# KTHLARGESTIF Function

Extracts the ranked value from the values in a column, where `k=1`

returns the maximum value, when a specified condition is met. The value for `k`

must be between 1 and 1000, inclusive. Inputs can be Integer, Decimal, or Datetime.

`KTHLARGESTIF`

calculations are filtered by a conditional applied to the group.

For purposes of this calculation, two instances of the same value are treated as separate values. So, if your dataset contains three rows with column values `10`

, `9`

, and `9`

, then `KTHLARGEST`

returns `9`

for `k=2`

and `k=3`

.

Input column can be of Integer, Decimal, or Datetime type. Other values column are ignored. If a row contains a missing or null value, it is not factored into the calculation.

**Nota**

When added to a transformation, this function is applied to the current sample. If you change your sample or run the job, the computed values for this function are updated. Transformations that change the number of rows in subsequent recipe steps do not affect the values computed for this step.

To perform a simple kth largest calculation without conditionals, use the `KTHLARGEST`

function. See KTHLARGEST 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

kthlargestif(POS_Sales, 1, DayOfWeek == 'Saturday')

**Output:** Returns the top value (rank=1) from the `POS_Sales`

column when the `DayOfWeek`

value is `Saturday`

.

## Syntax and Arguments

kthlargestif(col_ref, limit, test_expression) [group:group_col_ref] [limit:limit_count]

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

col_ref | Y | string | Reference to the column you wish to evaluate. |

k_integer | Y | integer | The ranking of the value to extract from the source column |

test_expression | Y | string | Expression that is evaluated. Must resolve to |

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

For more information on the `group`

and `limit`

parameter, see Pivot Transform.

### col_ref

Name of the column whose values you wish to use in the calculation. Inputs must be Integer, Decimal, or Datetime values.

**Nota**

If the input is in Datetime type, the output is in unixtime format. You can wrap these outputs in the DATEFORMAT function to output the results in the appropriate Datetime format. See DATEFORMAT Function.

** Usage Notes:**

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

Yes | String that corresponds to the name of the column | myValues |

### k_integer

Integer representing the ranking of the value to extract from the source column.

**Nota**

The value for `k`

must be an integer between 1 and 1,000 inclusive.

`k=1`

represents the maximum value in the column.If k is greater than or equal to the number of values in the column, the minimum value is returned.

Missing and null values are not factored into the ranking of

`k`

.

### test_expression

This parameter contains the expression to evaluate. This expression must resolve to a Boolean (`true`

or `false`

) value.

** Usage Notes:**

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

Yes | String expression that evaluates to | (LastName == 'Mouse' && FirstName == 'Mickey') |

## Examples

**Suggerimento**

For additional examples, see Common Tasks.

### Example - Second-most measurements for a specific city

This example illustrates how to use the conditional ranking functions.

**Functions:**

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

KTHLARGESTIF Function | Extracts the ranked value from the values in a column, where |

KTHLARGESTUNIQUEIF Function | Extracts the ranked unique value from the values in a column, where |

**Source:**

Here is some example weather data:

date | city | rain_cm | temp_C | wind_mph |
---|---|---|---|---|

1/23/17 | Valleyville | 0.00 | 12.8 | 8.8 |

1/23/17 | Center Town | 0.31 | 9.4 | 5.3 |

1/23/17 | Magic Mountain | 0.00 | 0.0 | 7.3 |

1/24/17 | Valleyville | 0.25 | 17.2 | 3.3 |

1/24/17 | Center Town | 0.54 | 1.1 | 7.6 |

1/24/17 | Magic Mountain | 0.32 | 5.0 | 8.8 |

1/25/17 | Valleyville | 0.02 | 3.3 | 6.8 |

1/25/17 | Center Town | 0.83 | 3.3 | 5.1 |

1/25/17 | Magic Mountain | 0.59 | -1.7 | 6.4 |

1/26/17 | Valleyville | 1.08 | 15.0 | 4.2 |

1/26/17 | Center Town | 0.96 | 6.1 | 7.6 |

1/26/17 | Magic Mountain | 0.77 | -3.9 | 3.0 |

1/27/17 | Valleyville | 1.00 | 7.2 | 2.8 |

1/27/17 | Center Town | 1.32 | 20.0 | 0.2 |

1/27/17 | Magic Mountain | 0.77 | 5.6 | 5.2 |

1/28/17 | Valleyville | 0.12 | -6.1 | 5.1 |

1/28/17 | Center Town | 0.14 | 5.0 | 4.9 |

1/28/17 | Magic Mountain | 1.50 | 1.1 | 0.4 |

1/29/17 | Valleyville | 0.36 | 13.3 | 7.3 |

1/29/17 | Center Town | 0.75 | 6.1 | 9.0 |

1/29/17 | Magic Mountain | 0.60 | 3.3 | 6.0 |

** Transformation:**

In this case, you want to find out the second-most measures for rain, temperature, and wind in Center Town for the week.

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

Parameter: Values | KTHLARGESTIF(rain_cm,2,city == 'Center Town') |

Parameter: Max number of columns to create | 1 |

You can see in the preview that the value is `1.32`

. Before adding it to your recipe, you change the step to the following:

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

Parameter: Values | KTHLARGESTIF(temp_C,2,city == 'Center Town') |

Parameter: Max number of columns to create | 1 |

The value is `20`

.

For wind, you modify it to be the following, capturing the third-ranked value:

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

Parameter: Values | KTHLARGESTIF(wind_mph,3,city == 'Center Town') |

Parameter: Max number of columns to create | 1 |

In the results, you notice that there are two values for `8.8`

. So you change the function to use the `KTHLARGESTUNIQUEIF`

function instead:

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

Parameter: Values | KTHLARGESTUNIQUEIF(wind_mph,3,city == 'Center Town') |

Parameter: Max number of columns to create | 1 |

The result value is `7.6`

. Note that this value appears twice, so if you change the rank parameter in the above transformation to `4`

, the results would return a different unique ranked value (`7.3`

).

**Results:**

You can choose to add any of these steps to generate an aggregated result. As an alternative, you can use a `derive`

transform to insert these calculated results into new columns.