In this section: |
It is important that you select a chart, grid, or map that appropriately displays a meaningful view of your data. InfoAssist provides a library of visuals.
You can select a visual type from the Select a Visual menu, on the Home tab, in the Visual group. The following table describes the types of charts available.
Icon |
Visual Type |
Description |
---|---|---|
|
Grid |
Grids provide a tabular view of data. They allow you to review data in a row and column format, similar to a printed report. |
|
Bar chart |
Bar charts plot numerical data by displaying rectangular blocks against a scale (numbers or variable measure fields that appear along the axis). |
|
Stacked bar chart |
A stacked bar chart is the default visual. |
|
Histogram |
Histograms graphically represent the distribution of numeric data. They facilitate the identification and discovery of the underlying frequency distribution within a set of continuous data. You can use histograms to identify trends and illustrate categorizations, or groupings, also known as bins. For more information, see Binning. |
|
Absolute line chart |
Line charts allow you to trace the evolution of a data point by working backwards or interpolating. Highs and lows, rapid or slow movement, or a tendency towards stability are all types of trends well suited for a line chart. |
|
Area chart |
Area charts analyze trends over time and look for differences in values. |
|
Stacked area chart |
Stacked area charts allow you to stack data on top of each other. |
|
Pie chart |
Pie charts are circular charts that represent parts of a whole. A pie chart emphasizes where your data fits, in relation to the other components in the pie. |
|
Ring pie chart |
Ring pie charts are useful when you want to review the value of each segment, which represents the measure value for the selected dimension, as it relates to the total for the selected measure. |
|
Scatter Plot |
Scatter charts enable you to plot data using variable scales on both axes. When you use a scatter chart, the data is plotted with a hollow marker, so that you can visualize the density of individual data values around particular points, or discern patterns in the data. |
|
Bubble chart |
Bubble charts can have two column fields representing X and Y data values, or have three column fields representing X, Y, and Z data values. The third variable (Z) represents size. The size of each bubble is used to show the relative importance of the data. |
|
Matrix Marker chart |
Matrix marker charts are useful for analyzing one or two measures against a crosstab of two categorical dimensions. The result is a color-scaled matrix chart that shows categorized trends. |
|
Treemap |
Treemaps are used to display large amounts of hierarchically structured data. Using a set of nested rectangles to illustrate data relationships, sections of a treemap represent branches of a tree. |
|
Gauge |
Gauges are used to display the value of a measure. In particular, circular gauges are used to represent a single data value within a given spectrum. You can create a single circular gauge for a measure or a matrix circular gauge, which shows the value of the selected measure across different dimensions, such as product category or yearly sales. |
|
Choropleth map |
A geographically-based heat map. It is useful for visualizing location-based data, trends, and distributions across a geographic area. |
|
Proportional symbol map |
A technique that uses symbols of different sizes to represent data associated with different areas or locations within the map. |
|
Heatmap |
A heatmap is a graphical representation of data where the individual values that comprise a matrix are represented as colors. Using radiant hues, you can track the intensity of a data relationship using the colors defined in the legend. |
|
Leaflet map |
Part of the Lightweight Mapping functionality, Leaflet maps enable you to visualize trends in your data. Choropleth and Proportional symbol maps are available. Note: Esri functionality is not integrated into Leaflet maps. |
Use the topics in this section to select and create your visuals.
How to: |
Grids provide a tabular view of data. They allow you to review data in a row and column format, similar to a printed report.
In the following example, we review the product category and subcategory data for the following measure fields:
When working with grids, you can lasso or select a range of values at one time, enabling you to filter the grid or exclude values from it.
Note: If you have a large number of fields specified in a grid in Visualization mode, the server may be slow to respond.
As you add, edit, or rearrange the fields in your Query field containers, your canvas refreshes.
How to: |
Bar charts plot numerical data by displaying rectangular blocks against a scale (numbers or variable measure fields that appear along the axis). The length of a bar corresponds to a value or amount. You can clearly compare data series (fields) by the relative heights of the bars. Use a bar chart to display the distribution of numerical data. You can create horizontal and vertical bar charts.
Note: If you are working with a large dataset, a scroll bar displays under your chart, enabling you to easily scroll through your data from left to right. In Visualization mode, scroll bars are automatically enabled, but if you want to disable or re-enable scroll bars, click the Format tab and then click Interactive Options. In the Interactive Options dialog box, select the Auto Enable X-Axis Scrolling check box. If you are working in any other mode, you must enable this functionality.
Use a bar chart when individual values are important. For example, the following image is a basic vertical bar chart that compares the individual products sold to the total amount in sales for each product. A retailer would find it important to know which pieces of inventory are selling and how much revenue each item is generating for the company.
A horizontal bar chart becomes useful when you want to emphasize a ranking relationship in descending order, or the X-axis labels are too long to fit legibly side-by-side. For example, the following image is a basic horizontal bar chart that ranks which products are generating the most revenue for the retailer.
Note: You can swap the orientation of your data in a bar chart. To do so, on the Home tab, in the Visual group, click Swap.
Note: You can also double-click a data field to add it to your Query field containers.
