When using barplots, it is misinformative not to start the bars at 0. This is because, by using a barplot, we are implying the length is proportional to the quantities being displayed. By avoiding 0, relatively small differences can be made to look much bigger than they actually are. This approach is often used by politicians or media organizations trying to exaggerate a difference. Below is an illustrative example used by Peter Aldhous in this lecture: http://paldhous.github.io/ucb/2016/dataviz/week2.html¹.

(Source: Fox News, via Media Matters².)

From the plot above, it appears that apprehensions have almost tripled when, in fact, they have only increased by about 16%. Starting the graph at 0 illustrates this clearly:

Here is another example, described in detail in a Flowing Data blog post:

(Source: Fox News, via Flowing Data. (link³))

This plot makes a 13% increase look like a five fold change. Here is the appropriate plot:

Finally, here is an extreme example that makes a very small difference of under 2% look like a 10-100 fold change:

(Source: Venezolana de Televisión via Pakistan Today and Diego Mariano. (link⁴))

Here is the appropriate plot:

When using position rather than length, it is then not necessary to include 0. This is particularly the case when we want to compare differences between groups relative to the within-group variability. Here is an illustrative example showing country average life expectancy stratified across continents in 2012:

Note that in the plot on the left, which includes 0, the space between 0 and 43 adds no information and makes it harder to compare the between and within group variability.