Departing Flights: General Case You Want To Research Morning

Departing Flights General Caseyou Want To Research Morning Flight De

Research morning flight departures from Tulsa International Airport (TUL) using data obtained from flightstats.com. Find the airport’s departing flight schedule for yesterday morning, copy the flight information into a new workbook, and name the workbook e05b1Tulsa_LastFirst. Clean up the data after copying it. Name the worksheet Departures.

Copy the worksheet and rename it Morning Departures. Sort the data on the Departures sheet by destination, then by airline. Insert subtotals at each change in destination, counting the number of flights, then collapse the subtotals to display the subtotals and grand totals. Create a blank PivotTable from the Morning Departures sheet, displaying Destination and Airline in rows, Status in columns (to show canceled, on-time, and delayed flights), and Flight in the values area with the count function. Add Departure Time as a filter, set it to include only departures from 6 to 9 a.m., and name the PivotTable Morning Departure Status. Apply PivotStyle Medium 13, adjust column widths, and create a new worksheet named PivotTable.

Generate a PivotChart from the original dataset, using Destination as the axis and Flight # as the value (Count). Change the chart type to bar, resize it to 3.75" height and 5.75" width, and add a slicer for the Status field, selecting only on-time departures. Add a chart title On-Time Departures. Insert a footer with your name, the sheet name code, and the file name code on each worksheet. Save and close the file.

Paper For Above instruction

In this comprehensive analysis, we explore the operations and data management techniques applicable to airport departure data for Tulsa International Airport (TUL) with an emphasis on morning flights, augmented by the practical use of Microsoft Excel tools such as sorting, filtering, subtotals, PivotTables, and PivotCharts to generate insightful reports.

Firstly, acquiring accurate and timely data is crucial for meaningful analysis; in this case, we utilize data from flightstats.com reflecting all departures from Tulsa Airport for the previous morning. Once obtained, the flight data is transferred into a new Excel workbook, ensuring proper organization and clarity. The file is saved with a specific naming convention, "e05b1Tulsa_LastFirst," to facilitate tracking and identification.

The initial step involves cleaning the dataset to remove irrelevant or duplicate information, and then structuring it appropriately to facilitate sorting and analysis. The data is sorted first by destination city, then by airline name, to group flights logically, facilitating the analysis of destination patterns and airline performance. To summarize flights per destination, subtotals are inserted at each change in the destination, counting the number of flights for each route, with the subtotals collapsed by default to avoid clutter, while still providing summary insights.

Next, a PivotTable is created from the sorted data, focusing on key dimensions: Destination, Airline, and Flight Status. The PivotTable displays Destination and Airline in row fields; in column fields, it shows flight Status categories: canceled, on-time, and delayed flights. The Flight number field is added as a value, set to count the number of flights, thus assessing operational volumes across categories.

Filtering is applied to include only flights departing between 6 a.m. and 9 a.m., enabling focused analysis on morning departure efficiency. The PivotTable is titled "Morning Departure Status" and styled with PivotStyle Medium 13 to ensure readability and professional presentation. The worksheet housing the PivotTable is named accordingly.

A PivotChart is then generated to visualize the data, leveraging the Destination as the x-axis and the count of Flight numbers as the y-axis. The chart type is set to bar for clarity, resized precisely to 3.75 inches in height and 5.75 inches in width, allowing for easy interpretation. A slicer is added for the Status field, initially set to filter only on-time departures, facilitating dynamic filtering without altering the underlying data. The chart receives the title "On-Time Departures" to highlight the operational metric displayed.

Finally, a footer is appended to each worksheet containing your name, the worksheet’s sheet name code, and the filename code to assist with document identification. The completed workbook is then saved and closed, ready for submission. This process exemplifies key Excel skills—including data import, cleaning, sorting, subtotaling, PivotTable and PivotChart creation, and dynamic filtering—that are integral to efficient data analysis in transportation and logistics environments.

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