编程与软件工程toddwschneider.com
分析 11 亿次纽约出租车与 Uber 行程
Analyzing 1.1B NYC Taxi and Uber Trips
2015 — 2018，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
作者用 Postgres/PL/pgSQL 分析了纽约市出租车与 Uber 共约 11 亿条行程数据，涵盖 2009 年以来的出租车数据及 2014-2015 年的 Uber 数据，并绘制出纽约夜间上车热点地图。文章还对比了出租车与 Uber 在不同街区的接单分布，展示了大数据分析在交通研究上的应用。
为什么经久不衰：它把海量公开交通数据变成了可复现的分析和可视化，既是数据工程的经典案例，也记录了 Uber 改变纽约街头的前夜，多年后仍是学习城市数据分析的好素材。
HN 评论精选
提供了复现可视化的教程，并建议用 BigQuery 避免下载 300GB 数据
昨天我发了一篇用 ggplot2 复现这张纽约地图可视化的教程。作者的代码与我独立采用了相似的方法和工具，但结果略有不同，这正是有趣之处。另外，今年 8 月时 TLC 只发布了 2014 和 2015 年的数据，不清楚为何现在补发了 2009-2012 年的。如果只是想玩玩数据，我推荐用 BigQuery，因为下载处理约 300GB 数据要花不少时间。
minimaxir查看英文原文
Yesterday, I made a post about how to reconstruct the NYC map visualization using the 1.1B Taxi Data using ggplot2: http://minimaxir.com/2015/11/nyc-ggplot2-howto/ Looking at the code for the visualization, the author did an independently similar approach (with the same tools), and one that turned out slightly different, which is what makes things interesting. It's worth nothing that back in August, only the 2014 and 2015 datasets were released by the NYC TLC. I'm not entirely sure why they decided to release 2009-2012 now. If you're looking to just playing with the data, I recommend using the BigQuery approach as noted in my article, since downloading and processing ~300GB might take awhile. However, the shape file approach used in the original article the next logical step after that, and one that is put to very good use in the article.
数据可反映新商家对周边夜间出行的影响，城市机构可借此做决策
能否从深夜数据中看出新开业商家带来的上车量激增？Williamsburg 的 N 11th St 街区之所以亮红，主要是因为一家酒店/餐厅和两家很火的电子音乐俱乐部开业。城市机构能否利用这种数据反馈环来评估商家对街区的影响，比如酒类执照审批或 MTA 规划？
apaprocki查看英文原文
Can spikes be seen in the late-night data when new businesses open around the pickup address? In the Williamsburg section, the reason why the N 11th St block area is bright red in the observation is mostly due to the opening of a hotel/restaurant and two very popular electronic music clubs. Prior to those 3 businesses opening I can't think of any reason why anyone would be in that 1 block area late at night. Is there anything city agencies could do with this feedback loop of data after businesses open to assess their impact on an area? Liquor licenses? MTA?
下车数据缺失反而保护了隐私，因为这类数据很容易被去匿名化
很高兴 Uber 没有发布下车数据。在这种数据集里，对某人去匿名化并不难。
superuser2查看英文原文
I'm happy to see that Uber is not releasing dropoff data. It's not terribly difficult to de-anonymize someone in a dump like this.
Uber 对纽约街头车流格局的改变肉眼可见、不容否认
在 Uber 出现前后都住过纽约，曼哈顿交通的变化令人震惊。如果把 2006 年的曼哈顿人传送到 2016 年，他会对街上大量非黄色出租车感到震惊。无论你怎么看待 Uber 这家公司，它对纽约街面的影响是不可否认的。
MattRogish查看英文原文
Having lived in NYC pre-and-post Uber, the difference in Manhattan traffic is astonishing. Manhattan 2006: http://www.shutterstock.com/video/clip-2475317-stock-footage-new-york-ny-circa-march-looking-down-a-manhattan-street-it-is-easy-to-see-why-the-yellow.html Manhattan now(ish): http://cdn.newsday.com/polopoly_fs/1.12078243.1469201706!/httpImage/image.jpg_gen/derivatives/landscape_1280/image.jpg If you were to teleport a Manhattanite from 2006 to 2016 I think they'd be shocked to see the large number of non-yellow cabs on NYC streets. Regardless of how you feel about Uber-the-entity, the mark it's made on NYC streets is undeniable.
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