4 ms·

Lots of people defending box plots here -- a lot more than I expected! What I don't see is anyone saying "box plots are useful because they're the best kind of

Lots of people defending box plots here -- a lot more than I expected! What I don't see is anyone saying "box plots are useful because they're the best kind of chart for [specific use case]". I can't off-hand think of any situation where I'd rather see a box plot than a strip plot or violin plot. When and why would you want to summarise the data so coarsely and visualize it so un-intuitively?

lkdfjlkdfjlg 2y ago
> What I don't see is anyone saying "box plots are useful because they're the best kind of chart for [specific use case]". Box plots are useful because they're the best kind of chart for when I have multiple populations and I want to quickly glance whether it's reasonable to assume that the populations have the same median, or not (you do that comparing not just the medians of the populations but also the shaded areas)
- johnbcoughlin 2y ago
  I can't see why a jitter plot with dark lines marking the quartile wouldn't be strictly better for this.
  - aniviacat 2y ago
    That's just a box plot with extra steps. Sure, the jitter plot provides more data, but if you only make use of the quartiles anyway, that extra data is but an unnecessary distraction.
- weebull 2y ago
  If you're only comparing medians, then just plot the medians. Why a box plot with the quartiles?
  - lkdfjlkdfjlg 2y ago
    Ok, so the difference between medians is 42.7. Is that a lot or a little?
DonsDiscountGas 2y ago
Violin plots are massively overhyped, IMHO. If your data is simple and unimodal, use a boxplot. If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information.
- inciampati 2y ago
  They really help when you're working with huge numbers. It's just a different kind of density plot. A vertical histogram can be nice too. Or you can use color and overlay a few regular old histograms. Go wild.
  - parpfish 2y ago
    Overlaid histos can be confusing because people don’t know if they are stacked or overlapped. One solution is to smooth into a kde and then use transparency to indicate overlap, but that’s introducing more complexity than you want for a quick n dirty first pass
- weebull 2y ago
  > If your data is simple and unimodal, use a boxplot. How is the reader to know you've used the right plot? How are they to know that you haven't hidden a bimodel dataset behind a box plot because it makes your conclusions easier? > If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information. They are just multiple, non-overlapping histograms plotted next to each other. They allow you to compare distributions without them getting in the way of each other. I can understand if it's the fitted PDF that you think hides the original data. That is unnecessary IMHO.
kaitai 2y ago
I deal with a lot of business people who have processes that rely on 15th/85th percentile, or 25th/75th percentile. They want to see the median, the low/high percentiles, the max/min or outliers, and they don't want to see all the data points jittered in between. It's just overwhelming extraneous information. They in fact like tables with those numbers written down, but they want to compare ten different (time series of historical prices for different markets) and see it on one Powerpoint slide. The box plot allows a fast visual comparison of medians and other key percentiles (label the plot with the percentiles if you're doing something non-standard!). With jitter or violin they get hung up on weird random stuff and it derails meetings. Important caveats: the generating processes for all these quantities are the same in a physical sense, so they are comparable. All the distributions are roughly lognormal-ish, so they are single-peaked distributions, as folks are discussing here. The point of the visualization in theses cases is not to understand the properties of the distribution per se, it's to show the important percentiles because they have business implications.
- iainmerrick 2y ago
  That’s a good explanation, thank you!
- callalex 2y ago
  Who drew those boundaries at 15/85? What makes those boundaries useful or correct?
  - s1artibartfast 2y ago
    It sounds like they are business relevant parameters. They are self selected and independent of the data or distribution. The point is that they are parameters of relevance to observer. I work in medicine sometimes work with box-plots for this reason. The questions "what is the 25th percentile outcome" is perfectly legitimate
s1artibartfast 2y ago
>When and why would you want to summarise the data so coarsely and visualize it so un-intuitively? Sometimes less is more; Box plots are specifically good for showing and comparing quartiles. If you want to compare several groups and care about gross differences, they are an excellent tool. They are an excellent to when you believe the data is normal and think the histogram is misleading. they are also great if you think the data isnt normal but care about quartiles. Any time you would be happy with a table of the 5 datapoints (min, max, median, 25th, and 75th percentiles), box plots a great tool for graphic comparison.

