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Roth"},"license":"MIT","homepage":"https://jupyter-ijavascript-utils.onrender.com/","keywords":["ijavascript","jupyter"],"repository":{"type":"git","url":"git+ssh://git@github.com/paulroth3d/jupyter-ijavascript-utils.git"},"description":"Utilities for working with iJavaScript - a Jupyter Kernel","maintainers":[{"name":"darkbluestudios","email":"proth@darkbluestudios.com"}],"readme":"<p align=\"center\">\n    <a href=\"https://jupyter-ijavascript-utils.onrender.com/\" alt=\"Documentation\">\n        <img src=\"https://img.shields.io/badge/Documentation-here-informational\" />\n    </a>\n    <a href=\"https://jupyter-ijavascript-utils.onrender.com/LICENSE\" alt=\"License\">\n        <img src=\"https://img.shields.io/badge/License-MIT-green\" />\n    </a>\n    <img src=\"https://img.shields.io/badge/Coverage-98-green\" />\n    <a href=\"https://www.npmjs.com/package/jupyter-ijavascript-utils\" alt=\"npm\">\n        <img src=\"https://img.shields.io/badge/npm-%5E1.X-red\" />\n    </a>\n    <a href=\"https://github.com/paulroth3d/jupyter-ijavascript-utils\" alt=\"npm\">\n        <img src=\"https://img.shields.io/badge/github-here-black\" />\n    </a>\n    <a href=\"https://mybinder.org/v2/gh/paulroth3d/jupyter-ijavascript-utils/main\" alt=\"Launch Binder\">\n                <img src=\"https://mybinder.org/badge_logo.svg\" />\n    </a>\n</p>\n\n# Overview\n\nThis is a library to help people that understand JavaScript\nto leverage for using Jupyter with the iJavaScript kernel\nas a way to load and explore data, and ultimately tell compelling stories with visuals.\n\nNotebooks are a way to explore and experiment, in addition to write and explain ideas.\n\n**All of the tutorials provided here, including this one, was written as a notebook and simply exported.**\n\n![Screenshot](docResources/img/started_jupyterSideBySide.jpg)\n\nSee Example binder here:\n[![Binder:what can I do with this](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/paulroth3d/jupyter-ijavascript-utils/main?labpath=example.ipynb)\n\n# Documentation\n\nSee documentation at: [https://jupyter-ijavascript-utils.onrender.com/](https://jupyter-ijavascript-utils.onrender.com/)\n\n# What is this?\n\nThe [jupyter-ijavascript-utils](https://www.npmjs.com/package/jupyter-ijavascript-utils) library is simply a collection of utility methods for Node and JavaScript Developers interested in Data Science.\n\n* Load\n* Aggregate\n* Manipulate\n* Format / Visualize\n* Refine and Explore\n* Export\n\nCurrently, we assume you'll be using [nriesco's iJavaScript Jupyter Kernel](https://github.com/n-riesco/ijavascript) and the [Jupyter Lab - the latest interface for Jupyter](https://jupyter.org/) - and the installation is fairly simple in the [How to Use guide](https://jupyter-ijavascript-utils.onrender.com/tutorial-howToUse.html). (Although suggestions welcome)\n\nThis is not intended to be the only way to accomplish many of these tasks, and alternatives are mentioned in the documentation as available.\n\n![Screenshot of example notebook](docResources/img/mainExampleNotebook.png)\n\n## NOTE - iJavaScript Stalemate\n\niJavaScript currently requires node v20 to run, and fails on versions higher due to zeromq issues [See bug 297 on iJavaScript](https://github.com/n-riesco/ijavascript/issues/297)\n\nAdditionally, vega has now moved to ESM Modules - [vega versions](https://www.npmjs.com/package/vega?activeTab=versions), and [vega-lite versions](https://www.npmjs.com/package/vega-lite?activeTab=versions)\n\niJavaScript only supports ESM Modules with [esm-hook](https://www.npmjs.com/package/esm-hook) - [see issue 210](https://github.com/n-riesco/ijavascript/issues/210)\n\n# What's New \n* 1.65 - update module type to explicitly state commonJS\n* 1.64 - using the latest version of vega/vega-lite prior to ESM update\n* 1.62 - Update to Array.peekableIterator to include peekItr() as sugar for .peek\n* 1.61 - Docs Updated\n* 1.60 - Make post-processing of documents easier with ijs.utils.markDocumentPosition\n* 1.59 - \n    * #95 - give control with page breaks. So we can render text before the page break (like for headers) - or even get the html used and render it how we want.