MODE Function
Computes the mode (most frequent value) from all row values in a column, according to their grouping. Input column can be of Integer, Decimal, or Datetime type.
If a row contains a missing or null value, it is not factored into the calculation. If the entire column contains no values, the function returns a null value.
If there is a tie in which the most occurrences of a value is shared between values, then the lowest value of the evaluated set is returned.
When used in a
pivottransform, the function is computed for each instance of the value specified in thegroupparameter. See Pivot Transform.
For a version of this function computed over a rolling window of rows, see ROLLINGMODE Function.
Datetime inputs to this function return Unixtime values.
These values can be wrapped in a DATEFORMAT function. See DATEFORMAT Function.
For a date-native version of this function, see MODEDATE 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
mode(count_visits)
Output: Returns the mode of the values in the count_visits column.
Syntax and Arguments
mode(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 function. Column must contain 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 generate the results in the appropriate Datetime format. See DATEFORMAT Function.
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
Sugerencia
For additional examples, see Common Tasks.
Example - Statistics on Test Scores
This example illustrates how you can apply statistical functions to your dataset. Calculations include average (mean), max, min, standard deviation, and variance.
Functions:
Item | Description |
|---|---|
AVERAGE Function | Computes the average (mean) from all row values in a column or group. Input column can be of Integer or Decimal. |
MIN Function | Computes the minimum value found in all row values in a column. Input column can be of Integer, Decimal or Datetime. |
MAX Function | Computes the maximum value found in all row values in a column. Inputs can be Integer, Decimal, or Datetime. |
VAR Function | Computes the variance among all values in a column. Input column can be of Integer or Decimal. If no numeric values are detected in the input column, the function returns |
STDEV Function | Computes the standard deviation across all column values of Integer or Decimal type. |
NUMFORMAT Function | Formats a numeric set of values according to the specified number formatting. Source values can be a literal numeric value, a function returning a numeric value, or reference to a column containing an Integer or Decimal values. |
MODE Function | Computes the mode (most frequent value) from all row values in a column, according to their grouping. Input column can be of Integer, Decimal, or Datetime type. |
Source:
Students took a test and recorded the following scores. You want to perform some statistical analysis on them:
Student | Score |
|---|---|
Anna | 84 |
Ben | 71 |
Caleb | 76 |
Danielle | 87 |
Evan | 85 |
Faith | 92 |
Gabe | 85 |
Hannah | 99 |
Ian | 73 |
Jane | 68 |
Transformation:
You can use the following transformations to calculate the average (mean), minimum, and maximum scores:
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | AVERAGE(Score) |
Parameter: New column name | 'avgScore' |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | MIN(Score) |
Parameter: New column name | 'minScore' |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | MAX(Score) |
Parameter: New column name | 'maxScore' |
To apply statistical functions to your data, you can use the VAR and STDEV functions, which can be used as the basis for other statistical calculations.
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | VAR(Score) |
Parameter: New column name | var_Score |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | STDEV(Score) |
Parameter: New column name | stdev_Score |
For each score, you can now calculate the variation of each one from the average, using the following:
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | ((Score - avg_Score) / stdev_Score) |
Parameter: New column name | 'stDevs' |
Now, you want to apply grades based on a formula:
Grade | standard deviations from avg (stDevs) |
|---|---|
A | stDevs > 1 |
B | stDevs > 0.5 |
C | -1 <= stDevs <= 0.5 |
D | stDevs < -1 |
F | stDevs < -2 |
You can build the following transformation using the IF function to calculate grades.
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | IF((stDevs > 1),'A',IF((stDevs < -2),'F',IF((stDevs < -1),'D',IF((stDevs > 0.5),'B','C')))) |
To clean up the content, you might want to apply some formatting to the score columns. The following reformats the stdev_Score and stDevs columns to display two decimal places:
Transformation Name | |
|---|---|
Parameter: Columns | stdev_Score |
Parameter: Formula | NUMFORMAT(stdev_Score, '##.00') |
Transformation Name | |
|---|---|
Parameter: Columns | stDevs |
Parameter: Formula | NUMFORMAT(stDevs, '##.00') |
Transformation Name | |
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | MODE(Score) |
Parameter: New column name | 'modeScore' |
Results:
Student | Score | modeScore | avgScore | minScore | maxScore | var_Score | stdev_Score | stDevs | Grade |
|---|---|---|---|---|---|---|---|---|---|
Anna | 84 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 0.21 | C |
Ben | 71 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | -1.18 | D |
Caleb | 76 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | -0.64 | C |
Danielle | 87 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 0.54 | B |
Evan | 85 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 0.32 | C |
Faith | 92 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 1.07 | A |
Gabe | 85 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 0.32 | C |
Hannah | 99 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | 1.82 | A |
Ian | 73 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | -0.96 | C |
Jane | 68 | 85 | 82 | 68 | 99 | 87.00000000000001 | 9.33 | -1.50 | D |