kldavenport

Am I the only one with memories of clicking it over and over again: "eep!,eep!,eep!,eep!,eep!"?

Is Shimano doing this because SRAM (a competitor) bought Hammerhead? Makes me skeptical we will ever see Shimano STEPS battery % and mode on the Hammerhead. Hammerhead sells an Android powered bike computer with a great set of features and UX compared to the legacy brands that have dominated the market forever (Garmin, Bryton, Wahoo).

So far it looks to have a better web and mobile interface than postmates and grubhub.

Pricing looks competitive https://aws.amazon.com/efs/pricing/ I wonder if this helps those who perceive S3 as vendor lock-in since it replicates a traditional file system.

This was my experience as well. It was refreshing.

A fantastic set of APIs with Matplotlib under the hood: Seaborn

Http://stanford.edu/~mwaskom/software/seaborn/

seaborn, bokeh, pandas' built in methods, and plotly fill in the ggplot gap for me.

Amazon's UX designers feel the same way. G+'s card layout does not make it easy to infer what's the latest vs the most commented on item and what the logic is behind it's positioning laterally. I think basic gestalt principles in cognitive science would support the problem with laterally adjacent but vertically edge overlapping tile placement.

The homeless have moved back into the I-5 Colonnade and the proximity of Duthie Hill leads most people away from the city for their rides.

Glad they added .query() to Pandas in .13. In general I find the methods in Pandas/NumPy much more consistent with general programming constructs than most of what I see in R. No doubt Hadley has bolted on a lot of great functionality to R, but the Rcpp dependency/GPL license is a turn off.

Another great piece from n+1.

Is this better or similar to Hue?

n+1 produces quality articles, check out http://nplusonemag.com/bad-education

Looks like he won't have to worry about working for a living anymore...

Check out the Python JIT compiler NUMBA. It compiles annotated Python and NumPy code to LLVM (through decorators). It's been wicked fast for my use cases: http://numba.pydata.org/

Their use case didn't seem especially Mongo-centric, I wonder why they chose to go down the road. We used MongoDB TokuMX to improve performance: http://www.tokutek.com/resources/benchmark-results/tokumx-be...

Joe Cheng and the rest of the team at RStudio have done an excellent job with this. It allows a statistician to spend their time on scripting the analysis instead of web development. Combine this with knitr/pandoc and you have a great toolkit.

CogSci depending on the school.

What about R?

It's hard to find a BI solution that has kept up with all the pure analytics platforms. I'm really interested in what RStudio is doing with Shiny.