Create buckets - Text
You can choose to implement bucketing in a text column using conditions.
Consider a situation where you need to assign people to specific teams.
You can implement the logic of adding values to a bucket, which in this case is the team name.
|
Name
|
Team
|
| Sena, Stephen, Alfy |
Sales
|
|
Weber, Tandy, Hallsy
|
Marketing
|
|
Jared
|
Engineering
|
|
Jerrie, Karim
|
Support
|
In order to start the bucketing process with this data, you can form the conditions, such as:
If value in (
Sena, Stephen, Alfy
), add to the bucket: Sales
If value in (
Weber, Tandy, Hallsy
), add to the bucket: Marketing
If value in (
Jerrie, Karim
) add to the bucket: Support
If value in (
Jared
) add to the bucket: Engineering
Apart from the "in" condition, you can use the following other conditions:
-
not in
-
contains
-
doesn't contain
-
begins with
-
doesn't begin with
-
ends with
-
doesn't end with
-
regex
To apply bucketing in a text column:
-
Right-click the text column in the
Studio
page.
-
Select the Create Buckets
option from the context menu.
-
In the Studio
panel, give a name to your new column under
Base column name
.
-
Enter the label for the bucket in the field
Bucket label.
-
If the selected column has values that won't fit in any of the conditions, it is marked with a separate label such as NA under the
Label for unmatched values
option.
-
Enter the conditions as required and click
Save
(please refer to the sample use cases and examples above).
-
A preview of the resultant column will be shown next to the selected column in the data grid.
-
Click Apply.
To apply filters
If you want to apply some filters along with this transform, you can use the filters functionality.
1. Click the
Filters
tab.
2. Click the
icon and add the required columns in the Filters section. You can also reorder the filters using the drag and drop method.
3. For every column added, you can select one of the following options from the drop-down:
- Actual: This option lets you filter rows based on the actual values in the column. Click here to know more.
-
Data quality: This option lets you filter rows based on the quality of data in the column. Click
here
to know more.
- Patterns: This option helps you filter rows based on the data patterns in the selected column. Click here to know more.
- Outliers: This option allows you to filter rows based on the outliers present in the data of the selected column. Click here to know more.
Note: The filter options are displayed based on the datatype of the column added for the filter.
4. When you add more than one filter to the
Filters
section, the logical operators, AND or OR appear next to the filters. You can click to toggle the logical operator between AND and OR.
-
Using the logical operators, you can combine the conditions and apply logic to determine the rule of precedence. The final expression is displayed in the
Criteria expression
box. You can click
Edit
to alter the default expression using logical operators and parenthesis to specify the precedence or the sequential order as to which condition should be evaluated first. Click Save after making the required changes.
- For example, In the expression, ((1 OR 2) AND (3 OR 4)) , at first the condition ( 1 OR 2 ) will be executed and the condition ( 3 OR 4 ) will be executed next. Thirdly, since, the AND operator is used, the filter will be applied when both the conditions are true.
5. You can further drill down to choose specific values based on the filter option selected for each filter, in the next section.
For example, in the above screenshot, the
Data quality
option is selected for the All columns filter in the
Filters
section. Based on the selection, further options to filter specific values are displayed in the
All columns (Data quality)
section.
6. You can choose to include or exclude the selected items in the last section.
7. If you want to remove all the filters for some reason, you can use the
Clear
button.
8. A live preview of the filter transform is shown as you make changes.
9. Click the
Apply
button to apply the transform along with the filters.
SEE ALSO
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