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Originally, calculator programming had to be done in the calculator's own command language, but as calculator hackers discovered ways to bypass the main interface of the calculators and write assembly language programs, calculator companies (particularly Texas Instruments) began to support native-mode programming on their calculator hardware ...
Formula weight calculator: The input is a chemical molecular formula, using the periodic-table symbols and notation, and there is a button to work out the percentages of its constituents. Astronomical calculator : The input is a date and one or multiple celestial bodies (usually the sun, moon, planets, planetoids or comets).
Here is a brief overview of what Xcas is able to do: [9] [10] Xcas has the ability of a scientific calculator that provides show input and writes pretty print; Xcas also works as a spreadsheet; [11]
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
The first scientific calculator that included all of the basic ideas above was the programmable Hewlett-Packard HP-9100A, [5] released in 1968, though the Wang LOCI-2 and the Mathatronics Mathatron [6] had some features later identified with scientific calculator designs.
In computer science, function composition is an act or mechanism to combine simple functions to build more complicated ones. Like the usual composition of functions in mathematics, the result of each function is passed as the argument of the next, and the result of the last one is the result of the whole.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...