For project 3 we have chosen a dataset called the economic indicator.
The dataset contains various economic indicators, organized by year and month. Below is a summary of what each column represents:
- Year and Month: The time frame for the data, with separate columns for the year and month.
- logan_passengers: The number of passengers at Logan Airport.
- logan_intl_flights: The number of international flights at Logan Airport.
- hotel_occup_rate: The occupancy rate of hotels.
- hotel_avg_daily_rate: The average daily rate for hotel stays.
- total_jobs: The total number of jobs.
- unemp_rate: The unemployment rate.
- labor_force_part_rate: The labor force participation rate.
- pipeline_unit: Information related to housing or development projects, possibly the number of units.
- pipeline_total_dev_cost: The total development cost for projects in the pipeline.
- pipeline_sqft: The total square footage of development projects in the pipeline.
- pipeline_const_jobs: The number of construction jobs created by pipeline projects.
- foreclosure_pet: The number of foreclosure petitions.
- foreclosure_deeds: The number of foreclosure deeds.
- med_housing_price: The median housing price.
- housing_sales_vol: The volume of housing sales.
- new_housing_const_permits: The number of new housing construction permits issued.
- new-affordable_housing_permits: The number of permits issued for new affordable housing.
This dataset offers a comprehensive view of various economic factors including transportation (air travel), hospitality (hotels), employment, real estate, and housing market indicators. Each of these metrics can provide insights into the economic health and trends of the region or area being studied.