Documentation

Line Chart

Line charts are generally used to show trends, an increase (as well as a decrease), or certain unpredictability. They are also very good at displaying developments in your data over time. They show how a measured variable changes at equal intervals of time. Therefore, a time field should be added to the X-Axis of a line chart. In general, line charts are a good starting point for your analysis to collect first insights about the evolvement of a particular variable. Line charts are also useful when you want to visualize a relationship between two linked metrics.

 

Line charts are not always the best visualization type though, especially when you have too many variables to display: overwhelming your graph with lines will make it hard to understand. To avoid such a hassle to your audience, you may need to create another graph in parallel. Likely, the axis scales should be adapted to your data: a Y Axis (what you measure) too high will flatten your line, and that can make you miss the point or tell a different story.

 

 

How to create a Line Chart in datapine

 

line chart created with datapine

 

1) In the Chart Creator, add your metric to Measures.

 

2) Then add a date field to the X-Axis dimension. When you add a time field to the X-Axis, you can edit the time interval in the Field Editor on the right side of the screen. You can set a special single time period (static or dynamic), or multiple time periods. To read more about it and see how to customize time periods, see in the chapter Transform data – Custom Time Periods or read the subchapter Modify Time Values.

 

Tip: Line charts have the advantage of not being too overwhelming on a graph. This particularity makes them especially great if you want to parallelize them with another graph -a bar chart for instance. Using a secondary Y Axis, you can display the two elements of the story you want to tell on one unique graph, facilitating the overall comprehension and exposing the relationship, complementarity (or not) of the two variables.