Geographical Data Aalysis (voting, demographics, etc.) with Python
Raw data was downloaded from Electoral Commission website in CSV format (http://www.electoralcommission.org.uk/find-information-by-subject/elections-and-referendums/upcoming-elections-and-referendums/eu-referendum/electorate-and-count-information).
Data file format as follows (header plus example data row):
"id","Region_Code","Region","Area_Code","Area","Electorate","ExpectedBallots","VerifiedBallotPapers","Pct_Turnout","Votes_Cast","Valid_Votes","Remain","Leave","Rejected_Ballots","No_official_mark","Voting_for_both_answers","Writing_or_mark","Unmarked_or_void","Pct_Remain","Pct_Leave","Pct_Rejected" "100","E00000000","xxxxxxx","E00000000","xxxxxxxxxxxx","123456","12345","12345","00.00","12345","12345","12345","12345","00","0","00","0","00","00.00","00.00","0.00"
Program reads raw data from file, updates to SQLite database, scores the voting and updates to database, then calcultes/displays various top ten results by voting area.