The multisectioned map above shows the San Francisco area with two storefronts of the hypothetical Better Books business, and various demographic aspects (household income, percent with some college, etc.) of the area. The one-part map on the left shows average house value (for my own interest) but it also indicates a one-mile buffer around each of the stores, which is presumed to be the market area. This week's work was relatively uncomplicated one. In some ways the tables I created (not shown) to go along with the maps were more interesting, because they showed a smaller overall dollar intake from the Steiner market area but a considerably higher average purchase for each Steiner Book Lover customer. Nice to know that it's not always maps that are illuminating.
An unrelated but useful map-related thing I learned this week - for my internship work, not for this - was that cutting down the size of your data can make a big difference. In my case it was the difference between having ArcGIS run and having ArcGIS freeze, so I was pretty thrilled when I finally figured it out. The dataset in question was a huge watershed file. It was a big advance when I realized that even though I could use a definition query to reduce the size of the visible file, that wouldn't stop my freezing problem. Selecting and exporting part of the data file made an astonishing difference. Next time I have big files I hope I remember to spend a small amount of useful time at the beginning to avoid spending a lot of unproductive time later.
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