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bgColor	white
titleBGColor	#f5f5f5
title	Combining Table Filter, Pivot Table and Table Chart macros

Table Filter for Confluence add-on allows you to transform you table data in the convenient view with the combination of Table Filter, Pivot Table and Table Chart. The combination of all these macros allows you to generate the pivot table with aggregated data that can be further used for visualization and chart generation. Filtration of your table data will also lead to automatic update of the pivot table and the chart.

Table filter add-on allows you to combine the following macros for your better performance with data tables:

Info
Combining the macros is not allowed in the new Confluence Cloud editor.

Widget Connector

width	432
url	https://www.youtube.com/watch?v=8nxGN3ETbv8
height	243

Working with Table filter and Table chart macro

Create or import a table with data values.
Insert the Table filter macro and place the table within the macro.
Configure the filtration parameters. For example, add filters by number range for the corresponding columns.
Insert the Table chart macro.
Place the Table filter macro with the table inside the Table chart macro.
Configure parameters of the chart. For example, select the chart type as 'Column' and select the columns with row labels and data columns.
Save the page.
Enter the appropriate number range in the filter. Filtration will be automatically applied to the data table and the chart will be automatically updated.
Change the Values column for another one, if needed.

Expand

title	Click to open the sample table...

Chart from Table

tfc-width	800
tfc-height	300
column	Agent
datepattern	yy-mm-dd
aggregation	Average Time per Call (min)
id	1435769205495_0
type	Column
separator	Point (.)

Table Filter

hideColumns	true
datepattern	yy-mm-dd
numberfilter	Average Time per Call (min),Average Time per Ticket (min),Calls per Hour
id	1435769251693_1810815350
separator	Point (.)

Agent	Tickets per Hour	Average Time per Ticket (min)	Calls per Hour	Average Time per Call (min)	Earned Money for Support ($)
Remy Deomampo	6.9	3.0	2.2	6.1	2 875.00
Rahul Dickstein	8.0	1.6	4.4	4.8	5 270.00
Radu Donahue	3.6	7.0	3.7	5.2	4 886.00
Preston Doorey	2.2	6.9	4.8	7.5	5 237.00
Phill Doyle	4.4	5.7	2.4	4.6	3 140.00
Philip Druckman	4.5	2.3	2.6	4.3	5 249.00
Philip Duncan	7.5	3.2	1.1	5.3	2 572.00
Peter Elia	6.7	6.1	4.7	6	2 944.00
Peter Erickson	8.1	5.9	2.1	6.3	3 767.00
Peter Espinosa	2.7	5.3	4.6	6.2	3 206.00
Peter Ferrero	4.3	3.2	4.0	7.2	3 625.00
Perez Figueiredo	5.6	1.7	4.9	7.6	1 399.00
Patrick Fixler	5.8	3.5	3.8	4.3	5 121.00
Patrick Flegal	8.7	4.9	2.0	7.3	4 170.00
Patino Forsyth	8.8	1.4	2.9	4.2	2 032.00
Pallavi Fox	2.9	4.4	3.6	5	3 418.00
Owen Franzoni	2.6	5.0	1.3	4.9	1 364.00
Ophir Friedman	6.3	3.3	2.0	6.8	3 554.00
Obaid Friis	5.7	2.4	4.8	3.9	4 005.00
Noelle Fu	3.6	3.1	3.4	3.3	4 672.00
Noel Gambino	4.9	1.1	1.8	7.1	4 711.00
Nicole Gao	2.9	5.8	1.6	5.4	4 908.00
Nishant Gao	5.7	1.2	4.6	5.5	5 162.00
Nicole Garcia	2.7	4.1	3.0	5.4	4 227.00
Negrin Gee	5.8	2.6	4.2	4.3	2 701.00

Working with Table filter and Pivot table macro

Create or import a table with data values.
Insert the Table filter macro and place the table within the macro.
Configure the filtration parameters. For example, add the filter by agent.
Insert the Pivot table macro.
Place the Table filter macro with the table inside the Pivot table macro.
Configure parameters of the pivot table. For example, select the Agent column as row labels and the Earned Money for Support as the calculated column.
Save the page.
Select the appropriate agents in the filter. Filtration will be automatically applied to the data table and the pivot table will be automatically updated.
Change the calculated column for another one, if needed.

Expand

title	Click to open the sample table...

Pivot Table

decimals	2
column	Agent
decimalseparator	Point (.)
aggregation	Earned Money for Support ($)
id	1474440979405_205582813
type	Average
separator	Space ( )

Table Filter

hideColumns	true
column	Agent
datepattern	yy-mm-dd
id	1474440979407_205582813
separator	Point (.)

Agent	Tickets per Hour	Average Time per Ticket (min)	Calls per Hour	Average Time per Call (min)	Earned Money for Support ($)
Remy Deomampo	6.9	3.0	2.2	6.1	2 875.00
Rahul Dickstein	8.0	1.6	4.4	4.8	5 270.00
Radu Donahue	3.6	7.0	3.7	5.2	4 886.00
Preston Doorey	2.2	6.9	4.8	7.5	5 237.00
Remy Deomampo	4.4	5.7	2.4	4.6	3 140.00
Rahul Dickstein	4.5	2.3	2.6	4.3	5 249.00
Radu Donahue	7.5	3.2	1.1	5.3	2 572.00
Preston Doorey	6.7	6.1	4.7	6	2 944.00
Phill Doyle	8.1	5.9	2.1	6.3	3 767.00
Remy Deomampo	2.7	5.3	4.6	6.2	3 206.00
Rahul Dickstein	4.3	3.2	4.0	7.2	3 625.00
Radu Donahue	5.6	1.7	4.9	7.6	1 399.00
Preston Doorey	5.8	3.5	3.8	4.3	5 121.00
Remy Deomampo	8.7	4.9	2.0	7.3	4 170.00
Rahul Dickstein	8.8	1.4	2.9	4.2	2 032.00
Radu Donahue	2.9	4.4	3.6	5	3 418.00
Preston Doorey	2.6	5.0	1.3	4.9	1 364.00
Phill Doyle	6.3	3.3	2.0	6.8	3 554.00
Remy Deomampo	5.7	2.4	4.8	3.9	4 005.00
Remy Deomampo	3.6	3.1	3.4	3.3	4 672.00
Rahul Dickstein	4.9	1.1	1.8	7.1	4 711.00
Radu Donahue	2.9	5.8	1.6	5.4	4 908.00
Preston Doorey	5.7	1.2	4.6	5.5	5 162.00
Phill Doyle	2.7	4.1	3.0	5.4	4 227.00
Philip Druckman	5.8	2.6	4.2	4.3	2 701.00

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Versions Compared

Old Version 15

New Version 16

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Working with Table filter and Table chart macro

Working with Table filter and Pivot table macro