1. Final Viz (and below)
2. Preferences file (all of my custom color palettes)
3. How to Create a Combination Bar Chart & Candlestick Chart 

1. Add values for the remainder (100 - index)
2. Add a sort column
3. Pivot the data so that the index and the remainder were in the same column

WHAT WORKED WELL

• To create the stacked bar chart, all you need to do is select the chart type and drop the fields on the appropriate shelves.
• Customizing the split of the colors for the index and the remainder was easy.
• I was able to customize the size of the viz.
• You can choose any font that Google supports!!
• The tooltips are super responsive.
• Everything looks very crisp.
• Hiding the gridlines leaves a nice thin black line on the y-axis without me needing to fiddle around with a few different settings.
• The overall UX is quite intuitive. I see they have a data explorer now too.

• I couldn't find a way to show only the mark labels for the purple bars.
• I couldn't add a reference line for the G7 average so I had to leave it in the view.
• I couldn't hide the x-axis only. When you do, the y-axis gets hidden as well.

1. Add values for the remainder (100 - index)
2. Add a sort column
3. Pivot the data so that the index and the remainder were in the same column

WHAT WORKED WELL

• Creating a stacked bar chart in Power BI was quite simple.
• Customizing the split of the colors for the index and the remainder was easy.
• The viz layout is super intuitive and automatically adjust to the size of the screen while maintaining the original chart ratio.
• The fonts look super crisp.
• Simple to add a constant reference line for the G7 average.

• I couldn't find a way to show only the mark labels for the purple bars.
• I had to change the mark labels so that the values of the grey bars wouldn't be visible by making the text the same color as the grey bars.
• I couldn't copy/paste into a text box.
• I couldn't customize the font size for the reference line.
• I'm sure there's a way, but I couldn't figure out how to color code the bars based on whether they were above or below the G7 average. For example, I wanted to make those countries below the G7 average a lighter shade of purple.

• The title explains what the chart is displaying.
• The x-axis and y-axis are easy to understand.
• Excluding 1993 and 2018 since they are partial years.
• The chart has the proper height-to-width ratio.

• The title could be a bit more informative. Something like "Over the last 24 years, there have been only three weekdays where women has constructed at least 50% of the crosswords."
• There are too many colors, making the chart distracting and the lines hard to follow.

• Separated the days into separate charts so the trends for each weekday would be easier to follow
• Created sparklines and highlighted the high point for each weekday
• Labeled the values for 1994 and 2017 for context
• Included a BAN for the overall percentage for each weekday
• Created a mobile layout
• Shaded every other row to distinguish the weekdays and help guide the eye across the chart

• Vertical groupings work well for comparisons
• Using more pronounced colors for the companies and greying out the comparators
• Nice filtering options
• Title and subtitle are simple and tell us what the viz is about
• Good labeling
• Including a white divider line at 50%
• Including sort options

• Including the gender breakdown as well as the ethnicity breakdown in the same chart makes it feel too cluttered.
• As the years are set as filters, it's overly difficult to see if companies are becoming more or less diverse over time.
• Are the logos necessary?

• Focused on the gender diversity
• Chose a simple dot plot to make the viz less cluttered
• Included a more impactful title
• Kept their background color, but used a different color for highlighting

• The title above the charts tells us the insights in the data. This is a very effective technique.
• The colors work well together.
• Labels for the ages are well-placed and colored to represent the lines
• Labeling the start and end of the lines
• Hiding the axis but still leaving the axis title
• Including the note about the 2016 data

• Remove the title at the very top, the entire blue section
• Make the footer less prominent; it's competing with the viz for attention when it should be secondary
• Kill the bar chart; it looks strange have axis labels for every five years, but then only showing the data for a set of years
• Remove the dots on the lines except for the start, end and where the lines cross
• Remove the vignette shading behind the charts

• I like the idea behind the line chart, so I used that as my starting point.
• I pivoted the data by age, then created age groups that match the original (under 18 and 65+).
• I wanted to compare ages and origins for the two age groups to see if the crossing of the populations is consistent (spoiler, it's not).
• I wanted to add focus to the year the lines cross. I did that by adding a black dot on that year and by including a reference line.
• I kept the labeling of the start and end of each line.

1. While the population in total gradually shifts towards the older generation, the split between hispanic and non-hispanic does not follow the same pattern. 
2. Older hispanics will likely outnumber hispanic children between 2070 and 2075, whereas non-hispanic older people will outnumber non-hispanic children much sooner.
3. The female population is shifting much more quickly to the older generation than males.

• It's simple and easy to understand.
• Nice and clean; there's no unnecessary decoration
• Using colors that represent the parties
• Using a line chart to represent change over time
• Labeling the end point makes us aware of the current situation

• The stepped lines are necessary.
• The ratio of the chart looks strange to me.
• The title could be more impactful.
• Adding a y-axis would add context.

• Focus on the % of women and men in each party
• Use the party colors, but still be able to distinguish men and women
• Use a line to break up the area chart
• Use an impactful title and subtitle
• Use a viz in tooltip to show BANs

• The colors are easy to distinguish.
• The footnotes help to explain the percentages...sort of.
• The chart layouts are easy to understand. Bar charts nearly always work well.
• Labeling the top of each bar removes the need for an axis.
• Good drill down from the overall to the per region level.

• I find the chart titles quite confusing.
• Comparisons within a single region are difficult.
• I had no idea how to read these charts without reading the article. A chart should, ideally, be able to stand on its own.

• I focused on making over the bottom chart.
• I kept the original colors.
• I changed the bars to dots to help show the range of responses better.
• I didn't convert the responses to percentages as I wasn't confident it was accurate.
• I included a sorting option to allow sorting by the total responses or the responses within a region.
• Based on a twitter conversation with Dan Caroli last week, I turned on advanced logging feature which tracks each change you make in a sheet and then I turned them into this gif.

• The symbols make it clear this about females and males.
• The BAN in the middle tells us what the bonus pay gap is.

• Both icons are filled to the same level, making it look like there is no bonus pay gap. These should be filled to the actual values for each gender.
• The icons don't add much value.
• The title could tell us a whole lot more.
• There's no source listed nor no timeframe.
• The gridlines aren't evenly spaced between 0% and 50%.

1. Remove columns that aren't needed
2. Splitting the data up into two streams, one for the female columns and one for the male columns.
3. Pivot the data so that the pay bands are listed down instead of across
4. Add a column for the gender
5. Union the data back together
6. Export to an extract