Sample Data Sets
For your convenience, this help reference includes sample data sets. You can copy the contents of these tables to Spotfire to use in tasks and exercises to learn how to call TERR expression functions.
Alternatively, you can write a TERR data function that imports one or more data sets into Spotfire from TERR. See Importing TERR Data Sets Using a Data Function for more information.
- Aggregation Data for Spotfire Examples
Use this data set for the task for learning to write TERR data functions in Spotfire. This data set has one column of groups (1-5) and two columns of numeric variables. You can use this sample create an aggregated table based on selections you make in this table. - Air Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set has four columns taken from an environmental study that measured ozone, solar radiation, temperature, and wind speed for five months in 1973 in the New York City area. - Car Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set gives information on makes of cars taken from the April, 1990 issue of Consumer Reports (pages 235-255). This data set contains 6 columns for 61 cars (rows). - Observation Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set has four columns for a fictional trial. Each row has a date, a start time, an end time, and the result of the observation, so it can be used with either a time span or a boolean expresssion. - Temperature Data Set for Spotfire Examples
You can use this data set for the task for learning to write TERR expression functions in Spotfire. This data set is extracted from the a data frame with observations (rows) on five variables (columns), taken from an environmental study that measured ozone, solar radiation, temperature, and wind speed for 5 months in 1973 in the New York City area. (This sample set shows a date range between August and September that have no missing values.)
- Aggregation Data for Spotfire Examples
Use this data set for the task for learning to write TERR data functions in Spotfire. This data set has one column of groups (1-5) and two columns of numeric variables. You can use this sample create an aggregated table based on selections you make in this table. - Air Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set has four columns taken from an environmental study that measured ozone, solar radiation, temperature, and wind speed for five months in 1973 in the New York City area. - Car Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set gives information on makes of cars taken from the April, 1990 issue of Consumer Reports (pages 235-255). This data set contains 6 columns for 61 cars (rows). - Observation Data Set for Spotfire Examples
Use this data set for the task for learning to write TERR expression functions in a custom expression in Spotfire. This data set has four columns for a fictional trial. Each row has a date, a start time, an end time, and the result of the observation, so it can be used with either a time span or a boolean expresssion. - Temperature Data Set for Spotfire Examples
You can use this data set for the task for learning to write TERR expression functions in Spotfire. This data set is extracted from the a data frame with observations (rows) on five variables (columns), taken from an environmental study that measured ozone, solar radiation, temperature, and wind speed for 5 months in 1973 in the New York City area. (This sample set shows a date range between August and September that have no missing values.)
Parent topic: Using TERR for Advanced Analytics in Spotfire
Related concepts
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