# Ways to Apply Pivot Table Calculations

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

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.

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

## 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.

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

## 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.

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.

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.

## 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.

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 bottom
right cell.

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.

## 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
```

.

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`

.

## 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).

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.

## 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).

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.

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.

## 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).

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.

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.