VizWiz

• It's way too long; I know I would never read all of it.
• The stacked bar / treemap charts things don't make sense at all.
• There's no structure to guide the user; like what is most important?

• I focused on the high-level goals.
• I noticed that there were a lot of people that said they would commit to action forever, so I made that the focus of my viz.
• I had originally split the view up by gender, but that didn't add anything to the analysis, so I took it out.
• I used the colors and fonts from the Positive Impact Events website.

• The y-axis is missing.
• The dots are double encoded by size and position on the y-axis.
• Google trends are included for some reason.
• The legend could be simplified.

• I keep having to refer back to the legend. Maybe label each bar once?
• This show a comparison of the ages within a season. If the viewer wants to compare the seasons by age, then that become difficult.

• The title clearly explains the story in the chart.
• The colors are easy to distinguish.
• The bar chart helps us see the increasing revenue.
• Placing mobile at the bottom of the stacked bars makes it easy to see the increase in the mobile share.

What could be improved?

• All of the labels make the chart look quite busy.
• Is the image of the platforms necessary?

• I wanted to look at the relationship of share and revenue over time, which led me to a connected scatterplot.
• I thought it was important to look at each platform independently, so I placed them inside "cards".
• I included BANs based on the estimated revenue for 2021.

• Too many colors
• The x-axis labels are slanted.
• It's way too long (but I understand why it was designed that way).
• There aren't any legends.
• There are too many shapes.
• The bubbles are trying to do too many things at once.
• Comparisons are very difficult.

• I used BANs for the enrollees per pharmaceutical company. I then used this as a set action to highlight that company in the line chart.
• I looked at the enrollees per status, but I don't think that makes sense since it's the latest status. 
• The same applies to the phase; it also only shows the latest phase.
• I looked at how many enrollees there have been since the start the first trial for each company.
• I included the enrollees per condition and used a set action for proportional brushing for the company selected.

• Not much; it's quite fantastic.
• Maybe make it more interactive so you can see the specific values when you hover

• Lose the red/green color palette.
• A diverging color palette should only be used if there's a natural midpoint; there isn't one with this data
• There's double encoding on every chart.
• The State filter list it too big; granted though that there was no multi-select dropdown filter at the time.
• The map and the states bar chart are the same.
• The sparklines and the bar charts represent the same data.
• The reference lines aren't needed. What does an average infection rate really mean?

1. Simplified the metrics
2. Used a map that weights all states equally (like a hex map but circles)
3. Used only a single color
4. Used highlighting more effectively
5. Created simple filter actions
6. Used simple chart choices

• Other than this being used to look up information, what purpose does it server? It merely a list of facts.
• There's no context for the numbers. How does a player rank amongst the team?
• It's visually unappealing.
• I can't find definitions for some of the stats. For example, what does "In Squad" mean? No clue!

• Is this colorblind friendly? I'd recommend verifying.
• Does green mean good?
• I don't know how they came up with the percentages they did. They don't match the source.
• Label the lines directly with their frequency instead of using a color legend.
• Lighten the gridlines.

• Like the original, I filtered out 2012 because the data looks corrupted.
• I liked the original, so I didn't change a whole lot. The main difference was splitting up the frequencies vertically.
• Because I split of the frequencies, I made the viz tall and skinny and mobile friendly.
• I labeled the start and end of each line.
• I labeled the highest value for each frequency.
• I included the change between 1989-2018 on the end of each line as a summary. I had to float everything to make this work, which damaged my soul a bit.
• I'm only displaying the first and last year on the y-axis.
• I included tooltips so the reader can see the exact values.
• I used three shades of a single color that go from least sex to most sex (since the focus is on less sex).
• I kept the same title and subtitle.
• I used fonts from the Washington Post website. NOTE: They won't render on Tableau Public unless you have the same fonts installed (Playfair Display and Yantramanav).

• The filled map makes it hard to find smaller countries and to compare them with larger countries.
• The diverging color scale of the dots on the map imply that once you get 50%, that means things are good. Is that true?
• There's no indication of what the size of the dots represent.
• There are too many colors fighting for attention.
• The stacked bar charts are good for showing the overall trend, but the patterns for the individual colors are hard to determine.

1. Most applications for asylum were lodged in Germany, France, Greece, Italy and Spain.
2. Citizens of Syria, Afghanistan, Iraq, Pakistan and Nigeria lodged the most applications. 
3. Only five out of the 20 most common citizenships of asylum applicants in 2018 applied in increasing numbers compared to the previous year: Iranian, Turkish, Venezuelan, Georgian and Colombian nationals.