Learn how to read data from BigQuery tables into the Python notebook data structures.
- [Instructor] Now we are ready to read data…from BigQuery using the command line.…Here is the query.…We select customer name, gender, age, and salary…from the website visits table where the type…of customer is one.…We limit to only 10 records.…The command we use is bq query.…The actual query should be in the second line.…On executing the query the results are directly printed…in the notebook.…
You can also create a named query.…You do so by using the attribute name…and providing an actual name here.…In this example we create a query called customer…using the same example as before.…Once a named query is created,…it is not executed immediately.…This name can later be referenced…in other operations as we will see in future videos.…The query gets executed only when the data…needs to be used for the next operation.…
A named query, once created, can be used…in any number of future operations.…
- Setting up Cloud DataLlb for exploratory data analytics
- Segmentation and profiling
- Reading and writing data from BigQuery
- Managing cloud storage buckets
- Creating visualizations of BigQuery data with the GCP Charting API
- Managing Datalab instances
Skill Level Intermediate
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. Exploration Options in GCP
2. Cloud Datalab Basics
3. Datalab: BigQuery
4. Datalab: Cloud Storage
5. Datalab: Visualizations
6. EDA with GCP: Use Case
7. Managing Datalab
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.