Query a public dataset and visualize the results using BigQuery Studio

Query a public dataset and visualize the results using BigQuery Studio

Learn how to query a public dataset and visualize the results by using BigQuery Studio.

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To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

Guide me

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Before you begin

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.
Go to project selector
Make sure that you have the following role or roles on the project: BigQuery Job User, Service Usage Admin
Check for the roles
1. In the Google Cloud console, go to the IAM page.

   Go to IAM
2. Select the project.

3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

4. For all rows that specify or include you, check the Role column to see whether the list of roles includes the required roles.
Grant the roles
1. In the Google Cloud console, go to the IAM page.

   Go to IAM
2. Select the project.
3. Click Grant access.

4. In the New principals field, enter your user identifier. This is typically the email address for a Google Account.

5. In the Select a role list, select a role.
6. To grant additional roles, click Add another role and add each additional role.
7. Click Save.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

Make sure that you have the following role or roles on the project: BigQuery Job User, Service Usage Admin

Check for the roles

1. In the Google Cloud console, go to the IAM page.

   Go to IAM
2. Select the project.

3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

4. For all rows that specify or include you, check the Role column to see whether the list of roles includes the required roles.

Grant the roles

1. In the Google Cloud console, go to the IAM page.

   Go to IAM
2. Select the project.
3. Click Grant access.

4. In the New principals field, enter your user identifier. This is typically the email address for a Google Account.

5. In the Select a role list, select a role.
6. To grant additional roles, click Add another role and add each additional role.
7. Click Save.

1. Verify that billing is enabled for your Google Cloud project.

If you don't enable billing for the Google Cloud project that you use in this tutorial, then you query the public data in the BigQuery sandbox. The BigQuery sandbox lets you learn BigQuery with a limited set of BigQuery features at no charge.

2. Ensure that the BigQuery API is enabled.

   Enable the API

   If you created a new project, the BigQuery API is automatically enabled.

View a public dataset

BigQuery public datasets are available by default in BigQuery Studio in a project named bigquery-public-data. In this tutorial you query the NYC Citi Bike Trips dataset. Citi Bike is a large bike share program, with 10,000 bikes and 600 stations across Manhattan, Brooklyn, Queens, and Jersey City. This dataset includes Citi Bike trips since Citi Bike launched in September 2013.

1. In the Google Cloud console, go to the BigQuery Studio page.

   Go to BigQuery Studio

2. In the Explorer pane, click Add data.

3. In the Add data dialog, in the Filter By pane, click Public datasets.

4. On the Marketplace page, in the Search Marketplace field, type NYC Citi Bike Trips to narrow your search.

5. In the search results, click NYC Citi Bike Trips.

6. On the Product details page, click View dataset. You can view information about the dataset on the Details tab.

Query a public dataset

In the following steps, you query the citibike_trips table to determine the 100 most popular Citi Bike stations in the NYC Citi Bike Trips public dataset. The query retrieves the station's name and location, and the number of trips that started at that station.

The query uses the ST_GEOGPOINT function to create a point from each station's longitude and latitude parameters and returns that point in a GEOGRAPHY column. The GEOGRAPHY column is used to generate a heatmap in the integrated geography data viewer.

1. In the Google Cloud console, open the BigQuery Studio page.

   Go to BigQuery Studio

2. Click SQL query.

3. In the query editor, enter the following query:

   SELECT
     start_station_name,
     start_station_latitude,
     start_station_longitude,
     ST_GEOGPOINT(start_station_longitude, start_station_latitude) AS geo_location,
     COUNT(*) AS num_trips
   FROM
     `bigquery-public-data.new_york.citibike_trips`
   GROUP BY
     1,
     2,
     3
   ORDER BY
     num_trips DESC
   LIMIT
     100;
   

   If the query is valid, then a check mark appears along with the amount of data that the query processes. If the query is invalid, then an exclamation point appears along with an error message.

   

4. Click Run. The most popular stations are listed in the Query results section.

   

5. Optional: To display the duration of the job and the amount of data that the query job processed, click the Job information tab in the Query results section.

6. Switch to the Visualization tab. This tab generates a map to quickly visualize your results.

7. In the Visualization configuration panel:

   1. Verify that Visualization type is set to Map.
   2. Verify that Geography column is set to geo_location.
   3. For Data column, choose num_trips.
   4. Use the Zoom in option to reveal the map of Manhattan.

   

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

Delete the project

If you used the BigQuery sandbox to query the public dataset, then billing is not enabled for your project, and you don't need to delete the project.

The easiest way to eliminate billing is to delete the project that you created for the tutorial.

To delete the project:

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

What's next

• Learn about the BigQuery sandbox.
• Learn how to create a dataset, load data, and query tables in BigQuery Studio.