# data[].attributes.body
X-Axis doesn’t begin at 0.

The graph is super vague.

The Y-Axis should not be as precise to show the data better.

# data[].attributes.body
1. There is no title for this graph.

2. They are all the same color so it is hard to differentiate between them.

3. They also should have started at ten for the way they portrayed there graph instead of jumping from 0-10 and then going by 1.

# data[].attributes.body
1. This graph contains title.

2. Graph contains horizontal and vertical axis labeled.

3. The graph starts at 0 and has a key.

# data[].attributes.body
Bad graph example

The percentages does not add up to 100%.

The data is not sourced.

The graph is vague and not fully labeled.

# data[].attributes.body
It is a good graph because it is labeled.

It is a good graph because it is color coordinated, and you can tell what data is which due to the key.

The graph starts at zero.

# data[].attributes.body
Very easy to read and digest

Not 3d so allows the reader to accurately understand the size of data

Colors make it easy to differentiate

# data[].attributes.body
Good graph

There is no truncation, the graph starts at zero.

The data is labeled, and so is the graph.

You can easily read the data.

# data[].attributes.body
There is not a title and the labels are not very specific.

The pieces are not divided to scale.

The percentages add up to over 100%