Here we have a Python script to audit a local Colorado congressional election and report the voting breakdown by county and candidate. The script reads the CSV file election_results.csv of format Ballot ID,County,Candidate and tallies the number of votes by county and candidate. It then reports the total number of votes cast, the breakdown by county and candidate, the largest county turnout, and the winner of the election to the terminal and output file election_results.txt.

• Data source: election_results.csv
• Software: Python 3.7.6, Visual Studio Code 1.51.1

To perform this analysis, we loop through each row in the input file using csv.reader, adding to the total vote count and acquiring the chosen candidate and voting county with each iteration:

# Read the csv and convert it into a list of dictionaries
with open(file_to_load) as election_data:
    reader = csv.reader(election_data)

    # Read the header
    header = next(reader)

    # For each row in the CSV file.
    for row in reader:

        # Add to the total vote count
        total_votes = total_votes + 1 

        # Get the candidate name from each row.
        candidate_name = row[2]

        # 3: Extract the county name from each row.
        county_name = row[1]

We then check if this is the first instance of each candidate and county and if so, add it to the results dictionaries candidate_votes and county_votes with initial counts of zero. We then increment the count for this and all subsequent instances of the current row's candidate_name and county_name. Finally, we loop through both results dictionaries to determine winner of the election and the county casting the most votes. In the case of the candidates, we first initialize the following variables:

winning_count = 0
winning_percentage = 0
winning_candidate = ""

We can then find the winner as follows:

for candidate_name in candidate_votes:
    # Retrieve vote count and percentage
    votes = candidate_votes.get(candidate_name)
    vote_percentage = float(votes) / float(total_votes) * 100

    # Write results votes and vote_percentage for candidate_name to
    # terminal and output file

    # Determine winning vote count, winning percentage, and candidate.
    if (votes > winning_count) and (vote_percentage > winning_percentage):
        winning_count = votes
        winning_candidate = candidate_name
        winning_percentage = vote_percentage

We are then left with the winning_count, winning_candidate, and winning_percentage set to the correct values from candidate_votes which we then write to the terminal and output file election_results.txt. The process is similar for the county results.

The analysis of the election shows that:

• There were 369,711 votes cast in the election.
• The county results were:
  • Jefferson: 10.5% (38,855)
  • Denver: 82.8% (306,055)
  • Arapahoe: 6.7% (24,801)
• The county with the largest voter turnout was:
  • Denver, with 82.8% of the vote and 306,055 votes
• The candidate results were
  • Charles Casper Stockham: 23.0% (85,213)
  • Diana DeGette: 73.8% (272,892)
  • Raymon Anthony Doane: 3.1% (11,606)
• The winner of the election was:
  • Diana DeGette, who received 73.8% of the vote and 272,892 votes.

Through this audit of a Colorado local congressional election, we find the county with the largest voter turnout to be Denver providing 82.8% of the vote for a total of 306,055 votes and the winner to be Diana DeGette with 73.8% of the vote for a total of 272,892 votes. This script is generalizable to other election data sources following the same format as election_results.csv with the replacement of the hard-coded input file name election_results.csv with an input parameter. One method to do so would be to move the entire script within a function analyze_election_data with input parameter infile, as shown below:

def analyze_election_data(infile):
    """
    Parameters
    ----------
    infile : str, file name of election results CSV file, placed in Resources
             directory
    """

We would then set our input file as:

file_to_load = os.path.join("Resources", infile)

and import/call the function from the Python interpreter as:

>>> from PyPoll_Challenge import analyze_election_data
>>> analyze_election_data(input_file.csv)

An alternative is to input the CSV file from the command line using sys.argv. This would require the following addition:

import sys
args = sys.argv

We then have a list args whose first element is the script name and all subsequent elements are those passed from the command line after the script from left to right. We can thus set our input file as:

file_to_load = os.path.join("Resources", args[1])

and run the script from the command line:

$ python PyPoll_Challenge.py input_file.csv

Looking forward, we could further this analysis by considering the breakdown of each candidate vote by county and plot the results to visualize potential relationships between the two. This would be particularly useful for a more general dataset with a wider distribution of counties in order to analyze regional trends.