A row that contains one or more aggregate calculations for each category within a dataset.

You can apply table calculations in the ways described following. Table calculations are applied to only one field at a time. Thus, if you have a pivot table with multiple values, calculations are only applied to the cells representing the field that you applied the calculation to.

Topics

  • Table across
  • Table down
  • Table across down
  • Table down across
  • Group across
  • Group down
  • Group across down
  • Group down across

Table across

Using Table across applies the calculation across the rows of the pivot table, regardless of any grouping. This application is the default. For example, take the following pivot table.

A row that contains one or more aggregate calculations for each category within a dataset.

Applying the Running total function using Table across gives you the following results, with row totals in the last column.

A row that contains one or more aggregate calculations for each category within a dataset.

Table down

Using Table down applies the calculation down the columns of the pivot table, regardless of any grouping. For example, take the following pivot table.

A row that contains one or more aggregate calculations for each category within a dataset.

Applying the Running total function using Table down gives you the following results, with column totals in the last row.

A row that contains one or more aggregate calculations for each category within a dataset.

Table across down

Using Table across down applies the calculation across the rows of the pivot table, and then takes the results and reapplies the calculation down the columns of the pivot table. For example, take the following pivot table.

A row that contains one or more aggregate calculations for each category within a dataset.

Applying the Running total function using Table across down gives you the following results. In this case, totals are summed both down and across, with the grand total in the lower-right cell.

A row that contains one or more aggregate calculations for each category within a dataset.

In this case, suppose that you apply the Rank function using Table across down. Doing so means that the initial ranks are determined across the table rows and then those ranks are in turn ranked down the columns. This approach gives you the following results.

A row that contains one or more aggregate calculations for each category within a dataset.

Table down across

Using Table down across applies the calculation down the columns of the pivot table. It then takes the results and reapplies the calculation across the rows of the pivot table. For example, take the following pivot table.

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Running total function using Table down across to get the following results. In this case, totals are summed both down and across, with the grand total in the lower-right cell.

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Rank function using Table down across to get the following results. In this case, the initial ranks are determined down the table columns. Then those ranks are in turn ranked across the rows.

A row that contains one or more aggregate calculations for each category within a dataset.

Group across

Using Group across applies the calculation across the rows of the pivot table within group boundaries, as determined by the second level of grouping applied to the columns. For example, if you group by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, Group across returns the same results as Table across.

For example, take the following pivot table where columns are grouped by Service Line and then by Consumption Channel.

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Running total function using Group across to get the following results. In this case, the function is applied across the rows, bounded by the columns for each service category group. The Mobile columns display the total for both Consumption Channel values for the given Service Line, for the Customer Region and Date (year) represented by the given row. For example, the highlighted cell represents the total for the APAC region for 2012, for all Consumption Channel values in the Service Line named Billing.

A row that contains one or more aggregate calculations for each category within a dataset.

Group down

Using Group down applies the calculation down the columns of the pivot table within group boundaries, as determined by the second level of grouping applied to the rows. For example, if you group by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, Group down returns the same results as Table down.

For example, take the following pivot table where rows are grouped by Customer Region and then by Date (year).

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Running total function using Group down to get the following results. In this case, the function is applied down the columns, bounded by the rows for each Customer Region group. The 2014 rows display the total for all years for the given Customer Region, for the Service Line and Consumption Channel represented by the given column. For example, the highlighted cell represents the total the APAC region, for the Billing service for the Mobile channel, for all the Date values (years) that display in the report.

A row that contains one or more aggregate calculations for each category within a dataset.

Group across down

Using Group across down applies the calculation across the rows within group boundaries, as determined by the second level of grouping applied to the columns. Then the function takes the results and reapplies the calculation down the columns of the pivot table. It does so within group boundaries as determined by the second level of grouping applied to the rows.

For example, if you group a row or column by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, Group across down returns the same results as Table across down.

For example, take the following pivot table where columns are grouped by Service Line and then by Consumption Channel. Rows are grouped by Customer Region and then by Date (year).

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Running total function using Group across down to get the following results. In this case, totals are summed both down and across within the group boundaries. Here, these boundaries are Service Line for the columns and Customer Region for the rows. The grand total appears in the lower-right cell for the group.

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Rank function using Group across down to get the following results. In this case, the function is first applied across the rows bounded by each Service Line group. The function is then applied again to the results of that first calculation, this time applied down the columns bounded by each Customer Region group.

A row that contains one or more aggregate calculations for each category within a dataset.

Group down across

Using Group down across applies a calculation down the columns within group boundaries, as determined by the second level of grouping applied to the rows. Then Amazon QuickSight takes the results and reapplies the calculation across the rows of the pivot table. Again, it reapplies the calculation within group boundaries as determined by the second level of grouping applied to the columns.

For example, if you group a row or column by field-2 and then by field-1, grouping is applied at the field-2 level. If you group by field-3, field-2, and field-1, grouping is again applied at the field-2 level. When there is no grouping, Group down across returns the same results as Table down across.

For example, take the following pivot table. Columns are grouped by Service Line and then by Consumption Channel. Rows are grouped by Customer Region and then by Date (year).

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Running total function using Group down across to get the following results. In this case, totals are summed both down and across within the group boundaries. In this case, these are Service Category for the columns and Customer Region for the rows. The grand total is in the lower-right cell for the group.

A row that contains one or more aggregate calculations for each category within a dataset.

You can apply the Rank function using Group down across to get the following results. In this case, the function is first applied down the columns bounded by each Customer Region group. The function is then applied again to the results of that first calculation, this time applied across the rows bounded by each Service Line group.

A row that contains one or more aggregate calculations for each category within a dataset.

Why would you create a slicer for a PivotTable?

Slicers provide buttons that you can click to filter tables, or PivotTables. In addition to quick filtering, slicers also indicate the current filtering state, which makes it easy to understand what exactly is currently displayed. You can use a slicer to filter data in a table or PivotTable with ease.

What is an association between tables where both tables contain a common field?

A table relationship works by matching data in key fields — often a field with the same name in both tables. In most cases, these matching fields are the primary key from one table, which provides a unique identifier for each record, and a foreign key in the other table.

Do you want to create a PivotTable that uses fields from to Excel tables What is the first step?

Create a PivotTable in Excel for Windows.
Select the cells you want to create a PivotTable from. ... .
Select Insert > PivotTable..
This will create a PivotTable based on an existing table or range. ... .
Choose where you want the PivotTable report to be placed. ... .
Click OK..

What is the default function for values in PivotTable?

Change the summary function or custom calculation for a field in a PivotTable report.