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This workbook visualized the box office data for the superhero movies that produced by Marvel Studio. Fast-Food vs. Vegetarian + Vegan Food Options In the US. When I was designing the visualization for the comics data, comparing two galaxies using suns and planets was the first thing that came to mind. It is not affiliated with Marvel Entertainment, LLC and is an unofficial community operated by dedicated fans. The correlation coefficient for budget vs review rating was found to be 0.67. We selected the top 20 most connected superheroes as subjects. Marvel Universe was created by Stan Lee, the most influential comic icon, with several artists in 1961. However, the feedback from users said the visualization turned out to be too much bars thus not visually clear enough, so we decided to narrow the database down to 10 top superheroes. Marvel Universe is a fictional universe which based on the American comic stories published by Marvel Entertainment. For more information on installation, visit http://igraph.org/python/, One of the requirement to build this network graph is to express the source and destination nodes as integer values. Get the Marvel and DC comic movies data. It consisting of thousands of separate universes and all the stories in this “multiverse” happened on Earth. Avengers: Endgame (2019) had a budget of 356 million US dollars and got the highest rating of 8.8 among all the Marvel movies. After data cleaning process, we visualized the statistics with Tableau. In terms of the powergrid, we compared “Intelligence”, ”Combat”, “Speed”, “Durability” and “Strength”. We utilized Openfire to clean the huge dataset, and only left the information of Marvel Universe. The percentages of good and bad alignments of male characters are 30% and 55% respectfully, and these percentages for female characters are 49% and 30%. If we can see something, we internalize it quickly. Photo from Washington Post Archive scanned on 2/17/2009. In Marvel Universe, the number of male character is 3 times bigger than female character, and 0.5% of the characters are agender. Some quick data cleaning to remove empty spaces, If you are playing around with the same code and want to explore additional characters, you can use the following line to explore what type of characters are included in the dataset. Each set of bar is treated as seperate data, we define the x and y values and the aesthetics for each group of bars. Pew’s The Next US takes a comprehensive look at demographic data in the United States and brings it all together into a massive, interactive, beautiful data visualization project with several “chapters” of … Visualization from Xingya’s last Marvel networking project. Probably, the reason caused this spike is the publishing of the new series of Uncanny X-Man, X-Man Unlimited as well as X-Men 2099. It includes their fan-given scores on their abilities (intelligence, strength, speed, durality, combat). See all awards and nominations. We selected the most representative characters from each superhero groups, found their profile picture on the internet, and used Adobe Photoshop to put them on each nodes that they belonged to. Browse our infographic to learn how to tackle the 23 Marvel movies released so far and dive deep into the box office numbers for the Marvel blockbusters. We really liked the flattened affect that illustration images have provided, so we used some of their superhero profile pictures on our graph and found more similar images from the internet. 4 months ago. #heros[heros['hero1'].str.contains('DAREDEVIL')]['hero1'].unique(), https://www.kaggle.com/csanhueza/the-marvel-universe-social-network, « Dimension Reduction with Principal Component Analysis. In this part of the visualization, first, we used Excel to manage the dataset with xlsx format. Taha07. Our goal for this project is to expand our knowledge beyond the cinematic Marvel universe and develop a new perspective for the comic Marvel universe. The Marvel team thinks they’ve built a solution: a massive database that uses graph theory to give fans a simple take on characters that span comics, movies, and video games. From the chart we can perceive that compare with good characters, the bad people are more likely to keep their villain identity in secret. Visualization by: Pew Research Center Learn more: Next America . DIY And Crafts. Marvel Cinematic Universe as a 3-D network Network Visualization / comics , fiction , Marvel The Straits Times visualized the Marvel Cinematic Universe with a 3-D browsable network.