How to Deal with Date&Time Data

We have access to historical Olympics data, however, the information is saved in different tables:

• First table: Athlete event results of the Summer Olympics Games 1972-2020 for sport "Athletics".

• Second table: Information about all German athletes, including their full name, gender, and date of birth.

We want to merge the two datasets and explore the Date&Time-related functionalities of KNIME to get advanced insights from the data:

• How old were the athletes when participating at the Olympic Games? We create age bins and visualize the distribution in a bar chart.

• Which athletes have their birthday today? We visualize the result in a table.

In this workflow, you will learn how to:

• Load data into a KNIME workflow

• Merge datasets

• Create date values and handle date&time data

• Inspect the results using KNIME View nodes

We load two datasets related to the Olympics Games into KNIME:

1. The athlete results of the Summer Olympics 1972-2020 (sport="Athletics").

2. Information about German athletes.

Access data

Join data

We perform a value lookup operation to add the athletes' birthdays to the Olympics data.

Convert strings to date cells

We convert the date columns from String to Date type.

Calculate time difference

We calculate the age of the athletes at the time of the Olympic Games.

We group the athletes into age bins:

• < 20: Rising Stars

• 20–24: Emerging Elites

• 25–29: Peak Performers

• 30–34: Experienced Professionals

• 35+: Veteran/Endurance 

Visualize data

We visualize the results:

1. The distribution of the age bins (Bar Chart)

2. The athletes whose birthday is today (Table View)

Create a date value

We create a single-cell data table with today's date (execution date).

Extract Date&Time Fields

We extract date fields from the date columns "born" and "Date": Month (Name) and Day of Month.

We filter the list of athletes to today.

Filter data

Transform data

💡 At a glance:

In KNIME, a node can be in four different states:

1. Not configured🔴. The node is waiting for configuration or incoming data.

2. Configured🟡. The node has been configured and can be executed.

3. Executed🟢. The node has been successfully executed. Results can be viewed in the node monitor and be used in downstream nodes.

4. Error❌. The node has encountered an error during execution.

⚙️ To configure a node, click the node to open the configuration panel (right side of the workflow canvas). Change the settings and don't forget to click "Apply".

▶️ After configuration, you can execute the node. Hover over the node and click the "Execute" button in the node action bar.

🤖 If you are stuck, let K-AI, our AI assistant, help you build workflows. Access K-AI in the "K-AI" panel on the left side of the workflow canvas.

For detailed instructions and a getting started guide, we recommend the KNIME Documentation.

💡 Click on a node to observe the respective dataset in the node monitor at the bottom of the screen.

💡 Click on the node to explore the interactive view in the node monitor at the bottom of the screen.