David McCormick
@dsmccormick.bsky.social
Neophyte #rstats practitioner; infographic #datavis aesthete; cyclist; dog lover
However when I see colleagues using Excel pivot tables for reports that they have craft repeatedly, it pains me deeply.
November 4, 2025 at 10:44 PM
However when I see colleagues using Excel pivot tables for reports that they have craft repeatedly, it pains me deeply.
For me it depends on the situation. I will use a pivot table in Excel for some quick and dirty, one off analysis. But in R I tend to use the tidy pivot functions when I’m formatting things to do repeatable analyses where there is natural groupings.
November 4, 2025 at 10:43 PM
For me it depends on the situation. I will use a pivot table in Excel for some quick and dirty, one off analysis. But in R I tend to use the tidy pivot functions when I’m formatting things to do repeatable analyses where there is natural groupings.
That’s the second time I’ve read the post you link to and it’s honestly one of the funniest things I’ve ever read. So on the money.
November 1, 2025 at 2:42 AM
That’s the second time I’ve read the post you link to and it’s honestly one of the funniest things I’ve ever read. So on the money.
I love that you did that for your friend. The generosity of this community is inspiring.
October 27, 2025 at 2:18 AM
I love that you did that for your friend. The generosity of this community is inspiring.
@libbyheeren.bsky.social that looks very promising. I have never seen missing data visualization like that before. Thank you very much.
October 13, 2025 at 10:21 PM
@libbyheeren.bsky.social that looks very promising. I have never seen missing data visualization like that before. Thank you very much.
I have not. I will check that out. Thanks for the suggestion.
October 13, 2025 at 4:43 PM
I have not. I will check that out. Thanks for the suggestion.
2/2 Is there an effective way to portray the fraction of hours that have values? I tried using alpha = fraction of hours, but it looks too muddy.
October 13, 2025 at 2:38 PM
2/2 Is there an effective way to portray the fraction of hours that have values? I tried using alpha = fraction of hours, but it looks too muddy.
What? Mind blown. Did not know that.
October 1, 2025 at 5:18 PM
What? Mind blown. Did not know that.
That is just so lovely and clever for the crane dataset. Bravo!
October 1, 2025 at 3:13 PM
That is just so lovely and clever for the crane dataset. Bravo!
The effect is subtle but does make the contrast more obvious. I wonder what shifting the minimum x to March or April would look like: that might make the length of the lowest levels more striking. The wrap-around in the middle of the lows breaks it up visually.
August 26, 2025 at 10:43 AM
The effect is subtle but does make the contrast more obvious. I wonder what shifting the minimum x to March or April would look like: that might make the length of the lowest levels more striking. The wrap-around in the middle of the lows breaks it up visually.
Very nice dataset. If this doesn’t use it, would you consider using one of the viridis family of perceptually uniform color scales for this? See cran.r-project.org/web/packages... for example. The turbo color scale might do the trick.
Introduction to the viridis color maps
cran.r-project.org
August 25, 2025 at 4:08 PM
Very nice dataset. If this doesn’t use it, would you consider using one of the viridis family of perceptually uniform color scales for this? See cran.r-project.org/web/packages... for example. The turbo color scale might do the trick.
The left convention is what we expect to see as a left-to-right reading language. But it wouldn’t hurt to have it on both left and right. I would be surprised to see y-axis annotation on the right only.
July 28, 2025 at 1:56 AM
The left convention is what we expect to see as a left-to-right reading language. But it wouldn’t hurt to have it on both left and right. I would be surprised to see y-axis annotation on the right only.
I think Positron will have a particular niche in the data analysis world, since it is data-centric, not code-centric. Also, there are tools that Posit are building for LLM that will allow the context of the data you are analyzing to be part of the queries, so that it understands your data.
July 5, 2025 at 1:59 AM
I think Positron will have a particular niche in the data analysis world, since it is data-centric, not code-centric. Also, there are tools that Posit are building for LLM that will allow the context of the data you are analyzing to be part of the queries, so that it understands your data.
@juliasilge.com that was a brilliant tutorial. Loved it. Thanks for the clever use of the dataset to learn poisson regression.
June 6, 2025 at 5:15 PM
@juliasilge.com that was a brilliant tutorial. Loved it. Thanks for the clever use of the dataset to learn poisson regression.
Is what you are trying to express a time lag between, arrival, admission, and subsequent specialist interaction? Are there distributions of time lags by time of day? day of week? Is there a time lag distribution that you could visualize? Could you group by day of week and show the distributions?
May 22, 2025 at 12:13 AM
Is what you are trying to express a time lag between, arrival, admission, and subsequent specialist interaction? Are there distributions of time lags by time of day? day of week? Is there a time lag distribution that you could visualize? Could you group by day of week and show the distributions?
…so I think that would have been helpful to point out, because I was scratching my head with the dataframe example for a couple of minutes, until I read the sample() documentation and saw you can provide *an integer*, vector, or other type to the function.
May 21, 2025 at 4:24 PM
…so I think that would have been helpful to point out, because I was scratching my head with the dataframe example for a couple of minutes, until I read the sample() documentation and saw you can provide *an integer*, vector, or other type to the function.
Thanks for the random sampling post. I think there is a subtlety to sample() that you didn’t explain, namely that if you invoke sample(n, num_samples), will get random samples of an integer vector from 1:n. That’s how your dataframe sampling trick works with nrow(df), which is an integer.
May 21, 2025 at 4:21 PM
Thanks for the random sampling post. I think there is a subtlety to sample() that you didn’t explain, namely that if you invoke sample(n, num_samples), will get random samples of an integer vector from 1:n. That’s how your dataframe sampling trick works with nrow(df), which is an integer.
And I thought of the great Jon Bon Neumann quote: “Anyone who attempts to generate random numbers by deterministic means is, of course, living in a state of sin.”
May 19, 2025 at 3:58 PM
And I thought of the great Jon Bon Neumann quote: “Anyone who attempts to generate random numbers by deterministic means is, of course, living in a state of sin.”
That was a complete tour de force of yak shaving.
May 19, 2025 at 3:57 PM
That was a complete tour de force of yak shaving.
Thanks for pointing that out. I think the axis rescaling by facet_wrap() made the log scaled axis too cluttered. I’ll have to find a workaround.
May 7, 2025 at 12:25 PM
Thanks for pointing that out. I think the axis rescaling by facet_wrap() made the log scaled axis too cluttered. I’ll have to find a workaround.
…but I was really trying to get rid of the *text* labels for minor breaks.
May 5, 2025 at 6:28 PM
…but I was really trying to get rid of the *text* labels for minor breaks.