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Pivot Table for Garlic
For my example of uses for pivot tables I decided to make a pivot table for some research I’ve been doing for the past 3 years at Stockton looking at yield data for garlic harvests.
The above screenshot is just a segment of the stacked data in its raw format. It floods you with numbers and is difficult to sort through and get any information out of. That’s where a pivot table comes in. These let you easily select data to look at with the click of a button, and they also have a huge amount of customization to get the exact information you need.
This first example shows how well each type of garlic grew during each year of the study. We can see from this that the top grower varied from year to year. Hardnecks were often grown in the highest volumes, making their total weight the highest, but either Rocambole or Softnecks had the highest average weight during each year. This means that if these varieties were grown in higher volumes they may outcompete the hardnecks.
Another factor we can look at is time. This pivot table selection shows us that overall, we grew larger crops with each year. This is probably because with each year we learned how to take better care of the garlic, as well as we selectively picked the best garlic to grow each year. These are factors that you have to take into consideration.
The final pivot table I made looks at each variety of garlic and is ranking them based on their average weight. We can see from this that on average, Kisklyk was the most successful variety. I like to have these numbers next to the total count and sum of the harvest weights because we can see the best producing garlic isn’t always the one that has the highest total weight. This graph shows us that Silver white is our highest producer because we also happened to grow way more of it then our other varieties.
In the end this process of creating pivot tables can give us answers to our experimental questions. However it also leads us to more questions, which we can answer with further experimentation or reasearch.
-Jack Swenson
Pivot Tables
I have found that pivot tables are good ways to summarize a lot of data. I think they work particularly well with data that involves a large quantity of numbers. They are very useful because they are great visual and interactive ways for readers to conceptualize numbers within the data set and clearly see what is being portrayed in the overall data story.
Here are some great examples of pivot charts and why they are so helpful:
Example #1
This is an example of a pivot table I got from a very helpful website that shows how to create great tables! On the left is their source data and on the right is their pivot table. It is much easier to see the data within the pivot table because it is much more condensed and only has the information that is important to the reader. Instead of being overwhelmed with numbers and data, it is way more digestible in this form.
Example #2
This next example also comes from a really helpful website to aid in creating pivot tables. What I really like about this particular example is that it highlights all the different ways the same information can be laid out. Excel does a really good job at offering the creator choices in layouts to make the creation of an effective pivot chart much easier. As seen here in this example, the layout of a pivot chart can really change the goals of what you want the chart to do.
All in all, I think pivot charts are great ways to display numerical information. There are plenty of websites to help in the aid of creating them and using tools like Excel also makes it very easy!
Pivot Tables
By: Veronica Perkins
Like any other visualization, the intention is to help visualize the data being presented to an audience. The purpose of a pivot table, is to help visualize and a large amount of data at one time. A typical pivot table looks like this:
As you can see, a lot of information is presented in the format of a pivot table. This pivot table is an example of how a lot of information is summarized. In this example, the maker wanted to present the sales from the past three years. They decided to break it down between the following: year, month, type (meaning what was sold), the salesperson that sold it, the region of the sale, the sale amount, how many units were ordered and the order number that correlates to the sale. Pivot tables can be so helpful to use because they can help break down a large amount of data at a glance. This information, can also be used to make visualizations to help represent the data.
Sankey Visualizations
I think the Sankey graphics have some upsides and downsides. I like the interactivity of the website, and I feel like in certain ways it can give you a good perspective of the energy breakdown nationally and regionally but other places it starts to faulter. In particular I don’t like the vagueness of how certain energy streams translate to used and unused power. In the first picture you can see that geothermal energy accounts for an extremely low percentage of total energy usage nationally, but then the avenues that it goes down have varying degrees of how much power is unused. When you have this discrepancy it’s hard to tell how efficient each power source actually is.
I do like the energy breakdowns for the regional map because I think this chart makes it easy to draw some conclusions about the plausibility of renewable energy reliance. As a disclaimer I am a large proponent of sustainable energy conversion, however, I think from the below two pictures you can see that this isn’t an easy task. Especially when you look at where the sources are going. The transportation sector is still dominated by oil, so there is a significant amount of progress that needs to be made in creating more efficient energy systems that can support the use of clean energy.
In conclusion I think that this website does some things right and some things wrong. A chart is supposed to guide the audience through the data that’s compiled, but I found myself questioning how accurate the numbers were, and without a lot of context for how much energy “.9” or “300” meant, it was hard to see the magnitude of differences. In terms of layout I thought the chart did a good job of graying out what wasn’t being actively clicked on, and that helped guide my eye through the different pathways that would otherwise be tangled up with each other.
-Jack Swenson
Sankey Visualizations
A Sankey Diagram is a visualization that Is used to depict a flow from one set of values to another. They help locate the most important contributions to a flow. Sankey visualizations are best used when the topic is energy, time, or money.
Although there is a ton of information presented in this visualization and it seems cluttered, I think this is the most effective way to view this data. This visualization is super effective considering that there are so many different aspects on this chart that are combined into one piece. Firstly, the energy system is broken down into the types of energy on the left hand side. The visualization allows you to click on each tab. When you click on each type of energy, it shows you what percentage of energy is expended and where it goes. For example, when you click on solar energy it shows you that solar energy accounts for 0.42% of all energy expended, and that 0.17% goes to electricity, and 0.25% goes to residential use. The infographic then breaks it down even more. It shows the amount of energy that is unused, and used from each category (electricity, residential, commercial, industrial, transportation). The thickness of the flow indicates the amount of energy. For example, you can see that most of the energy from transportation is unused because a larger flow moves from transportation to unused energy. All in all, there is so much information that can be digested from this visualization. It appears to be a lot, but when you break it down into pieces it is very effective. I believe this is the best way to display this information.
