GEOG 865
Cloud and Server GIS

Exporting data


Since your boss only speaks Excel, it might be nice to get your stores spreadsheet back with all these enriching variables added. This can be accomplished via a simple table join from the enriched service areas back onto the delivery points.

  1. In the map viewer, open your Delivery analysis map from the previous section of the lesson.
  2. Click Analysis, and click Summarize Data > Join Features.
  3. Set up the join with delivery as the target layer and the Enriched travel time polygons as the join layer. Using the Choose the fields to match button, make sure you are doing an attribute join between the NAME and the NAME_1 fields (do not use “Name”--that was a field added by Esri which caused some clunkiness here with our joins). Take the defaults for all attributes not shown below, and click Run Analysis.

    It may not always be a safe choice to do a join on a name field if there is the possibility of repeated names. In this case, it is fine because the name field contains a unique store number.

    You might have wondered why we didn't do a spatial join. This is because a store location could conceivably fall within two or more service areas. Doing an attribute join ensures a one-to-one relationship between a store and its polygon.
  4. Ensure that a join layer appears symbolized by points. You should be able to open the attribute table on this layer and see all your enriched variables.
    Let’s make a map with this layer. How about total restaurant spending of each service area symbolized by proportionally sized circles?
  5. In the left-hand layer list, hover over the layer name of Join Features to delivery and click Change Style (it’s the icon right next to the attribute table icon).
  6.  Choose to symbolize the TotalRestaurantSpending attribute, and choose Counts and Amounts (Size). Then click its blue Options button.
  7. Play around with the symbol properties until you find something you like.
  8. Turn off the other layers, and examine your resulting map of restaurant spending within each store’s service area.

    Remember that this spending pertains to all restaurants; the amount of spending on sushi at your company's stores could follow a quite different pattern. A choropleth map of the service area polygons might be a be an alternative choice, but it would have its own challenges due to polygons overlapping.

    That’s enough mapping for the time being. Let’s get back to exporting this data to a spreadsheet.
  9. Click Analysis, and choose Manage Data > Extract Data.
  10. Choose to extract Join features to delivery, and set the Study Area to be the same as display (just make sure your map is zoomed out to show all four stores).
  11. Leave the output format as CSV, and choose an output file name.
  12. Click Run Analysis.
  13. In the upper left corner of your map viewer, click Home > Content.
  14. Find your extracted CSV, and click on its name to see its item details. (If it's not there, wait a few minutes and refresh.)
  15. Click the Download button to save the CSV to your local computer.
  16. Open the spreadsheet in a program such as Excel, and verify that it contains all the original information about your four stores, plus the enriched variables. As a bonus, you’ll notice the data also comes with Lat and Lon fields since it was geocoded by your software.