The Cost of Energy
This website has a very immersive interactive display of the way energy is used in society. I spent a lot of my time clicking through and answering questions. That was probably my favorite part of the website, the option to answer questions along with the reading made it more interactive and entertaining. It also helped focus myself on to key facts I should take away. An example of one of these questions is pictured below.
This website provides a very clear and detailed description of different ways we use sources of energy. As a society we use water, wind, solar and other things to generate electricity and some of the statistics provided were very staggering. They used many different types of useful visuals to display increases in energy usage over time. My favorite were probable the simple line graphs because they were effective and clear.
My only problem with the websites layout is that it was often hard to get back to where I was once I clicked a new tab. There were so many links bringing me deeper into the website but I often forgot what I clicked to get back to that information. So some of this information needs to be more easily available with less searching.
Sankey Diagram
The Sankey Diagram originated in 1898 to show the energy efficiency of a steam engine. This makes it the perfect choice of visualization to depict the efficiency and usage of our energy systems in the United States. I appreciate that the diagrams show how different states aggregate their energy to show that the United States is not a monolith in energy production and consumption. Our energy use is nuanced and these diagrams show that our energy production and usage is very inefficient. This first screenshot shows the amount of energy that solar contributes to our total power usage. It is very low at 0.23%. I was actually shocked that less than ¼ of a percent of our energy is produced by solar. When you click on solar it also shows that most of our solar usage is going directly to residential homes and very little is going into the grid.
The second screenshot shows the MD/OH/PA/WV region, who are major exporters of coal energy. The diagram shows that the region has much lower energy efficiency than the nation due to the use of coal. 73% of energy is unused in this region because the region is heavily reliant on the coal, biomass, and oil.
The last slide shows energy production and import in California. California is one of the most energy efficient states in the country and this diagram shows why. The top 6 sources of energy listed: solar, nuclear, hydro, wind, geothermal, and natural gas are much more efficient than the bottom three. This results in 41% of California’s energy produced being usable.
I would say that this is one of the best use cases for a Sankey Diagram. It allows the user to easily follow the flow of information (energy) and understand more about the topic than many other types of charts. All of the relevant information was able to captured in three different versions of the same diagram, so when users move on to the second and third charts they are expert users and it makes analysis more streamlined. This was a great way to show inefficiencies and areas of opportunity in a simple and easy to understand way. My mind works in percentages so the only thing I would have done differently is include percentages in the useful and unused energy labels or tooltips. Lastly, the only thing that I don’t really like about this Sankey Diagram is that all of the numbers are not visible without clicking around. Many people prefer to be able to see all of the information and just be able to explore visually without interaction.
SANKEY
This website/article it highlights the intricate nature of the energy system in the United States, which involves a complex web of primary energy sources supplying energy to residential, commercial, industrial, and transportation sectors. Electricity, generated from various sources, distributes energy to these sectors. However, a significant portion of the energy supplied is lost as waste heat or inefficiencies. The United States’ energy consumption is projected to rise, and globally, energy demand is expected to increase substantially in the coming decades.
In how we use energy, it discusses the diverse mix of energy sources, including fossil fuels, nuclear power, and renewables, which contribute to the energy supply. It emphasizes the importance of understanding and visualizing this energy flow. Sankey diagrams can serve as powerful tools to represent this complexity, showcasing the sources and sectors involved, the environmental impact of different sources, and the importance of energy efficiency. Such visualizations can aid in informed decision-making about energy policy, sustainability, and the future of energy production and consumption in the United States and globally.
The comprehensive costs associated with energy use, extending beyond monetary expenses. It emphasizes that when making decisions about future energy options, it’s essential to consider environmental impact, national security, and sustainability factors. The text highlights the potential rise in global temperatures due to human-driven greenhouse gas emissions, the need to better understand and address climate change, and the risks associated with an energy supply heavily reliant on foreign sources. Additionally, it raises concerns about the unsustainable consumption of fossil fuels and emphasizes the imperative of accelerating the development and adoption of renewable energy sources for a more sustainable and secure energy future. In essence, it calls for a holistic and forward-thinking approach to energy decision-making that takes into account these critical factors.
All of the graphs were fun to play around with, but easily confusable. In the graphs, I liked how you could click individual parts and let you understand a little bit more about how it works. All in all I liked how the article came out.