… (Photo by Gerald Martineau/The Washington Post via Getty Images), Written by Wen Chen, Pei Liang and Xingya Wang. 4 months ago. We arranged the bar charts by comparison of gender and alignment, and identity and alignment, in order to make our visualization more interesting and insightful. Who would be interested in understanding this data better? Sep 25, 2019 - Explore Liz Schwartz's board "Data Visualization", followed by 550 people on Pinterest. For a data set with multiple information, a personalized visualization that group different visualization metaphors is necessary. Instead of bar chart, we are using Scatter3d for our data, Copyright © 2019 The Art of Marketing Science. Amanda did a lot of research on how we could interpret the characters demographic data in a refreshing and interesting way; Xingya learned to use Adobe Photoshop and Illustrator to put the profile pictures on the graph and make the legend; Pei collected and created the whole superhero ability dataset all by herself. Quite different with the other two datasets in the project, this dataset covered the information of  both superheroes and villains in the Marvel Universe. For each super power, we pulled out the winners and show their profile illustrations besides the graph, so that users can easily notice the winners. We also think it would be really interesting to look deeper into the development of Marvel, its ups and downs, its competition with DC, its relationships with Disney and Fox, and from there, maybe we can see if those factors have made impact on the characters(number of new character, their gender, race, and abilities) they created through the years. Commented on kernel Marvel Universe Data Analysis & Visualization. Fantastic, Scarlet Witch and Vision; the toughest(durability) ones are Wolverine and Thing; the fastest one is Vision; the strongest ones are Iron Man and Thing. Also, to make the centred characters more stand out and easier to be visually perceived, we decided to get rid out all the hero’s name labels, and use their profile pictures instead. The scores for all superheroes were voted by Marvel fans. The Marvel Cinematic Universe Interactive Data Visualisation Tool Exploring Categories and Connections Between Marvel Films, Characters, Artefacts and Attributes.. We filtered out only the Marvel characters. Also, to make the centred characters more stand out and easier to be visually perceived, we decided to get rid out all the hero’s name labels, and use their profile pictures instead. Summary. You just need to find the right element. https://drive.google.com/open?id=1ZgD-KGWe8WRDPCuhGMuREg0T7ltv5QpH. Directly link to the original source article of the visualization. Marvel Cinematic Data Visualization With Plot.ly I’m a huge sucker for Marvel cinematic and in this article I will do a fun exercise with building a simple interactive 3D network graph based on the relationship between Marvel characters. The scores for all superheroes were voted by Marvel fans. Area and trend chart of “Year of First Appearance”. What we did is to expand the size of the graph, further spread out the nodes, make the nodes bigger, and to use the “non overlap” function to avoid overlapping. When we see a chart, we quickly see trends and outliers. We learned a lot more characters and their relations. Based on the study of the superheroes networking. The layout function here defines the overall structure of our network graph and we use ‘sphere’. Commented on kernel Marvel Universe Data Analysis & Visualization. 4 months ago. All together, we’ve seen each of Iron Man, Thing and Vision’s name twice, so we think they might be considered the most powerful superheroes according to the fans. Excel: Helped us collecting the dataset with xlsx and csv formats. The Marvel Cinematic Universe is gigantic, and with the box office success of its previous films and TV shows, the Marvel franchise is still expanding. Saved from tulpinspiration.tumblr.com. When Avengers assemble, along with characters from far-flung corners of the Marvel universe, you’ll need this cosmic interactive graphic to tell who’s fighting whom, who has a hellish sister, and more. The dataset can be found on my GitHub or at the following link: https://www.kaggle.com/csanhueza/the-marvel-universe-social-network, Key thing to remember with Plot.ly is if you want to build graphs locally on you computer using Jupyter notebooks, you need to initiate offline notebook mode. This visualization used consistent and uniformed blue color scheme combine with relationship networking and bar charts with different styles that gave as many valuable inspirations for our whole project and final poster. Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources It’s not difficult to tell that superheroes in the Avengers group have more interactions with other superheroes, because the purple edges permeate the graph. We reduced the superhero ability charts from 20 rows to 10 rows. We want to pay our respect to this leading superhero behind all of the marvel superheroes and his comic legend. Ekrem Bayar. So we start off with encoding our heros into numbers. This idea was inspired by an interactive map called. Openfine: Used to clean and transform large sets of data. Stan Lee is one of the foundational architects of the superhero comics landscape, and he passed away on November 12, 2018 at the age of 95. We choose this Marvel Universe visualization as our group’s final project in honor of Stan Lee. Link to the full page of the source article. 