table overlay/subtract ...

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Function Names

table overlay, table overlay extend columns, table overlay intersect columns, table overlay columns, table overlay exclusive columns

Description

The functions described here overlay the contents of the source table into the destination table. Identifier columns can be defined for both tables in order to identify the overlapping table rows (e.g. same first and last names).

For the merging process, the principle of union set is applied. Different from the table merge() function family, all rows in the source tables which do not share the same identifier data as in the destination table will not be added to the end of the table. This does also apply if no identifier columns are specified (e.g. 3rd function parameter not used or {} or '' provided). In the other case, where rows in the source table share the same identifier data as in the destination table and are considered overlapping, the data from the source table row will be consolidated into the destination table row using available consolidation actions. The consolidation actions work similarly like in the function table consolidate() where exactly two rows are consolidated into one row.

In case the two tables contain multiple equal values in the identifier columns (for example if only the first name has been referred), then every affecting row in the source table will be consolidated in one row in the destination table and then checked off as 'done'. If another row in the source table has the same value, then the next match further below in the destination table will be seeked. If the source table contains more repeated contents in the identifier column than in the destination table, then the remaining rows will be added to the end of the destination table.

The following functions use different approaches to combine the data columns:

table overlay No further columns are added to the destination table
table overlay extend columns Columns in the source table but not found in the destinationtable will be added to the target table (union set)
table overlay intersect columns Removes columns from the destination table if they do not exist in the source table (intersection)
table subtract columns removes columns from destination table if they are found in the source table, but keeps the identifier columns.
Note: The function name does not contain the word overlay because it is meaningless here.
table overlay exclusive columns Removes columns found in both source and destination table, but keeps the identifier columns (exclusive OR).


Function 'table overlay'

Note: If the destination table does not yet exist, or if the table is entirely empty (i.e. no header inside), then the data in the source table will be copied into the destination table. Typical applications:

  • Enriching tables with additional information from other sources
  • Keeping key performance figures (KPI's) in tables up-to-date

Call as: procedure or function

Restrictions

Indirect parameter passing is disabled

Parameter count

2-6 (Max 3 for function names 'table overlay exclusive columns' and 'table subtract columns').
See table merge() for parameter and return value description

Program Examples with 'table overlay ...'

Merging tables into one without identifier columns specified
               echo("Loading farms in Hillboro and Hillville");
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               echo("Farms in Hillboro:");
               table list( hb );

               echo("Farms in Hillville:");
               table list( hv );

               count[] = table overlay( hv, hb );

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: Zero rows consolidated
Loading farms in Hillboro and Hillville
Farms in Hillboro:
    0 : Organic | Place    | Farmer     | Wheat | Oat | Sheeps | Cows | Acres | Speciality
    1 : No      | Hillboro | F. Fuller  | 3     |     |        |      | 4     | Hogs      
    2 : Yes     | Hillboro | R. Rudy    | 19    |     | 20     | 24   | 21    | Restaurant
    3 :         | Hillboro | D. Daniels | 2     |     |        |      | 3     |           
    4 : No      | Hillboro | M. Miller  | 2     | 1   |        |      | 5     |           
    5 : Yes     | Hillboro | K. Klein   | 10    | 10  | 40     | 30   | 28    | Vegetables
    6 :         | Hillboro | P. Pomme   |       |     | 50     | 40   | 21    | Apples    

Farms in Hillville:
    0 : Place     | Farmer     | Acres | Wheat | Barley | Corn | Cows | Organic | Speciality
    1 : Hillville | M. Miller  | 20    | 4     |        | 5    | 30   |         | Hops      
    2 : Hillville | F. Fuller  | 18    | 5     | 9      |      | 22   | Yes     | Pigs      
    3 : Hillville | B. Beaver  | 23    | 1     | 4      | 3    |      | Yes     | Sugar Pea
    4 : Hillville | J. Jill    | 14    | 8     | 1      | 3    | 10   |         |           
    5 : Hillville | D. Daniels | 21    |       | 18     |      | 0    |         | Lodging   

