Poverty

1 A:

Since the data is already in a .csv file, then I can simply open it via Excel and edit/reformat the values from there. For example, I will change the Sales’ format to Currency (with 2 or 0 decimal places, depending on the requirements) and I will center-align all the headings and titles. As per the categorization, I will use the Find and Replace command (Ctrl + F) and replace all the RS by R and WS by W. Of course, to do this, I will press Ctrl+F, click the Replace tab, put RS in the “find what” input, put R in the “replace with” input, then check the “Match case option” and “Match entire cells content”. This way, I am guaranteed that the only values I am replacing are the ones from the categories. I also chose to replace RS and WS because R and W are more common to find in the document, making replacing letters much more difficult. After that, I will Spellcheck the whole spreadsheet to look for typographical errors.

1 B:

After the file has been reformatted and cleaned, I will summarize monthly sales by adding the sales with respect to their months (of course, I will only add RS with RS and WS with WS, not RS with WS). For example, if the daily sales are given, then I will add everything for the month of June and put the total next to a cell named “June”, and so forth. I will display these monthly sales in another column for easier viewing, so that I will have Retail monthly sales and Wholesale monthly sales for each location per month. Then, as always, it is imperative to create a chart of sales, hence, I will create a column chart for these sales so that I can examine their growth (by location, category of sale is separated by color of bars), then I will add a regression line to further clarify how their growth goes.

1 C:

As said above, I will create a column chart for each location, putting Month in my x-axis and Retail and Wholesale sales to be contained in the columns. I will let the Retail columns blue and the Wholesale columns red. After that,...