OneDrive and SharePoint Data Connectors Authentication
This blog post is intended to help you understand and troubleshoot the OneDrive and SharePoint Data Connectors authentication process.
This blog post is intended to help you understand and troubleshoot the OneDrive and SharePoint Data Connectors authentication process.
JMP 18 has a new way to integrate with Python. The JMP 18 installation comes with an independent Python environment designed to be used with JMP. In addition, JMP now has a native Python editor and Python packages specific to JMP. This JMP Python environment has enhanced connectivity and interaction with JMP, which means using Python with JMP has never been easier. In this series of blog posts, I ...
JMP 18 introduces a lot of new capabilities, including revamped Python support, which allows users to directly access, modify, and create JMP data tables from Python. This is accomplished through the jmp.DataTable Python object. Keep reading to learn how to create a pandas.DataFrame from a JMP data table, as well as the reverse, a JMP data table from a pandas.DataFrame live and in-memory.
Get familiar with the Python integrated development environment (IDE) in JMP 18 and learn how to: Locate the Python IDE.Run a simple example.Install Python packages.Run JSL script from Python.Send a Python variable to JSL.Create a JMP data table from Python.
I needed to import and stack 660 XML files from my exercise activity tracking app. It's easy with the XML Import Wizard and Import Multiple Files in JMP 15.
Efficient propeller design is crucial for the electric Vertical Takeoff and Landing (eVTOL) industry, which is projected to reach a market value of $15.8 billion by 2030, according to a report by Market Research Future. Propellers play a key role in optimizing performance, reducing energy consumption, and enhancing flight stability in eVTOL aircraft, which are designed to revolutionize urban air m...
Optimal designs use one of several optimality criteria based on the goal of the experiment. Using the design evaluation tools we can compare, and contrast designs based on the goal of the experiment. In each of the case studies below, the tools relevant for each experimental goal are explored. Summary of practical goals and design evaluation tools I-optimal D-optimal Practical goal: Accurate ...
Why doesn't my code work when I try to use a variable as an argument to ...?
JMP’s Custom Design platform allows experimenters to create custom-built designs for their specific experiment needs by constructing optimal designs. The custom designer generates optimal designs by seeking to maximize one of several optimality criteria using the coordinate-exchange algorithm. The coordinate-exchange algorithm constructs a starting design by selecting random values within the desi...
Process Capability
You want to keep coding in JSL, but for a particular function, you know there's an easy way to write it in Python. So how do you create a JSL function that implements its functionality in Python?
I create a control chart, describe how the control limits are calculated and discuss how these limits can be used to make decisions.
This blog post shows a method to tune hyperparameters to improve your model performance, utilizing space filling DOE along with the new Python integration. This video shows some of the common techniques used to tune hyperparameters to improve model performance. (view in My Videos) This video gives a brief summary of Bayesian optimization and some of the limitations. (view in My Videos) This vid...
JMP® has a jpip wrapper that is just a thin wrapper around pip as such functionality, like installing packages via a requirements file, is fully supported. Below are two scripts, one JSL and one Python. Each uses a JSL Pick File() dialog to have the user select the requirements file, and the path is then passed through to jmputis.jpip() to process the requirements file. The majority of the code sh...
There are many different working pieces to consider when you look at performance in JMP Live and interactive HTML. Reports with large data sets and complicated graphs can be costly just to send over a network. Other times, a lot of data must be processed to make summary calculations. Drawing millions of markers, lines, and other shapes can also stress a machine. So what does this mean when publish...
The new Easy DOE tool encapsulates the entire DOE workflow into one platform.
A how-to on customizing graphs in JMP. The first of two posts on creating high-quality graphics for publications and presentations.
Introduction
Most of our data in R&D comes from databases, Excel or CSV files, or is entered directly into JMP. But supporting data often comes in other formats, most notably PDF files. For example, think of chemical reference tables, vendor information sheets, or even historic company data that now only exist as in PDF. This type of supporting information can be very helpful to complement experim...
Often as we are trying to gain insights from our data, understanding that two variables are related is not enough. We need to dig deeper and ask questions like: under what circumstances are they related? For whom are they related, why are they related, and how? The Moderation and Mediation JMP Add-In enables easy specification, fitting, and visual probing of interactions in three popular models: m...
JMP offers spline fits to help represent the relationship between two continuous variables. Learn how a spline is generated.