It’s a fact. If you have manual data entry, there will be errors. I found this out the hard way when working with our completions team on a Spotfire KPI project. We built the Spotfire KPIs and were attempting to tie out to spreadsheets. The numbers didn’t match. Discrepancies consistently traced back to bad data entry. We would fix the bad data, but without proper controls to keep it out, we were chasing our tails. So, we addressed bad data with a QAQC or error report. The first version was all Spotfire, but it had flaws. Version 2 performed error reporting with Alteryx. Ultimately, I wound up with a combination of Alteryx and Spotfire. To see what it looks like and how it was implemented, read on.
In last week’s post, I showed you how to populate type curve inputs with IronPython and toggle between different sets of inputs. This week, I’ll go one step further using an R function to select type curve inputs from a table and then load them into document properties. Read on to find out how.
Type Curve generators are standard in reservoir engineering workflows. They are also a bit problematic. They require lots of inputs, which are time-consuming to build and fill out. You can’t easily recreate them in other projects. Therefore, my next two posts will show you how to make type curve inputs more efficient. The first post will demonstrate how to populate type curve inputs with IronPython and toggle between different sets of inputs. The second post will go further by allowing users to load type curve settings in a table. Then, the user tells an R function which row to pull from the table and place in the type curve inputs. Read on for these great solutions!
A few weeks ago, I wrote a post on how to set up your machine to run Python Data functions in Spotfire. This post will follow up on that by explaining the next step — how to install Python packages in Spotfire. Read on to learn how.