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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. It is free software released under the three-clause BSD license. [2]
The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.
Pandas – Python library for data analysis. PAW – FORTRAN/C data analysis framework developed at CERN. R – A programming language and software environment for statistical computing and graphics. [149] ROOT – C++ data analysis framework developed at CERN. SciPy – Python library for scientific computing.
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
in the software itself, per skin (for example the class § sortable) collectively for all users of one wiki in MediaWiki:Common.css (for example, on this and some other projects there is or was the class wikitable, later moved to shared.css) separately per skin in MediaWiki:Monobook.css etc. individually on one wiki in a user subpage
In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model.
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Exploded pie chart for the example data (see below), with the largest party group exploded. A chart with one or more sectors separated from the rest of the disk is known as an exploded pie chart. This effect is used to either highlight a sector, or to highlight smaller segments of the chart with small proportions.