\n    * #96 - Support internal comments in notebooks (meaning it can render in markdown, but can be disabled when preparing to print)\n* 1.58 - \n    * #91 - add object.splitIntoDatums - to make working with datum libraries - like vega-lite - easier\n    * #92 - make using the cache easier - as you can say to use the cache, and it will still work if the cache file does not exist yet.\n    * #93 / #94 - bug fixes\n* 1.57 - #86 - include examples on binning based on time series\n    * #87 - add in fileExists to make things easier for new people getting started\n    * #89 - allow resizing arrays with defaults, if zipping arrays of different sizes\n    * #90 - correct issue with timezone offsets, so it is no longer possible to get a timezone offset +24:00\n    * #92 - make it easier to handle big expensive calculations with a cache\n* 1.56 - #84 (object.renamePropertiesFromList), #82 (date.getWeekday)\n* 1.55 - #76, #77, #74, #78\n* 1.54 - additional Date logic, and formatting. #70 #71 #72\n* 1.53 - additional docs and examples for color/colour package.\n* 1.52 - print a date to ISO in local time with date.toLocalISO\n* 1.51 - added in date - and addressed issues #69, #68, #67, #66\n* 1.50 - added in color/colour - and addressed issue #65\n* 1.49 - Additional documentation for issues #18, #63, #62, #61 (like table.generateObjectCollection)\n* 1.48 - Correct table rendering html if filter was used (#46)\n* 1.47 - \n  * allow conversion from a Collection of Objects to Arrays and back with object. (objectCollectionFromArray, objectCollectionToArray)\n  * Easier iterating over values and peeking with array with PeekableArrayIterator\n  * Support for delayed and asynchronous chaining of functions (array.delayedFn, chainFunction, etc)\n* 1.46 - Make it easier to extract data from \"hard-spaced arrays\" - (array.multiLineSubstr, array.multiStepReduce)\n* 1.45 - more ways to understand the data - aggregate.coalesce(), convert properties to arrow/dot notation / reverse it : object.flatten() / object.expand() and Object.isObject()\n* 1.43 - esm module fix since still not supported yet in ijavascript\n* 1.41 - object.propertyInherit - to simplify inheriting values from one record to the next\n* 1.40 - array.extract and array.applyArrayValue to allow for extracting values from arrays, transforming them on a separate process and applying them back\n* 1.39 - format.exportWords - to identify distinct words in strings using unicode character properties\n* 1.38 - object.extract / object.apply\n* 1.37 - {@link module:format.replaceString|format.replaceString} as convenience for replacing only a single string.\n* 1.36 - replaceStrings to allow for replacement dictionaries and tuplets\n* 1.35 - object.extractObjectProperties / object.extractObjectProperty - to do horizontal transposes on objects\n* 1.34 - format.mapArrayDomain and add notes in to random on using non-uniform distributions.\n* 1.33 - Object.augmentInherit and Object.union\n* 1.32 - Array.indexify to identify sections within a 1d array into a hierarchy.