B4P Reference

Function Names

table spread, table spread accumulating

Description

This is a pivot function which spreads vertically listed data horizontally across multiple columns using a key derived from information in other columns, (e.g. sequence info like dates, quarters, years, states, countries and/or category info like revenues,earnings, etc.). The columns created in horizontal order will be arranged in case sensitive alphabetic order. Values to be spreaded must not necessarily be numeric, unless you use table spread accumulating.
Function 'table spread'
This function creates new headers only if they are not yet existing. If headers are existing, then data below will be preserved unless overwritten by values being spread. The function table spread accumulating will add the new values to the existing value instead of overwriting it. You can do multiple calls of this function on the same table. Hint:To finalize a pivot from vertical horizontal, call table consolidate() as the net function to reduce the number of rows to the minimum necessary.

Call as: procedure or function

Restrictions

Indirect parameter passing is disabled
This function provides a table context for partial table specifications with table name and row number for selected function parameters

Parameter count

3-7

Parameters

No.	Type	Description
1. input	string	Name of existing table
2. input	table columns	Column with values to spread Specify the column which contains the values or any other conetns you want to spread horizontally. See table columns as function parameters for general ruling for this parameter. Specific rules apply for this function: Exactly 1 header name and column numbers may be specified
3. code	expression :string	Spreading key expression In order to spread the data horizontally across columns to be created, you need to specify how the new column headers names shall be formulated for the horizontal data. This parameter is an expression which is calculated for every table row and should preferably generate an output value of string type (string). Other types, such as numerals (e.g. years) will be converted to strings automatically. During the horizontal spreading, the applicable value (column specified in 2nd parameter) will be copied to the new columns with these header names. The table context for partial table specifications is available for referencing just the columns easily. Example: [Year]>=2022. Simple example if spreading by one column, e.g. year: Specify [year]. Multiple columns, e.g. quarter and year in separate columns: Specify Q+[Quarter]+' '+str([year]) for values like 'Q1 2022'. To spread values by 1st letter, consider , which picks the 1st leter and capitalizes it (+ operator on strings). For a simple distribution across years, quarters, countries, states, and the actual data is available one column, then specify the corresponding column name in brackets, e.g. [Year]. For a distribution of values across years where the full data is available, something like year([Delivery Dates]) is proposed. For an alphabetical distribution, use something like +[Name]{0} which picks the 1st letter and capitalizes it (unary '+' operator at the beginning). For a combination of multiple columns, e.g. category and sequence info, combine two columns, e.g. [KPI]+'/'+str([Year]) or [Quarter]+"-"+str([Yeaer]). Attention: New columns will only be created if they are not yet existing. This scheme allows running multiple calls of table spread and table spread accumulating with different data. This function does not delete any existing values. Values already existing will only be overwritten or added up.
Opt. 4. code	expression :string	Pivot limitation expression This is an expression which will be calculated for every table rowo and shall return a boolean value. If the value is true, then the value will be spread into a dedicated column. This feature lets you limit the creation of too many columns. All values excluded will appear in the column for all other values, if defined using the 6th function parameter. Specify the conditions or rules to select the rows. See expressions to select rows. The table context for partial table specifications is available for referencing just the columns easily. Example: [Year]>=2022. Attention: Comparison operators = and <> (instead of == and !=) may hijack the next function parameters for its own use as additional comparison operands, e.g. a[]=1,3,5. As long this comparison is not made in the last function parameter, then put parentheses around them, e.g. ... , (a[]=1,3,5), .... Examples: Your data contains a column containing years, but want to limit the spreading to 5 years, then specify something like ([Year]=2020..2024). Note the required parentheses as explained above so the expression does not hijack following function parameters. Default value: true
Opt. 5. code	numeral	Maximum number of columns to add You can limit the number of columns to be created in order to prevent overruns. In this case, only the first n columns (in alphabetic order) will be shown. Default value: (not limited)
Opt. 6. input	table column	Column for all other values This column will be used to allocate all values which cannot be allocate into the specified columns due to limitations defined by the 4th and/or 5th function parameters. See table columns as function parameters for general ruling for this parameter. Specific rules apply for this function: Max. 1 header name may be specified. Default value: (not applicable)
Opt. 7. input	table column	Destination column Specify a header name or column number where to insert the new columns added. The specified column and further ones to the right will shift to the right accordingly. Negative number are supported for indexing from right to left, however -1 refers to the end of the table, -2 to left of last column, etc. See table columns as function parameters for general ruling for this parameter. Specific rules apply for this function: Only 1 header name or column number may be specified. Default value: to the end of the table

Return value

Type	Description
numeral	Column count Number of new columns added. The 'column for other values' specified in the 6th function parameter is not included in the counting.

