The best way to understand the concept of a pivot table is to see one. Start with Figure 34.1, which shows a portion of the data used in creating the pivot table in this chapter.

Figure 34.1. This table is used to create a pivot table.

This table consists of a month’s worth of new account information for a three-branch bank. The table contains 712 rows, and each row represents a new account. The table has the following columns:

The bank accounts database contains quite a bit of information. But in its current form, the data doesn’t reveal much. To make the data more useful, you need to summarize it. Summarizing a database is essentially the process of answering questions about the data. Following are a few questions that may be of interest to the bank’s management:

You can, of course, spend time sorting the data and creating formulas to answer these questions. Often, however, a pivot table is a much better choice. Creating a pivot table takes only a few seconds, doesn’t require a single formula, and produces a nice-looking report. In addition, pivot tables are much less prone to error than creating formulas. (Later in this chapter, you’ll see several pivot tables that answer the preceding questions.)

Figure 34.2 shows a pivot table created from the bank data. This pivot table shows the amount of new deposits, broken down by branch and account type. This particular summary represents one of dozens of summaries that you can produce from this data.

Figure 34.2. A simple pivot table.

Figure 34.3 shows another pivot table generated from the bank data. This pivot table uses a drop-down Report Filter for the Customer item (in row 1). In the figure, the pivot table displays the data only for Existing customers. (The user can also select New or All from the drop-down control.) Notice the change in the orientation of the table? For this pivot table, branches appear as column labels, and account types appear as row labels. This change, which took about five seconds to make, is another example of the flexibility of a pivot table.

Figure 34.3. A pivot table that uses a report filter.

A pivot table requires that your data is in the form of a rectangular database. You can store the database in either a worksheet range (which can be a table or just a normal range) or an external database file. Although Excel can generate a pivot table from any database, not all databases benefit.

Generally speaking, fields in a database table consist of two types:

A single database table can have any number of data fields and category fields. When you create a pivot table, you usually want to summarize one or more of the data fields. Conversely, the values in the category fields appear in the pivot table as rows, columns, or filters.

Exceptions exist, however, and you may find Excel’s pivot table feature useful even for databases that don’t contain actual numerical data fields. Chapter 35 has an example of a pivot table created from non-numeric data.

Figure 34.4 shows an example of an Excel range that is not appropriate for a pivot table. This range contains descriptive information about each value, but it’s not set up as a table. In fact, this range resembles a pivot table summary.

Figure 34.4. This range is not appropriate for a pivot table.

If your data is in a worksheet range, select any cell in that range and then choose Insert Tables PivotTable, which displays the dialog box shown in Figure 34.5.

Figure 34.5. In the Create PivotTable dialog box, you tell Excel where the data is and where you want the pivot table.

Excel attempts to guess the range, based on the location of the active cell. If you’re creating a pivot table from an external data source, you need to select that option and then click Choose Connection to specify the data source.

Use the bottom section of the Create PivotTable dialog box to indicate the location for your pivot table. The default location is on a new worksheet, but you can specify any range on any worksheet, including the worksheet that contains the data.

Click OK, and Excel creates an empty pivot table and displays its PivotTable Field List, as shown in Figure 34.6.

Figure 34.6. Use the PivotTable Field List to build the pivot table.

Next, set up the actual layout of the pivot table. You can do so by using either of these techniques:

The following steps create the pivot table presented earlier in this chapter (see “A pivot table example”). For this example, I drag the items from the top of the PivotTable Field List to the areas in the bottom of the PivotTable Field List.

Figure 34.7. After a few simple steps, the pivot table shows a summary of the data.

Pivot Table Terminology

Understanding the terminology associated with pivot tables is the first step in mastering this feature. Refer to the accompanying figure to get your bearings.

• Column labels: A field that has a column orientation in the pivot table. Each item in the field occupies a column. In the figure, Customer represents a column field that contains two items (Existing and New). You can have nested column fields.

• Grand totals: A row or column that displays totals for all cells in a row or column in a pivot table. You can specify that grand totals be calculated for rows, columns, or both (or neither). The pivot table in the figure shows grand totals for both rows and columns.

• Group: A collection of items treated as a single item. You can group items manually or automatically (group dates into months, for example). The pivot table in the figure does not have any defined groups.

• Item: An element in a field that appears as a row or column header in a pivot table. In the figure, Existing and New are items for the Customer field. The Branch field has three items: Central, North County, and Westside. AcctType has four items: CD, Checking, IRA (Investment Retirement Account), and Savings.

• Refresh: Recalculates the pivot table after making changes to the source data.

• Row labels: A field that has a row orientation in the pivot table. Each item in the field occupies a row. You can have nested row fields. In the figure, Branch and AcctType both represent row fields.

• Source data: The data used to create a pivot table. It can reside in a worksheet or an external database.

• Subtotals: A row or column that displays subtotals for detail cells in a row or column in a pivot table. The pivot table in the figure displays subtotals for each branch.

• Table Filter: A field that has a page orientation in the pivot table—similar to a slice of a three-dimensional cube. You can display only one item (or all items) in a page field at one time. In the figure, OpenedBy represents a page field that displays the New Accts item. In previous version of Excel, a table filter was known as a Page field.

• Values area: The cells in a pivot table that contain the summary data. Excel offers several ways to summarize the data (sum, average, count, and so on).

