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by flowingdata on 2019-10-16 (UTC).

How commuting is too much? It depends on where you live. https://t.co/Zjsf3vlqwf pic.twitter.com/eIjAhzzxsS

— Nathan Yau (@flowingdata) October 16, 2019
dataviz
by seanjtaylor on 2019-10-19 (UTC).

I think this is an interesting topic but found this visualization hard to follow (no surprise if you've been reading my complaints about animated plots).

I have nothing to do tonight so i'm going to try to re-visualize this data. Starting a THREAD I'll keep updated as I go. https://t.co/aHl4S3L9iP

— Sean J. Taylor (@seanjtaylor) October 19, 2019
misc
by seanjtaylor on 2019-10-19 (UTC).

It's sadly not a CSV file, it's a "dat.gz" file and you need some XML schema file to read it in. In R you need the `ipumsr` package to actually load it (ughh). But about 10 mins later, I have a data frame! Game on. pic.twitter.com/Ip15Nxf6xV

— Sean J. Taylor (@seanjtaylor) October 19, 2019
misc
by seanjtaylor on 2019-10-19 (UTC).

Ok this is the one I'm going to end on.
- Cities are clearly ranked and listed in order.
- Divided it up into the important quantiles: 10th (shortest commutes), 25-75 (normal-ish range), and 90th (longest)
- Mean time is still visible (the dot), always higher than the median. pic.twitter.com/is7EZK9Ktp

— Sean J. Taylor (@seanjtaylor) October 19, 2019
dataviz
by flowingdata on 2019-10-22 (UTC).

I mapped when and where people start their commutes to go work in major cities. Here are the maps for the 3 busiest: Los Angeles, Chicago, and New York. https://t.co/JcDmCEJT47 pic.twitter.com/6WDgA3rTNK

— Nathan Yau (@flowingdata) October 22, 2019
dataviz

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