Examples

  // Remember the motor vehicles serialized ...

  table initialize( bils, // Swedisch for 'cars', aka 'automo-bils'

      { { Product, "2020-Q1".."2020-Q4" },

        { Sedans,   24, 34, 44, 14 },  { Pickpus,  11, 21, 31, 21 },

        { Cabrios,  '',  5, 10, '' },  { SUVs,     35, 25, 45, 55 } } );



  echo("Car sales in sequential order (including blanks here):");

  table serialize all( bils, Product, Quarter, { "2020-Q1".."2020-Q4" }, Cars sold );

  table list ( bils );



  echo("Let's shift to reverse gear: Spread the data");



  count[] = table spread( bils, Cars sold, [Quarter] );

  table list ( bils );



  echo("Number of new columns created. ", count[]);

  echo("And do a final consolidation and you get the original list.");

  table consolidate( bils, Product, { Quarter, Cars sold, "2020-Q1".."2020-Q4" }, { 2:delete, overwrite if blank }  );

  table list ( bils );

Output

Car sales in sequential order (including blanks here):
    0 : Product | Quarter | Cars sold
    1 : Sedans  | 2020-Q1 | 24       
    2 : Sedans  | 2020-Q2 | 34       
    3 : Sedans  | 2020-Q3 | 44       
    4 : Sedans  | 2020-Q4 | 14       
    5 : Pickpus | 2020-Q1 | 11       
    6 : Pickpus | 2020-Q2 | 21       
    7 : Pickpus | 2020-Q3 | 31       
    8 : Pickpus | 2020-Q4 | 21       
    9 : Cabrios | 2020-Q1 |          
   10 : Cabrios | 2020-Q2 | 5        
   11 : Cabrios | 2020-Q3 | 10       
   12 : Cabrios | 2020-Q4 |          
   13 : SUVs    | 2020-Q1 | 35       
   14 : SUVs    | 2020-Q2 | 25       
   15 : SUVs    | 2020-Q3 | 45       
   16 : SUVs    | 2020-Q4 | 55       

Let's shift to reverse gear: Spread the data
    0 : Product | Quarter | Cars sold | 2020-Q1 | 2020-Q2 | 2020-Q3 | 2020-Q4
    1 : Sedans  | 2020-Q1 | 24        | 24      |         |         |        
    2 : Sedans  | 2020-Q2 | 34        |         | 34      |         |        
    3 : Sedans  | 2020-Q3 | 44        |         |         | 44      |        
    4 : Sedans  | 2020-Q4 | 14        |         |         |         | 14     
    5 : Pickpus | 2020-Q1 | 11        | 11      |         |         |        
    6 : Pickpus | 2020-Q2 | 21        |         | 21      |         |        
    7 : Pickpus | 2020-Q3 | 31        |         |         | 31      |        
    8 : Pickpus | 2020-Q4 | 21        |         |         |         | 21     
    9 : Cabrios | 2020-Q1 |           |         |         |         |        
   10 : Cabrios | 2020-Q2 | 5         |         | 5       |         |        
   11 : Cabrios | 2020-Q3 | 10        |         |         | 10      |        
   12 : Cabrios | 2020-Q4 |           |         |         |         |        
   13 : SUVs    | 2020-Q1 | 35        | 35      |         |         |        
   14 : SUVs    | 2020-Q2 | 25        |         | 25      |         |        
   15 : SUVs    | 2020-Q3 | 45        |         |         | 45      |        
   16 : SUVs    | 2020-Q4 | 55        |         |         |         | 55     

Number of new columns created. 4
And do a final consolidation and you get the original list.
    0 : Product | 2020-Q1 | 2020-Q2 | 2020-Q3 | 2020-Q4
    1 : Sedans  | 24      | 34      | 44      | 14     
    2 : Pickpus | 11      | 21      | 31      | 21     
    3 : Cabrios |         | 5       | 10      |        
    4 : SUVs    | 35      | 25      | 45      | 55

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

table spread ...