Ten cities are used in the study – Mexico City, Johannesburg, Berlin, Tokyo, New York, Sydney, Vancouver, San Francisco, Hong Kong, and London.Ĭonversely, two cities are used for each graphic. The visualization is about How Many Avocado Toasts Does It Take To Afford A Deposit On A House. Therefore, to comprehend the data, you must consult all five graphics. There are up to 5 of them, and the interpreted data was shared between all five graphics. The above data visualization doesn’t tell you anything important. The Avocado Toast Index article by BBC Worklife features some of the bad data visualization examples you’ll find. The second player has the second most wickets, but the sixth player has a more extended bar than him. The player you would easily say has the second most wickets is the sixth player, Bhuvneshwar Kumar – which is wrong. Looking at it, the player you would easily say has the most wickets is the first player, Jasprit Bumrah – which is correct. This data visualization was meant to display most wickets in death and not most wickets in death + averages. The stacked up data also disorganizes the chart’s subject. On the other hand, averages have no units. Wickets are measured in length using mainly inches and centimeters. When making such a chart, a good color to use in contrasting orange is blue.įurthermore, the bar chart is stacked with numbers that have different units. Although the average is of a lighter shade, you can easily miss the color differences. Both wicket and average are represented in orange. The bar chart represents the wickets and batting averages of cricket players. However, it is bad because of one major thing the color. The above data visualization is a relatively simple one. You Might Want To Read: Best Tableau Courses 2. The lowest average is Mumbai at 35.51, but it is the tallest. In this data visualization by ESPN CricInfo, the shapes’ size, height, or width tells no difference. Looking at a bar chart, you can grasp the difference between each bar by the height difference. The closest it gets is to a bar chart, but instead of bars, the designer used different shapes representing each city.

You cannot categorize this visualization to any visual data visualization type. Such a color combination of red and blue is least friendly to the eyes. One of the things wrong with this data visualization is the color. To get an insight into what this visualization is all about, you’ll have to read the written texts – before the graphics and the ones associated with it. Looking at the graphics, it’s difficult to pick up any meaning from the data. Featured in it was the above data visualization that represented the cricket cities with the best batting averages. In 2019, ESPN CricInfo published an article on Which Top Cricket City Would Win the World Cup.

Data visualization cricket 3d