After exploring the Many Eyes site and playing with some of its visualizations, I thought it was time for you to make your own.
Your job for this week is this:
1) Go to the Many Eyes website: Many Eyes
2) Click on the link called "Data Sets."
3) Look at a bunch (between 6 and 10) of different kinds of data sets. As before, there is a search feature, so you can find a topic that interests you, like "sports" or "pets."
4) For the data sets you liked, create a visualization, save it, and post the link here. Then tell us about them on the blog. For each: a) put the link and b)say why you picked it and what you learned by visualizing it as you did.
This is due by Friday, April 30th.
Have fun!
Have fun!
Posts
26 comments:
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/drought-turns-southern-china-into-
I mostly picked this because I didn’t understand how a news article (which I suppose it was) could be turned into a visualization because I thought that visualization was just a fancy word for graph but once I saw what it looked like I loved it and kept it I also liked how the words make one big clump and the word water is in an angle in which it looks as if it is pouring life-giving water into a barren landscape. This taught me how writers try to avoid redundancy by using smaller words like the word water was used more than the word China or even drought.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/mannylautner-s-graph-on-what-pets-
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/mannylautner-s-weather-averages-du
The first graph that I had chosen was about what types of pets people own. I chose that graph because I know that many people have pets, and I also know that there are many different exciting pets in the world. By doing this graph, I could see if anyone had owned any exotic pets. The most exotic pet I had seen that somebody had own, was a snake. But that is still very crazy for me, since I am scared of snakes! And so, I learned that many people out in world actually do like pets like those... =]
The second Graph I had done was about the weather averages in the spring. I chose this graph because I knew how much crazy different weather happens in spring. Like, it might be raining one day, it might be 80 degrees one day, and it might be 40 degrees another day. And so, while making this graph, I wasn't surprised to see that one day in April was 70 and another day in April was 45. I learned that weather changes very easily!
those are the two graphs that I had made, and I have to say, I actually enjoyed searching through all different types of graphs, and seeing all the different information inside of them!
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/pie-chart/things-rick-astley-will-never-do/1
I picked this data set because the data in it is quite humorous and I love Internet memes. I learned that Rick Astley would never give you up more then he would never make you cry. Telling figures, indeed.
Link to visualization
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/inputs-first-visualization
I picked this visualization because since my interests are so unusual, I could not find any Data Sets that interests me (this one was pick at random). It showed me that US gas prices increased steadily over the past few years.
Input out!
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/millionaires-in-america
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/broadway-shows-average-ticket-pric
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/comparisons-of-us-colleges
I have to admit, I had a lot of trouble choosing which data set to make into a visualization. After eliminating data like favorite Disney characters, smoking and cancer effecting jobs, I came up with these three sets of data that I am particularly interested in.
Data Set #1: "Millionaires in America"
After recently watching the movie Annie and learning about the rich man Mr.Warbucks, I decided to focus in on a topic that I have not yet looked into, millionaires. I could have just chosen millionaires throughout the world, but I thought it might be more interesting if I did millionaires in America. As I was sitting and looking through data, I heard the word "millions" brought up in a conversation my mom was having on the phone. Automatically I typed in the word "millionaires" into the search bar and I got some interesting titles. Because I liked the look of the US map on the visualizations, I decided that choosing the title that had to do with both America and millionaires would be a great choice. What I learned from the map of millionaires was how many rich people there were in places like California, New York, Florida and Texas, states that some people consider to be the most populated states in America. After thinking it over I realized how that statement makes sense, especially because the map shows that in California (the darkest shaded in millionaire state) the population is about 33,871,648 people and the amount of millionaires is 572,000. This may not seem like it is a lot of people, but believe me, it is.
Data Set #2: "Broadway Shows Average Ticket Prices"
In past blog assignments I have always said how much I love Broadway and theater. In fact, for a recent blog report I chose the visualization for the same data set that I am using now that shows the ticket sales of recent shows. I chose the same one because it has already been done in a line graph, and I thought it would be cool to put it in the form of a bar graph. For some of the shows like The Little Mermaid and Gypsy they did not have the data which annoyed me, but for others they marked the average prices from 9/22/08 to 10/28/08. From this visual I learned that for the majority of the shows the pricing stayed the same every week. When it did drop or rise it only went up or went down a little bit. For example in South Pacific the pricing stayed at 111 dollars the whole time except for on 10/6/08, when it went up to 112 dollars. But, then again, for the show All My Sons the pricing one time was 94 dollars, and then the next week it went down to 80 dollars. I am wondering if this was because of the show's review, was it possibly not doing so well therefore making the shows price go down 14 dollars?