Hilltown is a merger of Hillboro and Hillville (0 rows consolidated):
    0 : Organic | Place    | Farmer     | Wheat | Oat | Sheeps | Cows | Acres | Speciality
    1 : No      | Hillboro | F. Fuller  | 3     |     |        |      | 4     | Hogs      
    2 : Yes     | Hillboro | R. Rudy    | 19    |     | 20     | 24   | 21    | Restaurant
    3 :         | Hillboro | D. Daniels | 2     |     |        |      | 3     |           
    4 : No      | Hillboro | M. Miller  | 2     | 1   |        |      | 5     |           
    5 : Yes     | Hillboro | K. Klein   | 10    | 10  | 40     | 30   | 28    | Vegetables
    6 :         | Hillboro | P. Pomme   |       |     | 50     | 40   | 21    | Apples    

Try it yourself: Open LIB_Function_table_overlay.b4p in B4P_Examples.zip. Decompress before use.
Declare 'Farmer' as unique identifier
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               count[] = table overlay( hv, hb, Farmer );

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: 3 farmers with land in both towns have been consolidated.
Hilltown is a merger of Hillboro and Hillville (3 rows consolidated):
    0 : Organic | Place    | Farmer     | Wheat | Oat | Sheeps | Cows | Acres | Speciality
    1 : No      | Hillboro | F. Fuller  | 3     |     |        |      | 4     | Hogs      
    2 : Yes     | Hillboro | R. Rudy    | 19    |     | 20     | 24   | 21    | Restaurant
    3 :         | Hillboro | D. Daniels | 2     |     |        |      | 3     |           
    4 : No      | Hillboro | M. Miller  | 2     | 1   |        |      | 5     |           
    5 : Yes     | Hillboro | K. Klein   | 10    | 10  | 40     | 30   | 28    | Vegetables
    6 :         | Hillboro | P. Pomme   |       |     | 50     | 40   | 21    | Apples    

Try it yourself: Open LIB_Function_table_overlay_01.b4p in B4P_Examples.zip. Decompress before use.
Merge data in smart way and add 2 columns from source table:
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               count[] = table overlay extend columns( hv, hb, Farmer, '*', { must match, append, 5:sum, append }, ", " );
               // '*' corresponds to {Organic, Place, Wheat, Oat, Sheeps, Cows, Acres, Speciality}

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: 3 farmers with land in both towns have been consolidated.
Hilltown is a merger of Hillboro and Hillville (3 rows consolidated):
    0 : Organic         | Place               | Farmer     | Wheat | Oat | Sheeps | Cows | Acres | Speciality | Barley | Corn
    1 : (Inconsistent!) | Hillboro, Hillville | F. Fuller  | 8     |     |        | 22   | 22    | Hogs, Pigs | 9      |     
    2 : Yes             | Hillboro            | R. Rudy    | 19    |     | 20     | 24   | 21    | Restaurant |        |     
    3 :                 | Hillboro, Hillville | D. Daniels | 2     |     |        | 0    | 24    | Lodging    | 18     |     
    4 : No              | Hillboro, Hillville | M. Miller  | 6     | 1   |        | 30   | 25    | Hops       |        | 5   
    5 : Yes             | Hillboro            | K. Klein   | 10    | 10  | 40     | 30   | 28    | Vegetables |        |     
    6 :                 | Hillboro            | P. Pomme   |       |     | 50     | 40   | 21    | Apples     |        |     

Try it yourself: Open LIB_Function_table_overlay_02.b4p in B4P_Examples.zip. Decompress before use.
Merge data in smart way and keep intersected columns:
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               count[] = table overlay intersect columns( hv, hb, Farmer, '*', { must match, append, 3:sum, append }, ", " );
               // '*' corresponds to {Organic, Place, Wheat, Cows, Acres, Speciality}

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: 3 farmers with land in both towns have been consolidated.
Hilltown is a merger of Hillboro and Hillville (3 rows consolidated):
    0 : Organic         | Place               | Farmer     | Wheat | Cows | Acres | Speciality
    1 : (Inconsistent!) | Hillboro, Hillville | F. Fuller  | 8     | 22   | 22    | Hogs, Pigs
    2 : Yes             | Hillboro            | R. Rudy    | 19    | 24   | 21    | Restaurant
    3 :                 | Hillboro, Hillville | D. Daniels | 2     | 0    | 24    | Lodging   
    4 : No              | Hillboro, Hillville | M. Miller  | 6     | 30   | 25    | Hops      
    5 : Yes             | Hillboro            | K. Klein   | 10    | 30   | 28    | Vegetables
    6 :                 | Hillboro            | P. Pomme   |       | 40   | 21    | Apples    

Try it yourself: Open LIB_Function_table_overlay_03.b4p in B4P_Examples.zip. Decompress before use.
Merge data in smart way and subtract the columns:
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               count[] = table subtract columns( hv, hb, Farmer ); // Note: 'overlay' is not part of function name.