1.1.1 Here Is The Sub-Mariner! Using data pulled from the Marvel Database API, I focused on all the different Marvel characters featured in issues by artist Adam Kubert. Adobe Photoshop: Used for Improving our visualization results and making the poster. However, our visualizations based on these datasets are all put together without any identifications. The subject of our datasets are different: two feature on the superheroes in Marvel Universe, one features on all the characters including superheroes, supervillains and those who stay neutral. This interactive data visualization was installed at the Gallery of Modern Art (GOMA) in Brisbane as a feature display during the Marvel Cinematic Universe exhibition that attracted record crowds from May 26 to September 3 … The challenge was to get it scraped. Part 9 — web page and graph visualization; Follow the duo on Twitter to see what’s coming: @mkheck and @jmhreif; Download Neo4j; Spring Data Neo4j docs; Spring Data Neo4j Guide; Marvel … Plot.ly is very easy to use and the way graphs are constructed is very intuitive. But each of all took on other tasks too, which might not necessarily be what we are good at or familiar with. Making Data Beautiful The most inspiring new art is visualized information Aaron Koblin's New York Talk Exchange shows, in real time, the volume of telephone and Internet data flowing to other cities. There seems to be a clear positive correlation between budget and the rating left by the reviewers for the MCU movies. Heroes will be listed in italics.. 1 1939. Based on these feedbacks, we made changes accordingly. Marvel Universe was created by Stan Lee, the most influential comic icon, with several artists in 1961. In Chrome, you right click on the table and select Inspect. Data visualization is another form of visual art that grabs our interest and keeps our eyes on the message. We practice industry standard double-pass data capture methodology to guarantee over 99.95% accuracy. Visualization of the Social characteristics of the Marvel Universe using the Javascript Infovis Toolkit (JIT). We do a quick count on how many relationships each avengers have and how many comic books they appeared in, Building a grouped bar chart in Plotly is very simple. Knitting And Crochet. And then we built our own database referred by information collected on the SHDb (https://www.superherodb.com/battle/) SHDb has data of side-by-side power comparison for all superheroes. In this personal project I developed an interactive visualization tool for the visualization of comic characters from Marvel and DC. https://www.tor.com/2015/07/20/the-marvel-cinematic-universe-has-more-than-enough-characters-for-captain-america-civil-war/comment-page-1/, https://public.tableau.com/views/MarvelCinematicUniverse_0/MCU?:embed=y&:display_count=yes&:toolbar=no:showVizHome=no. The major superhero groups are Avengers, marked in purple, featured by Captain America, Iron Man etc; the Spiderman’s group, marked in pink, featured by Spiderman and Daredevil; the X-Men group, marked in blue featured by Wolverine, Professor X, the Beast, etc; the Fantastic Four group, marked in orange, featured by the Thing, Human Torch, etc; Thor’s group, marked in light blue; Doctor Strange’s group, marked in apricot; the Sub-Mariner group, marked in yellow as well as the New Warriors group, marked in grey. ; 1.1.2 Kar … I will be using one of my favourite plotting libraries in Python, Plot.ly. The trend of year of Marvel characters’ first appearance had hit the bottom during 1950 to 1960. Stan Lee is one of the foundational architects of the superhero comics landscape, and he passed away on November 12, 2018 at the age of 95. Villains will be listed in bold.. We can see our fellow Captain Steve Rogers is quite popular along with friendly neighborhood Spiderman and Mr. Tony Stark. Link colors represent type of relationship, and proximity naturally represents commonalities between characters. During the class discussion, we’ve received a lot of questions and suggestions and we’ve found them very valuable. Marvel & DC Visualization. Data science in marketing with practical examples, I’m a huge sucker for Marvel cinematic and in this article I will do a fun exercise with building a simple interactive 3D network graph based on the relationship between Marvel characters. Play around with some of these to see the different structures. Our eyes are drawn to colors and patterns. SHDb has data of side-by-side power