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Julie Sebby

Add Bar Chart with IronPython

This is my third week working thru IronPython scripts from the Spotfire IronPython quick reference. Last week, we looked at for loops. The week before, we used IP to modify titles. This week, we’ll insert visualizations with IronPython and explore the API as we go. We’ll get started learning how to add a bar chart with IronPython to an analysis.

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Change Visualization Titles with IronPython

I promised a return to Spotfire API for IronPython posts, and that is finally happening. I had to get a few drafts cleared out, like 5 Ways to Approach Troubleshooting Data Problems, but now I’m back on track discussing how to change visualization titles with IronPython

In October last year, I committed to spending 100 hours learning IronPython. I wrote several “starter” IronPython posts, which can be found in the Data Shop Talk Archive. I have lost count of how much time I’ve spent on IronPython, but the clock starts again today.

My goals haven’t changed. They are still to ….

  1. Get an understanding of IronPython structure
  2. Develop an understanding of the Spotfire API
  3. Apply that understanding in Spotfire code examples

For the next several weeks, I’ll be using the code snippets posted on The Spotfire IronPython Quick Reference to explore the API. I’ll punctate that with an article here and there are the IronPython/Python structure as I go. Read on for this week’s code snippet.

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5 Tip for Troubleshooting Data Wrangling Problems

I’ve never found a great way to explain what I do. Analogies help right? The first analogous thing that pops into my head is a Rubix cube. My day to day work feels like trying to solve a Rubix cube over and over, and the cube is a big pile of dirty, messy data. Thus, much of my day to day is troubleshooting data wrangling problems.

Some days, it’s incredibly satisfying, as solving a Rubix cube is. Other days, I want to rip the stickers off and throw it out the window. When I drafted this post, I was in “rip the stickers off” mode. I was frustrated with how long it took to solve data wrangling problems. When I get in that mindset, I want to share what I learn so other people don’t suffer as much. Thus, this post discusses my top 5 ways to approach troubleshooting data problems. These methods will apply no matter what application you are working in or if the problem is related to data wrangling or logic problems. Read on for details.

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