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Home Page: https://public.tableau.com/profile/damien4566#!/
Analysis of AEC data
Home Page: https://public.tableau.com/profile/damien4566#!/
It seems that in the 2019 federal election data the two Trevallyn booths have been mixed up.
PollingPlaceID = 8338
PollingPlaceNm = Riverside West
PremisesNm = Trevallyn Life Church
Greens senate vote = 8%
PollingPlaceID = 8342
PollingPlaceNm = Trevallyn
PremisesNm = Trevallyn Primary School
Greens senate vote = 24%
PollingPlaceID = 8342
PollingPlaceNm = Trevallyn
PremisesNm = Trevallyn Life Church
Greens senate vote = 10%
PollingPlaceID = 8338
PollingPlaceNm = Trevallyn Central
PremisesNm = Trevallyn Primary School
Greens senate vote = 24%
The AEC makes available the full details of everyone's senate ballot (i.e. how they numbered every single column):
Prior to that group ticket voting was in place and hence the same richness of information was not available.
It looks like GeoPandas in combination with contextily can create maps similar to what Google Fusion tables used to produce:
http://geopandas.org/gallery/plotting_basemap_background.html#sphx-glr-gallery-plotting-basemap-background-py
I need to make sure that my overall results match those reported by the AEC:
https://tallyroom.aec.gov.au/SenateStateFirstPrefsByGroup-24310-TAS.htm
The AEC and TEC use a different format for their csv data files. I should therefore process the raw data files into a consistent format that I can use in all subsequent analysis. I'm thinking two different scripts - aec_to_tasgreens.py
and tec_to_tasgreens.csv
- that produce two different csv files:
ordinary_votes.csv
with the following column headers (i.e. for each polling place):
| PollingPlaceNm | PremisesNm | Latitude | Longitude | LegCo | LocalCouncil | DivisionNm | GreensVotes | TotalVotes | GreensPercentage |
vote_types.csv
with the following column headers (i.e. for the statewide and electorate totals and Greens totals):
| OrdinaryVotes | OutOfDivisionVotes | MobileVotes | PostalVotes | PrePollVotes | ProvisionalVotes |
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