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The mode of a sample is the element that occurs most often in the collection. For example, the mode of the sample [1, 3, 6, 6, 6, 6, 7, 7, 12, 12, 17] is 6. Given the list of data [1, 1, 2, 4, 4] its mode is not unique. A dataset, in such a case, is said to be bimodal, while a set with more than two modes may be described as multimodal.
Demonstration doctests ===== This is just an example of what a README text looks like that can be used with the doctest.DocFileSuite() function from Python's doctest module. Normally, the README file would explain the API of the module, like this: >>> a = 1 >>> b = 2 >>> a + b 3 Notice, that we just demonstrated how to add two numbers in Python ...
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
More generally, there are d! possible orders for a given array, one for each permutation of dimensions (with row-major and column-order just 2 special cases), although the lists of stride values are not necessarily permutations of each other, e.g., in the 2-by-3 example above, the strides are (3,1) for row-major and (1,2) for column-major.
Pythran compiles a subset of Python 3 to C++ . [165] RPython can be compiled to C, and is used to build the PyPy interpreter of Python. The Python → 11l → C++ transpiler [166] compiles a subset of Python 3 to C++ . Specialized: MyHDL is a Python-based hardware description language (HDL), that converts MyHDL code to Verilog or VHDL code.
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In Python, mangling is used for class attributes that one does not want subclasses to use [6] which are designated as such by giving them a name with two or more leading underscores and no more than one trailing underscore. For example, __thing will be mangled, as will ___thing and __thing_, but __thing__ and __thing___ will not. Python's ...
While that 215,000 figure in 2026 is only 5.3% of all vehicles coming off leases in the US, it will be significantly higher than the approximate 1.5% projected for 2024 and 2025.