To answer the student's questions, worksheets should be created in Tableau: a map visual for Total Flights by state with a filter for airlines, and a highlight table for Distance by Quarter and Airline. The airline with the most flights from NY and the one with the highest mileage can be identified by analysis within the created worksheets.
The student's question involves the creation of worksheets in Tableau, a popular data visualization tool used to analyze data and create insightful dashboards. Specifically, the student is asking to create worksheets based on U.S. airline flights data for the years 2010 and 2011.
To create a map showing the total number of flights for each origin state:
- Drag the 'State' dimension to the canvas and select the 'Map' visualization type.
- Ensure that the 'Number of Records' measure is included to display the total number of flights.
- From the 'Color' shelf, choose the purple color palette and set it to display darker shades for higher total flights and lighter for fewer flights.
- Add a filter for 'Airline' to the Filters shelf to allow data to be filtered by specific airlines.
After creating the map, you can determine which airline has the most flights coming out of New York (NY) by selecting NY on the map and viewing the list of airlines in the tooltip or sidebar, sorted by number of flights.
To create a highlight table:
- Drag the 'Airline' dimension to the Rows shelf and 'Quarter' dimension to the Columns shelf.
- Drag the 'Distance' measure to the Text shelf and set it to calculate the total distance (you may need to change the aggregation to 'Sum').
- Apply formatting to highlight cells based on the total distance value.
By analyzing the highlight table, determine the airline with the most miles flown across all quarters by finding the airline with the highest aggregated distance value.
The student is also asked to create an additional worksheet using the flights data set. This could involve a variety of analyses such as time series for flight delays, most popular destinations, load factor trends, etc.