RJC

Pink Limo (at San Francisco Jewelry Center)

5/21 Nationals vs Giants

West (at Top of Potrero Hill)

North Beach (at Little Italy)

Good to be back on the West Coast (at Under The Bay Bridge)

at AT&T Park

Quattro De Mayo

Someone else’s cards (at Zeitgeist)

“Over the next decade, Slam and Iverson shared a deeply symbiotic relationship, whereby the magazine would try to report what it felt was “real basketball,” which meant frequent trips to Rucker Park, interviews with J.R. Rider and Latrell Sprewell, and lots and lots of Iverson cover stories. “If the world was saying white, we wanted to say black,” Gervino continues. “We were dripping with idealism. We wanted the greater world — the people who watched basketball who didn’t like hip-hop, we wanted them to see a fearless guy who had come from nothing. We were trying to say that Allen Iverson was a hero to a generation.”

The new spot (at driggs and n 7th )

R.I.P. Big Pun by @Bawkwards

R.I.P. Nate Dogg by @bawkwards

Opening Day! (at Citi Field)

timcmclaughlin:

San Francisco Pelicans baseball

captain-d-o:

Williamsburg Bridge form the Brooklyn shore.  Such a calm night. 

“A Hard Day For Hubble” (at Under the Williamsburg Bridge (Brooklyn))

mapnostic:

Median Rent SF: One Bedroom Apartment Listings

Click the picture above to get to the map. It shows median rent for a one bedroom apartment in the second half of 2012. You can see the median rent for a San Francisco neighborhood, as well as the nuance of where the pricey stuff is clustered, plus what you *should* be making to live there, based on the assumption that rent is 1/3 of your income.

Here is why my analysis of devastatingly high housing prices in San Francisco is better than all the others that came out in the past two weeks:

1. I used a dataset that spans a longer time range than one month, so that the sample sizes per neighborhood are larger. My data spans the second half of 2012.

2. I filtered for duplicates, so that the same apartment listed multiple times does not skew the data.

3. I used median instead of mean, which makes sense when you are dealing with a lot of outliers. You should be suspicious every time you see some shocking statistic about the “average rent” in San Francisco. The high end skews things quite a bit.

4. The fact that I am even explaining my methods and assumptions.

5. Instead of a silly choropleth, I made a super-pretty heat map based on the spatial variability of listing prices. The interpolation is based on ordinary kriging, and I underlay it with contours to bring out the variation a bit more.

As with several previous projects, I designed this map in Tilemill and am hosting it via MapBox, and overlayed it on a hard working OpenStreetMap. For the raster processing I used ArcGIS and QGIS. The data was kindly donated by PadMapper.com.

Pop Quiz: Can you spot the new development in Bayview? What about the Tenderloin? Can you see where that is??

(via Instapaper)

(via Instapaper)

(via Instapaper)