Peek into beauty

This graphic feature is the best from the NYT team yet. I particularly love the two columns on the right which allows us to see regional differences.  For example, this "New in Town" movie was much popular in Minneapolis than any of the other metropolitan areas, and was particularly unwatched in New York.  Also, note the choice of sorting allowed on the top right.

Click here and enjoy!

Reference: "A Peek into Netflix Queues", New York Times, Jan 10 2009.

Comments

[Poku]

Ignoring the data altogether, the thing that struck me with this one is just how fast the response time is... obviously related to the use of flash to overlay the map.

Compared to maps which make heavy use of the google maps API this makes it a joy to toy with, which really helps to make the data something worth exploring. Instead of the 'this is going to take ages to load' syndrome.

[jane]

Those were some awesome maps, I agree. Also, New in Town was about Minnesota, hence the high number of watchers in the Twin Cities area.

[Jeff Weir]

I'm not so admiring of this map. The use of rankings – instead of a more meaningful indicator such as rentals per capita – mean we miss out on valuable information, such as –
• How much more popular was one movie compared to another? Think of Avatar and it’s runner up (whatever movie that one will be)...this graph fails to show how much more successful Avatar would be vs. that runner up.

• How do rental rates vary among the different regions?

This graphic takes up so much real estate that I can’t help but wonder what better use this real estate could be put to in order to tell a more detailed, interesting, and useful story. And the colour bands that result from using only rankings rather than more comparitive measures mean it is hard to spot trends and outliers. Not to mention that the use of colour to encode information might not be the best approach in the first place...to quote from Stephen Few’s book Now you see it: “Color is good at drawing your attention to something if used sparingly, but is one of the ‘pre-attentive attributes’ that is not quantitatively perceived in and of themselves”.

And to quote from a guest blog post I wrote over at http://chandoo.org/wp/2009/07/24/medicare-chart-critique/ about another map-based graphic “Is a map the best way to present this data in the first place? If you want something for people to play with online, then maybe…but if you want to compare things very closely to other things, then maybe not. For sure, a Choropleth Map looks cool, and has “natural context”. But from an analytical perspective, a map only really reports how one thing changes with regards to geography. If geography is a major determinant – or if you want to show people how things look in their own back yard compared to others – then perhaps this is the piece of kit you need. But if there’s other factors that have much more sway on your data than geography, then perhaps not.”

[Jeff Weir]

It would be interesting to see correlations between types of movies rented and some socio-economic factors. Here an xy graph would really shine.

[Jeff Weir]

They also missed the chance to see how strongly rental rank was correlated with metascore (i.e. critical rank). The average metascore of the top 20 rentals was 59.85; compared to (gasp) 59 for the bottom 20 rentals.