Charts (Part I?)

• We will be working with this data.
  • Housing sales in 2014/5 in Kings County Washington State.
  • From Kaggle.
• Setup
  • Delete the ID column.
  • Please add three columns after A and turn the date field into Year, Month, Day
    • Do this with text formulas just to remind yourself how.
    • 
    • 
  • Select the entire table and use the name manager to name the columns.
• In data science there are frequently two stages of making charts
  • Exploratory analysis
  • Presentation.
• You find MANY documents that discuss the difference.
  • Don't feed people a bunch of charts from data analysis.
  • These are your work, to figure out what is happening in the data.
  • These don't need to be completely documented.
  • But they do need to be accurate.
• For presentations
  • I love the book storytelling with data by Cole Nussbaumer Knaflic.
  • But This article will do.
• The rules for presentation graphs
  • Everything is labeled
    • Title
    • Axis
    • Data
    • Correctly labeling your data helps
    • Add titles and axis labels and everything else.
    • This is a matter of discipline.
    • It is way too easy to just slap up a chart and consider it done.
  • Make sure it is right
    • And don't change scales or other items to make it "better"
  • Don't go wild with chart types
    • Use charts people understand.
    • Avoid 3D
    • Make simple charts/graphs.
    • Eliminate clutter.
  • Some of what we will do in the next classes will contradict this.
    • For exploration we will probably not label everything.
    • We will probably overdo charts as well.
    • We want to learn as many pieces as we can.
    • But just because you know them doesn't mean you need to use them.
• Let's try a graph.
  • My intuition tells me that the size of the house is related to it's price.
  • So let's build a scatter plot to see if that is true.
  • Insert a new worksheet
  • Select the Price column (E) and the sqft_living(H)
  • On the insert tab, select the scatter plot chart
  • 
  • I cut and pasted this to the new worksheet.
  • 
• What is a scatter plot?
  • For each pair (price, sq_ft) it plots a point.
  • It does this for all of the data.
  • So what do we see in this scatter plot?
    • There is a correlation between these two values.
    • Correlation does not imply causation.
    • And it is perhaps not quite as strong as we would like
  • Let's try an experiment.
    • Grab a new worksheet
    • In column A generate the numbers 1 = 200 (just to keep track) in a column
    • In columns B and C generate 200 random numbers with (randbetween(1,1000)) in the next two columns.
    • Copy these to columns E-G, paste as values
    • Generate a scatter plot from columns F and G
    • Let's try something silly.
      • norm.inv will give us an inverse normal function.
      • We can use this to generate normally distributed data.
      • In J2 put x, K2 100
      • In J3 put s, K3 10
      • In H2 put =F2+norm.inv(rand(),$K$2,$K$#)
      • 
      • plot this (columns F and H)
      • Change s to be 50
      • Change s to be 1000
    • Sometimes it is helpful in a scatter plot to see a trendline
      • Click on the chart, the + sign and select trendline
      • 
      • Click on the arrow and select more options
      • If you are not on the Trendline Options, select these.
      • 
      • Select liner
      • Also select show trendline.
      • Move to the line section
      • 
      • Select red (so we can see the line)
      • 
• Adjusting elements of a graph.
  • Between the + tool clicking on elements.
  • This is a learn by exploring thing.
  • Back to the SQFT_Living
    • Change the title to Price vs Living Space
    • Add an x and y axis label for Price and Square Foot
    • Format the x axis as currency
    • Rotate the labels by -45 degrees.
    • Add a trend line.
    • 
  • Note charts are tied to the data.
    • Go back to the data and turn that into a table.
    • Filter price for values less than $1,000,000
    • Filter price for values less than $200,000
    • Notice that the scatter plot changes as well.
  • Plot the square foot of the lot vs the price.
    • Does this tell you anything?
• If there is time,
  • Can you find the average price of a house based on the condition?
  • How would you display this?