Overall, I am very happy with how my chart package turned out, but wish I had been able to commit more time to it before the deadline. There were a couple errors I made that I believe would’ve been avoided due to the lack of time I had. First, the font for the chart explainers isn’t consistent among all my charts. Also, I didn’t label the y-axis as “Percentage of Transpeople” for the chart describing the discrimination people face leading to confusion as to what is being represented there.
The biggest challenge I faced when putting this char package together was difficulty of gathering information. Overall, there aren’t many statistics available about the murder of transpeople. Most everything I found were private organizations documenting individual murders for the past seven years. Besides that it was difficult it was also difficult to find murder rates based on demographics the most recent information I had was a CDC report from 2014 about violent crime numbers broken down by race and gender. I had to make approximations based on stats from the Census Bureaus QuickFacts page. Despite all these challenges I feel like I was able to show meaningful trends when it comes to violent crime ad transpeople.
Fast-food has always been one of the great loves of my life. When I was little, my parents would take me to McDonald’s if I’d had a good day at school or if we’d had a successful outing to town. My grandmother would treat me to Taco Bell when she would watch me on weekends, and we’d always sit at the same table by window to watch the cars go through the drive-thru. I had my first In-N-Out Burger experience when I was six while visiting my family in California, followed shortly by my first Starbucks. Fast-Food is something I associate with a good time, and something I continue to eat despite what the FDA says about its health risks. And I am not alone. Millions of Americans visit fast-food chains each day, making it one of the most lucrative industries in the world. This project allowed me to combine two of the things I love most in this world: fast-food and data. So let’s digest the numbers.
President Trump announced Sept. 9 that the government would stop accepting new applications under DACA program and end this Obama program in the next six months. Thousands of hundreds of people receive benefits from the Deferred Action for Childhood Arrivals program, but now these DACA young people, known as DREAMers, might lose their legal status soon. Thus, I hope this chart can help people aware the “dreamers” situation.
I choose the bar chart to show the changes of active DACA recipients by month validity expires. It’s clear that the government has less or nearly stopped processing renewal applications. The renewal will going to the end in Feb. 2018. Plenty of DACA youth recipients would lose their legal status and go back to their “home” countries where they don’t have any social protection, even don’t the languages.
Then for the top 10 states with DACA recipients, I choose the horizontal bar chat to show the comparison. California and Texas own the most “dreamers”. I try to draw a U.S map here, which is the most challenge in this project. It spent a lot of time, since I am not familiar with drawing map and connecting it with data. It might be helpful for readers to think where are these places and why it happened.
The final chart is the percentage of undocumented by age. I choose pie chart for this one, showing the percentage of different age group in the total population. From the data, most “dreamers” are 21-25 and over half of them are under 25.
As Halloween approaches, Thriller by Michael Jackson will be heard on the radio with increasing frequency. The song was originally released on November 30, 1982 – ironically almost exactly a month after Halloween. However, since its release the song has been enjoyed year round, but especially during this spooky holiday.
Michael Jackson was easily one of the most influential artists of his time, and his legacy still lives on today. I have always loved Michael Jackson’s music, but I especially love seeing how current artists channel their own inspirations from him into their own musical styles. This is why I chose to create a tribute chart to Michael Jackson and compare similar artists to the King of Pop.
As far as the aesthetic of the chart, I am very happy with how it turned out. I think it works nicely as a whole package, and each individual section looks nice as well. I was having fun with this project, and chose to add the silhouette of Jackson using image trace and some Illustrator editing, as well as a couple call-outs of quotes from artists to add an extra element of interest to the page.
If I were to recreate this chart, I might make the overall look a little darker to correspond with the theme of “Thriller” and Jackson’s classic red and black color schemes. Additionally, I meant to add more call-outs to the line graph, to emphasize certain points. For example, it is incredible that the “Thriller” album stayed within the top 5 of the Billboard 200 for almost an entire year! That is worth drawing attention to, but once I started fine-tuning my graph the call-outs completely slipped my mind.
My biggest challenge for this project was compiling the data. Music Industry data offers a great database of Billboard chart information throughout history for various artists. They have interactive line graphs showing the trends of Billboard rankings, but they had no spreadsheets of the data available, so I had to manually create the spreadsheets myself. Moving forward, I will definitely need to give myself more time for research and data mining with future projects.
