Temporal data is commonly stored in columns or fields in attribute or stand-alone tables. For example, the historical medical costs for a county might be listed in separate columns in the table, with a single row containing values for years 1990, 1991, 1992, and so on. To visualize this data through time using the time slider's data filtering capabilities, you must reformat the table so that all time data is in a single column with multiple rows. That is, for each year for each county, you need a column for the year with a matching column for the medical cost of that year. This allows the information for a specific year to be filtered within a single row in the data, such as the 1992 medical costs for Greenbushes County.
An example of temporal data could be medical costs per county for 1990, 1991, 1992, and so on. In this case, each column contains a value of the medical costs for that county and the given year. To visualize this data in AllSource, the table needs to be reformatted .
Use the Transpose Fields geoprocessing tool to convert the data by shifting the dates in multiple fields into multiple rows in a table or feature class.
The tables below are an example of original data that has been converted to transposed data.
