This report is based on analysing the dataset of Zamfara election conducted, the analysis should help uncover any potential irregularities and transparency. Through identification of outlier detection in polling unit indicating potential influences or rigging .
Findings
https://docs.google.com/spreadsheets/d/15xf8NkvJtC29DCqvS2WVIGYe7PeoBRl1Pz0SPLCGEK4/edit?usp=drivesdk google sheet shows the conversation of the address into longitude and latitude.
Findings and methodology
https://drive.google.com/file/d/19gGI_FIyR21o2N6gKhjJ_IZYAwaDIv9G/view?usp=drivesdkrl
shows google sheet report on outlier detection score and calculations of each geodesic distance.Harvesine formula was used to calculate the geodesic distance between the coordinates.
Top Outlier scores
After sorting,
115 for PDP in KETA I / MAKARANTA polling unit and its neightbours are: ['BAKIN GULBI / DANFAKO', 'RUGGAR NA ALI / PRIMARY SCHOOL', 'UNG. SARKIN FAWA / DAN FAKO', 'CHEDIYA / BAKIN KASUWA', 'TABKIN KAZAI II / PRIMARY SCHOOL', 'MARKE / PRIMARY SCHOOL']
89 for PDP in TABKIN KAZAI II / PRIMARY SCHOOL polling unit and its neighbours are : ['KETA I / MAKARANTA', 'BAKIN GULBI / DANFAKO', 'RUGGAR NA ALI / PRIMARY SCHOOL', 'UNG. SARKIN FAWA / DAN FAKO', 'CHEDIYA / BAKIN KASUWA', 'MARKE / PRIMARY SCHOOL']
87.5 for APC in SHAMUSHALE I /SHIYAR SABON GARI polling unit and its neighbours are: ['MADAMBAJI / GARKAR HAKIMI']
An image showing the visualisation of each party votes with its respective outlier score with the help of a seaborn and matplotlib.
Conclusion
The analysis was performed using google sheet,Python with libraries such as pandas, numpy and geopy etc.Geospatial analysis of election data successfully identified polling units with significant deviations in voting results which was further elaborated with the outlier scores
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