5.16.3. Sum on Rows

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5.16.3. Sum on Rows

 

Icon: ANATEL~4_img205

 

Property window:

 

ANATEL~4_img204

 

Short description:

Sum n rows

 

Long Description:

This Action can be summarized as a "group by" 'n' consecutive rows Action.

 

Let's assume that:
 

You want to create a chart in excel that represents the average SALES amount per week.
 

you have an original table that contains, for each day, the SALES amount:
 

    +--------------------------+

    |        ORIGINAL TABLE    |

    +--------------+-----------+

    |          DATE| DAY SALES |

    +--------------+-----------+

    |June  1, 2010 |     1500 $|

    |June  2, 2010 |     1500 $|

    |June  3, 2010 |     1500 $|

    |June  4, 2010 |     5000 $|

    |June  5, 2010 |     1500 $|

    |June  6, 2010 |     1500 $|

    |June  7, 2010 |     1500 $|

    |June  8, 2010 |     2000 $|

    |June  9, 2010 |     2000 $|

    |June 10, 2010 |     2000 $|

    |June 11, 2010 |     2000 $|

    |June 12, 2010 |     2000 $|

    |June 13, 2010 |     2000 $|

    |June 14, 2010 |     2000 $|

    +--------------+-----------+

 

i.e. You want to obtain the following table, to be able to create your chart:
 

    +-------------------------------------------------+

    |                 TRANSFORMED  TABLE              |

    +--------------+----------------------------------+

    |          DATE|  AVERAGE DAY SALES FOR THIS WEEK |

    +--------------+----------------------------------+

    |June  1, 2010 |                            2000 $|

    |June  8, 2010 |                            2000 $|

    +--------------+----------------------------------+

 
The objective of this operator is to obain the final "TRANSFORMED TABLE" based on the "ORIGINAL TABLE".
 

 

ANATEL~4_img129

NOTE:

This operator is mainly useful when you want to reduce the number of rows of a table to obtain a "synthetized" version that is more suitable for visualization. In normal situation, this operator should not be used in conjunction with a predictive analysis because the "TRANSFORMED TABLE" contains a lot less information compared to the "ORIGINAL TABLE" and will usually generate less accurate predictive models.