Basic example:
Pivot table with one group and one pivot column

Question: How many male/female customers belong to each age bin?

• Group: Age Bin

• Pivot: Gender

• Aggregation Column: CustomerKey (or any other)

• Aggregation Operator: Count
  

Two group columns

Question: Which web activity classes are represented in groups according to marital status, gender and sentiment?

• Group: MaritalStatus, Gender

• Pivot: Sentiment Analysis

• Aggregation Column: WebActivity

• Aggregation Operator: Unique concatenate
  

Aggregation Column of Type Date and Time

Question: What is the age dispersion of the customers according to different product and sentiment groups?

• Group: Product

• Pivot: Sentiment analysis

• Aggregation Column: birthday

• Aggregation Operator: Date range(day)

Two aggregation operators

Question: What is the mean and standard deviation of income according to different sentiment and gender groups?

• Group: Sentiment Analysis

• Pivot: Gender

• Aggregation Column: EstimatedYearlyIncome

• Aggregation Operator: Mean, Standard deviation

Transform using Pivot node

Create a Pivot table with one or more group columns and one or more pivot columns. Apply basic aggregation methods like sum and count, statistical aggregation methods, and aggregation methods available for columns of type Date&Time. Apply multiple aggregation methods to one or more aggregation columns.

Two pivot columns

Question: What is the most common product among customers according to their sentiment, gender and marital status?

• Group: Sentiment Analysis

• Pivot: MaritalStatus, Gender

• Aggregation Column: Product

• Aggregation Operator: Mode
  
  

Workflow complete!

Keep the momentum going by exploring Just KNIME It!on the Hub to challenge yourself and see how these nodes can be integrated into more complex workflows and use cases.