- Query and analyze data
Filtering is an essential step in your analysis workflow, and it is a powerful and easy way to see different cuts of your data. Now with Helix, you can easily load millions of rows of raw data and filter on top of your large dataset.
Report vs visualization filters
There are two types of filters in Mode:
- Report-level filters: These are filters that you create from the Report Builder and apply to all charts in your report. Generally, you create these for your report viewers to be able to filter data themselves. For more information on report filters, refer to this section in our Reports page.
- Visualization-level filters: These are filters that you create from the Chart Editor and apply only to that one chart. Report viewers will not see the visualization filters that you’ve applied. Generally, you create these to filter data completely from view.
Once you have your dataset and have created a visualization, you can add and apply visualization filters.
- Drag and drop the field that you want to filter on into the Filters dropzone, highlighted above.
- Depending on the datatype of your field (i.e. if it’s timestamp or numeric), you may now see a modal pop-up appear that asks how you’d like to filter that field.
- Once you’ve configured the values that you want to include or exclude, hit
Applyso that the changes will reflect in your visualization.
Congratulations! You’ve created a visualization filter. There should be a now field pill in the Filters dropzone.
As previously mentioned, there are different filter options depending on the datatype of your field.
Boolean & string fields
When you drag and drop a string or boolean field into the Filters dropzone, you will see the list of values within that field.
Include values You can check values that you want to include in your visualization and uncheck values that you do not want to include. This is the default pattern.
Exclude values You can toggle on the mode to exclude selected values. Once this mode is turned on, all checked values are now explicitly excluded from this dataset.
There are several reasons why you may want to explicitly exclude as opposed to not include:
- If you only want to exclude a small number of values, excluding a few values is more performant than including everything but a few values.
- As new values appear in your field in the future, the filter will include these new values when in Exclude mode. Otherwise, these new values will not be included in Include mode.
There are 2 ways you can filter numeric data:
- Continuous range: You can set optional start and/or end values to create an inclusive range. If there is no start or no end value provided, the filter will assume there is no minimum or maximum.
- Discrete list of values: You can select from a list of individual values in your field.
There are 3 ways you can filter datetime data:
- Continuous range of dates: You can set optional start and/or end dates to create an inclusive date range. If there is no start or no end date provided, the filter will assume there is no limit.
- Discrete list of individual datetimes: You can select from a list of individual datetime values in your field.
- Discrete date parts: You can truncate your datetime from year up to the second and select from a discrete list of date part options.
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