I learned that there is a LOT to consider when creating an infographic. Aside from making it “look nice”, it is important to conceptualize which kind of chart would communicate each message the most effectively, which pieces of information are worth drawing attention to, and if the labeling decisions are intuitive.
I really enjoyed this project, despite the fact that it took me longer than I expected it to. The key was finding a subject I was excited to research and design for. My initial idea did not motivate me, but once I stumbled upon the final idea I couldn’t wait to start designing. I will learn from this lesson and start brainstorming for the next project now and throughout the next couple weeks.
Something that I feel like I missed the mark on that I like to pay a lot of attention to normally is color. Color is so deeply embedded in LGBT culture and history, and I should have done a better job taking that into account. Every identity has their own flag, and I struggled with thinking about how to incorporate that many colors into the design without looking tacky. So instead, I thought it would be interesting to use colors that you might find on a retro TV with no signal bars, tweaked a bit to look less bright. I am not sure this came through in my design how I intended when I first started to think about it– originally, my main graph was going to be a bar graph, and I think my idea would have been more obvious to others if I had followed through with my design.
I also wish that I had explored font choices beyond BentonSans. I really considered using Railway instead because I feel that it is very visually interesting while staying clean. However, when I had the final graphic put together, I ended up thinking it looked too busy, and I already knew I really liked and trusted BentonSans. I also wish I had remembered to use paragraph styles– that function always saves me a lot of time, except when I forget to use it.
I also wish I had put more thought into my layout– it made a lot more sense in my head and in my initial draft than in the final product. I need to be more flexible in future design projects so that I can adjust my idea so it makes more sense from a functional viewpoint.
Finding statistical information on my topic beyond the GLAAD report that I found initially was surprisingly difficult. I did not think about how difficult it would be to find information about my topic when I started. Data about the LGBT population is difficult to find and quantify because of the nature of the information, especially since Donald Trump decided to stop collecting data about LGBT households on the census. It is also just more difficult to find specific information about how many people identify with which labels or even as LGBT at all because it is so easy, and sometimes preferable, to lie in surveys about sensitive information like that. It is much easier to find information about age or nationality than sexual orientation and non-cisgender gender identities. So, finding numbers on approximated percentages of the population that identify with different labels actually took a long time.
Despite my problems that I have with my design, I am honestly really happy with how it turned out. While it might not be publishable in a newspaper because of the colors, I could see it being in a magazine with some tweaking. I like how my callouts work, I like how the colors remain linked to their respective identities throughout the design, and I like my keywords box. If I were to do this assignment over again I would have a lot of things I would change, but overall, considering that I am very new to the world of infographics, I am very proud of my work.
The main chart is about to tell readers that how does the import and export of U.S. with China changes in last 16 years. I chose to use the bar chart to present the changes because the bar chart can show the changes easily and clearly based on every year. And, I used the positive and negative chart to show the huge difference between the import and export apparently. On the main chart, I used the third chart- line chart to represent the balance, which is the apparently negative number. The color I chose is blue and red because those two colors are pretty contractive and easy for readers to compare two colors. For the balance line, I chose to use the light color because I want this color to stand out from the red color.
The second chart is the pie chart, which to represent what many percentages of the total trade does each top 3 countries take. I chose the top 3 countries- China, Canada and Mexico. I used 2004 year-to-date to compare 2016 year-to-date to show that China is taking more percentages of the total trade than before. That supports the main topic that China is the top 1 trade partner of U.S. I put Canada, Mexico, and China in the same order in the different year that makes readers easier to compare between 2 years.
The third chart is the bar chart, which shows readers how many billions of dollars that top 5 export goods to China. Some name of the goods are pretty long so I figured out to put the name on the top of the chart. I used the blue color because it belongs to export. Also, I put the value behind each bar that makes audiences more convenient to read the graph.
The process of this work was stressful, but I was really enjoying it. I think there is something I still need to improve in the next work. Hope I can do better next time.
Every few years, the southern United States experiences a large tropical storm. Many times the storms evolve to a full hurricane based on the power of the particular storm. However, while many storms bring some level of damage to the coasts, some of the larger storms ravage the coastal lands. In 2005, Hurricane Katrina demolished most of New Orleans, a city below sea level. In 2012, Hurricane Sandy destroyed the Northern Coast of the United States reaching as far in as Vermont. But what about the recent hurricanes, Irma and Harvey? Much to my surprise, the hurricanes are estimated to be upwards of $200 billion in cost.
