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Configuring missing values

A customer asked how they could read in a CSV file into a DataFrame (for eventual linear regression) with missing values.

← Convolution in CenterSpace’s NMATH 4.0

Convolution, Correlation, and the FFT →

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Math Class Library

NMath from CenterSpace Software is a .NET class library that provides general vector and matrix classes, complex number classes, and a large set of computational classes ranging from optimization to the FFT.
Complete documentation for all NMath libraries is available online.

Testimonials

"I would like to formally thank you for your kind and expert support in resolving the issue with the Normal distribution function. It is working as expected and we are very pleased with the quick turn-around. Your timely fixes are instrumental in continuity of our trading and risk management operations. Thank you once again for taking time during the weekend and providing us with a solution."

Principal Financial Engineer, a Chicago proprietary trading firm

"Thank you very much for your lightning fast support!"

Abdelali Zahi, Allianz

"To answer your question whether I had success in utilizing the NMath libraries in my software development work, my answer is a resounding "YES". Your libraries have significantly helped me cut down my development time and I would like to extend a great big thank you to your development team for a truly outstanding job in developing these libraries. Your product is truly exceptionally outstanding and rightfully deserves all the appropriate accolades."

Waldemar Dos Passos, PhD, author of Numerical Methods, Algorithms and Tools in C#

"I spent a year looking for a stats package that was native .NET as well as robust. After looking at dozens of websites and trying a half dozen demos, I bought the full NMath package--and it's great! I use it to analyze fixed income portfolios, where time is of the essence--and it's very fast. It couldn't be easier to integrate into my C# applications."

Eric Carlino, Ronin Capital

"I've been developing numerical scientific software for fifteen years. I typically write custom-tailored numerical codes, and I've regularly used IMSL, ESSL, Numerical Recipes and Matlab. The development environment of NMath with C# is by far the most elegant, flexible, and amenable to reuse that I've ever encountered. The more I worry about good object-oriented design, the more I like NMath. It is my preferred platform for day-to-day numerical work."

John Lee, Washington University School of Medicine

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