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  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    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]

  3. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    Depending on the amount and format of the incoming data, data wrangling has traditionally been performed manually (e.g. via spreadsheets such as Excel), tools like KNIME or via scripts in languages such as Python or SQL. R, a language often used in data mining and statistical data analysis, is now also sometimes used for data wrangling. [6]

  4. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

  5. RDFLib - Wikipedia

    en.wikipedia.org/wiki/RDFLib

    RDFLib is a Python library for working with RDF, [2] a simple yet powerful language for representing information. This library contains parsers/serializers for almost all of the known RDF serializations, such as RDF/XML, Turtle, N-Triples, & JSON-LD, many of which are now supported in their updated form (e.g. Turtle 1.1).

  6. List of Python software - Wikipedia

    en.wikipedia.org/wiki/List_of_Python_software

    Astropy, a library of Python tools for astronomy and astrophysics. Biopython, a Python molecular biology suite; Gensim, a library for natural language processing, including unsupervised topic modeling and information retrieval; graph-tool, a Python module for manipulation and statistical analysis of graphs.

  7. Leap year problem - Wikipedia

    en.wikipedia.org/wiki/Leap_year_problem

    The leap year problem (also known as the leap year bug or the leap day bug) is a problem for both digital (computer-related) and non-digital documentation and data storage situations which results from errors in the calculation of which years are leap years, or from manipulating dates without regard to the difference between leap years and common years.

  8. How to manipulate date and time in JavaScript - AOL

    www.aol.com/manipulate-date-time-javascript...

    On top of different date-time formats, you have to consider timezone and local differences. ... and, if necessary, manipulating dates. But as a JavaScript developer, you would know this theory ...

  9. Unix time - Wikipedia

    en.wikipedia.org/wiki/Unix_time

    Python provides a time library which uses Unix time. [23] JavaScript provides a Date library which provides and stores timestamps in milliseconds since the Unix epoch and is implemented in all modern desktop and mobile web browsers as well as in JavaScript server environments like Node.js .