﻿ 5. Detailed description of the Actions > 5.16. Time Series > 5.16.3. Sum on Rows

# 5.16.3. Sum on Rows

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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".

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.