CORREL Function
Computes the correlation coefficient between two columns. Source values can be of Integer or Decimal type.
The correlation coefficient measures the relationship between two sets of values. You can use it as a measurement for how changes in one value affect changes in the other.
Values range between -1 (negative correlation) and +1 (positive correlation).
Negative correlation means that the second number tends to decrease when the first number increases.
Positive correlation means that the second number tends to increase when the first number increases.
A correlation coefficient that is close to 0 indicates a weak or non-existent correlation.
Terms...
Relevant terms:
Term | Description |
|---|---|
Population | Population statistical functions are computed from all possible values. See https://en.wikipedia.org/wiki/Statistical_population. |
Sample | Sample-based statistical functions are computed from a subset or sample of all values. See https://en.wikipedia.org/wiki/Sampling_(statistics). These function names include Nota Statistical sampling has no relationship to the samples taken within the product. When statistical functions are computed during job execution, they are applied across the entire dataset. Sample method calculations are computed at that time. |
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
correl(initialInvestment,ROI)
Output: Returns the correlation coefficient between the values in the initialInvestment column and the ROI column.
Syntax and Arguments
correl(function_col_ref1,<span>function_col_ref2</span>) [group:group_col_ref] [limit:limit_count]
Argument | Required? | Data Type | Description |
|---|---|---|---|
function_col_ref1 | Y | string | Name of column that is the first input to the function |
function_col_ref2 | Y | string | Name of column that is the second input to 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_ref1, function_col_ref2
Name of the column the values of which you want to calculate the correlation. 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) | myInputs |
Examples
Suggerimento
For additional examples, see Common Tasks.
This example illustrates statistical functions that can be applied across two columns of values.
Functions:
Item | Description |
|---|---|
CORREL Function | Computes the correlation coefficient between two columns. Source values can be of Integer or Decimal type. |
COVAR Function | Computes the covariance between two columns using the population method. Source values can be of Integer or Decimal type. |
COVARSAMP Function | Computes the covariance between two columns using the sample method. Source values can be of Integer or Decimal type. |
ROUND Function | Rounds input value to the nearest integer. Input can be an Integer, a Decimal, a column reference, or an expression. Optional second argument can be used to specify the number of digits to which to round. |
Source:
The following table contains height in inches and weight in pounds for a set of students.
Student | heightIn | weightLbs |
|---|---|---|
1 | 70 | 134 |
2 | 67 | 135 |
3 | 67 | 147 |
4 | 67 | 160 |
5 | 72 | 136 |
6 | 73 | 146 |
7 | 71 | 135 |
8 | 63 | 145 |
9 | 67 | 138 |
10 | 66 | 138 |
11 | 71 | 161 |
12 | 70 | 131 |
13 | 74 | 131 |
14 | 67 | 157 |
15 | 73 | 161 |
16 | 70 | 133 |
17 | 63 | 132 |
18 | 64 | 153 |
19 | 64 | 156 |
20 | 72 | 154 |
Transformation:
You can use the following transformations to calculate the correlation co-efficient, the covariance, and the sampling method covariance between the two data columns:
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | round(correl(heightIn, weightLbs), 3) |
Parameter: New column name | 'corrHeightAndWeight' |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | round(covar(heightIn, weightLbs), 3) |
Parameter: New column name | 'covarHeightAndWeight' |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | round(covarsamp(heightIn, weightLbs), 3) |
Parameter: New column name | 'covarHeightAndWeight-Sample' |
Results:
Student | heightIn | weightLbs | covarHeightAndWeight-Sample | covarHeightAndWeight | corrHeightAndWeight |
|---|---|---|---|---|---|
1 | 70 | 134 | -2.876 | -2.732 | -0.074 |
2 | 67 | 135 | -2.876 | -2.732 | -0.074 |
3 | 67 | 147 | -2.876 | -2.732 | -0.074 |
4 | 67 | 160 | -2.876 | -2.732 | -0.074 |
5 | 72 | 136 | -2.876 | -2.732 | -0.074 |
6 | 73 | 146 | -2.876 | -2.732 | -0.074 |
7 | 71 | 135 | -2.876 | -2.732 | -0.074 |
8 | 63 | 145 | -2.876 | -2.732 | -0.074 |
9 | 67 | 138 | -2.876 | -2.732 | -0.074 |
10 | 66 | 138 | -2.876 | -2.732 | -0.074 |
11 | 71 | 161 | -2.876 | -2.732 | -0.074 |
12 | 70 | 131 | -2.876 | -2.732 | -0.074 |
13 | 74 | 131 | -2.876 | -2.732 | -0.074 |
14 | 67 | 157 | -2.876 | -2.732 | -0.074 |
15 | 73 | 161 | -2.876 | -2.732 | -0.074 |
16 | 70 | 133 | -2.876 | -2.732 | -0.074 |
17 | 63 | 132 | -2.876 | -2.732 | -0.074 |
18 | 64 | 153 | -2.876 | -2.732 | -0.074 |
19 | 64 | 156 | -2.876 | -2.732 | -0.074 |
20 | 72 | 154 | -2.876 | -2.732 | -0.074 |