Comparative Archaeology Database | Center for Comparative Archaeology | University of Pittsburgh
Rosario Valley Architectural Gini Coefficient and Neighborhood Dataset
The data files below provide information on the plazuela area measurements for Los Encuentros. They are listed from smallest to largest, accompanied by their Lorenz curve calculations. In the data, "mounds" are synonymous with "structures." Structures are the basic unit of analysis and consist of heavily eroded platforms (i.e., mounds) upon which domestic superstructures would have been built.
[Comma delimited UTF-8 format]
[Excel format]
Each line in the .CSV file represents one plazuela. There are 582 lines, each with 13 variables separated by commas. The variables are listed in the following order:
| 1 | Site Name -- a number used to identify sites. |
| 2 | Area of Plazuela in Square Meters |
| 3 | Wide Method: f' - An index of change, this is the difference between the prior and subsequent observations, divided by two and rounded down. |
| 4 | Wide Method: f'' - An index of acceleration, this is the difference between the f’ values of prior and subsequent observations, divided by two and rounded down. |
| 5 | Narrow Method: f' - An index of change, this is the difference between the observation and the one that follows, divided by two and rounded down. |
| 6 | Narrow Method: f'' - An index of acceleration, this is the difference between the f’ values of the observation and of its prior counterpart, divided by two and rounded down. |
| 7 | Individual # -- a number used to count sites used for Plazuela Area calculations |
| 8 | Pop. frac: The share of the total population that the house-group has; i.e. 1/ [sum of all observations] |
| 9 | Income frac: The proportion of the population's total area that the mound has; i.e. [Mound Area]/[Sum of Area from all observations] |
| 10 | Line of Equality sum pop.: The cumulative value of each “population fraction” value, adding up to 1 on the final observation. |
| 11 | Lorenz Curve sum income: The cumulative value of each “income fraction” value, adding up to 1 on the final observation |
| 12 | G(i)*F(i+1): Calculates the differences between the line of equality and the Lorenz curve in order to estimate the area between them (via sums of their values) and consequently the Gini coefficient. |
| 13 | G(i+1)*F(i): Calculates the differences between the line of equality and the Lorenz curve in order to estimate the area between them (via sums of their values) and consequently the Gini coefficient. |
The first line of the .CSV file, for example, looks like this:
4861,3.57,,,0.79,,1,0.001718213,4.30125E-05,0.001718213,4.30125E-05,1.47809E-07,1.80518E-07
This means that 4861 has an area of 3.57 meters squared. The two variables that follow show how quickly the area changes between consecutive values, therefore 4861 has no values or zero for these variables because it begins the sequence of observations. It has a value of 0.79 for Narrow Method f' and no value for Narrow Method f".("Individual #'=1). 4861 is the first observation of this analysis, it makes up 0.17% of the total population ("Pop frac.=0.001718213), it has 4.30125E-05 of the population's total area ("income frac."=4.30125E-05), the cumulative share of the population counted with this site is 0.17% ("sum pop."=0.001718213), the cumulative share of the area counted with this site is 4.30125E-05 ("sum pop."=4.30125E-05), and the difference between the line of equality and Lorenz curve at this point is 1.47809E-07 ("G(i)*F(i+1)"=1.47809E-07;"G(i+1)*F(i) =1.80518E-07).