Five Tricks that Make Your Data Visualizations Stand Out

Stories the data tell are easier to understand when visualized adequately. Visualizations don’t need to be complex to communicate effectively: the objective is to use the most straightforward and most suitable chart for the job.
In this post, I’ll explore the Makeover Monday dataset 2018/W14: World Wine Production. I’ll highlight what works and what doesn’t with the chart below, originally published in the International Organisation of Wine’s annual Publication State of the Vitiviniculture World Market, April 2017. I’ll also suggest how to make it better with a few simple adjustments.
Later, I’ll take a closer look at the original dataset and seek to present country and continent level data as an interactive and visually pleasing data dashboard. I’ll explain my design choices and how annotations, chart choice, alignment, and layouts make it engaging.
Let’s start with the Wine Production figure you can spot below. The line chart tracks changes or trends over time and is, therefore, a right choice for representing this type of information. The mark color red associates easily with the color of the wine.

Nonetheless, there is room for improvement: the chart looks crowded with the grid lines, axis and mark labels. The title overlaps the graph and adds to its business. The x-axis label is tilted to fit the two last years’ descriptions. The y-axis seems somewhat heavy and ranges from 180 to 320 million hectoliters, yet the lowest data point is at 257.
With some simple alterations, the representation of the same data appears much lighter; Changing the range of the y-axis adds space around the deep purple-red line. It makes annual increases and decreases in production more evident.

In the search for a maximal data-ink ratio, I decided not to show gridlines and mark labels. I highlighted the production of 2016 and 2017 with the annotations instead of making these data points stand out.
I used the dark gray font, Tableau light, to keep the text items airy. The titles, placed above the chart, are left-aligned, and the subtitle font size is four points less than the title. The annotations are right-aligned, font size 10 — equal with the font size of the axis labels.
Let’s now aim our attention at the source data extracted from the Wine database. The wine database includes many interesting statistics: vineyard surface area, production (fresh grapes, dried grapes, wine), trade and consumption at the world, continent and country levels for the years ranging from 1995 to 2017. These series could depict numerous stories about the viniculture!
There are some limitations and biases:
a) United States data is an OIV estimate based on USDA figures.
b) Adding up the production volumes of countries does not result in the world aggregate. The aggregation only includes producers with a production size greater than 1 million hectoliters per year.
c) Production, trade and consumption data sets naturally have a different number of countries: Wine is not produced everywhere but is consumed widely in the world.
d) Axis choices alter the impression of the amplitude of changes in production. A narrow range makes the changes appear more dramatic.
Finally, let’s address the interactive data dashboard that seeks to answer questions about the developments of wine production in 20 years in the four corners of the world. It attempts to demonstrate how wine production is concentrated in a few countries, yet new producers are emerging.
It also reveals the fluctuating nature of wine production due to the sensitiveness to weather; The number of freezing days and precipitation during the growing season influence the volume and quality of the wine produced.

The elements, an area chart that presents the swinging curve of global wine production, a set of area charts zooming into continents and a series of line charts comparing the countries, are placed horizontally on a grid.
The area chart takes about two-thirds of the first horizontal space, leaving some room for the buttons and filters.
The middle horizontal area is divided into five equal-sized columns plus the y-axis header on the left. The bottom-most container has fourteen equally wide columns and the y-axis header on the left.
Story headlines guide the reader and visual encodings assign an order that we naturally understand; Angles of the area on the first graph, the size of the area on the second, and the colors of the lines and their position on the third.
The filters support a year-to-year analysis. They also allow examining production volumes between the continents and comparing the quantities produced by country A to that of country B.
Red wine-inspired color chart with the complementary hue, blue please the eye.
The Tableau light font in white for titles and in dark gray for labels and other texts maintain the buoyant ambiance while the dashboard title font Copperfield, also applied to buttons, associates with wine.
All elements have outer padding of 4 pixels on each side.
The dashboard above, as the original line chart, is missing the supportive text. I decided to create a separate “dashboard” to introduce the topic which also has a navigation button linked to the data dashboard itself.

I wanted this first visualization to have a vivid look and altered the stunning wine icon made by Freepik from www.flaticon.com with the wine production graphs. I placed the navigation buttons to the right and included instructions on how to explore the dashboards in the text.
There is a vast choice of other suitable graphs for this dataset. I was not able to resist a temptation to try some of them. An animated map, for example, could feature the change of production volumes in the countries throughout the time.

Also, an annotated animated story could point at the interesting deviations of production, and supply reasons to the sudden up or downturns.

To conclude, these five rules make your data presentation remarkable:
- Choose a chart that visually answers your question.
- Use appropriate visual properties to encode your data. Shapes, color choices, text labels etc. determine the outlook of the final product.
- Use a consistent grid, keylines, and padding in your layout for a polished outcome.
- Align the elements properly to result in a clear and professional finished product.
- Keep in mind the resource limitations of humans, computers, and displays.
