There are many variations of a spline chart, each with its own benefits. Keep reading to learn about the different types of spline charts and when to use them.

## There are several different variations of this kind of chart.

A spline curve or graph is a data visualization tool that uses smooth curves to connect the points of data in a series. This can be helpful for visualizing nonlinear data or for creating more visually appealing charts than would be possible with straight lines. There are several different variations of this kind of chart, each with its own strengths and weaknesses.

The most common spline curve type is the cubic Bézier curve. This type of curve is used to create smooth transitions between points and can be adjusted to fit any shape. However, it can be difficult to control the exact shape of the curve, and it often produces jagged edges.

Another common type of curve is the Catmull-Rom curve. This curve is simpler than the cubic Bézier curve and produces fewer jagged edges. However, it is not as versatile as the cubic Bézier curve and cannot be used to create curved lines that intersect themselves.

There are also several other types of spline charts available, such as cardinal B-splines and tension charts. Each has its own strengths and weaknesses, so it’s important to choose the right type for your data visualization needs.

The natural spline curve uses the least amount of points to create the curve, while the uniform and cubic splines use more points to create a smoother curve. The cubic chart is most commonly used because it provides the best balance between accuracy and smoothness.

The linear variation connects the points with a straight line, making it ideal for representing data that is increasing or decreasing at a steady rate. The quadratic variation connects the points with a curved line that follows a parabolic pattern, making it ideal for representing data that is changing at an accelerating rate. The cubic variation connects the points with a curved line that follows a cubic pattern, making it ideal for representing data that is changing at a decelerating rate.

## How can you format each kind of chart in Excel?

In Excel, you can create a spline chart to show smooth data transitions between points. There are three basic categories of a spline: standard, X-Y, and polar.

A standard spline chart is used to show how one or more variables change over time or space. The data are plotted as points on a graph with lines connecting the points. A standard spline can be used to show changes in two or more variables over time or space.

An X-Y chart is used to compare values for two different variables at each point on the graph. The data are plotted as points on a graph with lines connecting the points. An X-Y chart can be used to compare two sets of data at each point on the graph or to compare values for one variable at multiple points on the graph.

A polar spline chart is used to show how one variable changes over time or distance. The data are plotted as points on a graph with lines connecting the points. A polar spline can be used to show changes in one variable over time or distance.

### There are three other categories to consider.

The simplest variation of the spline is the line chart. The line chart displays only the points and does not connect them with curves. This makes it difficult to see how the data changes over time.

The second simplest chart of this type is the spline area chart. The spline area chart also displays the series of points but connects them with filled curves. This makes it easy to see how the data changes over time, but it can be difficult to compare different datasets because they are all displayed on the same scale.

The third simplest variation is the stepchart. The stepchart also displays only the points but connects them with lines that have abrupt changes in direction. This makes it easy to see how individual points change over time, but it can be difficult to compare different datasets because they are all displayed on different scales.

A spline chart is important because it is a versatile data visualization tool that can be used to represent a wide range of data. Additionally, its smooth curve makes it an effective way to show changes over time or to compare data sets. Overall, this kind of chart is a useful tool for data analysis and visualization.