Pie Charts
Pie charts are used to show portions of a whole. An amount is divided into categories by percentage and the slice sizes are relative to the percentage of the category. Pie charts are great to use in showing the results of polls if there are a limited number of categories. If you have too many categories the chart becomes difficult to read. Below I have created two pie charts based on data from Pew Research regarding Americans’ views on money in politics.
The above chart highlights what a higher proportion of respondents believe while the chart below highlights what a lower proportion of respondents believe. Choosing the right chart but also a good title for the chart is key for letting viewers know what information is important.
I believe that both of these datasets are great use cases for pie charts because they show what portion of respondents. Other good uses of pie charts is in finance. Household budgets are well represented by pie charts. Pie charts are also a great tool to use when visualizing portfolio allocations. One of the most important things to avoid with pie charts is using incompatible data. If the proportions do not sum to 100%, the data is not a good use case for a pie chart. There are many different options for visualizations and a pie chart is great for a simple and quick way to represent proportional data effectively to viewers.
Pie Charts
Pie charts, when done the right way, can portray some of the simplest data in a very uniform and easy to comprehend way. The easiest data to portray using a pie chart would be data that represents “parts of a whole”, but this is not the only data that can be used in a pie chart. We can also use percentages to show contributions to a whole. One of the most important things to remember though when creating a chart to show this type of relationship, is that the data values within the pie chart must always add up to 100. It is also important to remember that pie charts, as well as any other chart or infographic, are used to tell stories. Because of this, we have to remember to keep the story as straightforward and concise as possible. Always remember to keep your infographics as clear as possible and to not jumble too much information or design in the graphic.
The information I gathered was from a study done of 626 restaurant goers, asking how many times a week they go out to eat. This information gathered from Tasting Table, I believe is best suited in a pie chart because it was presented to me in percentages of people. Percentages are easiest represented in a pie chart because it represents part of the 626 people surveyed.
Link to study: https://www.tastingtable.com/912246/new-survey-shows-how-often-people-typically-eat-out/
Pie Charts
Pie charts are something that we are used to seeing, and have been practically since elementary school. They are commonly used for comparisons because they help people visualize a difference and also allow them to understand different categories and severities of things. For this reason, it is always important to make sure a pie chart is used properly, otherwise information can become too overbearing and confusing.
When tasked with creating a pie chart, I felt that it was important to pick something that was equally important to me and had data that was easily comparable, as this is what would work best for a pie chart. The image below shows the pie chart I created with sample data taken from Statista about the percentage of college students who are diagnosed with some sort of mental disorder.
One thing that not many people are aware of (unless they were or are in college) is the amount of stress and hard work that comes with the role as well. More often than not, these stresses cause college students to be diagnosed with some sort of mental disorder, and I felt that as a college student who is also suffering from the stress and pressure put on me, this was a good thing to talk about. The pie chart features five different types of mental disorders that college students are most commonly diagnosed with, with anxiety and depression being the highest amongst them.
I think this data was best shown in this pie chart because it puts the numbers and diagnoses into perspective about how significant and problematic the pressures of college are on a student. Due to the two large percentages taking up more than half of the circle, you get an idea of the severity of it.
As previously mentioned, this sample data was taken from a larger data set on Statista. However, Statista showed this information on a horizontal bar graph (as shown below).
While the bar graph is still a great way to display this information, I think that taking the higher percentages/more common disorders and displaying them on the pie chart created a more urgent and dramatic effect that may not have been seen or fully acknowledged in the bar graph. On the other hand, if I were to include all of this information in the pie chart created, I do not think the pie chart would have as much of an effect or impact as it currently does.
In all, a pie chart is a great way to display certain types of information, including my sample data set on mental disorders in college students. It shows comparison of different categories and allows for easy interpretation and understanding of data. One thing that I discovered while creating this pie chart is that Excel has several hidden tools and features to help you create the pie chart to your liking, including pre-made color palettes that make it easy to keep a theme, as well as different examples of pie charts using your data. For instance, I found that it looked better to have the percentage and category labels on the outside of the pie chart rather than the inside due to clutter and I was able to do so with a simple click of a button. I think it is important to note these features because certain types of information and pie charts may need to be created depending on the data used, and Excel provides easy navigation to do just that!
