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The Math blocks are powered by Math.js (https://mathjs.org/). - Source: Hacker News / 4 months ago
Yes, I've learned that Heynote is lacking some documentation. Will improve that. Math.js (https://mathjs.org/) powers the Math blocks, so what's supported by Math.js should be supported by Heynote, with the addition of currency conversions (exchange rates are updated daily). > How to convert between fahrenheit and celsius? This should work:. - Source: Hacker News / 4 months ago10 celsius to fahrenheit
Math.js is a comprehensive JavaScript library that offers support for working with matrices and multidimensional arrays. It contains a huge array of mathematical functions in addition to array operations, making it suitable for a wide range of mathematical activities. - Source: dev.to / 5 months ago
Ii) Third-Party Libraries There are various libraries like math.js, decimal.js, big.js that solve the problem. Each library functions according to its documentation. This approach is comparatively better. - Source: dev.to / 6 months ago
Mathjs integration. Supports numbers, big numbers, complex numbers, fractions, units, strings, arrays, and matrices. Is compatible with JavaScript’s built-in Math library. Contains a flexible expression parser. Does symbolic computation. Comes with a large set of built-in functions and constants. - Source: dev.to / 9 months ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
jQuery - The Write Less, Do More, JavaScript Library.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Lo-Dash - Lo-Dash is a drop-in replacement for Underscore.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Mochajs - Mocha is a JavaScript test framework running on Node.js and the browser, making asynchronous testing simple.
OpenCV - OpenCV is the world's biggest computer vision library