Data Set #3: "Comparisons of US Colleges"
My mom recently showed me a sticker for the bumper on our car for the college she attended, Middlebury. When I was looking for data I thought maybe it would be cool to do a blog assignment on nation wide US colleges. When I found this one set that had a lot of data, I thought it would be a good idea to use it, especially because it was loaded with a lot of good facts. For example, for the category additional fees, I found out that the highest additional fees were in California Colleges like Santa Barbara, San Diego, Santa Cruz, etc. When I discovered this I wondered why it cost so much more? Maybe because they are good schools or because they have many students attending California Universities. The fees were all in the $4,000 price ranges, while other colleges additional fees were in the $90 price range.
A) http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/mens-basketball-titles-for-each-of
B) 1. I liked this collected data because I love the sport of basketball and the NCAA that I love to watch just like march madness. 2. I learned that only some things can go into the category that the data set gives you. Also it gives you experience to know how to organize data. Like in the future to come in my life and in everyone’s life.
Graph: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/pie-chart/macs-v-pc-users/1
Data Set: http://manyeyes.alphaworks.ibm.com/manyeyes/datasets/macs-v-pc-users/versions/1
My first data set i did was how many precent of people surveyed uses a mac, pc, both, other, or no computer (i noticed the person who did this did not spell computer right!) I chose this because i was on my computeer with the tv on one of those mac commercials came on and i thought what a great idea for my blog so then i found a data set on this! I learned that more people use a PC i probaly could guess that beacuse they are cheaper but MANY people i know (including me) use a mac so i though that mac might have been higher in precent, not many people i know use both a mac and pc, so i thought this number would be lower, the last thing i learned is that not every one has a computer even though a tiny prencentage (if this was out of 100 people it would only be one person) there is still some people that do not have a computer (the only ones i know are my grandparents who find that they wont get how to use it)
Graph: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/bubble-chart/ice-cream-fat-grams-by-sugar-grams-a-10/1
Data Set: http://manyeyes.alphaworks.ibm.com/manyeyes/datasets/ice-cream-fat-grams-by-sugar-grams-a-10/versions/1
My next data set was about fat sugar and taste of an ice cream, the ice creams were
• Dreyer's Girl Scouts Thin Mint
• Dreyer's Girl Scouts Tagalongs
• Dreyer's Tart Mango
• Private Selection Butter Pecan Praline
• Breyers Peanut Butter Fudge
• Breyers Chocolate Cookies & Cream
• Dreyer's Girl Scouts Samoas
• Reduced Fat Nilla Wafers
I choose this because who doesn't love ice cream? many of the data sets i found where like whats your favorite icecrem but i thought thats to simple i soon came a long this wonderful data set. right away i decide to do this for my blog i like bubbles so i thought what is better then a bubble chart the way it was shown surprised me some of the bubbles were small yet others where HUGE the most fat was Dreyer's girl scout tagalongs, with 7 grams of fat (i don't think thats a lot?) but the sugar was 15 when others had 18 (dreyers girl scout samosa) then for taste it was second highest with a 9. That suspired me because 1st i know a lot of people who don't like tagalongs and 2nd i never even knew they had that ice cream or ever saw it at the store.
<3 <3
Y.F.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/bar-chart/the-health-of-owners-and-their-attit/1
I picked bar graph to represent how a pet’s owner’s health affects the pets health. I learned that most of the time that it does affect that. The thing that I really didn’t like about the many eyes is that the data is so unspecific and sometimes it just doesn’t make sense. The thing that I did like about it was that the site is very easy to use.