The bar chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the bar chart.
The bar stacked visual is the default visual.
Note: You can also double-click a data field to add it to your Query field containers.
The stacked bar chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the stacked bar chart.
Note: You can also double-click a data field to add it to your Query field containers.
The matrix bar chart displays on the canvas. You can add additional fields for comparative purposes. You can also view underlying data by hovering over any particular point on the matrix bar chart.
How to: |
Line charts allow you to trace the evolution of a data point by working backwards or interpolating. Highs and lows, rapid or slow movement, or a tendency towards stability are all types of trends well suited for a line chart.
You can also plot line charts with two or more scales to present a comparison of the same value, or set of values, in different time periods.
Note: If you are working with a large dataset, a scroll bar displays under your chart, enabling you to easily scroll through your data from left to right. In Visualization mode, scroll bars are automatically enabled, but if you want to disable or re-enable scroll bars, click the Format tab and then click Interactive Options. In the Interactive Options dialog box, select the Auto Enable X-Axis Scrolling check box. If you are working in any other mode, you must enable this functionality.
Use a line chart when you want to trend data over time, for example, monthly changes in employment figures, or yearly sales of an item in your inventory. The following image is a line visual that shows the gross profit in monthly sales for products.
Note: You can also double-click a data field to add it to your Query field containers.
To add insight, you can drag a data field to the color Query field container. This displays the values for this field using color.
The line chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the line chart.
Note: You can also double-click a data field to add it to your Query field containers.
The matrix line chart displays on the canvas. You can add additional fields for comparative purposes. You can also view underlying data by hovering over any particular point on the matrix line chart.
How to: |
Area charts analyze trends over time and look for differences in values by using the see-thru nature of the area fills. Stacked area charts allow you to stack data on top of each other. Stacking allows you to highlight the relationship between data series, showing how some data series approach a second series.
Note: If you are working with a large dataset, a scroll bar displays under your chart, enabling you to easily scroll through your data from left to right. In Visualization mode, scroll bars are automatically enabled, but if you want to disable or re-enable scroll bars, click the Format tab and then click Interactive Options. In the Interactive Options dialog box, select the Auto Enable X-Axis Scrolling check box. If you are working in any other mode, you must enable this functionality.
Use an area chart when you want to distinguish the data more dramatically by highlighting volume with color. For example, the following image is a basic area chart that depicts the yearly gross profit for various electronic products.
Note: You can also double-click a data field to add it to your Query field containers.
The area chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the area chart.
Note: You can also double-click a data field to add it to your Query field containers.
The stacked area chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the stacked area chart.
Note: You can also double-click a data field to add it to your Query field containers.
A matrix area chart displays on the canvas. You can add additional data fields for comparative purposes. You can also view underlying data by hovering over any particular point on the matrix area chart.
How to: |
Pie charts are circular charts that represent parts of a whole. A pie chart emphasizes where your data fits, in relation to the other components in the pie. Pie charts work best when there are a limited number of slices (for example, less than 10) and the slices are all of a sufficient value as to reveal their fill color inside their wedge.
Use a pie chart when you have segments of data that you want to display as a whole. For example, the following image is a pie chart that shows the proportions of various electronic products based on the quarterly revenue.
You can add one or more measures to the Measure field container. Each measure will be used to create a separate, unique pie chart, to which you can add a measure or dimension to the Color field container to add color to your chart.
Note: When working with pie charts, you can add one measure field to the Color field container. This adds the measure as a By field, and determines how the pie chart is colored. Depending on your measure data, this may result in a large number of pie segments.
Note: You can also double-click a data field to add it to your Query field containers.
The pie chart displays on the canvas. You can add additional data fields for comparative purposes, or to create another pie chart on the same canvas. You can also view underlying data by hovering over any particular point on the pie chart.
Note: Each unique measure field is represented by a separate pie chart.
Note: You can also double-click a data field to add it to your Query field containers.
The matrix pie chart displays on the canvas. You can add additional data fields for comparative purposes, or to create another pie chart unique to the additional measure fields you select. You can also view underlying data by hovering over any particular point on the matrix pie chart.
How to: |
Ring pie charts are circular charts that display the total for the selected measure, as well as the individual segments that comprise the ring pie chart. You can hover over each segment to review the underlying data values. This is useful when comparing the measure value for an individual segment against the total for the measure, which displays in the center of the ring pie.
You can add one or more measures to the Measure field container. Each measure will be used to create a separate, unique ring pie chart, to which you can add a measure or dimension to the Color field container to add color to your chart.
Note: The font size of the value label in the middle of the ring is automatically set by the chart engine.
Use a ring pie chart when you want to review the value of each segment, which represents the measure value for the selected dimension, as it relates to the total for the selected measure. The following image is an example of a ring pie chart.
Note: You can also double-click a data field to add it to your Query field containers.
The ring pie chart displays on the canvas. The total for the selected measure displays in the center of the ring pie chart. You can view underlying data by hovering over any of the ring pie chart segments.
Note: Each unique measure field is represented by a separate ring pie chart.
Note: You can also double-click a data field to add it to your Query field containers.
