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08_​Visualization_​1

Visualization

Exercise 8 for the KNIME Analytics Platform for Data Wranglers course
- Visualize the customer data using a scatter plot, a stacked area chart, and a bar chart
- Produce an interactive table using the Table View node
- Define a custom color for the data to plot
- Combine the visualizations into a composite view



Exercise 8: Data VisualizationIn this exercise you generate interactive views to visualize data, add a slider to filter the data, and change the colors inthe graphs. At the end you combine the graphs into an interactive composite view. 1a) Use the data from first output port and assign a color to the customers based on their newslettersubscription1b) Build a scatter plot to show the relationship between the total purchase amount in the year 2019 andin the years before1c) (optional) Create an interactive range slider to filter the data shown in the scatter plot by the birthyear of a customer 2) Visualize the customer data in an interactive table (Table View node) 3) Create a stacked area chart to show the development of the total purchase amount over time foreach transaction type 4a) (optional) Convert the values in the column basket size from integer to string for the data of thelowest output port4b) (optional) Build a bar chart to show the number of products per order for the different transactiontypes 5) (optional) Change the colors of the bars and the stacked areas 5.1 Extract the column headers from the middle or bottomoutput of the metanode 5.2 Transpose the table with the column headers 5.3 Assign your preferred colors to the transaction typesin the resulting "Column Header" column 5.4 Use the colored table as the optional input for the BarChart and Stacked Area Chart nodes Top: Data aggregated by customer IDMiddle: Data aggregated by year, quarter, and typeBottom: Data aggregated by basket size and type Transform andaggregate data Read joined andpreprocessed data Exercise 8: Data VisualizationIn this exercise you generate interactive views to visualize data, add a slider to filter the data, and change the colors inthe graphs. At the end you combine the graphs into an interactive composite view. 1a) Use the data from first output port and assign a color to the customers based on their newslettersubscription1b) Build a scatter plot to show the relationship between the total purchase amount in the year 2019 andin the years before1c) (optional) Create an interactive range slider to filter the data shown in the scatter plot by the birthyear of a customer 2) Visualize the customer data in an interactive table (Table View node) 3) Create a stacked area chart to show the development of the total purchase amount over time foreach transaction type 4a) (optional) Convert the values in the column basket size from integer to string for the data of thelowest output port4b) (optional) Build a bar chart to show the number of products per order for the different transactiontypes 5) (optional) Change the colors of the bars and the stacked areas 5.1 Extract the column headers from the middle or bottomoutput of the metanode 5.2 Transpose the table with the column headers 5.3 Assign your preferred colors to the transaction typesin the resulting "Column Header" column 5.4 Use the colored table as the optional input for the BarChart and Stacked Area Chart nodes Top: Data aggregated by customer IDMiddle: Data aggregated by year, quarter, and typeBottom: Data aggregated by basket size and type Transform andaggregate data Read joined andpreprocessed data

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