Tag: Spotfire

Keeping Spotfire Visualizations Working when Replacing Data by Using Column Properties

Do you ever try to replace data in a Spotfire dxp only to find many of the visualizations no longer work?

At Ruths.ai, we create Spotfire templates as one of our main products.  Often, people have to replace our source data with their own to utilize our templates.  However, this can cause some complications when they match columns with different names than the ones in our source data.  Ideally, people would like to keep their column names because the names have business implications. Yet, when that column name has been hard coded into a Spotfire expression, a visualization, calculated column, or data limiting expression could break.

Until now.

In this post, we will demonstrate how to use column properties to ensure that expressions will remain intact in a Spotfire dxp even after changing a column name when replacing data.    

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Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.

“Whiting Out” a Visualization Label in Spotfire

When using Spotfire, do you ever place a variable on an axis to make the visualization look a certain way, only to see its label show up unwanted next to the other necessary labels?

I’ve had this happen when manipulating dates or forcing a visualization (scatter plot, waterfall chart, bar chart) to be in a certain rank order.  Recently, I wrote a post on how to rank and order a gantt chart, which faced this issue.  I discussed how to remedy the issue in that article, but here I want to highlight the method used since we can use it in many other scenarios.

In this post, we will discuss how to white out a label on an axis.

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Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.

How to insert a live Spotfire in a PowerPoint

I’m embarrassed to say that I have telling people this wasn’t possible for the longest time but turns out, the Office Add-ins store had a plugin for HTML code in PowerPoint.

Setting up the Add-on

Go into PowerPoint, and from the top select Store. This opens the Office Add-ins for PowerPoint:

Search for HTML and select Office Apps Fiddle for PowerPoint.

Adding the script

Drop in your new add-in and select HTML.

Use the code listed here and replace it with the link to your Spotfire file. Serious caveat: You will need to log into the server every time, but that can simply be prep for your meeting.

Finished! The web player will be interactive inside the PowerPoint and works great. This presentation will stay current with your live data.

For some further improvements, you can use JavaScript mashup to integrate it a little better.

Regards,

Lucas

Technical Director at Ruths.ai

Rank Sorting a Spotfire Gantt Chart’s by the X-axis

Recently, a client reached out to see if I could help re-order the categorical Y-axis of their gantt chart by the numerical value on the X-axis. The client wanted the Y- axis ordered by the date of the first occurrence of an event. As the chart descended on the Y-Axis, the values would get larger on the X-axis. To do so took some trickery and an outsmarting of Spotfire–the methods which I will share here. Solving the problem left me with two learned lessons:

  1. How to re-order a Gantt Chart’s (or any Scatter Plot’s) categorical Y-axis by the value on the X-axis.
  2. Bonus trick: how to “white-out” an axis label so that it doesn’t show, while other labels remain.

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Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.

How to set the Y-Axis in DCA Wrangler

To give you greater control when editing declines in the DCA Wrangler, we have added an option to lock the Y-Axis at a specific maximum. The ability to lock this axis gives us some neat follow on features.

  1. Fine control with the interactive decline curve editor in Single-Well mode.
  2. Ability to compare many declines with the same scale on the plot in Multi-Well mode.

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Robert Henkhaus is the Product Manager and a Developer at Ruths.ai. He has 5 years of experience in the oil and gas industry and was previously with ConocoPhillips supporting BD and Land in high value decision spaces. Robert has a BS in Geography with emphasis in Earth Science from Texas A&M University. Before completing school, he also served 8 years in the Army as a sniper.

New Result Tables workflow in DCA Wrangler

We’ve added a slick new feature to help you manage all that Well Decline and Type Curve data in Spotfire. Result Tables in the DCA Wrangler represent the current working set of data produced by the DCA Wrangler. In this article, I will show you how to:

  1. Add multiple Result Tables of the same type and target each separately.
  2. Compare different decline assumptions for the same set of wells – with the ability to tweak parameters.

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Robert Henkhaus is the Product Manager and a Developer at Ruths.ai. He has 5 years of experience in the oil and gas industry and was previously with ConocoPhillips supporting BD and Land in high value decision spaces. Robert has a BS in Geography with emphasis in Earth Science from Texas A&M University. Before completing school, he also served 8 years in the Army as a sniper.

Spotfire Solution: Replacing Data with Different Named Columns while Using the Data Limiting Expression

In Spotfire, the filter panel allows one to easily remove ranges of values from your data.  We can gain even further granularity and control of what we hide from a dataset by applying the “Limit data using expression” window.  However, the “Limit data using expression window” doesn’t play nice when you want to replace a data table by matching columns with different names.

When we use replace data functionality and the limiting expression uses a matched column, the expression doesn’t update the column name (as it does with other expressions), which leads to unexpected results.  Call this one of those “endearing” Spotfire intricacies.

Fortunately, we can get around this issue by creating a Show/Hide calculated column and rerouting our limiting expression through a calculate column, which will update when you replace data.

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Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.

Spatial Objects Using TERR

A key part of analytics in the oil and gas industry is evaluating opportunities at different locations. Space is always present when looking for profitable development projects. We usually look at the already in production wells and try to find some spatial trends. To stay competitive, we need to find better ways  to access the  data of different areas and its wells. For instance, we can transform the spatial information to compact objects that store the location and shape of each well and lease. These objects can be feed  to different calculations and analyses as geometries. For Spotfire, it also has some advantages, you can use the feature layers of the map chart. In this case, we can visualize the leases as polygons and wells as lines.

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Using Spotfire’s Data Relationships Tool to check for Multicollinearity

When building a Multiple Linear Regression model, we want to limit the correlation between predictor (X) variables.  Luckily, Spotfire has a tool that makes identifying the correlation (called multicollinearity) effortless.  I will walk you through the tool, and you can see the resulting template here.

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Jason is a Junior Data Scientist at Ruths.ai with a Master’s degree in Predictive Analytics and Data Science from Northwestern University. He has experience with a multitude of machine learning techniques such as Random Forest, Neural Nets, and Hidden Markov Models. With a previous Master’s in Creative Writing, Jason is a fervent believer in the Oxford comma.