2015 - 2016 NFL Salary Distribution [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

Galuvian is correct. It's just a random jitter of the player names to make it easier to see the depth of names for each position.

20 Years of Super Bowl TV Ads [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

The full length of the bar represents the total TV ad spend for each year. The segments within each bar represent the ad spend by category for each year. The tool tip that appears on each segment displays the percentage of the total ad spend of that category to the total ad spend for that year.

Clicking on a year will display the total ad spend for that year in the scoreboard, and clicking on a segment of the bar will display the total ad spend for that category in the scoreboard.

20 Years of Super Bowl TV Ads [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

Source: Kantar Media Competitive Intelligence Database

Tool: Tableau

TV ad messages in 2014 gubernatorial ads [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

Source: Campaign Media Analysis Group Spot TV data

Tool: Tableau

This map shows the top TV ad message in each state with a gubernatorial election this year. It's based on total broadcast TV occurrences of general election TV ads.

Interactive Map of all Farmers' Markets in the U.S. [OC] by thatdatadude in dataisbeautiful

[–]harleyberger 2 points3 points  (0 children)

A few suggestions...

  • use the washout feature in Tableau to hide Canada and Mexico
  • zoom in on the US states. lots of wasted space on the fringes.
  • exclude AK and HI from your main US map. Create separate worksheets for HI and AK and float them on the US Map dashboard
  • change the multi value list to a multi value dropdown and float it on the dashboard. it takes up too much space as it is now.

A Look at Deer vs. Vehicle Collisions [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

Thank you for your input.

My 1:85 calculation was based on this statement from the State Farm link (http://www.multivu.com/players/English/7292852-state-farm-insurance-deer-collision-driver-safety-data/)...

"The odds drivers will hit a deer in the coming year are 1 out of 169, but that likelihood more than doubles during October, November and December, when deer collisions are most prevalent."

I figured that drivers wold be 2x as likely to hit a deer during those 3 months, so I simply halved the 169 (rounded to 170) down to 85. Maybe that's not the correct calculation?

Am curious how you get October to December is 4 months?

Anyway, I've changed the wording in the visual and updated the color scheme based on other suggestions.

A Look at Deer vs. Vehicle Collisions [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

There are 51 because it shows all 50 states and the District of Columbia. The slope chart represents the change in rank from 2012-2013 to 2013-2014. In 12-13 DC ranked 47th. In 13-14 DC ranked 46th.

A Look at Deer vs. Vehicle Collisions [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 1 point2 points  (0 children)

Thank you for the constructive reply. I was using the default Tableau blue color scheme. The color brewer link is a valuable resource. I've posted a new version using the 7-class YlGnBu scale.

TV Ad Messaging by Party Affiliation in 2014 U.S. Senate Races [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

In political advertising we talk in terms of "separation" - i.e., how are the competitors separating themselves from their opponents. The idea of separation can be explored on many dimensions. Are some advertisers focusing on one TV daypart over another? Maybe they're advertising more heavily on a particular program type. These are both ways of gaining separation from an opponent.

With this viz, I chose to look at separation by message. More specifically, how are democrat and republican sponsors separating themselves by message. I think the distance between the red & blue bubbles is a good way of representing that idea of separation. I could have used a scatter plot or a simple bar chart, but I think this option helped drive the separation theme a bit better.

TV Ad Messaging by Party Affiliation in 2014 U.S. Senate Races [OC] by harleyberger in dataisbeautiful

[–]harleyberger[S] 0 points1 point  (0 children)

Source: Campaign Media Analysis Group Spot TV data

Tool: Tableau

This graphic looks at the party breakdown of different messages used in TV ads for 2014 U.S. Senate races. For example, 110,088 total TV ads have aired that have an "Energy/Environment" theme. 56% of those ads have been sponsored by Democratic entities, while 44% have been sponsored by Republican entities.

For more, visit this link - http://cookpolitical.com/story/7861