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In data processing, a pivot table is a data summarization tool found in data visualization programs such as spreadsheets or business intelligence software. Among other functions, a pivot table can automatically sort, count total or give the average of the data stored in one table or spreadsheet, displaying the results in a second table showing the summarized data. Pivot tables are also useful for quickly creating unweighted cross tabulations. The user sets up and changes the summary's structure by dragging and dropping fields graphically. This "rotation" or pivoting of the summary table gives the concept its name.
Pivot tables can be seen as a simplification of the more complete and complex online analytical processing concepts (OLAP).
In their book Pivot Table Data Crunching, Bill Jelen and Mike Alexander refer to Pito Salas as the "father of pivot tables". While working on a concept for a new program that would eventually become Lotus Improv, Salas noted that spreadsheets have patterns of data. A tool that could help the user recognize these patterns would help to build advanced data models quickly. With Improv, users could define and store sets of categories, then change views by dragging category names with the mouse. This core functionality would provide the model for pivot tables.
Lotus Development released Improv in 1991 on the NeXT platform. A few months after the release of Improv, Brio Technology published a standalone Macintosh implementation, called DataPivot (with technology eventually patented in 1999). Borland purchased the DataPivot technology in 1992 and implemented it in their own spreadsheet application, Quattro Pro.
In 1993 the Microsoft Windows version of Improv appeared. Early in 1994 Microsoft Excel 5  brought a new functionality called a "PivotTable" to market. Microsoft further improved this feature in later versions of Excel:
For typical data entry and storage, data usually appear in flat tables, meaning that they consist of only columns and rows, as in the following example showing data on shirt types:
While tables such as these can contain many data items, it can be difficult to get summarized information from them. A pivot table can help quickly summarize the data and highlight the desired information. The usage of a pivot table is extremely broad and depends on the situation. The first question to ask is, "What am I seeking?" In the example here, let us ask, "How many Units did we sell in each Region for every Ship Date?":
A pivot table usually consists of row, column and data (or fact) fields. In this case, the column is Ship Date, the row is Region and the datum we would like to see is (sum of) Units. These fields allow several kinds of aggregations, including: sum, average, standard deviation, count, etc. In this case, the total number of units shipped is displayed here using a sum aggregation.
Using the example above, software will find all distinct values for Region. In this case, they are: North, South, East, West. Furthermore, it will find all distinct values for Ship Date. Based on the aggregation type, sum, it will summarize the fact and display them in a multidimensional chart. In the example above, the first datum is 66. This number was obtained by finding all records where both Region was East and Ship Date was 1/31/2005, and adding the Units of that collection of records (i.e., cells E2 to E7) together to get a final result.
Pivot tables are not created automatically; one must first select the entire data in the original table (in Microsoft Excel for example) and then go to Insert -> Pivot table. This will create a new worksheet containing a Pivot Table Field List that will list all the column headers present in the data. For instance, if a table represents sales data of a company, it might include Date of Sale, Sales Person, Item Sold, Color of Item, Units Sold, Per Unit Price, and Total Price. This makes the data easy to access.
|Date of Sale||Sales Person||Item Sold||Color of Item||Units Sold||Per Unit Price||Total Price|
The fields that would be created will be visible on the right hand side of the worksheet. By default, the pivot table layout design will appear below this list.
Each of the fields from the list can be dragged on to this layout, which has four options :
Report Filter is used to apply an Excel filter to an entire table. For example, if the "Color of Item" field is dragged to this area, then the table constructed will have a report filter inserted above the table. This report filter will have drop-down options (Black, Red, and White in the example above). When an option is chosen from this drop-down list ("Black" in this example), then the table that would be visible will contain only the data from those rows that have the "Color of Item = Black".
Column Labels is used to apply an Excel filter to one or more columns that have to be shown in the pivot table. For instance if the "Sales Person" field is dragged to this area, then the table constructed will have a values from the column "Sales Person", i.e., one will have number of columns equal to the number of "Sales Person". There will also be one added column of Total. In the example above, this instruction will create three columns in the table — Harry, Larry, and Grand Total. There will be a filter above the data — Column Labels — from which one can select or deselect a particular sales person for the Pivot table.
This table will not have any numerical values as no numerical field is selected but when it is selected, the values will automatically get updated in the column of "Grand Total".
Row Labels is used to apply an Excel filter to one or more rows that have to be shown in the pivot table. For instance if the "Sales Person" field is dragged on this area then the table constructed will have a values from the column "Sales Person", i.e., one will have number of rows equal to the number of "Sales Person". There will also be one added row of "Grand Total". In the example above, this instruction will create three rows in the table — Harry, Larry, and Grand Total. There will be a filter above the data — Row Labels — from which one can select or deselect a particular sales person for the Pivot table.
This table will not have any numerical values, as no numerical field is selected, but when it is selected, the values will automatically get updated in the Row of "Grand Total"
This usually takes a field that has numerical values that can be used for different types of calculations. However, using text values would also not be wrong; instead of Sum it will give a count. So, in the example above, if the "Units Sold" field is dragged to this area along with Row label of "Sales Person", then the instruction will add a new column, "Sum of Units Sold", which will have values against each sales person.
|Row Labels||Sum of Units Sold|
Pivot tables are an integral part of a spreadsheet application. In addition to Microsoft Excel, competing software programs such as Apache OpenOffice Calc provide similar functionality; the implementation in Apache OpenOffice and LibreOffice up to release 3.3 is called DataPilot. In version 3.4 of both LibreOffice and OpenOffice, DataPilot is renamed "Pivot Table". Other companies, such as Quantrix and numberGo, provide similar implementations.
Pivot functionality can also be found in other data visualization tools, including business intelligence packages.
Google Docs initially allowed the creation of basic pivot tables via the pivot table gadget from Panorama called Panorama Analytics, but as of 2011[update] this gadget provided limited functionality and was extremely slow with large data sets. In May 2011, Google announced the roll-out of a natively hosted pivot table feature in the Google spreadsheets editor.
ZK, an Ajax framework, also allows the embedding of pivot tables in Web applications.
Excel Pivot Tables include the feature to directly query an OLAP server for retrieving data instead of getting the data from an Excel spreadsheet. On this configuration a pivot table is a simple client of an OLAP server. Excel's PivotTable not only allows for connecting to Microsoft's Analysis Service, but to any XML for Analysis (XMLA) OLAP standard-compliant server.
Other OLAP clients are JPivot, Dundas, IcCube (Client Library).
[...] Excel 5, released in early 1994, included the first version of VBA.
One of the most useful new features of the Oracle Database 11g from the SQL perspective is the introduction of Pivot and Unpivot operators.