SANKEY
After playing around with the simulators within our energy system on National Academics: What You Need To Know About Energy, I am actually quite shocked. Within their page, there are multiple different walkthroughs of how to conserve wasted energy at home and even on the road. When I first started going through the pages, the first one that popped up stuck out to me.
The picture above is one of the simulators on their website that shows you our energy system. Each category of energy is on the left side and it shows you where it goes to. What blew my mind was in the end, there were 38.4 Quads of useful energy, but there were 59.4 Quads of unused energy. Keep in mind “quads” is really quadrillion BTU. This is more than the used energy! I also liked how within this visualization, each category had a different color so you could see exactly where it goes to. For example, Natural Gas which is the color green goes to Industrial, commercial, and residential.
Another part of this website that I thought was beneficial, was the ways to conserve energy at home and on the road. Within the at-home section, you could choose between television, lightbulbs, and washing machines. I decided to play around with the washing machines page, which I thought was really cool. Washing machines were reported to use 36% of the original energy. You can turn the dial to either one load of laundry or 1 week of laundry. You could do the same with 1 month, and 1 year. You can see on each one how much energy you use, how much coal burns, and the CO2 vented between Top-loading and front-loading. This website is definitely beneficial to someone who could be looking to learn more about ways to conserve energy and interact with different pages of useful information.
Sankey
By: Veronica Perkins
Sankey is a tool that can be used to create interactive visualizations in a way that helps your audience follow. Upon exploring Sankey for over ten minutes, I was so intrigued. However, it can be a little intimidating.
Now let’s discuss the usage in our energy system…
Right upon entry of this visualization, it takes you to the home screen pictured above. Within this home screen, you can see how at the top, it lists several other tabs that can move you to another data set. For example:
When I clicked on the “Understanding Efficiency” tab, it brought me to this page. On this page, it briefly explains the point of efficiency and what it does, while on the side it has two interactive buttons. These interactive buttons are just one great example out of the whole project. They allow the audience to click on them and explore. By having interactive features throughout your project, it allows for the audience to read, comprehend, and travel through each data set at their own pace.
Overall, I really enjoyed how interactive this project was. It was very well organized and left the reader/audience to go through each data set at their own pace. However, sometimes I feel like an entire website can feel like a bit of overkill when it comes to project like these. I feel as though there are other ways to keep your audience entertained while presenting them with data set; without having to do all of this. To be less harsh, I believe that sometimes an entire website can be a bit much and sometimes the audience can get bored or not want to participate anymore. Also, the Sankey graphs themselves can be very overwhelming to the audience and may even leave them feeling lost. Instead, providing simpler graphs with a lot of color variations and details, may be easier for both the creator and the audience.
Sankey Visualizations
The picture above is an example of a snaky visualization. It is typically used to show the flow of the information being discussed. In this example, it is being used to show the flow of energy and how it is used.
Originally, I was extremely overwhelmed when looking at this chart. I had no idea where to look or where to start. After the initial shock, I just started reading from left to right like I would any other chart. I began clicking around on all the headings and reading what they said. I ended up finding this chart very helpful and interesting!
First, I really like the creativity behind it. It is about electricity and I could tell that right off the bat without actually reading anything on it. Second, I like that the information is hidden within the chart. I think it makes it look a lot more clean than it would if all the paragraphs were jumbled all over the screen. Lastly, I really like how it ties everything together. It starts out with the different kinds of ways we get electric and ends with how much we use.
Overall, while it can be a little overwhelming, I think it is a great way to show data because there are a lot of different facts that can be rolled up in one visualization that is easy to navigate.
Website: http://needtoknow.nas.edu/energy/interactive/our-energy-system/
UN CONTRIBUTION: Pie Chart Edition
Pie charts are a difficult tool to use because they require very specific scenarios to be the most applicable. For my perfect-use case I decided to display the contributions of countries to the UN budget, shown as a percentage.
I think this is a perfect data set to use a pie chart because it’s simple and doesn’t have an excess of labels. This data set as it’s shown tells you that the US contributes almost one quarter of the total UN budget, and that the top four countries combined contribute nearly as much as the remaining 130 members combined. You may be able to add a fifth or sixth country to this pie chart, but then you lose the 50:50 narrative that is very easily read here.
Source: www.auswaertiges-amt.de/
-Jack Swenson
Pie Charts
This data set is a perfect case for a pie chart. The percentages add up to 100. This means that all of the parts add up to a whole, which is a crucial part of a pie chart. A pie chart is also good to use here because there are only 6 categories. There is not too much going on and the chart does not look cluttered. It is very easy to read and the audience can easily compare the sizes of the slices to each other to tell which sport is more popular.
The data here is not served better as something other than a pie. A bar chart would work, but a pie chart is the most effective visualization for this data set.
I came across multiple design strategies to make this pie chart more appealing. First I color coded the different slices. This makes it easier to differentiate the slices from one another. Another thing I did was I put the category name and percentage in every slice of the pie. The percentage provides a more in depth look at the data. Also, adding the category name allowed me to take away the legend. This makes it easier for the reader to digest the information. They no longer have to glance at the legend, then to the chart, then back and forth. All of the information is in the pie chart.