cf-dataviz

Campaign Finance Visualization

This is a visual exploration about candidate’s campaign finance data by using several data visualization concepts from the book Fundamentals of Data visualization. The dataset has 26,828 rows and 50 columns, which is a combination of candidate summary file from year 2008 to 2020 obtained from the U.S. Federal Election Commission (FEC). Each summary file covers for a two year period of candidate’s financial activity summary. For more detailed file description, please visit: https://www.fec.gov/campaign-finance-data/candidate-summary-file-description/

Part 1. Figures with stories

In Part 1, several data representations were created along with corresponding stories. The figures presented conveyed messages extracted from the dataset and were useful in the exploratory data analysis process. It is believed that, when used properly, data visualization can help to facilitate understanding of the dataset by providing intuitive insights.

1.1 Bar plot of the top 5 parties

Among the top 5 popular parties, the number of candidates affiliated with the Republican Party and the Democratic Party significantly outweighs (at least 300%) candidates from other political parties. Republican and Democratic are the dominant parties in the dataset.

1.2 Density estimates of individual contribution

The density plot shows a bimodal distribution of total contributions from individuals. A high density of candidates made relatively low individual contribution around the mode compared to candidates who made 10 to 15 arcsinh units of individual contribution around the lower density peak.

1.3 Sina plot of total loan from 2020 reports

For reports in 2020, candidates from popular states tend to have a total loan located between 5 and 15 natural log of dollars, ignoring total loan being zero. There is a significantly small data point in Florida away from the cluster, so it can be an outlier.

1.4 Ending years of reports

The line graph shows the ending year of reports fluctuating between odd years and even years. Majority reports ended in even years (e.g., 2010, 2020), and a minor portion of reports ended in odd years (e.g., 2015).

1.5 Geographical distribution of candidate office

California has the greatest color depth than other states, so most candidates have their offices located in California. Also, many candidates have their offices in Texas, Florida, or New York. But there are less candidate offices in Alaska.

Part 2. Misleading figures

In part 2 of this project, two figures (1.4 & 1.5) from part 1 were transformed and presented in a way that conveyed different messages. While these figures were technically correct, they may have been misleading to some viewers who did not examine them carefully. This exercise demonstrated the importance of carefully considering how data is represented, as not all data representations can clearly convey the intended message. By understanding the potential for figures to be misleading, we can better avoid them in the future.

2.1 Log transformed ending years of reports

At a glance, the number of report ending years has little variations from year to year. It just varies within 4 to 8 units. Although the plot is technically right, the log transformation eases the periodic trend in the visual representation, making fluctuations less obvious. If one exponentiates the log unit, they will find the differences are actually distinct.

2.2 Dark colored office distribution

People may naturally think California and Texas are the most popular states of candidate offices (> 2000 counts). The dark color depth makes them hard to distinguish from one another. In fact, there are more than 2000 offices only in California, but not in Texas. They are not in the same category.

(All figures were created in R using packages)