Abstract
This study explores US House election results from 1976 to 2022, focusing on US House of Representative trends from 2016-2022, and state-wide trends in Arizona from 2012-2022. From 2016-2020, the data was wrangled into three subsets, one for each cycle. To simplify the analysis, all parties that are outside of Republican and Democrat were grouped into a new generalized party called “Other”. These subsets were then displayed on a US map, where the fill of the state indicates which party has the house majority, while the label of the state indicates which party had the popular vote majority. This revealed insights into how the electoral system can lead to politicians that may not represent the sentiment of the population of the state. Zooming in on the state of Arizona, voting trends were analyzed over a longer time frame of 10 years, from 2012 to 2022. The mode of voting as well as the change in party in each district was visualized to create insights into how mode of voting will influence the winning candidate, and how that influences the winning party in each district.
Insights into voting trends are very important metrics for politicians and the general population as it can be directly be related to other aspects of life such as the economy and global politics. These insights can then help politicians target states where voter sentiment can make or break a politicians campaign.
The analysis focused on time-series analysis as the variables were view over time and the changes noted as valuable insights. The limitations for this project include the assumption that the conglomeration of minor parties will create a larger third party that will vote different from Democrat and Republican, though this is not the case in real life, where some minor parties will align closer to the larger parties and some will votes on their own ideas. Ulitmately, This study provides insights into US voting patterns and the impact of election results on future voting trends.
Introduction
Introducing the Dataset
The dataset, US House Election Results is sourced from MIT Election Data and Science Lab (MEDSL), offers a comprehensive overview of US House elections.
This dataset contains observations for elections held over 47 years from 1976 to 2022, encompassing a total of 32,452 recorded events. Each event is represented as a row with 20 attributes as columns. These columns provide details including the year, state, district, political party, candidate’s name, votes received, and various indicators such as whether it was a runoff election or if it was a write-in candidate.
EDA
# A tibble: 32,452 × 21
year state state_po state_fips state_cen state_ic office district stage
<dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 1976 ALABAMA AL 1 63 41 US HOUSE 1 GEN
2 1976 ALABAMA AL 1 63 41 US HOUSE 1 GEN
3 1976 ALABAMA AL 1 63 41 US HOUSE 1 GEN
4 1976 ALABAMA AL 1 63 41 US HOUSE 2 GEN
5 1976 ALABAMA AL 1 63 41 US HOUSE 2 GEN
6 1976 ALABAMA AL 1 63 41 US HOUSE 2 GEN
7 1976 ALABAMA AL 1 63 41 US HOUSE 3 GEN
8 1976 ALABAMA AL 1 63 41 US HOUSE 3 GEN
9 1976 ALABAMA AL 1 63 41 US HOUSE 3 GEN
10 1976 ALABAMA AL 1 63 41 US HOUSE 4 GEN
# ℹ 32,442 more rows
# ℹ 12 more variables: runoff <dbl>, special <dbl>, candidate <chr>,
# party <chr>, writein <dbl>, mode <chr>, candidatevotes <dbl>,
# totalvotes <dbl>, unofficial <dbl>, version <dbl>, fusion_ticket <dbl>,
# State_Population <chr>
Summary Statistics for year :
Min. 1st Qu. Median Mean 3rd Qu. Max.
1976 1988 2000 2000 2012 2022
Summary Statistics for state :
Length Class Mode
32452 character character
Summary Statistics for state_po :
Length Class Mode
32452 character character
Summary Statistics for state_fips :
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.00 17.00 31.00 28.76 40.00 56.00
Summary Statistics for state_cen :
Min. 1st Qu. Median Mean 3rd Qu. Max.
11.00 23.00 52.00 50.95 74.00 95.00
Summary Statistics for state_ic :
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.00 14.00 40.00 37.09 52.00 82.00
Summary Statistics for office :
Length Class Mode
32452 character character
Summary Statistics for district :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000 3.000 6.000 9.848 13.000 53.000
Summary Statistics for stage :
Length Class Mode
32452 character character
Summary Statistics for runoff :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000000 0.0000000 0.0000000 0.0002465 0.0000000 1.0000000
Summary Statistics for special :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000000 0.000000 0.000000 0.002773 0.000000 1.000000
Summary Statistics for candidate :
Length Class Mode
32452 character character
Summary Statistics for party :
Length Class Mode
32452 character character
Summary Statistics for writein :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.00000 0.00000 0.00000 0.08412 0.00000 1.00000
Summary Statistics for mode :
Length Class Mode
32452 character character
Summary Statistics for candidatevotes :
Min. 1st Qu. Median Mean 3rd Qu. Max.
-1 4324 57328 66825 112144 1165136
Summary Statistics for totalvotes :
Min. 1st Qu. Median Mean 3rd Qu. Max.
-1 162266 206983 215165 263386 2656104
Summary Statistics for unofficial :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000000 0.000000 0.000000 0.001202 0.000000 1.000000
Summary Statistics for version :
Min. 1st Qu. Median Mean 3rd Qu. Max.
20230706 20230706 20230706 20230706 20230706 20230706
Summary Statistics for fusion_ticket :
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.00000 0.00000 0.00000 0.08135 0.00000 1.00000
Summary Statistics for State_Population :
Length Class Mode
32452 character character
No columns have null values.
