Using function fields in charts

In the Reports app, function fields create a new field in a chart that is based on a report field that already has a function applied to it. Use function fields in charts to include aggregate measures such as trends, averages, and variances.

How it works

A function field is a tool that performs complex calculations or operations on a report field that already has a function applied to it. Function fields accept an input and return an output.

Example

Scenario

You want to visualize the average cost impact for issues identified across multiple projects.

Process

You create a horizontal bar chart, and include the following fields in your chart:

  • Horizontal Axis Sum Cost Impact
  • Vertical Axis Issue Title

You add the Average function field in the chart and apply it to Sum Cost Impact.

Result

The average cost impact for issues across multiple projects is indicated by the dotted blue line in the chart:

Average cost impact for issues

Permissions

Only Report Admins and Report Writers can add a function field to a chart.

Add a function field to a chart

  1. Open the Reports app.

    The Browse page opens.

  2. Open the appropriate report and click Edit > Charts.
  3. Click on the thumbnail of the appropriate chart at the bottom of the screen.

    The chart displays in the preview window.

  4. Drag the appropriate function field from the Functions list to your chart building area, and configure any of the settings, as required.

    Tip

    You can apply basic function fields, such as average, trend, forecast, and accumulation, to advanced function fields (set analysis or variance). Click the down arrow next to the advanced function field, select Add Function, and select a basic function field.

Available function fields

Average

Type Description
Mean displays a line calculated as the sum of all values, divided by the number of values in the chart
Median

displays a line calculated by ordering all the values in ascending order and using the middle value

This can be a more useful measure than mean if the data contains extreme outliers.
Mode displays a line calculated by finding the value which occurs most in the chart

Trend

Type Description Associated settings
Auto Trend similar to Auto Chart, applies an automatic trend function to the chart based on complex algorithms
  • Confidence Intervals used to indicate a range where unknown or missing values are likely to fall
  • Interval Range specifies the certainty range of values to be displayed
Moving Average

displays the mean, calculated using values from a set number of periods before each point

For example, if your chart contains 10 periods, a moving average may be set to use 5 at a time. This can be used to follow changes in the data on a line that is smoother than the actual values, making it useful when displaying trends for noisy (spikey) data.

  • Periods specifies the number of periods the moving average will cover

    A higher number of periods will result in a smoother, but less responsive, trend line.

  • Missing Values specifies how missing data should be treated

    • Linear Interpolation gaps in the data will be treated as if they are on a line that connects the two bounding values
    • Treat as zero gaps in the data will be treated as zero
  • Confidence Intervals used to indicate a range where unknown or missing values are likely to fall
  • Interval Range specifies the certainty range of values to be displayed
Linear Regression

displays a straight line that indicates the relationship between the values on the x and y axes

This can be useful to give an idea of the general trend of data.
  • Confidence Intervals used to indicate a range where unknown or missing values are likely to fall
  • Interval Range specifies the certainty range of values to be displayed
Polynomial Regression

displays a curved line to the data which indicates the relationship between the values on the x and y axes

This can be used where the relationship between the values is not completely linear, for example if your trend has significant fluctuations through it.
  • Order specifies how many terms will make up the polynomial for the functions

    The higher the degree, the more tightly fitted the regression line.

  • Confidence Intervals used to indicate a range where unknown or missing values are likely to fall
  • Interval Range specifies the certainty range of values to be displayed

Forecast

Type Description Associated settings
Auto Trend similar to Auto Chart, applies an automatic trend function to the chart based on complex algorithms

  • Periods Forward specifies the number of periods into the future this function should forecast

    The granularity of these periods is controlled by the overall granularity of the chart.

  • Prediction Intervals used to indicate a range where the actual value is likely to fall
  • Interval Range specifies the certainty range of values to be displayed
  • Hide Non-Forecast Results specifies if forecast should be displayed either for the whole data set range OR only after the end of the data set range
Simple Exponential Smoothing

displays a forecast based on the average of previous values in the data set, with weighting defined by alpha (recent vs historic data)

This is useful or forecasting data which has no general trend or seasonality.
  • Alpha specifies how much weight is given to recent data vs older data

    The higher the alpha value, the more weight is given to recent data.

  • Periods Forward specifies the number of periods into the future this function should forecast

    The granularity of these periods is controlled by the overall granularity of the chart.