comparison for all superheroes. In a larger sense, we believe I have achieved this goal. This dataset only provides connections among the superheroes in Marvel Universe, villains are not included. The dataset include information about the character’s name, identity(secret/public), alignment, eye color, hair color, gender, status(living/deceased), appearances, first appearance, universe. Therefore, we created two pie charts, two bar charts as well as one area and line chart. What we did is to expand the size of the graph, further spread out the nodes, make the nodes bigger, and to use the “non overlap” function to avoid overlapping. Winner - Best individual 2017 Information is Beautiful Awards. Group work really is important because we can contribute what we do the best into this project. Next I’d like to seperate our good guys from the bad guys visually, so let’s group them up. Our purpose is to make our visualization more versatile. From Raw Data to Visualization: Marvel Social Graph Analysis May 19, 2015 Use Cases & Projects Pierre Gutierrez I've been reading comics since I was a little kid. Information is Beautiful Awards. But through this project, we’ve learned about this and people can see it on the poster, that the Sub-Mariner stands among Avengers. My network visualization in Gephi provides insights into the body of work over Adam’s career at Marvel. It has a beautiful circular layout and viewers can recognize different superhero groups and their relations by different colors. . We wanted to give a general outlook of the superhero’s network in the sense of who usually hang out together or who is the “it” superhero, and we wanted it to be visually aesthetic, so we decided to keep using the Yifan layout. Commented on kernel Marvel Universe Data Analysis & Visualization. Best Data Visualization. Since the beginning of the 21th century, the trend decreased again. We can see from the chart that the number of male supervillains are more than male heroes. Layout function helps us define the layout of the network graph, what we are doing here is populating our X, Y, Z coordinates for each node and edge to be placed into our 3D space, Same as how we built the bar chart, we define our data & layout and pass into the Figure function. One section is graphs about Marvel superheroes, the other one is graphs about all characters, regardless of their alignments. We collected the ability information for 20 most connected superheroes, but it’s too clustered and difficult to read considering the space allowed on the poster. One weird data point here is Thor who in my mind is should be quite popular… This might be because there are several Thor characters in the dataset, representing different Thors from different universes, as well as the comic book universe being different from cinematics. However, the number of female character is just reverse. The provided Ruby script takes the data provided by Joe Miro, Cesc Rosselló, Ricardo Alberich and the Marvel Chronology Project and formats it for use with a JIT Force-Directed Graph . From these two pie charts we can see that more characters in Marvel Universe kept their identity in secret rather than reveal it to the public. Data visualization : Marvel vs DC films visual analysis Marvel vs DC films visual analysis By aerozhx At infographic.tv we provide handpicked collection of the best infographics and data charts from around the … Data Capture. The hero-network.csv dataset contains two columns, hero1 and hero2 and represents a connection between the two characters. And then we built our own database referred by information collected on the SHDb (. ) We collected the raw data from https://www.superherodb.com/characters/. Started from our previous Marvel networking project, what we really wanted to improve is to make the graph easier to read and to make the characters more standout. Note: I've intentionally not shared the cached data pulled from Marvel Developer, only the directed graph data to build this visualization. At the same time, There are more supervillains than superheroes, and there are still 16.5% of characters didn’t pick up a side. This could be a very huge project in the context of various social movements, like gender and race equality. 