# data[].attributes.body
1. This graph is cosmetically confusing because the 3D shape of the graph makes interpreting the data very hard. The different colors and strange shape distract from the actual line of data.
2. The total enrollment percentage only goes up to 72% instead of 100% which is misleading for the interpreter because the data is not complete. We do not know what the rest of the 28% would tell us.
3. By stacking the graphs on top of each other, the data is misleading and confusing when looking at the age of the college student that is enrolled. Also the organization of putting younger on top and older on the bottom is confusing to the reader.

# data[].attributes.body
1. This graph has a clear and understandable key.
2. It is measured in units that are consistent and both axes are marked at even intervals.
3.The source is listed at the bottom.

# data[].attributes.body
1.  The graph has all of the axes labeled and clearly marked in units if required. There is a clear title of what is being compared in the graph.
2. The y-axis goes up by increments of 75,000 sq. mi each time. The spacing is consistent and therefore presents the data correctly.
3. The graph is clear to read because the bars are evenly spaced, the same color, and the cosmetics of the graph do not interfere with the interpreting of the graph.

# data[].attributes.body
1. This graph is cosmetically confusing because the bars are created with books making them distracting and unclear.
2. There are no labels on the vertical axis which adds to the difficulty of understanding the scale of the graph as well as the information. Also the label on the horizontal axis only has the years but is not labelled.
3. The bars/"books" are not to scale. The height difference between 78% and 79% is larger than the gap between 80% and 81%.

# data[].attributes.body
1.  The y-axis is very clear, and it offers specific prices down every 10 cents.
2. The subtitle correlates with the cities on the x-axis, and it compares South Florida to the entire state, and then to the entire country.
3. The bars are specific to which represents a month ago and which represents it now.

# data[].attributes.body
1. The clowns, which are supposed to be the bars, are all different sizes. This makes it hard to get an actual reading.
2. There is no title anywhere to describe what they are attempting to portray.
3. On the y-axis, there are no specific measurements, so the reader is left guessing the exact number.

# data[].attributes.body
1. Both the horizontal and vertical axes are labelled correctly and at even intervals.
2. The data source is noted at the bottom of the graph so it is known where the data came from.
3. The graph is not cosmetically distracting or confusing so the information is clear and neatly displayed due to the simple layout.

# data[].attributes.body
1. This graph does not have a unit of measure on the y-axis.
2. The x-axis is not marked at even intervals.
3. This graph does not account for inflation.