The reason that I picked a graph about pets was because I have a dog and I wanted to know how I affect her. For example I wanted to know if I was grumpy would she be grumpy, and it turns out that the pets personality is usually like the owners.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/bar-chart/the-health-of-owners-and-their-attit/1
I picked bar graph to represent how a pet’s owner’s health affects the pets health. I learned that most of the time that it does affect that. The thing that I really didn’t like about the many eyes is that the data is so unspecific and sometimes it just doesn’t make sense. The thing that I did like about it was that the site is very easy to use.
The reason that I picked a graph about pets was because I have a dog and I wanted to know how I affect her. For example I wanted to know if I was grumpy would she be grumpy, and it turns out that the pets personality is usually like the owners.
My 1st link : http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-bubble-chart
My chart was about the top articles you see in the NY times. This was around 2000-2009. The popular bubble was a world bank. The rest of the articles revolved around the U.N, and other international organizations. This tells me that there's a lot of issues around the world. I hope most of them can be solved. I can understand how all these organizations have increased, because of the war we're having with Iraq.
My 2nd link: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-tag-cloud
This chart I liked the best. My tag cloud showed the top smiley counts there are, when some one's tweeting. The most popular: Smiley face. There was also the sad face, winking, silly face, and the surprised face. I can now learn that when people are tweeting smiley faces, they're happy!
My 3rd link: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-pie-chart
I created this pie chart on wind energy, and which state uses it the most. I saw Texas, Kansas, Nebraska, and Montana use it the most. Those states have flat land and windy climate, which makes it perfect for wind power. I'm happy to learn that a lot of states are putting in the effort to be green. And wind power is one of the easiest alternative energies to harvest.
My 1st link : http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-bubble-chart
My chart was about the top articles you see in the NY times. This was around 2000-2009. The popular bubble was a world bank. The rest of the articles revolved around the U.N, and other international organizations. This tells me that there's a lot of issues around the world. I hope most of them can be solved. I can understand how all these organizations have increased, because of the war we're having with Iraq.
My 2nd link: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-tag-cloud
This chart I liked the best. My tag cloud showed the top smiley counts there are, when some one's tweeting. The most popular: Smiley face. There was also the sad face, winking, silly face, and the surprised face. I can now learn that when people are tweeting smiley faces, they're happy!
My 3rd link: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/sciencediva7s-pie-chart
I created this pie chart on wind energy, and which state uses it the most. I saw Texas, Kansas, Nebraska, and Montana use it the most. Those states have flat land and windy climate, which makes it perfect for wind power. I'm happy to learn that a lot of states are putting in the effort to be green. And wind power is one of the easiest alternative energies to harvest.
IF MY ARTICLE IS POSTED TWICE, THERE'S SOME GLITCH WITH THE SITE. fOR SOME REASON, MY COMMENT WON'T POST THE FIRST TIME.
a)http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/fredysnitchelburger
b) I picked it because i like baseball and when i saw somthing on babe ruth, i just had to see it. I learned how to deal with data and how much homeruns babe ruth can hit in a year.
a)http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/fredysnitchelburger
b) I picked baseball because I like baseball and when I saw somthing on Babe Ruth, I just had to see it. I learned how to deal with data and how much homeruns Babe Ruth can hit in a year. I also learned how old he was when he hit the most humruns in a year.
A) http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/mens-basketball-titles-for-each-of
B) 1. I liked this collected data because I love the sport of basketball. Like the NCAA that I love to watch on TV and root for my team. Just like “March Madness”. 2. I learned that only some things can go into the category that the data set gives you. Also it gives you experience to know how to organize data. In the future to come in my life, I will need to know in my life to come. Maybe in my job in the future, activities I will reach for in the future. Like goals to meet to succeed in life to come.
This is my revised version. Sorry Mr.Ardito
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/tag-cloud/internet-users-per-country/1
This graph was about how many people use the internet in different countries. I probably should have put it in a bar graph, or something, but I liked it was words, because it was like you could just see how one country used the internet so much more then another country, just by looking at how big the words were. From visualizing the data like that, I could tell things about a country, like how technological and developed they were.
