What is a line chart?
A line chart provides the clearest graphical representation of time-dependent variables. It is also the preferred mode of representing trends or variables over a period of time. People are familiar with this simple chart, which is made up of data values plotted as points along the X and Y axes and are connected using line segments. Usually, time is plotted along the X-axis, and the Y-axis represents some metric of interest in the context of the period being tracked.
For many, the line chart is the first type of chart learned in school, and one that they see again and again in life: in the media, in business reports, and in scientific studies.
Line charts represent everyday items like weekly weather trends, the price of stocks, what topics are trending on social media, and health information.
Where is a line chart useful?
1. When tracking a time-dependent variable
A line chart has some use to almost everyone in every industry:
- Publicists, brand managers, or public relations specialists track their client’s social media ranking over time to plan campaigns.
- Investors want to track the health of their stocks and other financial interests.
- Healthcare or public health officials follow trends in the prevalence of various diseases.
Using a line chart is ideal for tracking one or more variables over a defined or continuing period of time.
2. Keeping an eye on trends
Time charts enable viewers to pinpoint the exact time a significant event occurred and any ups and downs. For example, night-time temperatures take a sudden dip. Line charts are also useful for detecting anomalies in seismic activity. Line charts show viewers where to look for answers.
3. For spotting and comparing patterns between several related variables
Line graphs depict how relationships interact. For example, increasing preventative health measures compared to decreasing numbers of seasonal cold cases.
Best practices when creating a line chart
For the simplest iteration of a line chart, data can first be arranged into a table with a minimum of two columns. The values in the first column correspond to positions for points on the X axis. Each subsequent column corresponds to the positioning of points along the Y axis. Here are some best practices:
- Always start the scale at zero, and unless specifically required, use a linear scale.
- Label the graph clearly, and if there are multiple lines, ensure there is a key.
- Use different colors for different lines, if applicable.
Variants of the line chart
The line chart is a simple, two-dimensional chart with an X and Y axis, each point representing a single value. The data points are joined by a line to depict a trend, usually over time.
However, this simple two-dimensional line chart does have a few variants. From the list below, the zoom and scroll line charts are mostly applicable in digital media representations of charts:
- Multi-series line chart
- Multi-axis line chart
- Step-line chart
- Zoom line chart
- Scroll line chart
- Spline or fitted curve line chart
The multi-series line chart
As the name suggests, the multi-series line chart helps to visualize patterns when comparing trends across multiple datasets that may or may not be related. In other words, different entities or groups are plotted along the same scale for comparison. Line segments connect the data points. This type of line chart is useful in measuring the performance of one data set against another.
The multi-axis line chart
The multi axis chart is designed to plot data sets with a variety of measurement units and scale ranges. For instance, a multi-axis line chart can plot temperature against precipitation for a time unit such as a week or month. There is usually one X-axis representing the time unit, flanked by multiple Y-axes representing the tracked variables.
The step-line chart
This chart helps to visualize patterns for events that are non-continuous or fragmented. The step-line chart is great at depicting intermittent occurrences resulting from a change in values along the series. Vertical and horizontal lines connect the data points to form a step-like series progression. A step-line chart is ideal when showing intermittent production cycles or admission rates to an educational institute, for example.
The zoom line chart
This zoom chart multiplies the potential of line charts. For one, it is digital, which opens up the possibility of zooming and panning for a closer look at any point along the series. The zoom and panning features enable the analysis of multitude data points at both macroscopic and microscopic levels. If this were attempted in a simple line chart, the data would be indecipherable. This is why the zoom line chart is great for examining patterns over large chunks of time such as decades.
In the zoom line chart, each line is made up of data points belonging to a specific category joined together. Many such lines, each one representing a category, are juxtaposed against each other.
Zoom line charts come in handy in areas like real estate, making it easier to track and compare the various kinds of houses that are selling (or not) over a time period such as two decades. Or in healthcare, where patient data can be compared across several geographies and several generations.
The scroll line chart
The scroll line chart is continuously scrollable, thanks to the bar provided at the bottom. It is the digital cousin of the zoom line chart, albeit a structurally simpler one, tracking a large number of data points over a potentially infinite period of time. Sales or spend rates over time are typically monitored through this type of chart.
The spline chart
The spline chart is a curvy variant of the straight-line chart, with line segments joining the data points along the X and Y axes to create a free-flowing line as opposed to a rigid straight one. This “fitted curve” provides a different visual option. Multiple categories can be analyzed in the context of one another using a multi-series spline chart, which itself is a variant of the multi-series line chart.
Limitations of the line chart
1. The potential for clutter
When designing a multi-series line chart, stick to the elements that matter. Too many categories create clutter, and patterns become too tangled to make sense. Experts recommend keeping no more than four lines, each representing a group or category.
2. The mandate for uniformity of scale
To get an accurate sense of comparison, the groups or categories being juxtaposed must be measurable along the same scale. Also, the data must be continuously plotted along regular and equal intervals to be represented and read, accurately. Line graphs are accurate only if the axes follow the same, uniformly spaced scales.
3. The number of classes or groups is restricted
Even when the class interval is regular, the creator cannot plot too few or too many classes. Doing so will lead to missing important data patterns during analysis.
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