This is post 5 in my series on learning the Spotfire expression language. It will build on the content of the last few weeks and provide a comprehensive understanding of how over, intersect, and node navigation work together. The intersect keyword is the last piece of the puzzle. Read on to learn how it fits in.
This is the fourth post in my series on learning the Spotfire expression language. Last week, I talked about the over keyword and how it is used to group values in calculations. The next step in the learning process is using node navigation. Once this is second nature, you will be able to create any calculation desired. This week’s post focuses on understanding what node navigation is for and what a node is. Next week, I’ll add complexity and depth to the expressions. Read on to learn more.
Last week, I kicked off a series on learning how to use the Spotfire expression language. The first post explained the 2 different ways to create calculations in Spotfire. This week, I’m going to talk about the over keyword and how to use it. Without the over keyword, it’s impossible to really get into the Spotfire expression language. Read on to learn more.
I recently kicked off a series on learning how to use the Spotfire expression language. The first post explained different ways to create calculations in Spotfire. Next week, I’ll release a post on how to use the over keyword. Axis names are a more advanced topic, which technically puts it a bit “out of order”. But, axis names are what inspired me to write the series, and I know that if I don’t write about something when I am working it, I often never get to it. Thus, I am going to show you how to use axis names in Spotfire cross tables.
Since launching the Analytics Corner, I’ve focused heavily on IronPython with a dash of Alteryx. I’ve started working more with Axis Names recently, which was a reminder of how nonintuitive they are. Because I haven’t written much on Spotfire expressions since starting the Analytics Corner, I’m going to do a comprehensive series on how to learn the Spotfire expression language, which will include a good section on Axis Names.
Today’s first post will be a short summary of the different ways to write expressions in Spotfire. Next week, I’ll talk about the over keyword. Then, I’ll cover node navigation, which might take more than one post. I will also show you how to use important functions like $esc and $map. Finally, I’ll close out with a few posts on Axis Names. Read on to get started.
A coworker reached out to me for help on a visualization. He was using a drop-down property control to set the value of a bar chart x-axis. If he chooses option 1 or option 2, the display name should be a certain value. If he chooses option 3 or option 4, a different value should appear. I’ve definitely had this come up before when using dropdown property controls. There is an IronPython solution for creating dynamic display names. Let me show you.
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.