Stat-Xplore Documentation

The Remove Item Button

This section will cover:

  • Introduction
  • Remove Fields
  • Remove Values (Advanced)
  • Knowledge Check


Introduction

The learning objectives for this page are:

  • How to remove certain aspects of your table

As mentioned previously in (Clear table), if you have made a mistake while designing your custom bespoke table, instead of using the ‘Clear Table’ button, you can also use the ‘Remove Item’ button. Rather than clearing the whole table, the ‘Remove Item’ button allows for more precision in only deleting certain fields or values.



Remove Fields

To remove a certain field (any variable in the horizontal column) in your table you can,

  1. Manipulate your cursor to drag and drop your desired field name onto the remove item icon.

    2. In Employment filter added

  2. Stat-Xplore will then remove the entire field from the table. As you can see in the screenshot below, the empty field between the ‘Month’ and ‘Gender’ in the horizontal column is no longer there.

    3. In Employment filter added



Remove Values (Advanced)

The ‘Remove Values’ function allows you to select and remove individual values within any field (i.e.: any variable).

For example, suppose we have decided that we do not want to include all the values of the Age (bands and single year) field in our table. We can use the menu on the left-hand side to remove individual field values. To do this in our example we can,

  1. Click the black arrow icon to expand Age (bands and single year) (if it is not already expanded). Any field values that are currently in the table will appear in bold and italics.

    2. In Employment filter added

  2. Next, select the check boxes for any values you want to remove from the table. In the case of this example, this includes the values of ‘Over 65’ and ‘Unknown/Missing’.
  3. Click the ‘Remove’ Button that is located at the top of the menu of the left-hand side.
  4. Click the ‘Retrieve Data' button to repeat the cross tabulation with the newly updated values.

    5. In Employment filter added

  5. Your table is now updated with the new values.


Further Questions

If you still have any questions that are not answered in the guide, please feel free to email Stat.Xplore@dwp.gov.uk



Check your Knowledge!

Navigate to the dataset ‘NINO Registrations’, the data cube ‘HNINO Registration to Adult Overseas Nationals Entering the UK’, and open the table ‘NINO2 - Age by Gender by Latest Rolling Year’. Remove the field ‘Age by Registration’. How many Males had NINO Registrations in 2022?

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Attachments:

SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-With-Filter.png (image/png)
SW2-Filters-Add-1.png (image/png)
SW2-Filters-Add-2.png (image/png)
SW2-Filters-Remove.png (image/png)
SW2-Filters-Remove.png (image/png)
SW2-Filters-Add-1.png (image/png)
SW2-Filters-Add-2.png (image/png)
SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-With-Filter.png (image/png)
SW2-Default-Summation-Filter.png (image/png)
SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-With-Filter.png (image/png)
SW2-Default-Summation-Filter.png (image/png)
SW2-Filters-Add-1.png (image/png)
SW2-Filters-Add-2.png (image/png)
SW2-Filters-Remove.png (image/png)
SW2-Filters-Add-1.png (image/png)
SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-With-Filter.png (image/png)
SW2-Default-Summation-Filter.png (image/png)
SW2-Filters-Add-2.png (image/png)
SW2-Filters-Remove.png (image/png)
SW2-Filters-EG-No-Filter.png (image/png)
SW2-Filters-EG-With-Filter.png (image/png)
SW2-Default-Summation-Filter.png (image/png)
SW2-Filters-Add-2.png (image/png)
SW2-Filters-Remove.png (image/png)