# 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.