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What makes a data visualization a temporal visualization?


Asked by Owen Hahn on Dec 04, 2021 FAQ



Data visualizations belong in the temporal category if they satisfy two conditions: that they are linear, and that they are one-dimensional. Temporal visualizations normally feature lines that either stand alone or overlap with each other, with a start and finish time.
Consequently,
Essentially, these are visualizations that track time series data — the performance of an indicator over a period of time — also known as temporal visualizations. Temporal visualizations are one of the simplest, quickest ways to represent important time series data.
Accordingly, Therefore, the first step in a lot of data analyses is to see how the data trends over time. Frequency is also a fairly basic use of data visualization because it also applies to data that involves time. If time is involved, it is logical that you should determine how often the relevant events happen over time.
Additionally,
For temporal visualizations, time is always the independent variable, which is plotted on the horizontal axis. Then the dependent variable is plotted on the vertical axis. In the graph below, the populations of Europe and Ireland are the dependent variables and time is the independent variable.
One may also ask,
A line graph is the simplest way to represent time series data. It is intuitive, easy to create, and helps the viewer get a quick sense of how something has changed over time. A line graph uses points connected by lines (also called trend lines) to show how a dependent variable and independent variable changed.