lkdfjlkdfjlg 2y ago

> What I don't see is anyone saying "box plots are useful because they're the best kind of chart for [specific use case]". Box plots are useful because they're the best kind of chart for when I have multiple populations and I want to quickly glance whether it's reasonable to assume that the populations have the same median, or not (you do that comparing not just the medians of the populations but also the shaded areas)

johnbcoughlin 2y ago
I can't see why a jitter plot with dark lines marking the quartile wouldn't be strictly better for this.
- aniviacat 2y ago
  That's just a box plot with extra steps. Sure, the jitter plot provides more data, but if you only make use of the quartiles anyway, that extra data is but an unnecessary distraction.
weebull 2y ago
If you're only comparing medians, then just plot the medians. Why a box plot with the quartiles?
- lkdfjlkdfjlg 2y ago
  Ok, so the difference between medians is 42.7. Is that a lot or a little?

DonsDiscountGas 2y ago

Violin plots are massively overhyped, IMHO. If your data is simple and unimodal, use a boxplot. If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information.

inciampati 2y ago
They really help when you're working with huge numbers. It's just a different kind of density plot. A vertical histogram can be nice too. Or you can use color and overlay a few regular old histograms. Go wild.
- parpfish 2y ago
  Overlaid histos can be confusing because people don’t know if they are stacked or overlapped. One solution is to smooth into a kde and then use transparency to indicate overlap, but that’s introducing more complexity than you want for a quick n dirty first pass
weebull 2y ago
> If your data is simple and unimodal, use a boxplot. How is the reader to know you've used the right plot? How are they to know that you haven't hidden a bimodel dataset behind a box plot because it makes your conclusions easier? > If the distribution is more complicated and you need some detail, use a histogram or a ridge plot. Violin plots are never the best option; they're curvy so a little more pretty but don't do a good job of conveying information. They are just multiple, non-overlapping histograms plotted next to each other. They allow you to compare distributions without them getting in the way of each other. I can understand if it's the fitted PDF that you think hides the original data. That is unnecessary IMHO.

kaitai 2y ago

I deal with a lot of business people who have processes that rely on 15th/85th percentile, or 25th/75th percentile. They want to see the median, the low/high percentiles, the max/min or outliers, and they don't want to see all the data points jittered in between. It's just overwhelming extraneous information. They in fact like tables with those numbers written down, but they want to compare ten different (time series of historical prices for different markets) and see it on one Powerpoint slide. The box plot allows a fast visual comparison of medians and other key percentiles (label the plot with the percentiles if you're doing something non-standard!). With jitter or violin they get hung up on weird random stuff and it derails meetings. Important caveats: the generating processes for all these quantities are the same in a physical sense, so they are comparable. All the distributions are roughly lognormal-ish, so they are single-peaked distributions, as folks are discussing here. The point of the visualization in theses cases is not to understand the properties of the distribution per se, it's to show the important percentiles because they have business implications.

iainmerrick 2y ago
That’s a good explanation, thank you!
callalex 2y ago
Who drew those boundaries at 15/85? What makes those boundaries useful or correct?
- s1artibartfast 2y ago
  It sounds like they are business relevant parameters. They are self selected and independent of the data or distribution. The point is that they are parameters of relevance to observer. I work in medicine sometimes work with box-plots for this reason. The questions "what is the 25th percentile outcome" is perfectly legitimate

s1artibartfast 2y ago

>When and why would you want to summarise the data so coarsely and visualize it so un-intuitively? Sometimes less is more; Box plots are specifically good for showing and comparing quartiles. If you want to compare several groups and care about gross differences, they are an excellent tool. They are an excellent to when you believe the data is normal and think the histogram is misleading. they are also great if you think the data isnt normal but care about quartiles. Any time you would be happy with a table of the 5 datapoints (min, max, median, 25th, and 75th percentiles), box plots a great tool for graphic comparison.