Makeover Monday 2019 Week 21: Fatal Bear Attacks

Makeover Monday

This week’s Makeover Monday focuses on fatal bear attacks in North America from 1900-2018. The original chart is the following bar chart from an article on Vox.

What works well?

  • Summarizing the data by month provides useful insight into the annual pattern of incidents.
  • Using a bar chart allows easy comparison between months.
  • The “X” on January and March helps emphasize that there were no attacks in those months.
  • The bears on top of each bar are gratuitous, but don’t distract from the overall message.

What could be improved?

  • Not much. The original chart is very clean and clear.
  • Month labels could be consistently abbreviated to 3 letters.

What Marc did:

  • Filtered the data to attacks occurring in Canada only.
  • Added subtle gridlines with axis labels.
View in Data Studio

Makeover Monday 2019 Week 16: Info We Trust by R.J. Andrews

Makeover Monday

This week’s Makeover Monday features Info We Trust by R.J. Andrews and a word cloud of the most frequently used words in the book.

What works well?

  • The word “data” stands out due to its size, colour, and orientation. It is clearly the most common word.

What could be improved?

  • Beyond “data”, it’s very difficult to perceive which words are 2nd, 3rd, 4th, etc. Almost any other chart type would be better.
  • Colour is used arbitrarily, without any meaning.

What Marc did:

  • Charted the top 10 words by frequency, broken down by page, chapter, and section.
  • Used a bubble plot; larger circles indicate a higher frequency of the word on the given page.
View in Data Studio

Makeover Monday 2019 Week 15: Ranking States by Fiscal Condition

Makeover Monday

This week’s Makeover Monday chart is from a 2018 report by the Mercatus Center at George Mason University, ranking each state by its fiscal condition.

What works well?

  • Clean design without any distracting map details.
  • Colour palette is distinct and visually pleasing.

What could be improved?

  • As with any geo map, the size of each state can skew our interpretation. A equal-sized tile map would address this problem.
  • The map shows only the ranking, but not the actual measure on which the rank is computed. Hence, we can’t assess how the states are distributed, i.e. how far above or below average is each state?

What Marc did:

  • The overall ranking is based on an aggregate fiscal condition index, which is composed of 5 underlying indices. I re-calculated all the index values based on the underlying data, according to the formulas defined in the full Mercatus report.
  • Using a jitter plot, I charted the distribution of the states on the overall index and each component index.
  • I kept the original colour scheme for each ranking group.
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Makeover Monday 2019 Week 12: The Reykjavik Index

Makeover Monday

The Reykjavik Index measures the extent to which men and women are perceived to be equally suited for positions of leadership. This week’s Makeover Monday chart shows the Reykjavik Index across the G7.

What works well?

  • Clean, uncluttered design
  • G7 Average is highlighted with a different colour

What could be improved?

  • Circular bars are misleading. A typical bar chart encodes data in the length of the bars. In a circular bar chart, the data is in fact encoded in the radial angle, which is more difficult to interpret.

What Ryan did:

  • Used a traditional bar chart.
  • Added a reference line to show the G7 average.
  • Colour-coded countries above average and below average.
View in Tableau Public

What Marc did:

  • Straightened the bars to allow easier comparison.
  • Added grey bars stacked to 100 to show the maximum extent of the index.
  • Kept the original colours and overall style.
View in Data Studio

Makeover Monday 2019 Week 10: World Development Indicators

Makeover Monday

This week’s Makeover Monday challenge is in association with Operation Fistula. The original chart is the following map showing adolescent fertility rates in Africa. However, the dataset provided does not include the data needed to reproduce this chart:

What works well?

  • Clean and simple. Well-labelled. Easy to understand.
  • Colours are muted and not distracting. Visually-pleasing.

What could be improved?

  • Legend should be placed closer to the map to aid the viewer.

What Marc did:

  • Focused on female life expectancy in African countries.
  • Used a geo chart in Data Studio to map the data.
  • Added a jitter plot to show the distribution of life expectancy across countries. The filter allows you to select a particular country and see it in context of the distribution.
View in Data Studio

Makeover Monday 2019 Week 9: Bicycle Imports in the U.K.

Makeover Monday

This week’s Makeover Monday dataset comes from a report on the economic value of the bicycle industry in the United Kingdom. The chart shows the quarterly trend in bicycle imports from 2010 to 2016.

What works well?

  • Use of a line chart makes the seasonal trend easy to see.
  • Line markers clearly indicate the quarterly data points.

What could be improved?

  • Labels and gridlines can be re-formatted to eliminate some non-data ink.
  • Vertical axis title can be re-oriented to make it easier to read.

What Marc did:

View in Data Studio
  • Kept original line chart style.
  • Simplified labels on both axes and horizontal label on vertical axis.
  • Added shading for 2016 to correspond with the insight presented in the caption.

Makeover Monday 2019 Week 7: President Trump’s Official Schedule

Makeover Monday

This week’s Makeover Monday gives us a peek into how President Trump schedules his time, based on 3 months of leaked private schedules.

What works well?

  • Didn’t use a pie chart!
  • Minimalist design; High data-ink ratio
  • Clear titles and labels

What could be improved?

  • Honestly, not much.
  • Percentage labels would help more accurately compare the breakdown between categories.

What Marc did:

  • Recreated the original chart in Data Studio. There’s not much in need of a makeover.
  • Added percentage labels to the bars.
View in Data Studio

What Ryan did:

  • Created a Gantt chart to show Trump’s full schedule.
  • Coloured the periods of executive time in orange.
  • Added reference lines to frame the working hours.
  • Annotated some key events that took place from Nov-Feb.

Makeover Monday 2019 Week 6: Chinese New Year vs. American Thanksgiving

Makeover Monday

It’s Chinese New Year this week, and for Makeover Monday we get this chart that compares the Spring Festival in China with Thanksgiving in the United States.

What works well?

  • Colours are distinct and intuitive.
  • Values are labelled.
  • Circles are visually pleasing.

What could be improved?

  • Comparing the areas of circles is extremely difficult. Using bar charts would be much more effective.
  • Metrics are absolute totals and don’t account for the difference in population between China and the U.S.

What Ryan did:

  • Converted the total expenditure and trips to a per person amount and the TV viewership to percentage of population. Since China has a larger population, this makes comparisons easier.
  • Created bar charts for each measure comparing China and the USA.
View in Tableau Public

What Marc did:

  • I re-created the original graphic, converting the concentric circles to side-by-side bar charts.
View in Data Studio

Makeover Monday 2019 Week 5: Digital Economy and Society Index

Makeover Monday

The Digital Economy and Society Index (DESI) measures the digital performance and competitiveness of countries in the European Union. The original chart for this week’s makeover shows the 2018 DESI ranking of EU countries.


What works well?

  • Countries are ranked in order of total index score.
  • Bars allow easy comparison of total score.

What could be improved?

  • Stacked bars make comparing individual indicators across countries very difficult due to the lack of a common baseline.
  • Colours are overly vibrant. A more muted palette in the same tone would be less distracting.
  • Countries are not obvious based on two-letter country codes. The country names would be better as labels.

What Marc did:

  • Pivoted data to show each indicator in its own column in addition to the total score.
  • Created a table in Data Studio, allowing sort order to be changed by clicking on column headers.
  • Added reference line for the EU average of each metric.
View in Data Studio

What Ryan did:

  • Created slope graphs for total weighted score and for each indicator, comparing 2014 to 2018 ranking.
  • Used a highlight parameter to compare individual countries.
  • Added dimension descriptions from the source site to give context.
View in Tableau Public