1: Customizing Data Calculations

You can apply customized formulas to aggregated data sets. The following table lists the variables that you can use as building blocks for your customized formula.

In both examples below, formula <formula> is the actual formula to use for the customized data calculation.

Example: Shows the Formula in the Table

In the following example, the stats formula shows a formula in the table as shown in the graphic.

table "(mean * count) / median "
  stats formula,mean,median,sum,count,stddev,stderr,pct
  formula (mean * count) / median
  row q2.r1.val Brand A
  row q2.r2.val Brand B
  row q2.r3.val Brand C
  width 6

Example: Shows the Formula for the Chart Value

In this example, chart.stat formula uses the formula for the chart value as shown in the graphic.

chart "Mean Doubled"
  chart.stat formula
  formula mean * 2
  width 6 

table "Specify pre/postfix values"
  formula sum
  stats formula
  datapostfix '%'
  row "q1.r1.val"
  row datapostfix="*" "q1.r2.val" # overrides the original postfix
  row datapostfix="" "q1.r3.val"  # overrides the original postfix
  row dataprefix="$" "q1.r4.val"  # adds a prefix

table width=6 "Format Currency"
  formula sum
  stats formula
  dataformat currency
  dataprefix $
  row "q3.r1.val"
#outputs the sum of all q3.r1 entries as: "$X,XXX.00"

2:  Add Per-Table Weighting

A dashboard hook is available that enables you to control weight applied to a table based on a combination of table, selected filters and/or banners.

To create custom weights, add a file named dashboard_custom.py to your project directory containing a Python method named custom_weight. For example:

def custom_weight(banner, filters, table):
    # custom weight logic goes here

To add weights, we can reference the banner, filters and table variables to customize the weights that are applied. For example, given the following dashboard:

filter id=myFilter1 1 Weight #1
filter id=myFilter2 1 Weight #2

banner id=myBanner1 Weight #3
   segment 1 Brand 1
   segment 1 Brand 2

table id=myTable1 Table #1
    rows q1.r1-r3

table id=myTable2 Table #2
    rows q1.r1-r3

Using the id names of each component, we can add custom weights as illustrated below:

def custom_weight(banner, filters, table):
    # if current banner is "myBanner1", set weight to 4
    # this has first priority
    if banner == "myBanner1":
        return "4"

    # if filters are enabled, set a different weight depending on which is selected
    if "myFilter1" in filters:
        # set weight to 2 for "myFilter1"
        return "2"
    if "myFilter2" in filters:
        # set weight to 2.5 for "myFilter2"
        return "2.5"

    # for one specific table, set weight to "1.25"
    if table == "myTable2":
        return "1.25"

    # if none of the conditions above are met, set weight to default "1"
    return "1"

With the code above applied to dashboard_custom.py, custom weights will be used when viewing the dashboard.

For example, "myTable2" will have a weight of 1.25 if no filters or banners are set. "myTable1" will have the default weight of 1. If "myBanner1" is selected, then all weights will be set to 4.

Since this is simple Python code, you may prioritize these settings and combine those things in any manner you want. For example:

def custom_weight(banner, filters, table):
    # if current banner is "myBanner1", set weight to 4
    # this has first priority
    if banner == "myBanner1":
        if table == "myTable1":
            return "2"
        if table == "myTable2":
            return "2.5"

    return "1"

In the example above, we set table-specific weights only when "myBanner1" is selected.

3:  What's Next for Creating a Dashboard

The following topics describe the features that you can apply to your dashboard:

• Creating a Research Dashboard
• Enhancing a Dashboard with Add-ons and Extensions
• Managing a Dashboard