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A choropleth map (from Ancient Greek χῶρος (khôros) 'area, region' and πλῆθος (plêthos) 'multitude') is a type of statistical thematic map that uses pseudocolor, meaning color corresponding with an aggregate summary of a geographic characteristic within spatial enumeration units, such as population density or per-capita income.
The dataset should be stored at Wikimedia commons, in the Data namespace, as a tabular data (.tab) file. Currently, the file format should be JSON, representing a three column table, where the first column is the three-letter ISO country code, the second is the year and the third is the value.
Choropleth map showing estimated percent of the population below 150% poverty in the Contiguous United States by county, 2020 that uses the Jenks natural breaks classification. Jenks’ goal in developing this method was to create a map that was absolutely accurate, in terms of the representation of data's spatial attributes.
Gradient maps (scientific name: Choropleth) are a light and basic visualisation of spacial areas and their associated values for a single thematic issue, by example the population density by country. Gradient maps need 3 key things: 1. a solidly sourced list of regions⇔values for one issue, 2. a map displaying these regions, 3. a sequential ...
A bivariate map or multivariate map is a type of thematic map that displays two or more variables on a single map by combining different sets of symbols. [1] Each of the variables is represented using a standard thematic map technique, such as choropleth, cartogram, or proportional symbols. They may be the same type or different types, and they ...
scaleType: supported values are linear for a linear mapping between the data values and the color scale, log for a log mapping, pow for a power mapping (the exponent can be provided as pow 0.5), sqrt for a square-root mapping, and quantize for a quantized scale, i.e. the data is grouped in as many classes as the color palette has colors.
Because most types of thematic maps are designed to portray quantitative data, one could assume that a nominal variable would dictate the creation of a chorochromatic map. [12] However, choropleth maps can be used to portray nominal data that is created by aggregating and summarizing a geographic variable within predetermined districts. The ...
There has been significant debate around the best approach to solve this issue with choropleth maps, and most choropleth maps today continue to make use of class breaks. [40] [39] [41] [42] Other approaches to creating classes in choropleth maps include using the Jenks natural breaks optimization, quantile, or equal class intervals. [43] [44] [45]