A: http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/the-many-smiles-of-twitter
B: I choose this, because since many people say they go on Twitter, I wanted to check and see if Many Eyes had data for sign-ins. I then saw something called “Smiley Counts”. I picked it, because it sounded interesting. I made my own graph and here it is. I learned that a lot more people then I thought go on Twitter. Not everyone uses :) or :( but there were A LOT of counts of people doing that.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/tag-cloud/all-clash-lyrics/1
This measures how manny times each word is used in clash songs. I think its interesting because I really like the clash,also because its interesting to see what words they use. you can tell a lot about a band by there lyrics. this really proves that. I like how its organized because its really cool to look at.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/new/pie-chart/species-population-in-thousands/1
This measures how many penguins are populated on the earth. I think its interesting because we should pay attention to the animals that are becoming extinct. Our children may not see the types of animals we see today in our lives.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/reasons-for-homelessness (Link to site) I picked this data because it's a very common things; homelessness. I thought it would give people a visual on why you see someone sitting on a street corner asking for money. It shows the top reasons on why people are without homes. I like it because now people don't have to think "That person (rude comments)..." when you see a homeless person. =]
a)http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/eatsleepswims-graph-for-mcdonalds
b) I picked this topic because it really interests me and I wouldn’t pick it if I hadn't been interested in it. Another reason I picked it was because I wanted it to have important information that could help people. A third reason I picked it is because I wanted to see how it would look in a bubble graph like that.
One thing I learned from this graph was that in a bubble graph the biggest number has the biggest and the smallest number will have the smallest circle I did not know this before because I thought they were all the same size with numbers in them. Another thing I learned was the most fattening thing on the menu was the Angus Bacon and Cheese Burger which had 790 calories.
a)http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/unemployment-in-the-us-of-2010
b) I chose this topic because to me was interesting. Another reason I chose it is because I wanted to know what it would look like in this form. A third reason is because of all the things I've been hearing about unemployment I said to myself I might as well do it. A fourth reason is because I wanted to.
One thing I learned from this was that Franklin County, Kansas had the most job losses in the country which I found pretty interesting. Another thing I learned was that Douglas County, Kansas had the least amounts of job losses. A third thing I learned was that you can make any data into any graph on the computer even if it doesn’t make sense.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/jimbojones446-visualiztion This is the link to my visualizations. I chose this topic randomly after looking for how many football sacks there are in one year. I didn’t get to choose it because there was nothing on it. Instead, I chose birth rate in the U.S.A. from 1950-2007. I learned that birth rate decreased in numbers from 1950-2007.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/top-artists-by-soccerlovr
I picked it because i was really interested in what artists were in and where out. I also was interested in weather or not the bands i like were up on the top of the list.
What I learned about my data set was that there were lots of bands that i didn't even know about. I also learned that you can use words for a graph, and that the bigger the words the more popular. I thought that was really cool because I learned all different type of graph. I liked it because I learned a lot and now I can look at the new popular bands and maybe I will like there songs and get something pretty cool out of it. Lastly I lied this because I thought it was really cool if you touched the band and it went to all gray but the one you pressed which turned orange. That's why I enjoyed it.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/top-artists-by-soccerlovr-2
I picked this because... I thought it was pretty cool for two reason. The first reason is because of the bands that were up there at the top. I was really surprised that none of the bands that I really like were up there. The second reason that I thought it was cool was because if you touch the artists then everything would get gray but the one you pressed that turned orange. That was cool because it was a way to focus of that one artist you want to see.
The reason I liked it and what I learned was that a graph can be words. The bigger the word the more popular the artist is, so i learned another graph. The reason I liked this was because I learned different types of data which was cool, and while learning I found out cool new bands. That is why I really enjoyed this assignment.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/gotlax18-popular-names
I picked this because I wanted to know popular names and see if people I know had those names.
The one thing I learned is that the same name as most of the people I know had those names.
Sorry for it being short
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/plays-on-itunes
I liked this data set because now that I have gotten it to work on my computer itunes is something I use a lot. I also liked it because it had a big range of artists on it and because ther were a bunch of different ways to organize it.
I didn't learn much from the chart itself because it wasn't clear if it was representing the amount of times a track was played on someone's personal itunes or if it was for itunes in general. I did learn about making the charts from the many eyes website. I learned that there were a couple different ways I could organize the chart and that depending on the type of data (for example: numbers or words) you could represent it in a different type of chart.
http://manyeyes.alphaworks.ibm.com/manyeyes/visualizations/species-of-indangered-penguins
This one works better.
Post a Comment