The bar chart that I created compares the costliest storms in U.S. history adjusted for 2017 inflation rates. I used a stacked bar chart to show the difference between the lower end estimate and the higher end estimate (150 billion and 200 billion dollars, respectively). I also used a pie chart in the lower left hand corner to show the different categories of the top 30 costliest storms in history. Much to my expectation, most of the storms were either category 3 or 4, however, Hurricane Irma was a category 5 hurricane at its beginnings. The last chart I made shows the deadliest hurricanes in modern history in comparison to Irma and Harvey. Much to my surprise, cost does not necessarily correlate to death toll. I thought perhaps they may be in direct correlation, but after review, I believe they have some connection to the quality of evacuation tactics and infrastructure.
Overall I was not happy with this assignment. I felt like I didn’t have interesting data that I found, and I felt like I lacked creativity with my graphs despite the many hours I spent working. I like my style guide, though I think my typeface could be a more professional type than Roboto (I didn’t have any of the professional types on my personal computer). I don’t know right now how I could improve my graphic other than improving my data. I felt very limited in my ability to create something memorable. I hope this project can be an early obstacle to get over for future graphics and that my creativity will expand going forward.
The past decade has shown a trend named the “vinyl revival,” characterized by a surge of interest and sales of vinyl records and record players, as well as interest in record stores.
I am one of those people who are into vinyl and music as a whole, which is why I wanted to research this topic. I have a small but highly curated record collection of about 50 classic records. My boyfriend has 600 though, and I consider those mine, too (I’m sure he would happily agree). I have a dedicated section of my room with my record player, audio setup and records. I also love going to record stores, and I usually go to all the stores in an area when I travel.
Being the 10 year mark of this trend, the subject is newsworthy. It would work well in a magazine or on a music content platform but wouldn’t be as well-placed in a daily newspaper, beside a feature. If it was released around Record Store Day, then it could work in a daily paper.
There seems to have been an emphasis on collecting music data in only the last few years. Nielsen puts out a music industry report bi-yearly now, but it didn’t seem to before 2015. In the last two years, Nielsen’s music reports have become quite an elaborate package of information, stories, data, trends, visualizations – while before 2015 the reports were basic statistics on sales.
Nielsen seems to be one of the only providers of this information, but recently Buzzangle Music has put out mid-year and year-end reports on the music industry. However, Nielsen’s measurements and Buzzangle’s are not the same. Because of this, I did not mix-and-match sources within individuals graphs. I used Buzzangle’s data for the pie chart, and Nielsen for the other two. Buzzangle was more clear on separating vinyl and CDs than Nielsen. I haven’t pinpointed why the two data sets differ, but I assume it lies somewhere in the methodology.
I spent a long time looking through the years of reports and compiling the data in order to compare it. The bottom chart is a result of that, and I think it’s a very accurate reflection of how vinyl has climbed while all other album format’s sales have dropped. I wish I could have figured out how to make the graph more detailed so vinyl’s section was more readable, such as being able to see its share of 2007-2011.
This graph really surprised me because I had no idea people were abandoning albums as a whole. I want to analyze more data to try and find out why that is. It would be interesting to see how many singles and singular tracks sell in comparison to entire albums. I could have done that, but I wanted to focus more on vinyl albums and albums themselves, and chose not to bring in streaming or digital, beside in the pie chart to show the 2017 sale breakdown.
Another thing that surprised me was the top vinyl albums being sold in 2017 compared to the top albums of 2017. Every top album of mid-2017 was from 2016 or 2017, while the vinyl records only had three of 10 made in those years. That gives some insight into what vinyl sellers are buying, and shows record shoppers still value older music. It doesn’t show, however, if record shoppers are typically older or if young record shoppers are seeking out older music on vinyl.
What is always going to be missing from vinyl data, though, is how many used vinyl albums are being sold. It seems virtually impossible to track because these albums have been cycled for decades and it would depend on the self-reporting of every record store in the world. Most stores carry more than half used, sometimes only used. This missing data leaves out a great portion of vinyl sold.
Overall, I think the layout of the package is nice and cohesive. The colors are carried throughout to mean the same thing. Dark orange is vinyl – vinyl sales in 2017, top vinyl of 2017, and vinyl’s share over the decade – which appears in each graph because it is the central aspect of the package. I don’t have a reason for choosing orange, but it certainly pops.
