Visualizing data that is highly skewed is tricky because most points get overshadowed. To fix that, try using a log scale.
Here’s an example of a skewed data set. Total votes for each presidential candidate in the 2020 election:
As you can see, once you get past the two main presidential candidates, you can’t see the bars for anybody else.
To solve for that, change the scale to a log scale. A log scale will essentially shrink the range. The scale grows by a factor of 10 and that’s how you get a more even distribution. So the scale for a log chart will go from 1 to 100 to 10,000 to 1,000,000. Each window is given an equal weight which allows for a smoother chart.
The data above was visualized using Plotly and aggregated using Kaggle. You can check out the notebook by clicking on the link.
Thanks for reading!