# SUM Function

Computes the sum of all values found in all row values in a column. Input column can be of Integer or Decimal.

If a row contains a missing or null value, it is not factored into the calculation. If no numeric values are found in the source column, the function returns

`0`

.When used in a

`pivot`

transform, the function is computed for each instance of the value specified in the`group`

parameter. See Pivot Transform.

For a version of this function computed over a rolling window of rows, see ROLLINGSUM Function.

**Wrangle vs. SQL:** This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

## Basic Usage

sum(myRating)

**Output:** Returns the sum of the group of values from the `myRating`

column.

**Wrangle vs. SQL:** This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.

## Syntax and Arguments

sum(function_col_ref) [group:group_col_ref] [limit:limit_count]

Argument | Required? | Data Type | Description |
---|---|---|---|

function_col_ref | Y | string | Name of column to which to apply the function |

For more information on the `group`

and `limit`

parameters, see Pivot Transform.

For more information on syntax standards, see Language Documentation Syntax Notes.

### function_col_ref

Name of the column the values of which you want to calculate the sum. Column must contain Integer or Decimal values.

Literal values are not supported as inputs.

Multiple columns and wildcards are not supported.

** Usage Notes:**

Required? | Data Type | Example Value |
---|---|---|

Yes | String (column reference) | myValues |

## Examples

**提示**

For additional examples, see Common Tasks.

This example demonstrates you to extract values from one column of an array into a new column.

**Functions**:

Item | Description |
---|---|

LIST Function | Extracts the set of values from a column into an array stored in a new column. This function is typically part of an aggregation. |

UNIQUE Function | Extracts the set of unique values from a column into an array stored in a new column. This function is typically part of an aggregation. |

DATEFORMAT Function | Formats a specified Datetime set of values according to the specified date format. Source values can be a reference to a column containing Datetime values. |

You have the following set of orders for two months, and you are interested in identifying the set of colors that have been sold for each product for each month and the total quantity of product sold for each month.

**Source:**

OrderId | Date | Item | Qty | Color |
---|---|---|---|---|

1001 | 1/15/15 | Pants | 1 | red |

1002 | 1/15/15 | Shirt | 2 | green |

1003 | 1/15/15 | Hat | 3 | blue |

1004 | 1/16/15 | Shirt | 4 | yellow |

1005 | 1/16/15 | Hat | 5 | red |

1006 | 1/20/15 | Pants | 6 | green |

1007 | 1/15/15 | Hat | 7 | blue |

1008 | 4/15/15 | Shirt | 8 | yellow |

1009 | 4/15/15 | Shoes | 9 | brown |

1010 | 4/16/15 | Pants | 1 | red |

1011 | 4/16/15 | Hat | 2 | green |

1012 | 4/16/15 | Shirt | 3 | blue |

1013 | 4/20/15 | Shoes | 4 | black |

1014 | 4/20/15 | Hat | 5 | blue |

1015 | 4/20/15 | Pants | 6 | black |

**Transformation:**

To track by month, you need a column containing the month value extracted from the date:

Transformation Name | |
---|---|

Parameter: Columns | Date |

Parameter: Formula | DATEFORMAT(Date, 'MMM yyyy') |

You can use the following transform to check the list of unique values among the colors:

Transformation Name | |
---|---|

Parameter: Row labels | Date |

Parameter: Values | unique(Color, 1000) |

Parameter: Max number of columns to create | 10 |

Date | unique_Color |
---|---|

Jan 2015 | ["green","blue","red","yellow"] |

Apr 2015 | ["brown","blue","red","yellow","black","green"] |

Delete the above transform.

You can aggregate the data in your dataset, grouped by the reformatted `Date`

values, and apply the `LIST`

function to the `Color`

column. In the same aggregation, you can include a summation function for the `Qty`

column:

Transformation Name | |
---|---|

Parameter: Row labels | Date |

Parameter: Values | list(Color, 1000),sum(Qty) |

Parameter: Max number of columns to create | 10 |

**Results:**

Date | list_Color | sum_Qty |
---|---|---|

Jan 2015 | ["green","blue","blue","red","green","red","yellow"] | 28 |

Apr 2015 | ["brown","blue","red","yellow","black","blue","black","green"] | 38 |