\n* 1.31 - harden Array.transpose for arrays with nulls, and Table.generateTSV\n* 1.30 - add Format.wordWrap and Format.lineCount\n* 1.29 - Updated TableGenerator.format method\n* 1.28 - Sticky table headers for table.render\n* 1.27 - Multi-Dimensional arange (initialize array along multiple dimensions)\n* 1.26 - Support for file.writeFile and file.writeJSON to append\n* 1.25 - Additional chain methods and documentation\n* 1.24 - format.stripHtmlTags, TableGenerator.offset, chain.chainFlatMap, chain.chainFilter\n* 1.23 - add format.parseNumber and TableGenerator.styleColumn, align group.separateByFields to vega-lite fold transform\n* 1.22 - make chain iJavaScript aware, but still able to work outside of Jupyter\n* 1.21 - include chain - simple monoid\n* 1.20 - fix vega dependency\n* 1.19 - add in describe and hashMap modules, along with format.limitLines\n* 1.18 - tie to vega-datasets avoiding esmodules until ijavascript can support them\n* 1.17 - provide object.propertyValueSample - as a way to list 'non-empty' property values\n* 1.16 - provide file.matchFiles - as a way to find files or directories\n* 1.15 - provide object.formatProperties - as a way to quickly convert to string, number, etc.\n* 1.14 - provide format.compactNumber and object.mapProperties\n* 1.13 - provide utils.random() to genrate random values\n* 1.12 - provide `utils.table(...)` instead of `new utils.TableGenerator(...)`\n* 1.11 - provide topValues (like top 5, bottom 3)\n* 1.10 - provide percentile (like 50th percentile) aggregates\n* 1.9 - allow transposing results on TableGenerator.\n* 1.8 - add in What can I Do tutorial, and object.join methods\n* 1.7 - revamp of `animation` method to htmlScript\n* 1.6 - add SVG support for rendering SVGs and animations\n* 1.5 - Add Latex support for rendering Math formulas and PlantUML support for Diagrams\n* 1.4 - Add in vega embed, vega mimetypes and example choropleth tutorial\n* 1.3 - Add Leaflet for Maps, allow Vega to use explicit specs (so [Examples can be copied and pasted](https://vega.github.io/vega-lite/examples/), and add in htmlScripts\n\n# Running Your Own Notebooks\n\nA many of the tutorials are simply exports of Jupyter notebooks (*.ipynb),\nfound under the [docResources/notebooks](https://github.com/paulroth3d/jupyter-ijavascript-utils/tree/main/docResources/notebooks) folder.\n\n(Note that if you wish to `require` additional packages - like `jupyter-ijavascript-utils`,\nsimply create a package in the folder you will run the `jupyter lab` command\n- such as the sample one under [docResources/notebooks/package.json](https://github.com/paulroth3d/jupyter-ijavascript-utils/blob/main/docResources/notebooks/package.json))\n\n## Converting Local Functions to a Local Library\n\nOften - Jupyter is not the best place to do development, and folks would like to develop in their own favourite IDE.\n\nYou can write local modules (ex: `lib.js`) relative to your notebook, and then use `require('./lib')` to access them in your notebook. (see the section below on ESM Modules)\n\nNOTE: re-running the require will use a `cached version` of your module, and `may not reflect changes you just made`.\n\n(For this and other reasons, it can be helpful to have a `version` attribute to your module - to ensure the latest code is accessible)\n\nThere typically are two options:\n\n* re-run the entire notebook\n\n* use a \"cache bypass\" only for your local library. ex: [https://www.npmjs.com/package/import-fresh](import-fresh)\n\nUsing a cache bypass is fairly simple, and behaves somethng similar to this:\n\n```\nutils = reqire('jupyter-ijavascript-utils');\nimportFresh = require('import-fresh');\n// other imports go here\n\n//-- clear the output so it doesn't pollute with nonsense we don't care about.\nutils.ijs.clearOutput();\n```\n\nand then load your module in a separate cell:\n\n```\nlib = importFresh('./lib');\nlib.version; // 1.0.0\n```\n\nand if you change your library, you can then just rn tat cell again\n\n## ESM Modules + D3\n\nNote that we strongly recommend using this with other modules like D3 - that only support ESM modules now.