When importing your data, you can also choose to filter the dataset you'd like to import. For example, you can skip any rows that don't have a location input or unique IDs. Below are some examples on how to skip rows when importing data to Stae.
This Tutorial is for Admins only
Only accounts with Admin Access can import data. For non-admins, if you have a dataset you'd like to upload to Stae, get in touch with us at firstname.lastname@example.org
At the end of this tutorial, you’ll be able to
- Use the Importer to filter data
View of Step 3 of the Importer to transform your data.
1. Navigate to the Importer and the Transform page
To navigate to a data source's importer, select the **Sources** button and then find the data source from the list. For information on creating your own data source, visit the Creating a Data Source tutorial.
Sources page in Seattle
Once on the Source's page, navigate to the Importer portion of the page and select Create Importer. The Importer can accept a variety of formats as either a file or an API: JSON, CSV, XML, Excel, SHP, GTFS, and GTFS-RT.
Select "Create Importer" to build a new importer
You can import a variety of formats as either a file or an API: JSON, CSV, XML, Excel, SHP, GTFS, and GTFS-RT
Depending on the file type, you may have an additional step that prompts you to target the fields you'd like to import. In most cases, you'll want to import all the data. Select "Features > All" from the dropdown menu.
Step 2 allows you to target what portion of data you'd like to transform.
Once you're on step 3, you can begin mapping and filtering your fields. The following section will show you how to use different utility functions in the Code tab to transform your data.
You can use filters on the datasets when Importing to specify which data you'd like and data that you'd like to skip. Below are a few different use cases on how to skip or specify certain data. You can also choose whether the filter has to match all the conditions or any of the conditions in order for the filter to apply.
Skip rows without a location
Geometry > Exists > No
This filter will skip any rows that don't have a location input
Skip rows without an ID
properties.ID > Exists > No
This filter will skip any rows that don't have a Building Permit number. For the data transformation, this field was mapped to ID so this filter will ensure you're getting unique IDs only.
Skip rows relative to a date
properties.Date > Before/After/Between > xx/xx/xxxx
This filter will skip any Building Permit data that was received after January 1st, 2018.
Skip rows based on Type or Issue
properties.Type > Contains > Family
There may be particular class of information you'd like to omit. For example, the filter above would allow you to filter out buliding permits for family homes and just keep commercial ones. The Type will vary on the dataset.
*“The essential characteristic of the city ... is that it demands participation.”*
Lawrence Halprin, Cities
Have any questions or running into issues with this feature?
Reach us at: email@example.com