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Review fields

You'll start by reviewing the fields available in your data to determine which ones will be necessary for your project.

  1. Download the Japan Prefectures project package.

    A file named JapanPrefectures.ppkx is downloaded to your computer. A .ppkx file is an ArcGIS Pro project package and may contain maps, data, and other files that you can open in ArcGIS Pro.

  2. Locate the downloaded file on your computer. Double-click JapanPrefectures.ppkx to open it in ArcGIS Pro. If prompted, sign in with your ArcGIS account.
    Note:

    If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

    A map appears, showing the prefectures of Japan.

    Map of prefectures in Japan

    The data for this map comes from Natural Earth. The original dataset covered the whole world, but this copy is limited to Japan.

  3. On the map, click one of the prefectures.

    A pop-up appears.

    Pop-up for Toyama prefecture

    The pop-up displays a long list of fields, most of which won't be needed for your project.

    Some of the fields contain codes and other values that you don't recognize, some contain the name of the prefecture in different languages, and some are empty.

    One attribute that you'll need frequent access to during your project is region. Japan is divided into eight regions, which are in turn divided into prefectures. You'll need to sort and filter data based on regions, so before you continue, you'll ensure this information is included in the layer's attributes.

  4. Scroll through the pop-up and search for a region field.

    Pop-up with region field highlighted

    A region field can be found about one-sixth of the way down the list. It would be easier to find if there were fewer fields to scroll through.

  5. Close the pop-up.

Hide fields

Most of the fields in this layer are not needed for your project and are getting in the way of the ones that are. You can choose which fields to show and which to hide in the layer's fields view.

  1. In the Contents pane, right-click Japan Prefectures, point to Data Design, and choose Fields.

    Fields in the layer's context menu

    The fields view appears. Each row in this table represents a field in the Japan Prefectures layer. In this view, you can create, edit, and delete fields.

  2. Click the header of the Visible column.

    All of the check boxes in the column become unchecked.

    Visible column in fields view

    A green square appears to the left of every row to indicate that it has been edited.

    You'll recheck those layers that are useful to your project.

  3. In the Visible column, check the box for the OBJECTID row.
  4. Also check the box for the iso_3166_2 field.

    Visible column checked for two rows

    ISO stands for International Organization for Standardization. This field contains unique identifiers for each prefecture using the ISO 3166 standard. You'll need these codes later to perform joins with other datasets.

    Note:

    Learn more about table joins in the tutorial Join tabular data to a spatial layer.

    The other fields will be easier to find if you search for them.

  5. On the ribbon, if it is not already active, click the Fields tab.
  6. In the Filter group, for Filter Name, type name.

    Filter Name box on the ribbon

    The table filters to show only those fields that contain the word name.

  7. In the Visible column, check the box for the name field.

    Visible column checked for the name field

  8. Filter the table to find the following additional fields. Turn on visibility for each of them:
    • type_en
    • region
    • abbrev
  9. Clear the filter.
  10. Scroll through the table to confirm that only six fields are marked as Visible.

    Fields view table

  11. On the ribbon, in the Manage Edits group, click Save.

    Save button on the Fields tab of the ribbon

    The green squares disappear from the left column of the table.

  12. Close the fields view.

    Next, you'll open the attribute table to view your changes and determine whether they are appropriate for your project.

  13. In the Contents pane, right-click Japan Prefectures and choose Attribute Table.

    Attribute Table in the layer's context menu

    The attribute table appears below the map. It only displays 6 fields instead of the original 124.

    Attribute table

  14. Review the attribute table. Look for fields where all values are the same.

    Every row in the type_en field appears to contain the same value: Prefecture. It seems likely that this field is unnecessary and should be hidden. But before you decide to hide the type_en field, you'll sort it to find out whether there are other values.

  15. Right-click the header of the type_en column and choose Sort Ascending.

    Sort Ascending in the type_en context menu

    Two rows at the top of the column have type_en values other than Prefecture. Hokkaidō is a Circuit and Tokyo is a Metropolis.

    Circuit and Metropolis type_en values
  16. Double-click the header of the type_en column to sort it in the opposite direction.

    Two more rows (Kyōto and Ōsaka) have a type_en value of Urban Prefecture.

    Urban Prefecture type_en values

    There are different kinds of prefectures in Japan, and it may be useful later to compare demographic variables across prefecture types, so you will keep the type_en field.

    The abbrev field is empty. You had hoped that it would contain abbreviations that might help with joining certain datasets, but it does not provide any useful information, so you'll hide it. You can hide fields directly through the attribute table instead of the fields view.

  17. Right-click the header of the abbrev column and choose Hide Field.

    Hide Field in the abbrev context menu

    Tip:

    You can also hide a field with the following shortcut: press the Ctrl key and double-click the field header.

    The abbrev field disappears from the attribute table. Only five fields remain.

Edit field aliases

Next, you'll edit the aliases of the fields so they are easier to interpret in the attribute table and pop-up.

  1. In the attribute table, right-click the header for the iso_3166_2 field and choose Fields.

    Fields in the iso_3166_2 context menu

    The fields view reappears. The iso_3166_2 field is highlighted.

  2. In the fields view, in the Alias column, double-click iso_3166_2. Type ISO code.

    Alias edited to ISO code

  3. Edit the alias of the type_en field to type.
  4. Right-click anywhere on the table and click Save.

    Save in the fields view context menu

  5. Above the fields view, click the Japan Prefectures tab to switch to the attribute table.

    Japan Prefectures attribute table

    The attribute table has updated to display the new aliases.

  6. On the map, click one of the prefectures.

    Pop-up for Okayama prefecture

    The pop-up that appears has only a few fields and none of their names are unclear. It is easier to find the information that you need.

  7. Close the pop-up.

Highlight a field

Later, you'll need frequent access to the ISO code field, since you will use it to join demographic data to the layer. This field is easy to find now, but later, when you join dozens of extra fields, it may become lost. You'll highlight the ISO code field to differentiate it visually from all the others in the attribute table.

  1. Above the attribute table, click the Fields: Japan Prefectures tab to switch to the fields view.
  2. In the fields view, in the Highlight column, check the box for the iso_3166_2 row.

    Highlight column checked for the ISO code field

  3. Save the changes to the fields view.
  4. Switch to the attribute table.

    In the attribute table, the ISO code column is highlighted in yellow.

    ISO code field highlighted in the attribute table

  5. Close the attribute table and the fields view.
  6. On the Quick Access Toolbar, click the Save Project button.

    Save Project button on the Quick Access Toolbar

In this tutorial, you prepared a layer for analysis by tidying its fields. You learned the following skills:

  • How to hide fields
  • How to sort a field in the attribute table
  • How to edit field aliases
  • How to highlight a field

The rest of your analysis will proceed more smoothly thanks to the time you have taken to prepare the data.

You can find more tutorials in the tutorial gallery.