GitHub - p3ris0n/Outlier-Detection-with-Geospatial-Analysis-: Outlier Detection in Election Data Using Geospatial Analysis. The analysis will involve geospatial techniques to find neighbouring polling units and calculate an outlier score for each party in each unit. The goal is to pinpoint polling units where the voting results significantly deviate from their neighbours, indicating potential irregularities

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
.gitattributes		.gitattributes
KOGI_PU_maps.html		KOGI_PU_maps.html
KOGI_crosschecked.csv		KOGI_crosschecked.csv
KOGI_crosschecked_coordinates.csv		KOGI_crosschecked_coordinates.csv
KOGI_outlier_scores.csv		KOGI_outlier_scores.csv
KOGI_outlier_scores.xlsx		KOGI_outlier_scores.xlsx
Top_3_outliers_APC.png		Top_3_outliers_APC.png
Top_3_outliers_LP.png		Top_3_outliers_LP.png
Top_3_outliers_NNPP.png		Top_3_outliers_NNPP.png
Top_3_outliers_PDP.png		Top_3_outliers_PDP.png
geo.py		geo.py
polling-units.csv		polling-units.csv

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Outlier Detection in Election Data Using Geospatial Analysis. The analysis will involve geospatial techniques to find neighbouring polling units and calculate an outlier score for each party in each unit. The goal is to pinpoint polling units where the voting results significantly deviate from their neighbours, indicating potential irregularities