Why Some Charts Use Logarithmic Scales
Launch library · evergreen read
Most charts quietly assume that equal steps on the axis mean equal distances in the underlying reality, but some data grows so quickly that a standard axis squashes the small early values into an unreadable clump near the bottom. A logarithmic scale solves that problem by spacing values according to their ratio rather than their raw numerical difference.
On a properly built log scale, doubling always covers exactly the same visual distance, whether that jump happens to run from ten up to twenty or from a million up to two million instead. That consistency makes it far easier to compare genuine growth rates across wildly different sizes on a single, honest chart without one extreme value quietly dwarfing everything else around it.
The tradeoff is readability for anyone taking only a casual glance at the page. A log scale rewards a reader who properly understands what it is showing, but it can quietly mislead anyone who assumes the spacing works the same familiar way it does on an ordinary linear chart, which is exactly why a clear axis label matters so much here.