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Data Functions

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Data Functions

Add advanced analytics features into your data pipelines with prebuilt data functions

61 files

  1. Spotfire data function removing duplicate records.
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  2. Spotfire data function which unpivots data table.
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  3. This data function takes address info and returns a latitude and longitude coordinate.
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  4. This data function takes latitude and longitude coordinates and returns a table of data detailing the address info at given locations.
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  5. This Python data function performs both NER tagging and POS tagging.
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  6. TERR data function to get trade area for a given driving distance.
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  7. TERR/R data function to get trade area for a given driving distance around given GPS coordinates.
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  8. Spotfire data function that converts an imported shapefile.
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  9. Spotfire data function that converts an imported shapefile.
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  10. This Python data function identifying combination of products that are frequently bought together.
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  11. This geospatial feature computes distances between two collections of locations.
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  12. This geospatial feature finds locations in a given dataset that are closest to other locations.
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  13. Takes any number of numerical columns and interpolates missing values.
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  14. This geospatial feature converts line geometries to a set of points.
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  15. This data function takes an entire data table and sorts it by a specified column and in a specified order.
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  16. This data preparation feature finds approximate string matches between two columns.
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  17. Spotfire data function for returning Twitter tweeds.
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  18. Spotfire data function that converts columns of geographic coordinates from one reference system to another.
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  19. This Data Function generates Voronoi polygons forming a tessellation that covers study region. Polygons can be used as a feature layer on a map chart.
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  20. This component in the form of data function reads data from JHU and updates the data tables.
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  21. Spotfire data function which converts a column of polygons from one coordinate reference system to another.
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  22. A/B testing refers to a number of similar marketing use cases where the goal is to compare the effect of different 'treatments' on a response, such as click-through rates, orders or sales dollars.
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  23. Geospatial data can come in several forms, for example locations of specific points, or polygons that define areas of interest. When both point and polygon data are present, it is often useful to identify the enclosing polygon for each point.
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  24. Spatial Heat Maps allow you to visualize overall patterns in numeric spatial data.
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  25. Exports a data table with geometries to a shapefile (.shp) on a local drive.
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