Explore how to create line charts with data from BigQuery.
- [Kumaran] Let me show you how easy it is…to create charts using data from the query.…We already have campaign data loaded…and stored in the BigQuery.…We will now create a line graph…that shows the number of offers…and conversions for campaigns, by date of the campaign.…First, we extract the conversion ratio…for each offer_date from BigQuery.…We do so by creating a named query called campaign_line.…
This query does a group by of offers and conversions…for campaigns for a given offer date.…Next, we use the charting command line to do the line chart.…We need to indicate the fields for the line chart.…The first field is the x-axis.…The subsequent fields are multiple y-axis lengths.…We provide offer_date, offers, and converts…for these parameters.…We then specify the named query through the data option.…
Finally, we specify the height…of the chart to be 500 pixels.…When this chart is executed,…it in turn executes the named query.…The data from the named query is then mapped to the chart,…and the chart is drawn successfully.…
- 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.