Description
Homework Overview
“Visualization gives you answers to questions you didn’t know you have” – Ben Schneiderman
This homework focuses on exploring and creating data visualizations using two of the most popular tools in the field. Data visualization is an integral part of exploratory analysis and communicating key insights. All of the questions in this homework use data on the same topic in order to highlight some of the uses and strengths of different types of visualizations. The data for this homework comes from BoardGameGeek and includes information on games’ ratings, popularity, and metadata.
Part 1 of the homework uses Tableau to connect to online data which feeds multiple visualizations including a table and bar charts. Part 2 of the homework uses D3 and includes graphs with different scales, network graphs, and a map.
Below are some terms you will often see in the questions:
• Rating – a value from 0 to 10 given to each game. BoardGameGeek calculates a game’s overall rating in different ways including Average and Bayes, so make sure you are using the correct rating called for in a question. A higher rating is better than a lower rating.
In Q1, you will design a table, a grouped bar chart, and a stacked bar chart with filters. The data for this question is hosted online and will help you practice connecting Tableau to online data sources.
Questions 2-5 highlight different features of D3. The provided skeletons scaffold coding in D3 with the most complete template code being provided for Q2. Q4 and Q5 provide scaled back templates. Q3 does not provide template code, and is an excellent opportunity to separate html, css, and js files because a separate js file can be used for each of the visualizations.
Q2: a network graph shows relationships between games. You will add interactive features like pinning nodes to give the viewer some control over the visualization.
Q3: you will explore temporal patterns in the BoardGameGeek data, using line charts to compare how the number of ratings grew from month to month for 8 games. You will also integrate additional data about board game rankings onto these line charts and explore the effect of axis scale choice on what information is emphasized in the graph.
Q4: you will create line charts that use interactive elements to display additional data. This time, the line charts will show the number of games with each rating for multiple years. You will then implement a bar chart that appears when you mouse over a point on the line chart.
Q5: you will create a choropleth map to explore the average rating of each game in different countries.
Note the following important points
1. We highly recommend that you use the latest Firefox browser to complete this question. We will grade your work using Firefox 80.0.
2. You will work with version 5 of D3 in this homework. You must NOT use any D3 libraries (d3*.js) other than the ones provided in the lib folder.
3. You will need to setup a local HTTP server in the root (hw2-skeleton) folder to run your D3 visualizations, depending on your web browser, as discussed in the D3 lecture (OMS students: the video “Week 5 – Data Visualization for the Web (D3) – Prerequisites: JavaScript and SVG”. Campus students: see lecture PDF.). The easiest way is to use http.server for Python 3.x. (for more details, see link).
4. All d3*.js files in the lib folder must be referenced using relative paths, e.g., “../lib/<filename>” in your html files. For example, suppose the file “Q2/graph.html” uses d3, its header should contain: <script type=”text/javascript” src=”../lib/d3.v5.min.js”></script> It is incorrect to use an absolute path such as:
<script type=”text/javascript” src=”C:/Users/polo/hw2-skeleton/lib/d3.v5.min.js”></script>
6. You can and are encouraged to decouple the style, functionality and markup in the code for each question. That is, you can use separate files for CSS, JavaScript and html.
Q1 [25 points] Designing a good table. Visualizing data with Tableau.
a. [5 points] Good table design. You want to help a board game design company to analyze the current popular board game data from the website BoardGameGeek. Create a well-designed table to visualize the data contained in popular_board_game.csv. You can use any tool (e.g., Excel, HTML, Pandas, Tableau) to create the table. If you choose to use a tool other than Tableau to make the table, you will still need to load the same data into Tableau for use in Q1b.
The company is interested in grouping popular games into “support solo” (minimum player = 1) and
“not support solo” (minimum player > 1), because single-player games require a different design strategy.