\n\nThere is a [known issue #210](https://github.com/n-riesco/ijavascript/issues/210) in the iJavaScript kernel.\n\nSo if you try to import libraries like d3 [and get comments like this](https://github.com/n-riesco/ijavascript/issues/279)\n\n```\n$ node -e \"import defaultExport from './test.mjs'\"\n[eval]:1\nimport defaultExport from './test.mjs'\n^^^^^^\n\nSyntaxError: Cannot use import statement outside a module\n    at new Script (vm.js:88:7)\n    at createScript (vm.js:263:10)\n    at Object.runInThisContext (vm.js:311:10)\n    at Object.<anonymous> ([eval]-wrapper:10:26)\n    at Module._compile (internal/modules/cjs/loader.js:1151:30)\n    at evalScript (internal/process/execution.js:94:25)\n    at internal/main/eval_string.js:23:3\n```\n\n### Use [esm-hook](https://github.com/alex-kinokon/esm-hook) as a workaround for now.\n\n```\nrequire(\"esm-hook\"); // must come before requiring esm modules\nd3 = require('d3');  // import esm modules\n```\n\nMore is found on the documentation for [issue #210](require(\"esm-hook\"))\n\n## Google Collab\n\nYou can very easily use iJavaScript and the jupyter-ijavascript-utils within Google Collab.\n\n[See the excellent writeup from Alexey Okhimenko](https://dev.to/obenjiro/silence-of-the-fans-part-1-javascript-quickstart-5f3m)\n\nAnd the shortlink to run your own: [https://tinyurl.com/tf-js-colab](https://tinyurl.com/tf-js-colab)\n\nSteps Overview:\n\n* Clone the Google Collab Document\n* Run the first cell\n  * If you notice an error `unrecognized runtime \"JavaScript\"` - that's expected\n* Refresh your browser (see [Alexey's writeup for more](https://dev.to/obenjiro/silence-of-the-fans-part-1-javascript-quickstart-5f3m))\n* Run a cell to install modules, ex: `sh('npm install jupyter-ijavascript-utils')`\n* Then continue to run your code past this point.\n\n## Running on Binder\n\n[mybinder.org](https://mybinder.org/) is a great place to run a Jupyter Notebook online.\n\nIt means you can run Jupyter Notebooks with additional kernels without having to install anything,\nand can try right in your browser.\n\nGive it a try here:\n[![Binder:what can I do with this](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/paulroth3d/jupyter-ijavascript-utils/main?labpath=example.ipynb)\n\n# For Example\n\n## Get Sample Data\n\n([See the DataSets module for more on sample datasets](https://jupyter-ijavascript-utils.onrender.com/module-datasets.html))\n\n([See the ijs module for helpers to use async/await](https://jupyter-ijavascript-utils.onrender.com/module-ijs.html#.await))\n\n```\n//-- get the data\nutils.ijs.await(async ($$, console) => {\n\tbarley = await utils.datasets.fetch('barley.json');\n\n\t//-- continue to use the barley dataset, or wait to the next cell\n});\n```\n\n## Group By\n\nThen we can group using a process similar to d3js\n\n([See the Group Module for more on grouping](https://jupyter-ijavascript-utils.onrender.com/module-group.html))\n\n```\n//-- get the min max of the types of barley\nbarleyByVarietySite = utils.group.by(barley, 'variety', 'site')\n\n// SourceMap(10) [Map] {\n//   'Manchuria' => SourceMap(6) [Map] {\n//     'University Farm' => [ [Object], [Object] ],\n//     'Waseca' => [ [Object], [Object] ],\n//     'Morris' => [ [Object], [Object] ],\n//     'Crookston' => [ [Object], [Object] ],\n//     'Grand Rapids' => [ [Object], [Object] ],\n//     'Duluth' => [ [Object], [Object] ],\n//     source: 'site'\n//   },\n//   'Glabron' => SourceMap(6) [Map] {\n//     'University Farm' => [ [Object], [Object] ],\n//     'Waseca' => [ [Object], [Object] ],\n//     'Morris' => [ [Object], [Object] ],\n//     'Crookston' => [ [Object], [Object] ],\n//     'Grand Rapids' => [ [Object], [Object] ],\n//     'Duluth' => [ [Object], [Object] ],\n//     source: 'site'\n//   },\n//   ...