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Pito

Pivot tables are a technique in data processing. This leads to pito figures and facts quickly making them integral to data analysis. This ultimately leads to helping businesses or individuals make educated decisions.

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. Lotus Development released Improv in 1991 on the NeXT platform. In 1993 the Microsoft Windows version of Improv appeared. In 2007 Oracle Corporation made PIVOT and UNPIVOT operators available in Oracle Database 11g.

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? These fields allow several kinds of aggregations, including: sum, average, standard deviation, count, etc. Using the example above, the 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, the quantities of Unit, and display them in a multidimensional chart. In the example above, the first datum is 66. Pivot tables are not created automatically.

The user then has the option of either inserting the pivot table into an existing sheet or creating a new sheet to house the pivot table. A pivot table field list is provided to the user which lists all the column headers present in the data. 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. Pivot Table fields are the building blocks of pivot tables. Some uses of pivot tables are related to the analysis of questionnaires with optional responses but some implementations of pivot tables do not allow this use cases. Report filter is used to apply a 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. Column labels are used to apply a filter to one or more columns that have to be shown in the pivot table. For instance if the “Salesperson” field is dragged to this area, then the table constructed will have values from the column “Sales Person”, i. There will also be one added column of Total. 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 are used to apply a filter to one or more rows that have to be shown in the pivot table. For instance, if the “Salesperson” field is dragged on this area then the other output table constructed will have values from the column “Salesperson”, i. There will also be one added row of “Grand Total”. 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. Sum, it will give a count. So, in the example above, if the “Units sold” field is dragged to this area along with the row label of “Salesperson”, then the instruction will add a new column, “Sum of units sold”, which will have values against each salesperson. Pivot tables or pivot functionality are an integral part of many spreadsheet applications and some database software, as well as being found in other data visualization tools and business intelligence packages. Apache POI “Creating a Pivot Table”. Google Sheets natively supports pivot tables.

MariaDB, a MySQL fork, allows pivot tables using the CONNECT storage engine. Microsoft Access supports pivot queries under the name “crosstab” query. Oracle Database supports the PIVOT operation. Some popular databases that do not directly support pivot functionality, such as SQLite, can usually simulate pivot functionality using embedded functions, dynamic SQL or subqueries. ZK, an Ajax framework, also allows the embedding of pivot tables in Web applications. Programming languages and libraries suited to work with tabular data contain functions that allow the creation and manipulation of pivot tables.

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