Notice that the pivot table uses General number formatting. To change the number format used, select any value and choose PivotTable Tools Options Active Field Field Settings to display the Data Field Settings dialog box. Click the Number Format button and change the number format.

You can apply any of several built-in styles to a pivot table. Select any cell in the pivot table and choose PivotTable Tools Design PivotTable Styles to select a style.

You also can use the controls in the PivotTable Design Layout group to control various elements in the pivot table. For example, you can choose to hide the grand totals if you prefer.

The PivotTable Tools Options Show/Hide group contains additional options that affect the appearance of your pivot table. For example, you use the Show Field Headers button to toggle the display of the field headings.

Still more pivot table options are available in the PivotTable Options dialog box, shown in Figure 34.8. To display this dialog box, choose PivotTable Tools Options PivotTable Options Options. Or, rightclick any cell in the pivot table and choose Table Options from the shortcut menu.

Figure 34.8. The PivotTable Options dialog box.

Pivot Table Calculations

Pivot table data is most frequently summarized using a sum. However, you can display your data using a number of different summary techniques. Select any cell in the Values area of your pivot table and then choose PivotTable Tools Options Active Field Field Settings to display the Data Field Settings dialog box. This dialog box has two tabs: Summarize By and Show Values As.

Use the Summarize By tab to select a different summary function. Your choices are Sum, Count, Average, Max, Min, Product, Count Numbers, StdDev, StdDevp, Var, and Varp.

To display your values in a different form, use the drop-down control in the Show Values As tab. Your choices are described in the following table.

Function	Result
Difference From	Displays data as the difference from the value of the Base item in the Base field.
% Of	Displays data as a percentage of the value of the Base item in the Base field.
% Difference From	Displays data as the percentage difference from the value of the Base item in the Base field.
Running Total	Displays the data for successive items in the Base field as a running total.
% Of Row	Displays the data in each row or category as a percentage of the total for the row or category.
% Of Column	Displays all the data in each column or series as a percentage of the total for the column or series.
% Of Total	Displays data as a percentage of the grand total of all the data or data points in the report.
Index	Calculates data as follows: ((value in cell) x (Grand Total of Grand Totals)) / ((Grand Row Total) x (Grand Column Total))

Once you’ve created a pivot table, it’s easy to change it. For example, you can add further summary information by using the PivotTable Field List. Figure 34.9 shows the pivot table after I dragged a second field (OpenedBy) to the Row Labels section in the PivotTable Field List.

Figure 34.9. Two fields are used for row labels.

The following are some tips on other pivot table modifications you can make:

Figure 34.10. The pivot table is filtered by date.

What is the daily total new deposit amount for each branch?

Figure 34.11 shows the pivot table that answers this question.

Figure 34.11. This pivot table shows daily totals for each branch.

Note that the pivot table can also be sorted by any column. For example, you can sort the Grand Total column in descending order to find out which day of the month had the largest amount of new funds. To sort, just right-click any cell in the column to sort and choose Sort on the shortcut menu.

How many accounts were opened at each branch, broken down by account type?

Figure 34.12 shows a pivot table that answers this question.

Figure 34.12. This pivot table uses the Count function to summarize the data.

The most common summary function used in pivot tables is Sum. In this case, I changed the summary function to Count. To change the summary function to Count, right-click any cell in the Value area and choose Summarize Data By Count from the shortcut menu.

What’s the dollar distribution of the different account types?

Figure 34.13 shows a pivot table that answer this question. For example, 253 of the new accounts were for an amount of $5,000 or less.

Figure 34.13. This pivot table counts the number of accounts that fall into each value range.

This pivot table is unusual because it uses only one field: Amount.

When I initially added the Amount field to the Row Labels section, the pivot table showed a row for each unique dollar amount. I right-clicked one of the Row Labels and selected Group. Then I used Excel’s Grouping dialog box to set up bins of $5,000 increments.

The second instance of the Amount field (in the Values section) is summarized by Count. I right-clicked a value and chose Summarize Data By Count.

I added another instance of Amount to the Values section, and I set it up to display the percentage. I used the Show Values As tab of the Data Field Settings dialog box and specified % Of Total. To display the Data Field Settings dialog box, right-click any cell and choose Summarize Data As More Options.

What types of accounts do tellers open most often?

Figure 34.14 shows that the most common account opened by tellers is a Checking account.

Figure 34.14. This pivot table uses a Report Filter to show only the Teller data.

This pivot table uses the OpenedBy field as a Report Filter and is showing the data only for Tellers. I sorted the data so that the largest value is at the top, and I also used conditional formatting to display data bars for the percentages.

How does the Central branch compare to the other two branches?

Figure 34.15 shows a pivot table that sheds some light on this rather vague question. It simply shows how the Central branch compares to the other two branches combined.

Figure 34.15. This pivot table (and pivot chart) compares the Central branch with the other two branches combined.

I grouped the North County and Westside branches together and named the group Other. The pivot table shows the amount, by account type. I also created a pivot chart for good measure.

In which branch do tellers open the most checking accounts for new customers?

Figure 34.16 shows a pivot table that answers this question. At the Central branch, tellers opened 23 checking accounts for new customers.

Figure 34.16. This pivot table uses three Report Filters.

This pivot table uses three Report Filters. The Customer field is filtered to show only New, the OpenedBy field is filtered to show only Teller, and the AcctType field is filtered to show only Checking.