# The way Gadfly chooses ticks leads to ugly plots very often?

**URL:** <https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328>\
**Category:** Visualization\
**Tags:** gadfly\
**Created:** [June 14, 2023, 12:39pm UTC](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328 "2023-06-14T12:39:59Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![nsajko](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nsajko/32/221187_2.png) [@nsajko](https://discourse.julialang.org/u/nsajko)\
**Post date:** [June 14, 2023, 12:39pm UTC](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328/1 "2023-06-14T12:39:59Z")

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There’s an experiment for evaluating the claim in the title [here](https://gitlab.com/nsajko/gadfly_ugly_ticks). See the readme, and the SVG plots, viewable directly there (in the browser, on Gitlab).

My conclusion was that a very large percentage of these random Gadfly plots of polynomials over random intervals are ugly, stemming from Gadfly’s bad choices of x-axis ticks (I only evaluated the beauty over the x-axis).

I wonder how representative my tastes are.

Poll for my “issue 1”:

_Poll ([view on site](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328/1))_

Poll for my “issue 2”:

_Poll ([view on site](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328/1))_

General poll:

_Poll ([view on site](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328/1))_

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<div class="post-metadata">

**Author:** ![nsajko](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nsajko/32/221187_2.png) [@nsajko](https://discourse.julialang.org/u/nsajko)\
**Post date:** [June 14, 2023, 2:13pm UTC](https://discourse.julialang.org/t/the-way-gadfly-chooses-ticks-leads-to-ugly-plots-very-often/100328/2 "2023-06-14T14:13:10Z")

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I notice that providing `Stat.xticks(coverage_weight = 7/8)` to `plot` fixes most or all of these issues. Perhaps the default should be changed?