Instructions:
Your table should clearly communicate information about these two groups (games that support solo & games that do not support solo) simultaneously. For each group, show:
1. Total game count in each category (fighting, economic, …)
2. The most representative game (game with the highest number of ratings) in each category. If more than one game have the same ratings, pick the game that you prefer.
3. Average rating of games in each category, rounded to the nearest 2 decimal places
4. Average playtime of games in each category, rounded to the nearest 2 decimal places
5. In the bottom left corner below your table include your GT username. (If you decide to use Tableau, this can be done by including a caption when exporting an image of a worksheet or by adding a text box to a dashboard. Refer to the tutorial here.)
6. Save the table as table.png. (If you decide to use Tableau, to save a worksheet image, go to Worksheet – Export – Image. And to save a dashboard image, go to Dashboard – Export Image. Do not simply take a screenshot since your image should have a high resolution.)
Note: If there is no game under a particular group and category, think about how to visually represent missing data in your table. For this exercise, you can replace Null/NA/Empty values with 0 in the table.
Setting Up Tableau
If you do not have access to a Mac or Windows machine, please use the 14-day trial version of Tableau Online:
1. Visit https://www.tableau.com/trial/tableau-online
2. Enter your information (name, email, GT details, etc.)
3. You will then receive an email to access your Tableau Online site
4. Go to your Site and create a workbook
Connecting to the Data
Complete all parts of Q1b-c using a single Tableau workbook. (Technically, you could use multiple workbooks, but we do not recommend that here. The directions below assume you are using one workbook.)
1. You will need a data.world account (created using any email you want) to access the data for Q1c.
2. Q1 will require connecting Tableau to multiple data sources. You can connect multiple data sources within one workbook by following the directions here.
3. For data in Q1b: Open Tableau and when prompted to connect to a data source, choose To a File – Text file. Select the data file from the skeleton.
4. We recommend renaming the data connection since you will have multiple connections in this workbook. Rename the connection to something that makes sense to you. (Clicking on the text lets you edit it.)
5. For Q1b, you can use either a live connection or data extract. (You can read a comparison of Tableau’s data connection options here.) Click to create a new worksheet. You now have the data needed for Q1b!
6. For data for Q1c: Add a new data source by clicking on Data – New Data Source.
9. Click to create a new worksheet, and Tableau will then automatically create a data extract. You now have the data needed for Q1c! (Live data connections are not an option when connecting to data.world. You can read a comparison of Tableau’s data connection options here.)
b. [10 points] Grouped bar chart. You want to help this board game design company better understand the relationship between game playtime and game category among popular board games. Visualize popular_board_game.csv as a grouped bar chart. Your chart should display game category (e.g., fighting, economic) along the horizontal axis and game count along the vertical axis. Also show game playtime (e.g., <=30, (30, 60]) for each game category. Note: Do not differentiate between ‘support solo’ and ‘non-support solo’ for this question.
The main goal here is for you to get familiarized with Tableau. Thus, we keep this part more open-ended, so you can practice making design decisions. We will accept most designs from you all. We show one possible design in Figure 1a, based on the tutorial from Tableau, and you are not limited to the techniques presented there.
Instructions:
1. Your design should be a vertical grouped bar chart. For each game category, show the game count for each game playtime.
2. Your design should have clear labeled axes and a clear chart title. Include a legend for your chart.
3. In the bottom left corner of your image include your GT username. In Tableau, this can be done by including a caption when exporting an image of a worksheet or by adding a text box to a dashboard. Refer to the tutorial here. Note: The default Tableau caption can be deleted or rewritten.
4. Save the chart as grouped_barchart.png
5. To save a worksheet image, go to Worksheet – Export – Image. And to save a dashboard image, go to Dashboard – Export Image (Do not simply take a screenshot since your image should have a high resolution).
c. [10 points] Stacked bar chart. After understanding the relationship between game category and their playtime, the game company now wants to know the count of games in different category, and if there is any relationship between game category and how they are played (their playing mechanics). They also want to know how player size changes this information.