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: 3 farmers with land in both towns have been consolidated.
Hilltown is a merger of Hillboro and Hillville (0 rows consolidated):
    0 : Farmer     | Oat | Sheeps
    1 : F. Fuller  |     |       
    2 : R. Rudy    |     | 20    
    3 : D. Daniels |     |       
    4 : M. Miller  | 1   |       
    5 : K. Klein   | 10  | 40    
    6 : P. Pomme   |     | 50    

Try it yourself: Open LIB_Function_table_overlay_04.b4p in B4P_Examples.zip. Decompress before use.
Merge data in smart way and show all columns except comomon ones:
               table load( hb, "Examples/Table Merge Examples Hillboro.csv");
               table load( hv, "Examples/Table Merge Examples Hillville.csv");

               count[] = table overlay exclusive columns( hv, hb, Farmer );

               echo("Hilltown is a merger of Hillboro and Hillville (", count[], " rows consolidated):");
               table list( hb );
Output: 3 farmers with land in both towns have been consolidated.
Hilltown is a merger of Hillboro and Hillville (3 rows consolidated):
    0 : Farmer     | Oat | Sheeps | Barley | Corn
    1 : F. Fuller  |     |        |        |     
    2 : R. Rudy    |     | 20     |        |     
    3 : D. Daniels |     |        |        |     
    4 : M. Miller  | 1   |        |        |     
    5 : K. Klein   | 10  | 40     |        |     
    6 : P. Pomme   |     | 50     |        |     

Try it yourself: Open LIB_Function_table_overlay_05.b4p in B4P_Examples.zip. Decompress before use.

Tables with multiple non-unique identifiers being merged:

In case you plan to merge two tables with a one or a selection of column identifiers which cannot guarantee uniqueness, e.g. a list of names identified by first name only, then this function will match first name pairs first, then the next ones below, and so forth. As a result, every row is considered only once. Long story short: Every row in the destination table will be consolidated only once. The following code example demonstrates this:

One Jill and tow Micheles will be consolidated:
               table load( h1, "Examples/Table Merge Examples Hobbies 1.csv");
               table load( h2, "Examples/Table Merge Examples Hobbies 2.csv");

               echo("Hoobies 1:");      table list( h1 );
               echo("Hoobies 2:");      table list( h2 );

               count[] = table overlay( h2, h1, Name, '*', append, ', ' );

               echo("Combined list of hobbies (", count[], " rows consolidated):");
               table list( h1 );
The outcome
Hoobies 1:
    0 : Name    | Hobby   | Sport     | Color    | Animal
    1 : Jill    | Games   | Snowboard | Gray     | Dog   
    2 : Michele | Games   |           | Pink     | Cat   
    3 : Michele | Reading | Riding    | Red      | Horse
    4 : Jill    | Theatre | Sailing   | Turquois | Whale

Hoobies 2:
    0 : Name    | Hobby       | Sport    | Color   | Animal
    1 : Michele | Playing     | Golf     | Brown   | Tiger
    2 : Michele | Writing     | Riding   | Magenta | Pony  
    3 : Michele | Photography | Soccer   | Blue    | Fish  
    4 : Michele | Movies      | Handball | Green   | Crabs
    5 : Jill    | Drama       | Surfing  | Skyblue | Trouts

Combined list of hobbies (3 rows consolidated):
    0 : Name    | Hobby            | Sport              | Color         | Animal     
    1 : Jill    | Games, Drama     | Snowboard, Surfing | Gray, Skyblue | Dog, Trouts
    2 : Michele | Games, Playing   | Golf               | Pink, Brown   | Cat, Tiger
    3 : Michele | Reading, Writing | Riding, Riding     | Red, Magenta  | Horse, Pony
    4 : Jill    | Theatre          | Sailing            | Turquois      | Whale      

Try it yourself: Open LIB_Function_table_overlay_06.b4p in B4P_Examples.zip. Decompress before use.

See also

table merge
table intersect
table subtract
table exclude
table consolidate