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Python supports normal floating point numbers, which are created when a dot is used in a literal (e.g. 1.1), when an integer and a floating point number are used in an expression, or as a result of some mathematical operations ("true division" via the / operator, or exponentiation with a negative exponent).
Python has two directives – from __future__ import feature (defined in PEP 236 -- Back to the __future__), which changes language features (and uses the existing module import syntax, as in Perl), and the coding directive (in a comment) to specify the encoding of a source code file (defined in PEP 263 -- Defining Python Source Code Encodings).
Different cultures used different traditional numeral systems for naming large numbers.The extent of large numbers used varied in each culture. Two interesting points in using large numbers are the confusion on the term billion and milliard in many countries, and the use of zillion to denote a very large number where precision is not required.
An ORDER BY clause in SQL specifies that a SQL SELECT statement returns a result set with the rows being sorted by the values of one or more columns. The sort criteria does not have to be included in the result set (restrictions apply for SELECT DISTINCT , GROUP BY , UNION [DISTINCT] , EXCEPT [DISTINCT] and INTERSECT [DISTINCT] .)
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
In programming language theory, lazy evaluation, or call-by-need, [1] is an evaluation strategy which delays the evaluation of an expression until its value is needed (non-strict evaluation) and which also avoids repeated evaluations (by the use of sharing).
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.