It’s common these days to highlight few dates among all the data and label them with different colours or sizes compared to other date data points for each customer or transaction. Table calculations are the most efficient way to solve this problem in this scenario. They help you quickly locate the dates you’re looking for and differentiate them from other date data points on your plot.
I will use table calculations and Level of Detail (LOD) expressions to demonstrate how to find the second order date for each customer through different ways.
1. Create a calculated field to calculate the index for each customer’s order date and drag and drop it to Label shelf to show all the indices.
Next, create another calculated field to select the second order date for all customers. Then drag and drop it into the Colour and Size shelves to highlight the second order date for each customer. After that, the index can be removed for better visualisation.
2. Create a calculated filed to find the first order date for each customer across the dataset.
Create another calculated field to exclude the first order date for each customer.
Then create the third calculated field to find each customer’s current first order date after the exclusion, which is their second order date.
Drag and drop the second order date into columns to create a dual axis with all order dates. Adjust colour and size to highlight the second order date, synchronize the axes, and hide header for the upper axis for better visualisation.