Pie Chart
The humble pie chart, a simple yet effective tool for anyone interesting in making data visualizations. Aside from the necessities that pie charts should represent 100% of a total figure, and the chart should be legible, it’s hard to go wrong with a pie chart.
In addition to the above factors, there are others that make a pie chart go from a working choice to the correct one. For the true strengths of a pie chart to shine the data should tell a story. Components of the chart should be instantly recognizable as a very large or small fraction of the total figure.
For my example I chose the distribution of wealth in the United States, and I was able to find data from 2017. This data has a clear total figure, the sum total wealth owned by civilians in the U.S., and the data tells a clear story.
No other chart would tell readers what I was trying to convey as quickly and clearly, that wealth inequality in the U.S. is staggering.
When making your own visualizations, remember to choose a pie chart if the individual components tell a story by their relation to the total figure.
Usage of Pie Chart
From my knowledge, pie charts alongside with bar graphs and line graphs are the most used type of graphs when it come to comparing data. They each have different uses. For bar graphs, it can be used to compare between different groups or track the progression over time. For line graphs, it usage can be quite the same literally but it can pick out the tiny difference between values and can compare data progression over a much longer period of time and wouldn’t cluster the graph like a bar graph would do. Pie chart does compare between groups or categories. However, a pie chart does not compare the values over time. Instead it compares the data of a whole subject and represents percentage, as if everything would add up to 100%, the total.
Here I take an example about the total municipal solid waste (MSW) produced in 2018 from the EPA. Using pie chart is ideal here because you would want to compare between each value (type of waste) of an entire subject (waste produced) and each slide of color here represent each value. Readers can easily see the difference base solely on the size of each slide and quickly understand the data. A pie chart of this consist of 11 values and if used on a bar graph, I would think the graph would be clustered with 11 bars and from there you would have to adjust the size accordingly to squeeze every bar into a graph thus made a bar graph a hassle for this type of data. A line graph for this one is also out of consideration. The topic here is the ‘Total amount’ and not ‘Wastes produced from month to month’, there are no over time progression in the data to compare using a line chart. Overall, a pie chart for this type of data is easy to made, easy to understand with minimal effort.
Pie Charts. AS
In the world of data visualization tools, pie charts appear simple and easy to use upon appearance, but actually require significant prior consideration and thought upon creation. This is due to its simplistic nature and form of distribution, which may lead many to believe that categorical data will translate well.
Pie charts may best be utilized to accomplish several end goals:
- To demonstrate a part to whole relationship
- To place emphasis on a particular segment (smaller or larger)
The pie chart I have created attempts to demonstrate how many individuals in the population of Texas lack health insurance coverage. As these two demographics are easily separated into two groups, a pie chart is an extremely effective way of calling attention to this statistic by placing emphasis on one segment.
Source:
Bureau, U. C. (2019, November 7). State-by-State Health Insurance Coverage in 2018. The United States Census Bureau. https://www.census.gov/library/stories/2019/11/state-by-state-health-insurance-coverage-2018.html
Pie charts
By Joseph
Pie charts are one of the many types of visualizations that one can use to portray both complex or simple data. A pie chart can be especially good when the data being portrayed are all parts of a whole. As shown by the pie chart above, the values for the Recommended diet intake are all individual parts that add up to a 100%. Furthermore there are both small and large data sets that needed to be represented such as, the dairy value and the fruits value. Both data sets are vastly different in terms of percentage and hence the amount of space that they take up visually. To convey this, a pie chart is the perfect visualization to use in this instance. This is especially true when one considers that the appearance of a pie chart also falls in line with the topic of the graph itself which is diet and food intake. the values not only add up to a 100%, but also the data appear to reflect a plate, with each data set representing a specific food intake. Upon making this pie chart, I did come across some suggestions as to how I could improve my data such as changing the color of the data set or make one value stand out by removing color from every value except for one. One could also disconnect a certain piece from the whole to visually represent something to the audience. These design methods are all very valid and useful in data visualization, but I decided to make the pie chart I created very simple to understand. The more elements that one adds to something, the more important it is that the information is clearly conveyed. Not only was there not a need to apply extra designs for the data that was conveyed, but there would also be a risk that the audience may misinterpret certain designs choices if they poorly represent the data. All in all, a pie chart is very efficient visualization to represent data that is part of whole.