Databases Reference
In-Depth Information
The initial location plot view is a map where all observations are plotted as
red dots. Map navigation is:
pan - right-button drag
zoom - mouse scroll; as you scroll, the map is automatically centered at the
current mouse pointer position.
Notice in the original display, that most of the homes are located around or
near Utah Lake. There is one home located to the north and east in the South
Snyderville Basin near Park City, Utah. This observation is an outlier. (Outliers
are discussed later in the chapter.) It most likely got its location due to a data
entry error.
To begin exploration:
move the mouse pointer to a position near Provo Bay on Utah Lake; use
your mouse wheel to zoom in a single click. At this zoom level, all
observations are visible except for the previously mentioned outlier. You
may, however, need to pan slightly to include the upper or lower concen-
tration of points.
As you explore this visualization, you may be tempted to think of the
application as a home-finding tool for a potential home buyer. With a few
modifications, it could be used for that purpose. Keep in mind that the objective
here is data mining. We are looking for patterns in the dataset, not great homes at
a bargain price.
In the pane to the right of the map are controls to facilitate the pattern search.
(See Figure 3.3.) On top are the category and color encoding options that
implement color highlighting of potential relations. Below are the numeric and
category filters that allow selective viewing of subsets of data using both the
numeric and nominal (category) column values as filters. The numeric filters are
double-ended sliders that delineate the range of filtered values. The category
filters allow you to include in the display observations having selected
values only.
In the Category drop-down, select “schoolDistrict”.
To make it easier to read and visually locate, drag the small category key
from the upper right corner of the map down over Utah Lake.
Can you readily locate school district boundaries? Although you probably
would not use a data mining tool to look up political boundaries, the visualiza-
tion does provide a quick assessment of the data quality. For example, notice the
inconsistencies in school district for homes located up highway 189 in the
