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A Jupyter Notebook application is a browser-based REPL containing an ordered list of input/output cells which can contain code, text (using Github Flavored Markdown), mathematics, plots and rich media. Jupyter Notebook is similar to the notebook interface of other programs such as Maple, Mathematica, and SageMath, a computational interface ...
According to Stephen Wolfram: "The idea of a notebook is to have an interactive document that freely mixes code, results, graphics, text and everything else.", [4] and according to the Jupyter Project Documentation: "The notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based ...
IPython continued to exist as a Python shell and kernel for Jupyter, but the notebook interface and other language-agnostic parts of IPython were moved under the Jupyter name. [11] [12] Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. [13]
Cython (/ ˈ s aɪ θ ɒ n /) is a superset of the programming language Python, which allows developers to write Python code (with optional, C-inspired syntax extensions) that yields performance comparable to that of C.
In 1964, the expression READ-EVAL-PRINT cycle is used by L. Peter Deutsch and Edmund Berkeley for an implementation of Lisp on the PDP-1. [3] Just one month later, Project Mac published a report by Joseph Weizenbaum (the creator of ELIZA, the world's first chatbot) describing a REPL-based language, called OPL-1, implemented in his Fortran-SLIP language on the Compatible Time Sharing System (CTSS).
Mathcad's central interface is an interactive notebook in which equations and expressions are created and manipulated in the same graphical format in which they are presented (WYSIWYG). This approach was adopted by systems such as Mathematica, Maple, Macsyma, MATLAB, and Jupyter.
Scientific tools integration: integrates with Jupyter Notebook, supports Anaconda as well as multiple scientific packages including Matplotlib and NumPy. Front-end and back-end web development: special support for Django, [9] Flask, [10] FastAPI [11] and Pyramid, [12] CSS [13] and JavaScript [14] assistance, Npm, Webpack and other JavaScript tools
Using Jupyter Notebook, run this code until "Save to file" for the month of the version of this file. For instance, if this file was last updated in December 2022, set analyze_last_month = False and last_month = date(2022, 12, 1) in "Month to analyze". This will save the data from that month in a text file.