In a world where data abounds, people see Data Visualization as essential for transform Of informations complexes In stories visuals clear and powerful. By harnessing the power of visual processing, it facilitates instant understanding of data.
However, users should adopt a nears Thoughtful to avoid the pitfalls of deception and ensure transparent and effective communication. This article therefore explores the importance of Data Visualization and offers tips for producing impactful data visualizations and accurate.
In the complex world of data, the Data Visualization plays an essential role. She us Help to navigate in a sea of information and at produce impactful data visualizations. Visualizations transform Raw figures in visual narratives powerful and they can also influence or bias perception.
In fact, visual processing takes up more than 50% of the human brain, making visualizations the most effective way to understand and interpret complex information instantly.
As data scientists, we play a central role in data visualization. It allows us to explore the data by highlighting key elements and to present the results in a compelling way.
This article will explore the crucial importance of Data Visualization and the pitfalls to avoid through striking examples.
The climate “stripes” have rapidly made their impact and influence felt since they were launched in 2018 by Professor Ed Hawkins. These colorful vertical bands convey a powerful message without the need for words, of numerals Or of graphs. Each band represents the average temperature for a year compared to the average over the entire period. Shades of blue indicate cooler years than normal, while red highlights warmer years. The alignment marked with bright red bands on the right side of the image reveals the rapid warming of our planet over the past few decades.
This visualization was quickly felt, with over 1 million downloads in a week after its launch in 2019. The climate “stripes” have become a universal symbol, adopted by weather presenters, scientists, activists, and exhibited on stage at festivals or on electric vehicles.
This visualization illuminates the number of civilian and military deaths in Iraq during the American presence. This powerful and disturbing inverted red bar chart gives the impression of forming a bloodstain. Beyond its striking visual meaning, this graphic representation evokes the extent of the tragedy that affected Iraq during this period. It goes beyond simple numbers to remind us of the human impact of conflicts and wars, with an emphasis on suffering and the loss of life.
Other dimensions such as the region, the cause of death, the key dates, the key dates, present also make it possible to provide context to the main graph.
This visualization compares Leonardo DiCaprio's age over time with that of his female companions, revealing a narration intriguing. Logically, DiCaprio's age draws a straight line. On the other hand, that of his companions follows a generally constant pattern, showing a tendency to be in a narrow range, between 18 and 25 years of age.
This representation, which is easy to understand at first glance, raises questions about social norms, fame, and personal relationships, while highlighting how visual data can tell intriguing, sometimes unexpected, stories.
This visualization shows how the Bitcoin price has fallen over the last 13 years. By using a Fall effect visually striking, it reinforces the reader's idea that Bitcoin represents a very unfavorable investment.
Donald Trump released the first visualization during the 2019 presidential elections. It shows a map of the United States, mostly colored in red, thus suggesting a landslide victory for the Republican Party. This visualization has been widely disseminated, becoming a key communication tool and being printed on a variety of promotional products, thus symbolizing its considerable impact.
However, a second visualization presents the same data in a different way and suggests that blue is more prevalent.
In reality, the first visualization shows the municipalities that vote for the Republicans and those that vote for the Democrats. The second presents the same information, but with municipalities represented by circles whose size is proportionate to the voting population in these municipalities.
This case illustrates how visually representing data can influence the understanding of election results and highlights the importance of transparency and objectivity in visualizing data, especially in the political context.
“Earth doesn't vote, people do! ”
All three visualizations show the same figure, which represents an infant mortality rate of 4.3%. In the first visualization, this figure evokes the impression of severity because it is isolated. In the second visualization, it is compared to the infant mortality rate in the European Union, which is lower at 0.45%. This comparison offers a slightly more perspective. upbeat, although a difference remains, thus suggesting that the situation could be improved. In the third visualization, the figure is compared to the past infant mortality rate, which was around 50%.
This comparison highlights a very positive trend since the current figure is much lower. These different representations of the same number demonstrate how information framing can significantly influence interpretation and conclusions, underlining the importance of critical data analysis in terms of visualization.
In these two bar charts, the color difference creates a striking contrast in the way the information is presented. In the first diagram, where each bar is a different color, it is difficult to distinguish a key message. The variety of colors can be distracting and does not contribute to information. In contrast, in the second diagram, using the color gray for most of the bars highlights the singularity of the colored bar, making it clear where the important message. This simplified approach to visualization helps the viewer quickly interpret critical data. It makes it possible to produce impactful data visualizations.
Color perceptions vary considerably from person to person. Approximately 8% of men and 0.5% of women have color blindness, a condition that prevents them from distinguishing colors correctly. People with color blindness cannot distinguish colors properly, which is a condition affecting approximately 8% of men and 0.5% of women. The most common form is color blindness red-green, colors that are precisely often used in visualizations. In addition, various studies show that cultural and gender factors can influence color perceptions. Understanding these differences is critical when designing data visualizations to ensure that they are accessible to a diverse audience.
You should avoid using three-dimensional graphics in the field of data visualization, as they can be deceivers and not reflect reality. A famous example illustrates this problem during a presentation by Steve Jobs in 2008, where he used a 3D pie chart. This choice gave the impression that the share representing 19.5% was larger than that representing 21.2% when presenting the market shares of smartphone sales.
Nonetheless, pie charts can sometimes be relevant, especially when the data does not present the aspects described above. Here are some examples of inefficient pie charts:
This pie chart shows that slices A and B seem similar at first glance, but the bar chart shows otherwise.
In this example, we can observe two phenomena. First, the graph becomes unreadable due to the large number of categories. Second, some categories have very small values, making them invisible.
It is essential to take your time when creating a data visualization. This process makes it possible to refine the details, to choose the appropriate colors, and to structure the information in a logical manner in order to guarantee transmission clear and impactful of the message. Investing time in the design of visualization results in better understanding and greater efficiency in the transmission of information.
The field of Data Visualization is constantly expanding and is seeing a proliferation of visualizations, as well as the emergence of new jobs such as data journalists, data designers and data artists.
Data Visualization is a artistry, but it is also a science. Visualization designers need to be aware of the impact of their choices on the understanding and interpretation of data. In particular, they should pay attention to questioning. The impact, the accuracy and harmony of their creation. It should also be noted that a single interesting and “actionable” perspective will be more relevant than 1000 detailed analyses.
As a viewer, it's critical to remember that data is just a tool for telling a story, and how it's presented can have a significant impact on perception of this story. Ask yourself questions about the relevancy charts, the choices of colours, the scales used, and ensure that the visualization accurately reflects the underlying data.
Data Visualization is a powerful tool for communicating complex information, but it should be used with responsibility. It can illuminate the world, but it can also distort it. By understanding its potential and pitfalls, we can navigate the data age with confidence and clarity.
In this example, we can observe two phenomena. First, the graph becomes unreadable due to the large number of categories. Second, some categories have very small values, making them invisible.