I think I struggled with trying to create a hierarchy. I messed around with changing the weights of graphic headlines but decided to keep them consistent. I think it’s obvious the pie chart is dominant but the other two are pretty much equal. I also grappled with deciding whether to keep the pullouts equal size on the pie chart vs. the others because of the pie chart’s size. I ultimately decided to stay equal.
I think there’s a lot more to be broken down and analyzed in the music industry, but this is a brief introduction into the vinyl revival and a mid-year look at 2017.
On October 2nd, one of the most iconic rock artists, Tom Petty, passed away due to cardiac arrest. Tom Petty made music with his band, the Heartbreakers, for more than 40 years, letting their music speak for themselves. Since Tom Petty’s death was big in the news for the next couple of days, I thought using something news worthy like this would be interesting to base my charts package on.
I thought this would be a relevant topic with a lot of information out on Tom Petty that I could use towards my research and chart but I found it very difficult to find reliable sources that have statistics on Tom Petty. I think the research processes was my biggest issue in the project. I found a lot of interesting information but I couldn’t figure out how to take that information and make a chart out of it. Once I found a good deal of information, the rest started to just all come together.
For my process, I began to take the information that I found to be the most surprising and interesting as my main chart – songs sold day before vs day of his death. I knew right away I wanted this to be my main element, especially because it was including something about his death. I then set up how I wanted my package to be layed out to show hierarchy in the charts.
Picking a color scheme was pretty easy for me. I found an image of Tom Petty online that I used to get inspired by, grabbing colors from the image that I thought work well together but stood out very different from one another. I came up with using those colors sparingly throughout so that it wasn’t overloaded with them. I wanted to place the package on a very light grey background so the package felt whole and would be differentited from the page it is placed on.
Picking a typeface that I liked wasn’t too difficult for me. I have taken a typography class already and have a good idea of which type faces I really enjoy using and Raleway is definitely one them. This is such a great typeface because of its many options in weight and other variations. I thought this typeface would work very well with the charts package because it is thin and san serif, which give it a very clean feel. I wanted the overall feeling of the package to be clean, with room to breath throughout the charts and callouts.
Despite the problem of finding reliable sources with interesting information to make into a chart, I enjoyed making this project. I am happy with the overall design and look of the package. I think my style is shown clearly throughout. One thing I would have included more within my design was more artwork of some kind, whether that be a picture or a drawing I created to give it more of a fun feeling. Next time I would give myself more time and do more research on the topic and hopefully find better sources with information.
The Holy War is the biggest football rivalry in the state of Utah. Beginning in 1922, Brigham Young University (BYU) began playing the University of Utah (the U) and it has continued to be a tradition ever since. BYU is known to be a university mainly for those of the Mormon faith, unlike the U who has a diverse variety of faiths, or lack thereof. This is mostly where the rivalry stems from – Mormons vs. the non-Mormons.
I created two chart packages, the first about the statistics of the Holy War, and the second about who of the two schools is the better team.
In the first chart package, the main chart illustrates the points scored by each team for each rivalry match by year. It also includes a win-streak graphic at the bottom. It includes important call-outs as well as graphic at the top which shows the conferences the U and BYU were a part of and when. I chose a stacked bar chart so that it would be easy to compare the number of points each team made, therefore easily showing the winner of each year.
The supporting graphics on the right clarify all-time Holy War wins, which is shown in a pie chart, and the number of games played by location in a bar graph, to show where one team may have had an advantage over the other.
In the second chart package, the main chart shows the number of games each team has won per-season by year. It again includes important callouts as backing information to why the Utes appear to be the better team, which I felt was important to show.
The supporting graphics include a pie chart, which shows the number of bowl games each team has won, which I felt again helped solidify the claim of the better team, a bar graph which shows the number of players that were drafted from each team (another important backing fact,) and another bar graph that summarizes each team and their all-time wins.
In terms of typography I chose BentonSans and BentonSans Compressed. I felt it clearly displayed the information and felt informative in style. The colors were taken from each team’s hexadecimal color palette from their styling website, and helps each team be easily distinguished from the other.
Overall I’m very happy with how my charts turned out. In hindsight, I could have included the teams logos on the Holy War graphic for someone who is not familiar with the team, but my design was focused on a Utah (my home!) audience. In the future I hope to further my creativity in these packages to use forms other than those provided (circles, and rectangles.)