| Excerpt |
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For each unique value in a column, a separate column is created. For each row that contains the value in the source column, an indicator value is inserted in the new column. |
- This indicator value can be a literal value or the output of a function.
- If no indicator value is generated, a null value is written.
This transform is used to generate indicator columns, which can be used in statistical analysis.
- It evaluates entire cell values for uniqueness. It does not scan for individual elements in Object or Array data.
- If a row in the source column contains a missing value, an indicator value is added in a new
Empty column. - It is not appropriate for tabulating counts of strings or patterns in a column. See Countpattern Transform.
Optionally, you can specify a default value, which is applied to all non-indicator value cells in the new column.
| Info |
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NOTE: When this transform is applied in the data grid, it only identifies the unique values in the current sample. If there are other unique values in the entire dataset, new columns are not created for them when the transform is executed across the entire dataset. |
Source:
| Data |
|---|
| Happy |
| Dog |
| Happy Happy Dog |
Transform:
| D code |
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valuestocols col:Data value:'X' |
Results:
| Data | Happy | Dog | Happy_Happy_Dog |
|---|
| Happy | X | | |
| Dog | | X | |
| Happy Happy Dog | | | X |
| D code |
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valuestocols col:column_ref value:(expression) default:(expression) [limit:int_num] |
| Token | Required? | Data Type | Description |
|---|
| values tocols | Y | transform | Name of the transform |
| col | Y | string | Name of source column |
| value | Y | string | String literal, column, or function call that defines the value to use as the indicator value in any newly generated column |
| default | N | string | String literal, column, or function call that defines the value to use to indicate a false match in any newly generated column |
| limit | N | integer (positive) | Maximum number of columns to generate. Default is 50. |
Identifies the column to which to apply the transform. You can specify only one column.
| Required? | Data Type |
|---|
| Yes | String (column name) |
For the valuestocols transform, this parameter specifies the value to insert in each row of a generated column where the column name of the generated column appears in the same row of the source column. This value can be a string literal, a column reference, or a function.
| Required? | Data Type |
|---|
| Yes | String literal, column reference, or function call |
Optionally, this parameter can be used to specify the value to insert in each row of a generated column where the column name of the generated column does not appear in the same row of the source column. This value can be a string literal, a column reference, or a function.
If this parameter is not specified, a missing value is inserted.
| Required? | Data Type |
|---|
| No | String literal, column reference, or function call |
The limit parameter defines the maximum number of columns to create from the unique values detected in the source column. If not specified, the limit is 50.
| Info |
|---|
NOTE: Be careful setting this parameter too high. In some cases, the application can run out of memory generating the results, and your results can fail. |
| Required? | Data Type |
|---|
No. Default value is 50. | Integer (positive) |
Source:
This dataset contains onboarding milestones for three employees who joined the company at the same time. The milestones were recorded and organized by date as individual items, so it's not easy to verify that all five milestones have been checked off for each employee:
Orientation
Contact Info
Acquire Computer
HR Policies Training
Product Training
| Date | Name | onboardingChecklist |
|---|
| 4/4/16 | Bowie Kuhn | Orientation |
| 4/4/16 | Happy Chandler | Contact Info |
| 4/4/16 | Bowie Kuhn | Contact Info |
| 4/4/16 | Bowie Kuhn | Acquire Computer |
| 4/4/16 | Bud Selig | Product Training |
| 4/4/16 | Bud Selig | Orientation |
| 4/5/16 | Happy Chandler | HR Policies Training |
| 4/5/16 | Happy Chandler | Orientation |
| 4/5/16 | Happy Chandler | Acquire Computer |
| 4/5/16 | Bowie Kuhn | HR Policies Training |
| 4/5/16 | Bud Selig | HR Policies Training |
| 4/5/16 | Bud Selig | Contact Info |
| 4/6/16 | Happy Chandler | Product Training |
Transform:
The following transform creates columns for each of the values in the onboardingChecklist column and adds a yes value where there is a match for the row:
| D code |
|---|
valuestocols col: onboardingChecklist value:'yes' |
Results:
In the generated columns, you can quickly assess whether all three employees have completed an individual onboarding item:
- Bud Selig has not acquired his computer.
- Bowie Kuhn has not had product training.
| Date | Name | onboardingChecklist | Orientation | Contact_Info | Acquire_Computer | Product_Training | HR_Policies_Training |
|---|
| 4/4/16 | Bowie Kuhn | Orientation | yes | | | | |
| 4/4/16 | Happy Chandler | Contact Info | | yes | | | |
| 4/4/16 | Bowie Kuhn | Contact Info | | yes | | | |
| 4/4/16 | Bowie Kuhn | Acquire Computer | | | yes | | |
| 4/4/16 | Bud Selig | Product Training | | | | yes | |
| 4/4/16 | Bud Selig | Orientation | yes | | | | |
| 4/5/16 | Happy Chandler | HR Policies Training | | | | | yes |
| 4/5/16 | Happy Chandler | Orientation | yes | | | | |
| 4/5/16 | Happy Chandler | Acquire Computer | | | yes | | |
| 4/5/16 | Bowie Kuhn | HR Policies Training | | | | | yes |
| 4/5/16 | Bud Selig | HR Policies Training | | | | | yes |
| 4/5/16 | Bud Selig | Contact Info | | yes | | | |
| 4/6/16 | Happy Chandler | Product Training | | | | yes | |
| Include Page |
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| EXAMPLE - Flatten and Valuestocols Transforms |
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| EXAMPLE - Flatten and Valuestocols Transforms |
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| D s also |
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| label | wrangle_transform_valuestocols |
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