Creating Charts and Gauges



Charts and gauges can be generated to give a visual overview of your analysis.


Select the ‘Add Chart’ tab to use the feature for creating charts and gauges. A separate Chart panel with its own configuration area will be displayed:


Here's how to use this feature:

  1. Select the relevant item for the type of chart to be created - Specific controls will be displayed, depending on the selected type.

  2. Assuming a Bar chart was selected, select the ‘Label Column’ - This provides data for the X-axis of the chart. If the column selected is a date type column, an interval control (Year, Quarter, Month, Day) will be displayed.

  3. Select the ‘Data Column’ (Y-axis data, the "height" of each bar). You'll see that the options are grouped and colour-coded to make it easier for you to identify them. If you created any Formula columns, they'll be in there, too. You can also choose to show the actual data values on the chart.

    • Select a Data Aggregation function. Options include: Sum, Average, Standard Deviation, Count, Distinct Count, Minimum, and Maximum (columns with null values are excluded by from aggregations)
    • Select whether or not to show the actual data values as labels within the chart.
  4. The ‘Additional Column’ specifies a second data series that will be charted along with the Data Column values for comparison. Depending on the chart type, other controls will appear for use configuring a second series, including aggregation options and charting types.

  5. Bar Orientation allows you to choose whether the bars are vertical or horizontal

    • Like the chart shown above, Bar charts that are not time-oriented will automatically be shown in a horizontal format. This allows greater clarity in reading the "X-axis" label text.
  6. Relevance allows you to tune the data to be shown. Options include Automatic, Rank, and Percentage.

Although not shown above, depending on the data being used, the option for Data Forecasting can also be available for Bar, Line, and Curved Line charts - See the section below for more information.

Select the ‘OK’ button to apply all of your selection changes to the chart at once. - Hide the chart configuration area by clicking the Gear icon, or delete the chart by selecting the Bin icon.

Charts are displayed in their own panels, so you can expand and collapse them using the relevant ‘+’ and ‘-’ icons - You can also rearrange the order of chart and table panels by selecting it with your mouse near the top of a panel, and dragging it up or down.


Charts will automatically include Quicktips, which appear when you hover your mouse over a data value, as shown above. In addition, ‘resizing handles’ (circled, in red above) will appear when the mouse is over the chart, allowing you to drag and resize the chart.

Data Forecasting


Data Forecasting, is available for Bar, Line, and Curved Line charts.

If it's available, extra controls for it will appear in the Chart configuration panel, as shown above.

Data forecasting is the process of generating values based on events that have not yet occurred. "Prediction” is a similar but more general term. Forecasting refers to formal, statistical methods that use time series, cross- sectional, or longitudinal data to produce predicted data. Typically, forecasts are displayed most effectively on charts.

Forecasting analysis options include:

  • Time Series (Time Series Decomposition), consisting of data in a natural, time-related order with a strong interval, where the Label Column data is of DateTime-type and the Data Column is a number.
  • Regression, using one of several regression analysis functions. Regression analysis is recommended when the focus is on a relationship between a dependent value and one or more independent values. Available regression analysis functions include:
    • Linear - used to calculate predictive values based on a trend line.
    • Autoregressive - used when attempting to predict an output of a system based on previous outputs. The estimation technique used is based on "Burg's" method.
    • Exponential, Logarithmic, Polynomial, or Power - non-linear types used to display the relationship between dependent and independent variables as a curvilinear function, which may provide more accuracy than a linear regression.
  • Trend Line - Used to plot a trend within a dataset there are two options available to display this; straight or curved

Click the Gear icon to hide the configuration area.

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