Instructions:
1. Create a ‘Worksheet’ with a stacked bar chart that shows game count for each game’s playing mechanics (sub-bars) for each game category
2. This data contains duplicate rows because each row represents a distinct game. Do not remove duplicate rows from the data when creating your chart.
3. Your chart should display game counts along the vertical axis and category along the horizontal axis
4. Your design should have clear axes labels and a clear chart title. Include a legend for your chart.
5. Create a dashboard using the sheet you created in the step 1
6. Add a filter for number of ‘Max.Players’ allowed in each game. Then update the chart using this filter to generate the following chart images (Refer to the tutorial on how to add filter in a dashboard here. Make sure to add ‘Max.Players’ in the filter shelf in the Worksheet first, like this.):
a. Select “2 Players” only in the filter. Save the resulting chart as ‘stacked_barchart_1.png’
b. Select “4 Players” only in the filter. Save the resulting chart as ‘stacked_barchart_2.png’
c. Both images should include your GT username in the bottom left. This can be added using a text box. Refer to the tutorial here. Note: Text boxes can only be added to a dashboard in Tableau, not a worksheet.
7. To save a dashboard image, go to Dashboard – Export Image. Do not submit screenshots.
Q1 Deliverables:
The directory structure should be as follows: Q1/
table.png grouped_barchart.png stacked_barchart_1.png stacked_barchart_2.png
● table.png – An image/screenshot of the table in Q1.a (png format only).
● grouped_barchart.png – An image of the chart in Q1.b
● stacked_barchart_1.png – An image of the chart in Q1.c after filtering data for Max.Players = 2
● stacked_barchart_2.png – An image of the chart in Q1.c after filtering data for Max.Players = 4
Note: Your Tableau workbooks will not be graded. Your images should be clear and of high resolution.
Q2 [15 points] Force-directed graph layout
You will experiment with many aspects of D3 for graph visualization. To help you get started, we have provided the graph.html file (in the Q2 folder) and an undirected graph dataset of boardgames, board_games.csv file (in the Q2 folder). The dataset for this question had inspiration from this post on reddit network visualization using boardgames in which the author calculates the similarity between board games based on categories and game mechanics where the edge value between each board game (node) is the total weighted similarity index. This dataset has been modified and simplified for this question and does not fully represent actual data found from this post. The provided graph.html file will display a graph (network) in a web browser. The goal of this question is to experiment with the visual styling of this graph. Here is a helpful resource (about graph layout) for this question.
Note: You are welcome to split graph.html into graph.html, graph.css, and graph.js. Make sure that all paths in your code are relative paths.
a. [2 points] Adding node labels: Modify graph.html to show the node label (the node name, i.e., the source) at the top right of each node in bold. If a node is dragged, its label must move with it.
b. [3 points] Styling edges: Style the edges based on the “value” field in the links array:
• If the value of the edge is equal to 0 (similar), the edge should be gray, thick, and solid.
• If the value of the edge is equal to 1 (not similar), the edge should be green, thin, and dashed.
c. [4 points] Scaling nodes:
Note: Regardless of which scale you decide to use, you should avoid extreme node sizes, which will likely lead to low-quality visualization (e.g., nodes that are mere points, barely visible, or of huge sizes).
2. [2 points] The degree of each node should be represented by varying colors. Pick a meaningful color scheme (hint: color gradients). There should be at least 3 color gradations and it must be visually evident that the nodes with a higher degree use darker/deeper colors and the nodes with lower degrees use lighter colors. You can find example color gradients at Color Brewer.
d. [6 points] Pinning nodes:
1. [2 points] Modify the code so that dragging a node will fix the node’s position such that it will not be modified by the graph layout algorithm (Note: pinned nodes can be further dragged around by the user. Additionally, pinning a node should not affect the free movement of the other nodes). Node pinning is an effective interaction technique to help users spatially organize nodes during graph exploration. The D3 API for pinning nodes have evolved over time. We recommend reading this post when you work on this sub-question.