Question 1: How did congressional voting trends change from 2016-2020
Introduction
The goal of Q1 is to understand how voting trends in the House of Representatives change over the course of a presidency. To answer this question, district majority (the number of districts a party won), and party vote majority (the number of votes a party received overall), will be visualized. The data will be narrowed down to the district, party, candidate votes and state for the years 2016, 2018, and 2020. The interest in this question stems from the recent volatility in the US political climate and to understand how voter sentiment changed in the last presidential cycle. Data from the House of Representatives is used rather than general election data because it gives insight into voter sentiment every two years and is more of a direct reflection of voters’ beliefs since there are more candidates that can be elected.
Approach
Election data from 2016, 2018, and 2020 were extracted from the data set. To quantify party majority metrics in a more simplified manner, all parties that are outside of Republican and Democrat were grouped into a new generalized party called “Other”. For each year of interest, a map of the USA is plotted with all 50 states, where the color of the fill and the color of the label of each state represent different voting metrics. The fill of each state is based on which party has the most districts, which is called “House Majority”. The color of the label of each state is based on which party has the most votes overall, called “Popular Vote Majority”. The three maps will then be set in a tabbed format, which will allow years to be toggled between. Maps are useful to analyze this question because they show state-wise data in an accessible way. The colors are then mapped to each party’s traditional color, which makes for an easy way to correlate the colors to a party.
Discussion
The visualization of the House of Representatives broken down by district majority and popular vote majority provides multiple insights.
The sentiment of the general population is often overlooked by the electoral (district) system. This is evident in the fact that the color of the state differs from the color of the label. This is due to the fact that some districts will have different population concentrations, so when one district might have a large population and votes for one party and two other districts with less than 1/2 the population each vote for the opposite party, the district majority will favor the second and third example districts and the popular vote will favor the first more populous district.
During a single presidency, the sentiment of the people will change significantly. In the 2018 plot, the house majority changes to Democrat for 49 of the 50 states. This is a well known trend that is typical of most presidencies where the House of Representatives will flip to the opposite party of the president in the midterm elections. It is reasonable to assume that if 2022 is analyzed, it would show a more red map with the house majority becoming Republican since it is the opposite party of the presidency currently in office in 2022.
Some states show no change with each feature. States on the west coast show no change in popular vote or house majority. Other states like Texas, see the House majority change over the time frame, but the popular vote majority stays the same way. This reveals that state as a population supports one party, while the district system will elect a different one based on how the districts are created.
Question 2 : How often did change occur in House representation from the years 2012-2022 in the state of Arizona and which voting methods played a significant role in these elections?
Introduction.
This question seeks to achieve two objectives: firstly, to identify recurring patterns in Arizona’s House representation, and secondly, to examine the impact of different voting methods on election outcomes. We have utilized comprehensive data on House elections in Arizona spanning from 2012 to 2022 to answer this question. This dataset contains details regarding the voting methods employed, election results, party affiliations, districts, and the total votes garnered by each candidate. Through scrutinizing fluctuations in House representation, we aim to gain deeper insights into Arizona’s political landscape. Simultaneously, analyzing voting techniques allows us to assess the fairness of elections and devise strategies to increase voter participation.
Approach
The analysis will examine election results from 2012, 2016, and 2022 to assess changes in Arizona’s congressional district alignments over time. Focusing on specific details such as the year, voting type, and election results, it will determine both the frequency and percentage of each vote result. The visualization for the first part of the question will be a color-coded map of Arizona’s congressional districts throughout the years, indicating the political party that won each seat. For the second part, the visual representation of the data will distinguish between victories and defeats through color-coded bars and labeled percentages. The objective is to identify patterns of political representation within the state’s districts, detecting movements in party control over both short-term and decade-long periods. Additionally, the analysis will investigate the influence of various voting procedures, specifically their impact on election outcomes in Arizona.
Arizona Congressional District Maps
Discussion
The first visualization is a color-coded map of Arizona’s congressional districts in 2012, based on the political party that won each seat. Each district is assigned a color that represents the winning party blue for Democrats and red for Republicans.The representation offers a visual picture of Arizona’s political distribution in 2012, highlighting regions of Democratic and Republican strength and providing insights into regional political processes. This localisation reveals the political leaning of most of the congressional districts in Arizona during that election cycle was towards the Democratic party. One key feature of the 2016 and 2022 visualizations is the use of transparency to highlight shifts in political representations. Districts with a party change are displayed with a lower opacity, distinguishing them from those with no change, which keep full-color saturation. The 2016 visualization reveals that the political leaning of 2nd congressional district has changed from Democratic party to Republican party. The 2022 visualization reveals that the political leaning of 1st and 9th districts has changed from Democratic party to Republican party. Additionally, 4th congressional district has changed from Republican party to Democratic party.
The second representation of the data offers a detailed description of election outcomes by voting type from 2012 to 2022, distinguishing between victories and defeats through color-coded bars and labeled percentages. The analysis of Arizona’s electoral data over the past decade shows varying success rates for conventional voting methods, with a significant decline in 2020 followed by a notable recovery in 2022. In contrast, candidates utilizing write-in approaches consistently faced electoral setbacks year after year. This highlights the ongoing difficulty write-in candidates face in gaining political success in Arizona, despite traditional voting procedures maintaining dominance. These visual representations provide valuable insights into evolving political dynamics and voter preferences within the state.
