The other red curved line is a LOWESS (LOcally WEighted Scatter-plot Smoother) that fits a smooth curve between these two variables. The linear regression curve (straight red line) gives us an r-square value of 0.276. Well, we can put each variable on the x-axis and y-axis of a graph and see how it all looks. What’s the best way to see how variables relate to each other? For example, how does the resource deprivation/affluence composite variable relate to homicide rates? READ MORE: Cartogram Maps: Data Visualization with Exaggeration You may not have even known this represented the United States population if I didn’t tell you! This means that readers may have difficulty understanding the features on the map.
However, the downfall of these types of cartograms is that the centroid and shape are not maintained. This is also known as Dorling Cartograms. For example, here we see clusters of the population in the United States. The cartogram tool substitutes appropriately-sized circles to represent a variable. The neat thing about is how it interactively generates a histogram as you change the dividing lines in your data. If you don’t want to use these types of data classification methods, then GeoDa has a Category Editor tool for you to interactively edit custom breaks in the data. READ MORE: Choropleth Maps – A Guide to Data Classification Rates-Calculated Map – Uses spatial weights to classify data.Equal Intervals Map – Divides classes into equal groups.Natural Breaks Map – Arranges each groupings so there is less variation in each class.Unique Values Map – Uniquely groups values into categories.Standard Deviation Map – Each standard deviation becomes a class.
Box Map – A quartile map where outliers are shaded differently.
Percentile Map – Shades data in different percentiles (99%).Quantile Map – Arranges groups so they have the same quantity.The maps and rate drop-down give you an abundance of ways to classify your data. Really, you get more options than QGIS and ArcGIS in terms of data classification. Anyone can gain insights from their data through the means of visualizations in the forms of thematic maps, cartograms, and map movies. This is one of GeoDa’s specialties – its geo-visualization tools.
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