre = 43560 square feet # - Don't spend more than 5-10 minutes on this; stop and move on # 4.a) Plot your numeric lotSize versus cityTax on principal residences. # b) How many values of lot size were missing? ## Read in the Salary FY2012 dataset # 5. Plot annual salary versus hire date. # Hint: first convert to numeric and date respectively # 6. Create a smaller dataset that only includes the # Police Department, Fire Department and Sheriff's Office. # a. How many employees are in this new dataset? # b. Replot annual salary versus hire date, color by Agency using # i) regular plotting and ii) ggplot2