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07_​Visualization_​Exercise

Visualization - Exercise

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 7: 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) Assign colors to the customers based on their newsletter subscription (top output of the metanode)1b) Build a scatter plot to show the relationship between the total purchase amount in 2019 (BasketSum 2019) and overall (Overall BasketSum)1c) (optional) Create an interactive range slider to filter the data shown in the scatter plot by the birthyear of a customer. This widget will appear in the composite view that you build later on. 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 Optional5a) Convert the basket sizes from integer to string in the data of the lowest output port5b) Build a bar chart to show the number of products per order for the different transaction types Optional4) Change the colors of the stacked areas via the following steps: 4.1 Extract the column headers from the middle or bottomoutput of the metanode (Extract Column Headers node) 4.2 Transpose the table with the column headers(Transpose node) 4.3 Assign your preferred colors to the transaction typesin the resulting "Column Header" column (Color Manager node) 4.4 Connect the colored table to the optional input port ofthe Stacked Area Chart node 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 7: 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) Assign colors to the customers based on their newsletter subscription (top output of the metanode)1b) Build a scatter plot to show the relationship between the total purchase amount in 2019 (BasketSum 2019) and overall (Overall BasketSum)1c) (optional) Create an interactive range slider to filter the data shown in the scatter plot by the birthyear of a customer. This widget will appear in the composite view that you build later on. 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 Optional5a) Convert the basket sizes from integer to string in the data of the lowest output port5b) Build a bar chart to show the number of products per order for the different transaction types Optional4) Change the colors of the stacked areas via the following steps: 4.1 Extract the column headers from the middle or bottomoutput of the metanode (Extract Column Headers node) 4.2 Transpose the table with the column headers(Transpose node) 4.3 Assign your preferred colors to the transaction typesin the resulting "Column Header" column (Color Manager node) 4.4 Connect the colored table to the optional input port ofthe Stacked Area Chart node 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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