Charts in Virtuous Analytics are graphical representations of data that provide visual context to your analysis. By incorporating visualizations into your workbook, you can uncover patterns, trends, outliers, and correlations essential for crafting a compelling data story.
When selecting which Chart, consider the type of data, questions to be answered, and the audience. This ensures clear and detailed storytelling in your analysis.
Types of Charts
Here are several Charts you can add to your Virtuous Analytics report:
- Bar Chart: Display variations in values across categories or data groups. Compare values to each other, against a reference point, or as proportions of a whole. You can create simple single-series bar charts or develop advanced charts to compare multiple variables.
- Line Chart: Illustrate changes in one or more metrics over time. Identify trends and anomalies within your dataset. You can also create advanced multi-line charts to analyze and compare multiple variables over the same period of time.
- Combo Chart: Combine bar, line, area, and/or point marks to compare multiple types of metrics. Evaluate the relationship to identify correlations and variations between the datasets.
- Area Chart: Illustrate the magnitude or cumulative values of one or more metrics over time. Compare categories or groups of data, or evaluate the data composition or part-to-whole relationship.
- KPI Chart: Emphasize a single metric value to assess performance or progress toward a goal. Summarize the total value for a specific period, track changes over time, or compare against benchmarks or targets.
- Donut and Pie Chart: Both of these Chart types portray values as proportions of a whole to convey the data distribution and part-to-whole relationship.
- Scatter Chart: Demonstrate the presence and strength of a correlation between metrics. Analyze patterns, understand distribution, and identify outliers in your dataset.
- Box Chart: Show the value distribution of one or more metrics. Mark the minimum, median, and maximum values, and identify outliers in your dataset.
- Waterfall Chart: Show changes in one or two categories of data over a time period.
- Sankey Chart: Show how data flows and changes throughout a process or system. Compare the movements and proportions of data across different paths to analyze distributions, workflow, networks, and more.
- Funnel Chart: Measure values across sequential stages in a linear process. Gain insight into inputs across stages, identify bottlenecks and other issues, and assess the overall health of the process.
- Gauge Chart: Measure a single-value metric against a radial scale. Evaluate growth, assess performance, and track progress toward a goal.
- Region Map: Illustrate data distribution by region, including country, state, county, and city. Compare scale to identify variability and patterns across distinct geographical areas.
- Point Map: Illustrate data distribution with precise positioning based on latitude and longitude coordinates. Reveal geospatial patterns and identify outliers in your dataset.
- Geography Map: Demonstrate data distribution, reveal patterns, illustrate spatial networks, or assess data variability across distinct geographical areas.
Building a Chart
There are a couple of ways to begin the process of building a Chart into your Workbook.
1. Click the Chart icon in the Element Bar at the bottom of the screen to view the various types of Charts. Once your Chart type is chosen, select the source, or dataset, for the Chart.
2. Alternatively, click the toolbox in the upper right-hand corner of a Table in your Workbook and select the Chart icon (bar chart with a plus sign).
Configuring Element Properties
Use the Element Properties menu in the navigation bar on the right-hand side to begin customization.
From here, drag and drop your source data into the designated axes or value areas or select the plus signs in the axis boxes to add a new column. Add complexity by adding multiple columns to the X or Y axis. You can further group the data by using Trellis rows and columns. Use the Element Properties to further customize your Chart with Color options, Tooltips, Trellis groupings, and Labels for your datapoints.
Aggregate Settings and Limits
Note: Bar charts support up to 25,000 data points. If your data set exceeds this limit, the Chart will show the first 25,000 points and a warning message will indicate the chart is incomplete. To reduce the number of data points, consider aggregating the values or applying data filters.
To change aggregate value settings, select the down arrow next to the chart variable.
Then click Set Aggregate to view other aggregate options.
Maps Configuration
Regardless of the Chart type you select, the process from start to finish is generally similar for all types, including Maps.
Virtuous Analytics supports three types of Maps: Region, Point, and Geography. The key is to choose your Map type based on your data and what you want to show. For example, Region Maps require a text-based or number-based column source to pull states or zip codes where Point Maps require a number-based column source to pull longitude and latitude coordinates. Geography Maps require WKT or JSON data to build the visualization.
Just like all other Charts, Maps can be customized using the Elements Properties menu on the right-hand side to configure different colors, labels, tooltips, or change the Chart type or data source altogether.
Final Adjustments
Once your Chart elements are customized, you can resize them directly from the dashboard by clicking and dragging the corners. You can also move Charts to different locations on the dashboard to improve the overall appearance and presentation.