  • Missing Values specifies how missing data should be treated
    • Linear Interpolation gaps in the data will be treated as if they are on a line that connects the two bounding values
    • Treat as zero gaps in the data will be treated as zero
  • Prediction Intervals used to indicate a range where the actual value is likely to fall
  • Interval Range specifies the certainty range of values to be displayed
  • Hide Non-Forecast Results specifies if forecast should be displayed either for the whole data set range OR only after the end of the data set range
Double Exponential Smoothing

displays a forecast based on the average of previous values in the data set, with weighting defined by alpha (recent vs historic data) and beta (trend)

This is useful for forecasting data which has a general trend, but no seasonality.

same as Simple Exponential Smoothing, with the addition of:

Beta specifies how much weight is given to the trend of the data

The higher the beta value, the more weight is given to the data's trend.
Triple Exponential Smoothing

displays a forecast based on the average of previous values in the data set, with weighting defined by alpha (recent vs historic data), beta (trend), and gamma (seasonality)

This is useful for forecasting data which has a general trend and varies seasonally. Triple exponential smoothing requires at least two years of data for its seasonality calculations.

same as Double Exponential Smoothing, with the addition of:

Gamma specifies how much weight is given to the seasonality (what happened in corresponding periods of previous years)

The higher the gamma, the more weight is given to the data's seasonality.
Moving Average

displays the mean, calculated using values from a set number of periods before each point

For example, if your dataset contains 10 periods, a moving average may be set to use 5 at a time. This can be used to follow changes in the data on a line that is smoother than the actual values, making it useful when displaying trend for noisy (spikey) data.
  • Periods specifies the number of periods the moving average will cover

    A higher number of periods will result in a smoother, but less responsive trend line.

  • Periods Forward specifies the number of periods into the future this function should forecast

    The granularity of these periods is controlled by the overall granularity of the chart.

  • Missing Values specifies how missing data should be treated
    • Linear Interpolation gaps in the data will be treated as if they are on a line that connects the two bounding values
    • Treat as zero gaps in the data will be treated as zero
  • Prediction Intervals used to indicate a range where the actual value is likely to fall
  • Interval Range specifies the certainty range of values to be displayed
  • Hide Non-Forecast Results specifies if forecast should be displayed either for the whole data set range OR only after the end of the data set range

Accumulation

The Accumulation function field displays an accumulative percentage of the total line on the chart, using a secondary axis.

Set Analysis

The Set Analysis function field displays a subset of the data contained within a specified field.

To define a Set Analysis function field, you need to select a report metric field to base the results on, and specify the range of filters that will be applied solely to the field within the chart.

Setting Description
Set Name specifies the display name of the resulting set analysis field, used in the chart labels and / or legend
Set Metric

allows you to select the field to filter down to your specified set

Only metric fields included in your report are available in this list.
Filter

allows you to specify the filters to be applied to your set field

For more information, see Configuring filters in reports.

Variance

The Variance function field displays the difference between two fields from either the table or chart. Variance can be displayed as either the calculated value, or a percentage difference.

Setting Description
Variance Name specifies the display name of the resulting variance field, used in the chart labels and / or legend
Variance Between

allows you to select two fields to apply the variance calculation to

The values in the second field are subtracted from the values in the first field, as part of the calculation, so order is important.

There are two types of field available to be used as part of a variance:

  • Chart Fields all standard fields used in a chart will be available, as well as:
    • chart aggregated fields allows you to calculate the variance between the chart aggregated field and its original report field
    • set analysis fields allows you to calculate the variance between two sets
  • Report Fields all metrics included in your table

    You do not have to use a metric in your chart to include it in the variance calculation.
Display Variance as

allows you to select how the resulting variance values are displayed:

  • # Value displays the result of subtracting field one from field two, as a number
  • % Percentage displays the result of subtracting field one from field two, divided by field one (a percentage result)
  • % of Total Variance calculates the percentage of the total variance

    The total variance is either set on the report / chart field or is the default sum.

  • % Change in Relative Proportion calculates the percentage change in relative proportion

    The percentage of the total second value is subtracted from the percentage of the total first value, and the amount is divided by the percentage of the total second value. The total is either set on the values, or is the default sum.