The matrix ring pie chart displays on the canvas. You can add additional fields for comparative purposes, or to create another pie chart unique to the additional measure fields you select. You can also view underlying data by hovering over any particular point on the matrix ring pie chart.
How to: |
Scatter charts enable you to plot data using variable scales on both axes. When you use a scatter chart, the data is plotted with a hollow marker, so that you can visualize the density of individual data values around particular points, or discern patterns in the data. A numeric X axis, or sort field, always yields a scatter chart, by default.
Note: You can specify a non-measure (dimension) data field on the horizontal or vertical axis, or both.
If your chart reveals clouds of points, there is a strong relationship between X and Y values. If data points are scattered, there is a weak relationship, or no relationship.
Adding data fields to the Detail Query field container creates additional BY fields on the scatter chart. For example, the following image shows the results when adding the Product,SubCategory and Model dimension fields to Detail Query field container in a scatter chart which showed gross profit and MSRP data.
Note: You can also double-click a data field to add it to your Query field containers.
The scatter chart displays on the canvas. You can also view underlying data by hovering over any particular point on the scatter chart.
How to: |
A bubble chart is a chart in which the data points are represented by bubbles. Bubble charts can have two column fields representing X and Y data values, or have three column fields representing X, Y, and Z data values, in that order. The Z variable represents size. The size of each bubble is used to show the relative importance of the data.
When you add a data field to the Size field container, this value is represented as the Z Axis Title in the legend. It displays as an empty Z Axis Title when a size data field is not specified. If you choose to indicate a Z, or size, data value, the data label displays in the legend. A Size Legend also displays, showing the estimated data value for a range of circle sizes. This allows you to estimate the value of the data based on the size of the circle.
Note:
In the following image, a bubble chart is used to show the Manufacturer's Suggested Retail Price (MSRP) plotted against Revenue for a variety of electronics products. It also shows the values for Gross Profit, which was specified in the Size field container in the Query pane.
Note: You can also double-click a data field to add it to your Query field containers.
The bubble chart displays on the canvas. You can also view underlying data by hovering over any particular point on the bar chart.
How to: |
Matrix marker charts are useful for analyzing one or two measures against a crosstab of two categorical dimensions. You can use the Size Query field container for one measure and the Color Query field container for a second measure. The result is a color-scaled matrix chart that shows categorized trends, as shown in the following image.
The matrix marker chart displays.
How to: |
Treemaps are used to display large amounts of hierarchically structured data. Using a set of nested rectangles to illustrate data relationships, sections of a treemap represent branches of a tree. Each branch is given a rectangle, to which any number of smaller sub-branches can be assigned. The size of each branch is proportional to the summed values of the elements inside the branch.
The following treemap shows the categories of the selected dimension fields, using two data fields to determine the size and color of the treemap segments.
The treemap displays.
How to: |
Gauges are used to display the value of a measure. In particular, circular gauges are used to represent a single data value within a given spectrum. These gauges have a circular shape. You can create a single circular gauge for a measure or a matrix circular gauge, which shows the value of the selected measure across different dimensions, such as product category or yearly sales. The value of the measure that displays in a circular gauge is determined by the underlying data stored for that measure in the database.
The circular gauge functionality uses only one measure in its presentation. The legend reflects the color of the measure within the circular gauge.
In the following example, we review revenue data for each product category by quarterly sales in a matrix circular gauge chart.
Note: You can also double-click a data field to add it to your Query field containers.
The circular gauge displays on the canvas. You can select additional measure fields for which to include in the tooltip.
Note: Since the gauge relies on a constant (measure field), each intersection of the matrix chart is calculated using that measure along with the various matrix rows and columns in the matrix chart.
Note: You can also double-click a data field to add it to your Query field containers.
The matrix circular gauge displays on the canvas. You can select additional measure fields for which to include in the tooltip.
How to: |
A heatmap is a graphical representation of data where the individual values that comprise a matrix are represented as colors. Using radiant hues, you can track the intensity of a data relationship using the colors defined in the legend.
Heatmaps are useful when you are looking for hot spots in your data, or areas of focus or interest, as shown in the following image.
Note: You can optionally populate the Matrix Rows and Columns fields to increase the segmentation of your heatmap.
The heatmap displays.
How to: |
Matrix charts are powerful, comparative tools. They provide enough detail to show a trend and they organize information in a categorical fashion.
Matrix charts display data in a grid, showing the comparative values on either axis. They provide you with a quick glance at trends over time, giving you a succinct synopsis of a situation (for example, sales or investment trends).
You can use various formats in your matrix chart (for example, pie or line chart).
In the following example, we review quarterly revenue data, by product category, for a range of years (2014 - 2016, specifically). Using a bar chart for the matrix, we are able to review how gross profit for each product category shifts over time.
You can plot one value on the X axis and one value on the Y axis. For example, sales against region. You can also plot just one value for the rows or columns in the matrix chart.
The matrix chart displays on the canvas. You can view underlying data by hovering over any particular point on the chart.
Note: You can change the bar matrix chart to a line, area, or pie matrix chart by changing the type of visual in the Visual group on the Home tab.