This page describes how to delete and get information about your datasets.
For information about creating a dataset and importing data into it, see Creating datasets and importing data.
Before you begin
Before you can use AutoML Tables, you must have set up your project as described in Before you begin.
Listing datasets
A project can include numerous datasets. This section describes how to retrieve a list of the available datasets for a project.
Console
To see a list of the available datasets using the AutoML Tables UI, click the Datasets link at the top of the left navigation menu and select the Region.
REST
To list your datasets you use the datasets.list method.
Before using any of the request data, make the following replacements:
-
endpoint:
automl.googleapis.com
for the global location, andeu-automl.googleapis.com
for the EU region. - project-id: your Google Cloud project ID.
- location: the location for the resource:
us-central1
for Global oreu
for the European Union.
HTTP method and URL:
GET https://endpoint/v1beta1/projects/project-id/locations/location/datasets
To send your request, choose one of these options:
curl
Execute the following command:
curl -X GET \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: project-id" \
"https://endpoint/v1beta1/projects/project-id/locations/location/datasets"
PowerShell
Execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "project-id" }
Invoke-WebRequest `
-Method GET `
-Headers $headers `
-Uri "https://endpoint/v1beta1/projects/project-id/locations/location/datasets" | Select-Object -Expand Content
You should receive a JSON response similar to the following:
{ "name": "projects/29434381/locations/us-central1/datasets/TBL75559", "displayName": "test_dataset", "createTime": "2019-03-21T00:50:20.660378Z", "updateTime": "2019-08-23T19:32:52.025469Z", "etag": "AB3BwFoV4USmhM3pT8c6Y5AIA6n51dAmSuObc=", "exampleCount": 94356, "tablesDatasetMetadata": { "primaryTableSpecId": "16930321664", "targetColumnSpecId": "46579780096", "areStatsFresh": true, "targetColumnCorrelations": { "6788648672679690240": { "cramersV": 0.16511808788616378 }, "87292427152392192": { "cramersV": 0.20327159375043746 }, "2393135436366086144": { "cramersV": 0.15513206308654948 }, "9094491681893384192": { "cramersV": 0.021499396246101456 }, "7004821454793474048": { "cramersV": 0.030097587339321379 } }, "statsUpdateTime": "2019-08-16T01:43:38.583Z", "tablesDatasetType": "BASIC" } }, ...
Java
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
Node.js
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
Python
The client library for AutoML Tables includes additional Python methods that simplify using the AutoML Tables API. These methods refer to datasets and models by name instead of id. Your dataset and model names must be unique. For more information, see the Client reference.
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
Deleting a dataset
Deleting a dataset removes the dataset permanently from your project. This operation does not delete any models created from that dataset. If you want to delete the models, you must delete them explicitly.
Console
In the AutoML Tables UI, click the Datasets link at the top of the left navigation menu and select the Region to display the list of available datasets.
Click the more actions menu at the far right of the row you want to delete and select Delete dataset.
Click Confirm in the confirmation dialog box.
REST
To delete a dataset you use the datasets.delete method.
Before using any of the request data, make the following replacements:
-
endpoint:
automl.googleapis.com
for the global location, andeu-automl.googleapis.com
for the EU region. - project-id: your Google Cloud project ID.
- location: the location for the resource:
us-central1
for Global oreu
for the European Union. -
dataset-id: the ID of the dataset you want to delete. For example,
TBL6543
.
HTTP method and URL:
DELETE https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id
To send your request, choose one of these options:
curl
Execute the following command:
curl -X DELETE \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: project-id" \
"https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id"
PowerShell
Execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "project-id" }
Invoke-WebRequest `
-Method DELETE `
-Headers $headers `
-Uri "https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id" | Select-Object -Expand Content
You should receive a JSON response similar to the following:
{ "name": "projects/29452381/locations/us-central1/operations/TBL6543", "metadata": { "@type": "type.googleapis.com/google.cloud.automl.v1beta1.OperationMetadata", "createTime": "2019-12-26T17:19:50.684850Z", "updateTime": "2019-12-26T17:19:50.684850Z", "deleteDetails": {}, "worksOn": [ "projects/29452381/locations/us-central1/datasets/TBL6543" ], "state": "DONE" }, "done": true, "response": { "@type": "type.googleapis.com/google.protobuf.Empty" } }
Deleting a dataset is a long-running operation. You can poll for the operation status or wait for the operation to return. Learn more.
Java
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
Node.js
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
Python
The client library for AutoML Tables includes additional Python methods that simplify using the AutoML Tables API. These methods refer to datasets and models by name instead of id. Your dataset and model names must be unique. For more information, see the Client reference.
If your resources are located in the EU region, you must explicitly set the endpoint. Learn more.
What's next
- Create your model.
- Learn more about data types.