2. [2 points] Mark pinned nodes to visually distinguish them from unpinned nodes, e.g., show pinned
nodes in a different color, border thickness or visually annotated with an “asterisk” (*), etc.
3. [2 points] Double clicking a pinned node should unpin (unfreeze) its position and unmark it. When a node is no longer pinned, it should move freely again.
e. Add GT username: Add your Georgia Tech username (usually includes a mix of letters and numbers, e.g., gburdell3) to the top right corner of the force-directed graph (see example image).
Q2 Deliverables:
The directory structure should be as follows:
Q2/
graph.(html / js / css)
board_games.csv
● graph.(html / js / css) – the html file created, and the js / css files (if you decide to save js and css in their own separate files)
● board_games.csv – the dataset
Q3 [15 points] Line Charts
Use the dataset provided in the file boardgame_ratings.csv (in the Q3 folder) to create line charts.
Refer to the tutorial for line chart here or here.
Note: You will create four charts in this question, which should be placed one after the other on a single HTML page, similar to the example image below (Figure 3). Note that your design need NOT be identical to the example.
● Horizontal axis label: Month. Use D3.scaleTime().
● Vertical axis label: Num of Ratings. Use a linear scale (for this part a).
b. [5 points] Adding board game rankings. Create a line chart (Figure 3b) for this part (append to the same HTML page) whose design is a variant of what you have created in part a. Start with your chart from part a.
Modify the code to visualize how the rankings of [‘Catan’, ‘Codenames’, ‘Terraforming Mars’, ‘Gloomhaven’] change over time by adding a symbol with the ranking text on their corresponding lines. Show the symbol for every three months, similar to the x-axis ticks in part a. (See Figure 3b). Add a legend to explain what this symbol represents next to your chart (See the Figure 3b bottom right).
■
First chart (Figure 3c-1)
■ Second chart (Figure 3c-2)
Q3 Deliverables:
The directory structure should be organized as follows:
Q3/ boardgame_ratings.csv linecharts.(html / js / css) linecharts.pdf
explanation.txt
● boardgame_ratings.csv – the dataset.
● linecharts.(html / js / css) – the html file created, and the js / css files (if you decide to save js and css in their own separate files).
● linecharts.pdf – a PDF document showing the screenshots of the four line charts created above (one for Q3.a, one for Q3.b and two for Q3.c). You should print the HTML page as a PDF file, and each PDF page shows one chart (hint: use CSS page break). Clearly title the charts as instructed (see examples in Figure 3). Make sure your Georgia Tech username that you added in the last chart (see example figure 3c-2) is shown in this PDF document.
● explanation.txt – the text file explaining your observations for Q3.c.
Q4 [20 points] Interactive Visualization
Use the dataset average-rating.csv provided in the Q4 folder to create an interactive frequency polygon line chart. This dataset contains a list of games, their ratings and supporting information like numbers of users who rated and year it was published. In the data sample below, each row under the header represents a game name, year, average rating, and number of users who rated the game. Helpful resource to work with nested data in D3: http://bl.ocks.org/phoebebright/raw/3176159/
name,year,average_rating,users_rated Codenames,2015,7.71148,51209
King of Tokyo,2011,7.23048,48611
All axes must start at 0, and their upper limits must automatically adjust based on the data. Do not hard-code the upper limits.
• The vertical axis represents the count of board games for a given rating. Use a linear scale.
• The horizontal axis represents the ratings. Use a linear scale.
b. [3 points] Line styling, legend, title and username.
• For each line, use a different color of your choosing. Display a filled circle for each rating-count data point.
• Display a legend on the right-hand portion of the chart to show how line colors map to years.
• Add your GT username (usually includes a mix of lowercase letters and numbers, e.g., gburdell3) beneath the title (see example figure 4b).
Interactivity and sub-chart. In the next few sub-questions, you will create event handlers to detect mouseover and mouseout events over each circle that you added in Q4.b.