2017. The following analysis is an exploration of a dataset related to movie releases between the years 1986-2016. Now were ready to build our nodes and links. It’s been really enjoyable for our group doing this project and we are really satisfied with our final poster. Visual Learning Learning Centers Annual Report Design Makeup Store Dashboard Design Cardcaptor Sakura Japanese Artists Data Science Data Visualization r/Marvel This is a subreddit dedicated to Marvel Comics, its publications and hundreds of characters. There are only 2 new characters were created in 1958. UNKNOWN LOCATION, DC – FEBRUARY 17: Marvel Comics Publisher, Stan Lee, poses with a book of “Spider Man” comics which he created along with comics on the “Hulk” and others. We collected the raw data from. The 25 Best Data Visualizations of 2019 Get inspired with this ultimate list of the best data visualizations of 2019. Also, there’s a lot of purple in on the winner list of each ability, which means that the Avengers has gotten a great team! The peak appeared between 1989 to 1995, and the highest number of first appearance in a given year was 1993 which reached 554 characters. We applied similar or identical colors in different graphs on different topic to make the poster visually consistent, however it can be misleading. Thankfully, Wikipedia already lists the movie data for us. But, with the popularity of Marvel movies, it would interest a large part of the general populace as well. Explore. We divided the poster into to sections based on the subject of their datasets. It includes their fan-given scores on their abilities (intelligence, strength, speed, durality, combat). From the (revised)chart, among the 10 most connected superheroes, we can see that the the best fighter are Captain America (we’re not surprised) and Wolverine; the smartest ones are Iron Man, Mr. We also applied another set of palettes to different superhero groups to make it more visually pleasant. Meanwhile, we narrowed down to just Name, Identity, Alignment, Gender, and Year of first appearance these 5 criterias and 16,377 records. Adobe Illustrator: Served as the tool for adding profile illustrated pictures on our networking graph. This page contains every death from every comic book from the Marvel universe in order of release date. At the same time, more good superheroes choose to neither keep their identity in secret nor reveal it to the public than the supervillains. We can quickly identify red from blue, square from circle. Marvel Cinematic Universe from The Straits Times. However, it was a little bit challenging to see the main characters in the original graph, because both the node size and the text are small and clustered. Data visualization : [OC] Captain Marvel took $455 Million in its opening weekend, the second most of any MCU movie [OC] Captain Marvel took $455 Million in its opening weekend, the second most of If you’re looking for uniquely crafted & beautiful visualizations of data — let’s get in touch! The m dimension values of a record are mapped to m pixels at the corresponding positions in the windows May 18, 2012 - Every Single Avenger That Marvel Ever Invented. Lastly we pass data and layout into Plot.ly’s figure function to build the graph. These are the artifacts in my sandbox playground. Before, we didn’t even know the existence of, for example, the Sub-Mariner, let alone the fact that he serves closely to Avengers and Fantastic Four. Or we can make a chart about the the number of new characters that DC has created during the years, together with the chart we have now, and see if there’s any associations with the success of their company development. We applied different colors to avoid color-overlapping among graphs on different topics. See more ideas about Data visualization, Visualisation, Infographic. So it could be confusing for viewers to read. We found this visualization online, despite the fact that it focuses on much fewer characters that we have, we still like the entertaining and straightforward style it has, concerning the pop-culture nature it is. Originally, there are over 30,000 records in the dataset which including 12 criterias and also included DC and other universes’ data. First off, there are a whole lot of characters in our dataset, lets just keep our avengers and villains, Next we use the igraph libary which is a library for high-performance graph generation and analysis. We’ve found in the year of 1993, more characters than ever made their first appearance, but we didn’t explain why. Gephi 0.9.2: Created network and graph data. We looked into Marvel in 1993 and tried to explain that why more characters were created in that specific year. We selected the most representative characters from each superhero groups, found their profile picture on the internet, and used Adobe Photoshop to put them on each nodes that they belonged to. This dataset is about ten superheroes that have the most nodes from the networking dataset. This is the timeline history of all movies from Marvel Comics brand versus DC Comics brand starting 1989 to 2019. Then we define the layout like axes, chart title etc. We selected the top 20 most connected superheroes as subjects. We clearly understand the importance of appropriate usage of technology in offshore business process management. At the meantime, the X-Men are more connected within their own group. For this exercise, I’m interested in looking at the connection between some of the marvel characters