S8: plotting insights with ggplot2

Instructions
Use this template for the in-class activity. Create a graph to addresses each of the following insights from the global superstore data set. Where applicable, your graph and/or description should clearly explain any relevant definitions. For example, if you are discussing the “most important” market, then you should explain how you are measuring “most important”. For each graph, include a 1-2 sentence description with a deeper analysis of the main insight of the graph.

orders <- read_csv("Global Superstore Orders.csv")

Parsed with column specification:
cols(
  .default = col_character(),
  `Row ID` = col_integer(),
  Sales = col_double(),
  Quantity = col_integer(),
  Discount = col_double(),
  Profit = col_double(),
  `Shipping Cost` = col_double()
)
See spec(...) for full column specifications.

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Insight #1: The most profitable sub-categories are in Technology.
Create a graph to describe the most profitable subcategories and fill the color by category. The graph should look like this:

Your description here

# INSERT CODE HERE

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Insight #2: There is seasonality in our global sales.

Your description here

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Insight #3: The most important market is APAC Market

Your description here. Remember to explain the measure of importance and narrate your graph.

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Insight #4: (Find your own)

Your description here

# INSERT CODE HERE

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