• The title and subtitle give you an immediate sense of what the chart is about and the story it will tell.
• Coloring the bars above and below the league average different colors
• Using bars, so that you can compare the length of them instead of a line that would show trends.
• Really nice annotations
• Shading the background to draw attention to a set of seasons
• Minimal axis labels
• Clean design

• Why does better go down? That's not very intuitive.
• The shading might give the impression that the coach ended where the shading ends, but Popovich is still the coach.
• It looks strange the 1980 and 2000 are offset, but 2020 isn't.

• Instead of comparing to the league average, I decided to compare the Spurs to the team of the user's choosing.
• Instead of using variance to the league average as the metric, I used defensive rating.
• I liked how the original had two colors for better or worse, so I followed that theme. My color for Spurs is always black since that's their team color.
• I included a note in the tooltip to clarify that a lower score is better.
• I wanted the Spurs going upwards if they are better, despite the axis being negative as it goes up.

Before

After

Before

After

1. Spending time with my kids is my highest priority and even if it’s just a few more hours per week, that’s still a few more hours per week than I currently get with them. 
2. I’m training for Challenge Roth, my first full distance triathlon. This will obviously take up A LOT of time. 
3. I want more time to continue to create new content for The Data School. We have lots in store and I’m excited about the possibilities.

• I like the handwriting font. It makes the viz look fun.
• The colors are distinct enough.
• Using shading on the title as a legend

• Some hands are holding another, some are not. What does that mean? Does two hands mean union? If so, I don't understand why they join where they do.
• Using weekly wages is a tough concept to grasp. Why not convert it to annual wages?
• The viz is clearly not designed for any sort of precision or comparison.

• I really liked this Viz of the Day recently by Spencer Bauke and thought this was a good data set to try to emulate his work.
• I wanted to use parameter actions to allow the user to change the comparison year.
• I also wanted to use set actions like Spencer did, but this data wasn't structured in a way that made sense to try to do that.
• This turned out to be very good practice for LOD expressions.
• I loved using containers to lay all of this out!! It's a lot of work, but much easier to get everything to line up and all be the same size.

• A map is a good way to represent the location of the squirrels.
• Showing the details on the map, like the ponds in the park and the roads around the park, help provide context.
• The dots are easy to see against the background.
• The title and description help explain the data.

• There are some red dots. What do those mean?
• It would be interesting to see when the squirrels are spotted. Are there more in the winter? How do their habits change?

• Clear title
• X-axis is clearly labeled
• Including the data source
• Colors are easy to distinguish
• Vertical lines help draw the eye to compare the years within each age
• Including labels since the y-axis is hidden

• The title could be less bold.
• The title uses the color for 2015, but it's not related to one year only.
• The dots are distracting since they are so large.
• The labels are helpful, but do they need to be so big?
• With the vertical lines connecting the dots within the year, and the line connecting the ages across the years, I'm not sure which is more important. Given the title, the focus seems like it should be on comparing years within an age.
• The vertical lines don't need to be so broad.

• Removed the lines to make the focus comparing the ownership within an age group
• Surrounded the dots with a band to ensure the user reads the data within each age group
• Colored the bands by the change to accentuate the ages that have changed the most
• Included the labels, but made them very small as to not distract from the analysis
• Created a mobile version for practice

• The data by region is ordered alphabetically, making it easy to find each region.
• The bar chart is sorted by largest to smallest.
• Nice filtering options

• A diverging color palette should only be used when there is a logical midpoint or goal. I don't see those in this viz.
• The squares are hard to understand.
• I don't find the map very useful. It would be more useful if it zoomed in when a region is selected.
• There's no title.
• There's too much text.
• The bar chart seems to go out past the edge, or at least visually it appears that way.

• I created a KPI scorecard so that I could understand the patterns for the overall or an individual country. Are literacy rates improving or regressing?
• Show the distribution of the rates of the countries within each region
• Within each region, which countries are above or below the median for that region?
• How has the literacy rate changed over time?
• Allow simple filtering options.

• The axes aren't synchronized; I'd like to see how they would look synchronized.
• Without referring back to the color legend, I don't know which axis goes with which metric.
• Using a dual axis chart implies there's a correlation between the two measures. There might be, but it could be displayed other way to make that more evident.
• There no indicator of the data source.

Historically, declines in Las Vegas visitor traffic have been associated with economic weakness, so the slight declines over the last two years was concerning.