Addressing Employee Attrition For this assignment we will look at the employee attrition data. Ideally, companies would like to keep attrition rates (the proportion of employees leaving a company for other opportunities) as low as possible due to the variable costs and business disruptions that come with replacing productive employees on short notice. In the recent past, before Covid struck, the company had seen an increase in the rate of employee departures. Being a tech company, and with certain skills being rare, employee retention has been a challenge. This has taken a toll on their operations and ability to deliver quality products. The information related to the dataset is available below. Employee Attrition Data The following data consists of 1,470 employee records for a U.S. based product company. The rows in this data frame represent an employee's attributes across the variables listed in the table below. Variable Definition Did the employee leave the company? (Yes/No) Department within the company Job Level (Associate - Vice President) Employee yearly salary (US Dollars) Data Type Factor Categorical Categorical Numeric left_company department job_level salary weekly_hours Self-reported average weekly hours spent on the Numeric job (company survey) business_travel Level of required business travel Categorical yrs_at_company Tenure at the company (years) Numeric yrs_since_promotion Years since last promotion Numeric previous_companies Number of previous companies for which the Numeric employee has worked job_satisfaction Self-reported job satisfaction (company survey) Factor performance_rating Most recent annual performance rating Factor marital_status Marital status (Single, Married, or Divorced) Categorical miles_from_home Distance from employee address to office location Numeric While importing the data csv file, the data type may not match with the data type given above. Please convert them to appropriate data type, before doing any analysis.