and villains that we’ve see in theatres! Tableau: Utilized as the tool for visualizing the bulk data and creating dashboard. Visualizing Marvel characters and related information would most definitely interest comic book fans. Jan 10, 2014 - The business of heroes needs saving from the crushing weight of its own data. If we had more time, we would like to make graphs on, for instance, gender, and see how many new characters in each gender have made debut through the years, and see if it has any associations with any social movements. Based on Mike Bostock's Les Misérables co-occurrence matrix diagram. This part looks a little intimidating and complicated but its not so bad. This idea was inspired by an interactive map called Marvel Cinematic Universe we found on The Straits Times. From the final visualization, we can see that Captain America is the most centralized superhero in the Marvel Universe followed by Spiderman and Iron Man. We choose this Marvel Universe visualization as our group’s final project in honor of Stan Lee. The movies are all based on characters that appear in American comic books published by Marvel comics. Neil Gaiman, Alan Moore, Warren Ellis, and Art Spiegelman are among my favorite authors now, but when I was younger, I was a big fan of Marvel superheroes. Scroll down and right and hover. To make the graph more comprehensible, we also made a legend so people could easily understand what the different colors stand for. Personal Project | 2019. For examples, the superhero intelligence chart was applied the same purple that marked the Avengers in the networking graph, so viewers would tend to associate this chart with the Avengers, when the avengers are in fact not relative at all. See the Visualization: Marvel Social Network Graph . This dataset is about ten superheroes that have the most nodes from the networking dataset. Network Visualization / comics, fiction, Marvel The Straits Times visualized the Marvel Cinematic Universe with a 3-D browsable network. However, it was a little bit challenging to see the main characters in the original graph, because both the node size and the text are small and clustered. Our culture is visual, including everything from art and advertisements to TV and movies. We really liked the flattened affect that illustration images have provided, so we used some of their superhero profile pictures on our graph and found more similar images from the internet. Use Case. For the color scheme, we used red, blue and white to represent the spirit of America, just like what the Marvel Universe want to express in their comics.At the end, we used Adobe Photoshop made the title, inserted more numbers into one graph, also made the graphs more coordinate. It’s storytelling with a purpos… This data visualization is a beautiful attempt to put the series of movie plots in a timeline arrangement. Based on the study of the superheroes networking. Playing is the most natural way to learn. For the superhero networking graph, we decided to go on with the work that Xingya had done for the Gephi lab. This trend is confirmed by the second highest-rated movie Avengers: Infinity War (2018), which is also the MCU movie with the second highest budget. There are other options like, gfr, grid_fr, grid_fruchterman_reingold: grid-based Fruchterman-Reingold layout, kk_3d, kk3d, kamada_kawai_3d: 3D Kamada-Kawai layout. Fabric Crafts. Amanda is skillful with Tableau, Xingya has explored more about Gephi, and Pei is the expert when it comes to the visual design. If you made the visualization yourself, tag it as [OC] [OC] posts must state the data source and tool(s) used in the first top-level comment on their submission. It has a beautiful circular layout and viewers can recognize different superhero groups and their relations by different colors. Gold in Unusual. Now you can watch the Marvel Cinematic Universe in chronological viewing order. ... Get data visualization tips every week: New features, special offers, and exciting news about the world of data visualization. In the first iteration, we compared top 20 most connected superheroes’ powergrid. 1.1 Motion Picture Funnies Weekly Vol 1 1. Original source article doesn't mean the original source image. The package rvest makes it very easy. We wanted to give a general outlook of the superhero’s network in the sense of who usually hang out together or who is the “it” superhero, and we wanted it to be visually aesthetic, so we decided to keep using the Yifan layout. Drops Design Inspired .. North American Digital Media Awards. This dataset provides information for characters regardless of their alignment. We start off with links by putting our (source, destination) for every node into Edges and pass Edges into our igraph. View in a new tab or click to view live version.

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