This screen shot illustrates an area chart in 2D plotting data points taken monthly.  You can see each data point can be given a label, and an alternating color style can be applied to the Y-Axis.  The legend displays a key containing different colors (magenta, purple) that identify each data series.

This screen shot illustrates an area chart in 3D.  Its data points, occuring monthly, represent some measurements taken from two different data series (one data series consists of measurements for France, the other data series consists of the same measurements taken for Germany).  As the chart is in 3D, you see planes along the X and Y-Axes.  Depth along the Z-Axis is used to graph each data series, one in front of another.  This chart has been oriented to give you this look at the data, but you can apply your own transforms and lighting effects to orient it and give it the appearance you want.

This screen shot illustrates the bubble chart in 2D.  The bubbles representing individual data points are plotted on the X-Y plane, with a third data value that determines the bubble's radius.  You can see that the bubbles are painted with a lighted, pseudo-3D appearance.  The legend displays a color key (red, blue) that identifies bubbles belonging to the two different data series being displayed by this chart.

In this screen shot you see a 3D bubble chart with bubbles positioned according to their X- and Y- data points, and having third data point value that determines the bubble's size in relation to other bubbles.  Each bubble represents a different data series, and can be identified by a different color as those listed in the legend to the right side of the bubble chart.  Unlike the 2D bubble chart you looked at before, you can see these are real, three-dimensional bubbles with lighting effects and everything.  Each bubble also has a data point label appearing on it that corresponds to the size of the bubble (third data point value) making it easy for users to know the precise size of every bubble.

Here you see a candle chart with accompanying volume column chart beneath it, where both X-axes have to be closely-correlated because the columns in the bottom chart represent the 'volume' data point for the candle directly above it.  Candle charts were developed in Japan for depicting price action in a marketplace, and are often used in financial applications such as charting securities.  Each individual candle you see drawn on the chart represents several data points for the price action on that day or time period: 'high' and 'low' price, and 'opening' and 'closing' price.  Consequently, the candle chart includes sophisticated data binding support so that you can use a multi-valued data source to convey to it the price (and volume) data points it needs.

In this screen shot there is a candle chart illustrating the share price action of a public company over a period of time.  You see that you can style the background and gridlines of the chart differently from other screen shots of the candle chart in this Gallery. This screen shot also shows the labels being rotated at an angle (to prevent label collisions) along the X-Axis for the various dates.  An often requested feature is the ability not to necessarily have a date on every single candle (because that would produce label crowding), so you can see the date labels on the X-Axis have been spaced apart from one another.

This column chart in 2D shows five data points being plotted, each in their own data series (you can tell this because the columns appear separated from each other).  Each data point is labeled by the number of its data series along the X-Axis.  The height of the columns determines the value of that data point, with taller columns representing higher values.  Data point labels, with small round markers, make it clear what the value of each data point is.

The chart control also supports bar charts, which are simply column charts oriented horizontally instead of vertically.  You can have column and bar charts in both 2D and 3D.

This stacked column chart in 2D shows five data series being plotted, each containing two data points (you can tell this because of the number of stacked column segments appearing in each column).  Labels along the X-Axis identify the data points, so that you know you are seeing correlated data points (typically all coming from the same field in a series of data records) in each series (the series of  data records).  Stacked charts are useful when you want to see the contribution of multiple data points to the sum value.

The chart control also supports stacked bar charts, which are simply stacked column charts oriented horizontally instead of vertically.  You can have stacked charts in both 2D and 3D.

In this screen shot you see a doughnut chart in 3D.  Doughnut charts are related to pie charts, the main difference being that a doughnut chart has a hole in the middle and so resembles a ring-shape or three-dimensional toroid (the name of this chart comes from its resemblance to a pastry called the "doughnut" or "donut").

You can use doughnut charts where your users want to see the relationship between one data point and other data points (for example, one data field and other data fields in a given data record).  With different lighting effects and transformations to the 3D shape, you can give it the appearance and perspective you want, and you can also cut out pieces of the doughnut to draw attention to them.  The legend serves as a convenient way to identify the slices of the doughnut by their color, tying them to the names of fields in the data record whose values are being charted.

This screen shot illustrates a line chart in 3D.  Its data points, occuring monthly, represent some measurements taken from several countries based on two data series (for instance, imports and exports).  As the chart is in 3D, you see planes along the X and Y-Axes.  Depth along the Z-Axis is used to graph each data series, one in front of another.  Each data point along the line in this case represents a different country, as identified by the X-Axis label beneath that data point.  This chart has been oriented to give you this look at the data, but you can apply your own transforms and lighting effects to orient it and give it the appearance you want.

In this screen shot you see a pie chart in 3D.  Pie charts are often used when your users want to see the relationship between one data point and other data points (for example, one data field and other data fields in a given data record).  You can apply lighting effects and transformations to the 3D pie chart to give it the appearance and perspective you want, and you can also pull out the pie slices individually to call attention to them.  A legend can be displayed as a key of colors to identify the different fields being depicted by the pie chart.