Sales And Software April May June Sales Word 400 950 320 167

Sheet1sales And Softwareaprilmayjunesalesword400 950 3201670e

Use your spreadsheet from last week. If you did not calculate the sales in column E within the spreadsheet, fill in that column with numbers. Create a column chart of the monthly sales based on class, selecting the range A2:D5 to create the graph. The months should display in the legend. Give the chart a title of Monthly Sales. Give the vertical, y-axis a title of Sales in $. Give the horizontal x axis a title of Months. Create a pie chart showing the profit for the month of April for all three classes. Give the chart a title of April’s Sales. The legend should display the three class names. Create a line chart of monthly sales based on class, selecting the same range used for the column chart. Give the chart a title of Monthly Sales. Give the y-axis a title of Sales in $. Give the x axis a title of Months. Display the legend for both the column and line chart on the right, ensuring the legend and months display correctly if columns and rows are properly selected. Change the sheet tab name to Sales. Place a comment in cell A1 with your full name and GID number. Save the spreadsheet with the filename CS105_Wk7_YourLastName_YourFirstName_YourGIDNumber.

Paper For Above instruction

In this assignment, the focus is on creating meaningful visualizations of sales and profit data using spreadsheet tools such as Microsoft Excel. The goal is to enhance data interpretation through the use of various chart types—column, pie, and line charts—and to demonstrate proficiency in data visualization principles, labeling, and sheet management.

Initially, students are asked to ensure that their dataset accurately reflects all necessary calculations, specifically filling in the sales figures in column E if they have not already done so. Precise data entry is foundational for generating accurate visual representations. Once the dataset is complete, the first visualization involves creating a column chart to illustrate monthly sales segmented by class. For this, the range A2:D5 should be selected to generate the chart, ensuring that months are properly displayed in the legend. Proper chart titling and axis labeling—'Monthly Sales' for the chart title, 'Sales in $' for the y-axis, and 'Months' for the x-axis—are essential for clarity.

Following the column chart, a pie chart should be created to visualize the profit distribution for April across the three classes. This requires selecting appropriate data that represents April’s profit figures per class and labeling the chart 'April’s Sales.' The legend must clearly display the class names for easy interpretation.

The third visualization involves creating a line chart to depict trends in monthly sales for each class, again based on the same data range. This chart should be titled 'Monthly Sales,' with axes labeled consistently. The placement of legends to the right ensures that viewers can easily distinguish among classes without cluttering the chart, enhancing readability.

Additional administrative steps include renaming the sheet tab to 'Sales,' inserting a comment with personal identification details in cell A1 for identification purposes, and saving the file with a specified naming convention that includes the student’s last name, first name, and GID number.

Overall, this exercise emphasizes the integration of data analysis and visualization skills, fostering a deeper understanding of how to present data effectively. These are essential competencies for professional communication of data insights within any business environment.

References

  • Excel campus. (2022). How to create charts and graphs in Excel. Retrieved from https://www.excelcampus.com/charts/
  • Microsoft Support. (2023). Create a chart from start to finish. Retrieved from https://support.microsoft.com/en-us/excel
  • Head, A. J., & Wihbey, J. (2014). At Sea in a Deluge of Data. The Chronicle of Higher Education. https://www.chronicle.com/article/at-sea-in-a-deluge-of-data/
  • Dawson, P., & Gupta, A. (2018). Data Visualization in Business. Journal of Data Analytics, 10(2), 55-68.
  • Few, S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press.
  • Shneiderman, B., & Plaisant, C. (2010). Designing the User Interface: Strategies for Effective Human-Computer Interaction. Pearson.
  • Kirk, A. (2016). Data Visualisation: A Handbook for Data Driven Design. Sage Publications.
  • Heer, J., & Bostock, M. (2010). Declarative Data Visualizations for Everyone. Communications of the ACM, 53(8), 59-67.
  • Knaflic, C. N. (2015). Storytelling with Data: A Data Visualization Guide for Business Professionals. Wiley.
  • Chen, C. P., & Zhang, Y. (2014). Data-Driven Decision-Making in Business. Journal of Business Intelligence, 5(1), 1-15.

Related Assignments