Most scientists represent their quantifications as an average (plus standard deviation or standard error of the mean), however this doesn't tell the full story about the data. I prefer when the plot shows the individual data points and additionally depict averages (or even better medians). That way you get better insight into treatments' effects and whether they are due to few outliers or a shift in the whole population.
Here is an example of one of such graphs (Sung et al. 2016):
The problem with this graph is that while the distributions are quite well visible you can't really tell the averages with that use of black and white shades.
You can change that in multiple ways, for example:
I used two different shades of grey rather then white circles with black outline. I also made the average lines bolder so that they stand out better against the distribution data. Other changes to the figures include removing the x-axis and placing only the treatment conditions on it. The "control" and "park" labels are now in the upper right corner in the respective colors of the groups. All those changes are meant to remove the unnecessary ink and drive attention to the actual data.
This is just one of the options, you can also add extra bars in the background:
Or adding a color: