Example of Pivoting in Information Designer


Pivoting a data table means changing it from a tall/skinny format to a short/wide format. Consider the following tall/skinny table, based on a series of temperature measurements:

City

Month

Temp

London

February

4

New York

February

6

London

May

16

New York

May

19

London

August

28

New York

August

26

London

November

13

New York

November

11

 

As we add more observations, the table grows taller, but remains three columns wide. While useful during data collection, this format may not be appropriate for certain types of calculations or visualizations. For example, the entities that interest us are the different cities, so we may want a representation with a single row for each city.

Pivoting this table produces the following (note that avg(Temp) is the average of a single cell):

City

avg(Temp) for February

avg(Temp) for May

avg(Temp) for August

avg(Temp) for November

London

4

16

28

13

New York

6

19

26

11

 

Each city is now represented by a single row. The following steps have been performed during the pivoting:

The following settings were made in the Pivot Conditioning dialog to produce this result:

See also:

Pivoting Data

Example of Pivoting with Aggregation