An Easter themed #PreppinData for 2024 week 13. Preparing sales of products in the 12 weeks running up to Easter to allow for easy comparison of the period across years in Tableau Desktop. A nice one step solution this week (see screenshot at the end of this post): a FIXED level of detail calc to get the first sale date per year; then date calcs to get the week, day and day order. ...
#PreppinData 2024 week 12, graduate student loan repayment calculator. Good to try out the “value ranges from two fields” option within a “new rows” step. Like some others my interest figure is a little different from the supplied output, however the calc appears to be the same. I also shortcutted the join onto repayment info for undergraduates with a filter (down to just the undergrad row), and joiner fields allowing a simple join on 1=1. ...
Week 11 of #PreppinData, and the question: what if there were 13 months in a year? Nice concept to have consistent 28 day months, with 4 weeks per month and each month starting on a Monday and ending on a Sunday. As we found out when we expanded the two row data set though … it’s not as neat as it seems, ending up with a spare day (or two in a leap year). ...
My solution for the #PreppinData 2024 week 10 challenge follows below. Cool to check out the New Rows step this week to fill in the missing days in the data set.
A couple of weeks ago I wrote about a Tableau Prep approach to transposing data from a text file that had a field per line, with another line separating records. At the time I noted that the approach wasn’t robust enough to handle optional fields, and that it would be annoying to need a join per field in cases where you had a large number of fields. In this follow up post I look at an alternative that doesn’t have those drawbacks. ...
Finishing #PreppinData intermediate-level month with a 1-step solution … fun, but definitely harder and less easy to maintain!
This quarter I set myself the goal to learn more about Tableau Prep, and a key part of that has been participating in the weekly #PreppinData challenges. Something I’ve noticed, and have been super intrigued about, is that some participants have been posting one-step solutions. That wasn’t surprising during beginner month, but now I’m seeing one-step flows covering reasonably complex multi-step data transformations. Cool! This week I took a deeper dive into one of those one-step solutions to learn, and share, how they’re being done. ...
I recently answered a question on the Tableau Community Forums about transposing data from a text file that had a field per line, with a line of dashes separating records. I’m not sure what the formal name for this format is, but there are similarities with RecFiles. Here is an example: I don’t know of a way to use data formated like that directly in Tableau Desktop. But we can use Tableau Prep to transform it into a more natural row per record format! ...
#PreppinData 2024 week 8 – a “what if?” analysis of two different customer loyalty reward systems for Prep Air. Aiming to identify cost and number of customers benefiting. The “estimated yearly flights” calculation tripped me up for a while, out thinking it with a datediff on days, and only when the flights spanned more than a year. The challenge just required a division by the number of years flown over! I enjoyed expanding the data set throughout the flow (pivoting the benefits, joining onto cost per benefit, and then joining onto those tiers less then or equal to each customer’s tier) to then roll back up at the end. ...
#PreppinData 2024 wek 7: