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HouseVis M2 Report & Presentation October 19, 2016 1 Project - - PowerPoint PPT Presentation
HouseVis M2 Report & Presentation October 19, 2016 1 Project - - PowerPoint PPT Presentation
HouseVis M2 Report & Presentation October 19, 2016 1 Project description 2 A design study Analyze and understand the U.S. House of Representatives. Data set: roll call data of the 108th Congress for House bills and 439 Representatives.
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A design study
Analyze and understand the U.S. House of Representatives. Data set: roll call data of the 108th Congress for House bills and 439
- Representatives. (2003 & 2004.)
Figure 1: Emblem
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Team
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Who we are
Apostolos Papadopoulos 1125972 a1125972@unet.univie.ac.at Anastasios Mangelis 1227902 a1125972@unet.univie.ac.at Website: http://wwwlab.cs.univie.ac.at/~a1125972/vis/ Github repo: https://github.com/VDA-Vis2016/HouseVis-project
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House of Representatives?
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What’s Congress?
House: one of the two chambers in the Legislative branch.
- Debate, write, & make laws.
- 435 Members, 1 for each district.
- Also known as Representatives.
- Workload distributed in committees.
- Serve 2 year terms.
Second chamber: the Senate. Senators represent their home state and serve 6 year terms. Same duties.
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What’s Congress?
Figure 2: Energy & Commerce Committee
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HouseVis
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Charts
The roll call data from the 108th Congress (pertaining only to the House of Representatives votes) is in the following format: Bill ID CQ # Year Month Day Bill Title
- Rep. Name
HRES 5 4 2003 JANUARY 7 “On Agreeing to (…)” BACHUS Party State State Code CD # Vote REPUBLICAN ALABAMA 41 6 YEA
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Charts
Non-contiguous cartogram
- 1. Plot districts and Representatives;
- 2. plot Yeas for bills related to X1 subject per district level;
- 3. plot Nays for bills related to X1 subject per district level.
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Charts
Figure 3: Non-contiguous cartogram
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Charts
Streamgraph/histograph
- 1. Plot yearly frequency of overall voting (date when bill was voted;)
- 2. plot bill subject frequency (eg: approprations and budget bills based
- n the date voted;)
- 3. plot overall frequency of bills passing the House (“work done factor.”)
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Charts
Figure 4: Streamgraph/histogram
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Charts
Calendar
- 1. Plot yearly frequency of voting.
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Charts
Figure 5: Calendar
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Charts
Treemap
- 1. Plot bill subject / category distribution.
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Charts
Figure 6: Treemap
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Charts
Partition
- 1. Plot state delegations sizes or S or HRes bill distribution.
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Charts
Figure 7: Partition
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Charts
Bubble chart
- 1. Plot vote frequency by each Representative (the bigger a bubble the
more votes casted.)
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Charts
Figure 8: Bubble chart
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Missing chart
Figure 9: Hierarchal edge bundling
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Mockup
Figure 10: Dashboard mockup
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Use cases
Typical user: journalism, data science and visualization, policy analysts, political scientists, strategists, chief of staffs and legislative staffers, and anyone else who might be interested in legislative arcana. In-depth look in congressional data. Tasks include “consuming” the visualizations and playing with the interactions between certain charts.
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Users
Who: John Appleseed, 21 years old, Political Science & CS student, future campaign operative Why: As a political science and computer science student, John is very much into analyzing current affairs with an analytical approach. With HouseVis he can study how Representatives from different parties & ideologies vote over time. How: Using most of the charts and with the interactivity tools, John can deduct how a particular district and its Rep. behave. Then, he can target ad spending during the campaign on specific issues based on Rep’s vote record.
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Users
Who: Nate Silver, 35 years old, Journalist Why: As a journalist, Nate analyzes and covers current affairs and Congress. Using data, Nate, uncovers unseen before perspectives of Congressional
- behavior. Nate can understand and write how different policy subjects
evolve over time. How: Using most of the charts and with the interactivity tools, Nate can deduct how a particular subject and its voting records behaves over time. He can see vote distributions over party, date, subject, and state.
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Implementation details
- Tableau instead of D3
- Python as data manipulation & exploratory environment
- Git
Goal: powerful, with minimal engineering overhead, functional tools. But: given enough time, we can port back to D3!
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Milestones
Duration Apostolos Anastasios Data expl. Data expl. 1-2 Data prep. Data prep. 3-5 Tableau Tableau (+2-3) Port D3 Port D3 6 Finalize web Finalize web
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Task distribution for M2
Apostolos Anastasios mockups mockups report/slides website
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References
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Some resources
- 1. D3 Gallery https://github.com/d3/d3/wiki/Gallery
- 2. Roll Call Data http://hci.stanford.edu/courses/cs448b/
data/108thHouse/108thHouseReadme.txt
- 3. GovTrack.us https://www.govtrack.us
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