First a bit of history:
Did you know that the earliest known 2-dimensional chart was a line chart? It is presumed to be created in the 10th century and the creator is unknown. Let's take a look and try to find out what it represents:

The visual shows the celestial latitude of the sun varying with time. Everything is plotted on a grid, where the vertical and horizontal lines aid the user to be able to see the proximate location of the celestials. Funny enough, only 700 years later, this grid would be used as standard 'graph paper'.
Usage:
The line chart is useful in your visualization project when you want to compare values over time. In some occasions, like plotting sequencial variables, the line chart can be combined with categorical attributes.
Key indicators:
Visuals like the line chart are used to indicate trends or patterns. They should invoke an immediate comprehensive outline that can be interpreted by the viewer. In these indications the user can identify peaks, cliffs, or see that the values are high or low. With the help of additional annotations, the visual artist can prepare the viewer to which action needs to be taken. some tools (like Power BI) also have some machine learning models that can calculate this for you.
Why should you use line charts?
The answer to this question is rather simple. The line chart looks familiar, it is easy to read and see the representation of the data to identify trends or patterns. As a human being we are addicted to finding patterns,
Hints and Tips:
Make sure that your line chart gets breathing space, do not make them too small or too high. This can influence your users' decision making process.

When comparing periods over time, using gradient colours to indicate the relation between the current and prior period. The current period should show the darker colour, while the prior period (which faded away) should show the lighter colour.

Some tools provide the possibility to show data markers, this is very useful for the end user to immediately link the value to the attribute on the X-axis. However take into account that this can also invoke unnecessary clutter so be careful to use this.

Conclusion:
Line charts are seen as one of the most powerful charts in the data visualization process to discover trends and patterns in data. It looks familiar and is easy to read if the graph gets its breathing space. Even though most of the graphs respresent an evolution through time, it is also possible to visualize data based on an incremental value which is not time related.
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