data visualisation
Data visualization is a discipline created by John Tukey.
Principles
Choose the right chart: For instance, bar are good to show frequencies, absolute quantities. Lines are good to show variations over time, it can also show relative quantities, as a zoom to highlight some difference.
Avoid misunderstanding: For instance, the bar must be proportional to what it represents.
Choose the right colour scheme: if colours are showing important differences, so they must be easily differentiated. It is also good to avoid too much
Remove unnecessary information: avoid any label and extra data. Less is more!
Have in mind the story the chart is supposed to tell: at the end, it is expected to tell some story giving to the user some information. It is important to make sure the chart is delivering it.
Navigating
This topic is related to many disciplines among them: machine learning, writing and math.
Sources
Drawing from data presents some challenges on data visualization and some possible solutions, for instance, how to filter and aggregate data and how to make a pairwise distance matrix.
The Beauty of Data Visualisation briefly talks about the importance of this discipline giving a few examples.
Data is ugly and data is beautiful are reddit communities (subreddits) for discussing data visualisation
Some beautiful customized palettes: 20 unique and memorable brand color palettes to inspire you and branition
Seaborn framework documentation also brings useful information about palettes.
Covid-19 dashboards in Java data visualization using vaadin an open-source framework for development of progressive web applications.
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