Note: No bar chart should be displayed when the count of games is 0 for hovered year and rating.
Axes: All axes should be automatically adjusted based on the data. Do not hard-code any values.
• The vertical axis represents the board games. Sort the game names in ascending order, such that the game with the smallest users_rated is at the bottom, and the game with the highest users_rated is at the top. Some boardgame names are quite long. For each game name, display its first 10 characters (if a name has fewer than 10 characters, display them all). A space counts as a character. The horizontal axis represents the number of users who rated the game (for the hovered year and rating). Use a linear scale.
• Set horizontal axis label to ‘Number of users’ and vertical axis label to ‘Games’.
d. [3 points] Bar styling, grid lines and title
• Bars: All bars should have the same color regardless of year or rating. All bars for the specific year should have a uniform bar thickness.
• Grid lines should be displayed.
• Title: Display a title with the format “Top 5 Most Rated Games of <Year> with Rating <Rating>” at the top of the chart where <Year> and <Rating> are what the user hovers over in the line chart. For example, hovering over rating 6 in 2015, the title would read: “Top 5 Most Rated Games of 2015 with Rating 6”
e. [3 points] Mouseover Event Handling
• The bar chart and its title should only be displayed during mouseover events for a circle in the line chart.
• The circle in the line chart should change to a larger size during mouseover to emphasize that it is the selected point.
• When count of games is 0 for hovered year and rating, no bar chart should be displayed. The hovered-over circle on the line graph should still change to a larger size to show it is selected.
f. [3 points] Mouseout Event Handling
• The bar chart and its title should be hidden from view on mouseout and the circle previously mouseover-ed should return to its original size in the line chart.
The graph should exhibit interactivity similar to Figure 4f where the mouse is over the larger circle.
Q4 Deliverables:
The directory structure should be as follows:
Q4/
interactive.(html/js/css) average-rating.csv
● interactive.(html/js/css) – The HTML, JavaScript, CSS to render the visualization in Q4.
● average-rating.csv – The dataset of game information.
Q5 [25 points] Choropleth Map of Board Game Ratings
Choropleth maps are a very common visualization in which different geographic areas are colored based on the value of a variable for each geographic area. You have most probably seen choropleth maps showing quantities like unemployment rates for each county in the US, or the number of confirmed COVID-19 cases per 10,000 people at the county level.
We will use choropleth maps to examine the popularity of different board games across the world. We have provided two files in the Q5 folder, ratings-by-country.csv and world_countries.json.
• Each row in ratings-by-country.csv represents about a game’s information for a country, in the form of <Game,Country,Number of Users,Average Rating>, where o Game: the name of a game, e.g., Catan.
o Country: a country in the world e.g., United States of America. o Number of Users: the number of users who have rated Game who are from Country.
o Average Rating: the mean rating given to Game by users who are from Country. This dataset has been preprocessed and filtered to include only those games that have been rated by more than 1000 users in the world.
• The world_countries.json file is a geoJSON, containing a single geometry collection: countries. You can find an example of map generation using geoJSON here.
a. [20 points] Create a choropleth map using the provided data, and use Figure 5a and 5b as references.
1. [5 points] Dropdown lists are commonly used on dashboards to enable filtering of data. Create a dropdown list (see example in Figure 5a) to allow users to select which game’s data are displayed.
• The list options should be obtained from the Game column of the csv file.
• Sort the list options in alphabetical order. Set the default display value to the first option.
• Selecting a different game from the dropdown list should update both the choropleth map (see part 2) and the legend (see part 3) accordingly.
2. [10 points] Load the data from ratings-by-country.csv and create a choropleth map such that the color of each country in the map corresponds to the average rating of the game selected in the dropdown in each country.
Promise.all() is provided within the skeleton code and you can use it to read in both the world json file and game data csv file. Example usage can be seen here.
Many countries have no ratings for some games – these should be colored grey.
