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gLocal

Performs the Gi or Gi* statistic on the x column of the dataframe. 
def gLocal(
      dataframe: DataFrame,
      x: String,
      weights: String = "weights",
      permutations: Int = 0,
      star: Boolean = false,
      islandWeight: Double = 0.0): DataFrame =
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dataframe
DataFrame
the dataframe to perform the G statistic on
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x
String
The column name we want to perform hotspot analysis on
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weights
String
The column name containing the neighbors array. The array should be of type Array<Struct<value: T, neighbor: U>>, where each element is a Struct with two fields:
  1. value: The weight for the neighbor (e.g., spatial weight).
  2. neighbor: A Struct containing the data of the neighboring row (schema must match the parent row, excluding the neighbors/weights column itself). You can use wherobots.weighing.add_distance_band_column to generate this column in the required format.
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permutations
Int
Not used. Permutation tests are not supported yet. The number of permutations to use for the significance test.
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star
Boolean
Specifies whether to calculate the Getis-Ord Gi* statistic.
  • true: Calculates the Gi* statistic, which includes the focal observation (the row itself) in the local sum. When star=true, the weights array must include the focal observation as one of its own neighbors.
  • false: (Default) Calculates the G-statistic, which excludes the focal observation.
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islandWeight
Double
Not used. The weight for the simulated neighbor used for records without a neighbor in perm tests

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Returns

A DataFrame with the original columns plus the following additional columns:
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G
Double
The calculated local G or G* statistic.
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E[G]
Double
The expected value of G/G* under spatial randomness.
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V[G]
Double
The variance of G/G* under spatial randomness.
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Z
Double
The Z-score (standard score) for the statistic.
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P
Double
The p-value (significance) derived from the Z-score.

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Usage Examples

import org.apache.sedona.stats.clustering.GetisOrd

// Example usage
val result = GetisOrd.gLocal(dataframe, epsilon, minPts)