For those countries that do have ratings for the selected game, use a quantile scale to generate the color scheme based on the average rating by country. Color them along a gradient of exactly 4 gradations from a single hue, with darker colors corresponding to higher rating values and lighter colors correspond to lower values (see gradient examples at Color Brewer).
About Scaling Colormaps: In order to create effective visualizations that highlight patterns of interest, it is important to carefully think about the relationship between the range and distribution of values being displayed (the domain) and the color scale the values are mapped to (the range). Many types of mapping functions are possible, e.g., we could use a linear mapping where the lowest game rating is mapped to the first value in the color scheme, the highest game rating is mapped to the highest value in the color scheme, and intermediate ratings are mapped to hues in the middle. This article illustrates the value of choosing appropriate endpoints for linear color maps, or log-scaling the domain so that large but relatively infrequent values do not cause differences between smaller values to be washed out. In our case, most board games have similar average ratings across countries, e.g. Catan has an average rating close to 9.3 in almost all countries, making it challenging to perceive relative differences in popularity. To address this, we can compute quantiles of the domain data—game rating values that divide the ordered list of average ratings per country into roughly equally-sized groups. Here, we will get 4 groups, a special case of quantiles called
“quartiles” since the data are divided into quarters.
Hint: You can verify the correctness of the quartiles generated by using the ‘quartile’ function in Excel. Open ratings-by-country.csv and filter the data for one game (say Catan). Then use the quartile function to get the 0th, 1st, 2nd, 3rd and 4th quartile values from the Average Rating column. Here [0th quartile, 1st quartile], [1st quartile, 2nd quartile], [2nd quartile, 3rd quartile], [3rd quartile, 4th quartile] will represent the 4 groups of values generated by the d3 quantile scale.
3. [5 points] Add a vertical legend showing how colors map to the average rating for a particular game. The legend must update for the quartiles of the selected game, and display values formatted to show precision up to 2 decimal places. You must use exactly 4 color gradations in your
submission. It is recommended, but not required, to use d3-legend.min.js (in the lib folder) to create the legend for the scale you use. Also, display your GT username (e.g., gburdell3) beneath the map.
b. [5 points] Add a tooltip using the d3-tip.min library (in the lib folder). On hovering over a country, the tooltip should show the following information on separate lines:
• Country name
• Game
• Avg Rating for that game in that country (Figure 5b demonstrates this for Catan)
• Number of Users from the country who rated the game
For countries with no data, the tooltip should display “N/A” for Avg Rating and Number of Users.
Note: You must create the tooltip by only using d3-tip.min.js in the lib folder.
Note about skeleton:
• It is optional for your visualization to show (or not show) Antarctica.
Q5 Deliverables:
The directory structure should be organized as follows:
Q5/
choropleth.(html/js/css) ratings-by-country.csv world_countries.json
● choropleth.(html /js /css)- The html/js/css file to render the visualization.
● ratings-by-country.csv – The datasets used to show the information of each state. ● world_countries.json – Dataset needed to draw the map.
Extremely Important: folder structure & content of submission zip file
You are submitting a single zip file HW2-GTusername.zip (e.g., HW2-jdoe3.zip).
The files included in each question’s folder have been clearly specified at the end of the question’s problem description.
The zip file’s folder structure must exactly be (when unzipped):
HW2-GTUsername/ lib/ d3.v5.min.js d3-tip.min.js
d3-geo-projection.v2.min.js d3-dsv.min.js d3-legend.min.js topojson.v2.min.js Q1/ table.png grouped_barchart.png stacked_barchart_1.png stacked_barchart_2.png Q2/
graph.(html / js / css) board_games.csv
Q3/
linecharts.(html / js / css) linecharts.pdf boardgame_ratings.csv explanation.txt Q4/
interactive.(html / js / css) average-rating.csv Q5/
choropleth.(html / js / css) ratings-by-country.csv world_countries.json