\n// }\n\n//-- now group by variety and year\nbarleyByVarietyYear = utils.group.by(barley, 'variety', 'year')\n\n// SourceMap(10) [Map] {\n//   'Manchuria' => SourceMap(2) [Map] {\n//     1931 => [ [Object], [Object], [Object], [Object], [Object], [Object] ],\n//     1932 => [ [Object], [Object], [Object], [Object], [Object], [Object] ],\n//     source: 'year'\n//   },\n//   'Glabron' => SourceMap(2) [Map] {\n//     1931 => [ [Object], [Object], [Object], [Object], [Object], [Object] ],\n//     1932 => [ [Object], [Object], [Object], [Object], [Object], [Object] ],\n//     source: 'year'\n//   },\n//   ...\n// }\n```\n\n##  Aggregating\n\n([See the Aggregation module for more](https://jupyter-ijavascript-utils.onrender.com/module-aggregate.html))\n\n```\nutils.group.by(barley, 'variety', 'site')\n    .reduce((collection) => ({\n        years: utils.aggregate.extent(collection, 'year'),\n        numRecords: utils.aggregate.length(collection),\n        yield_sum: utils.aggregate.sum(collection, 'yield'),\n        yield_min: utils.aggregate.min(collection, 'yield'),\n        yield_max: utils.aggregate.max(collection, 'yield'),\n        yield_diff: utils.aggregate.difference(collection, 'yield')\n    }));\n\nreturns\n[\n  {\n    variety: 'Manchuria',\n    site: 'University Farm',\n    years: { min: 1931, max: 1932 },\n    numRecords: 2,\n    yield_sum: 53.9,\n    yield_min: 26.9,\n    yield_max: 27,\n    yield_diff: 0.100\n  },\n  {\n    variety: 'Manchuria',\n    site: 'Waseca',\n    years: { min: 1931, max: 1932 },\n    numRecords: 2,\n    yield_sum: 82.33333,\n    yield_min: 33.46667,\n    yield_max: 48.86667,\n    yield_diff: 15.39999\n  },\n  ...\n];\n```\n\n## Render as a Table\n\n([See the TableGenerator class for more](https://jupyter-ijavascript-utils.onrender.com/TableGenerator.html))\n\n```\nnew utils.TableGenerator(barley)\n    .sort('-yield')\n    .formatter({ year: (v) => `${v}`})\n    .limit(10)\n    .render()\n```\n\n![Screenshot of table](docResources/img/BarleySimpleTable.png)\n\n## Show a Graph\n\n(See the {@tutorial vegaLite1} tutorial or the {@link module:vega|Vega module} for more)\n\n```\n//-- make a point chart\nutils.vega.svg((vl) => vl.markPoint()\n    //-- data as an array of items\n    .data(barley)\n    .title('Barley Yield by Site')\n    .width(600)\n    .encode(\n        //-- x position is Nominal - not a number\n        vl.x().fieldN('site'),\n        //-- y position is Quantitative - a number\n        vl.y().fieldQ('yield'),\n        //-- Color is based on the year field\n        vl.color().fieldN('year')\n    )\n)\n```\n\n![Screenshot of Vega Cell](docResources/img/BarleyYieldBySite.png)\n\nWhere making it into a bar chart, to understand the proportions of varieties grown is simply changing the mark type\n\n```\n// change from markPoint to markBar\nutils.vega.svg((vl) => vl.markBar()\n    //-- data as an array of items\n    .data(barley)\n    .title('Barley Yield by Site Variety')\n    .width(600)\n    .encode(\n        //-- x position is Nominal - not a number\n        vl.x().fieldN('site').title('Site'),\n        //-- y position is Quantitative - a number\n        vl.y().fieldQ('yield').title('Yield'),\n        //-- Color is based on the variety field\n        vl.color().fieldN('variety').title('Variety')\n    )\n)\n```\n\n![Screenshot of variety type](docResources/img/BarleyYieldBySiteVariety.png)\n\nWith further options to zoom, pan, or setup interactive sliders:\n\n![Screenshot of vega lite with sliders](docResources/img/vegaLiteSliders.png)\n\nOr try your hand at the [Vega Lite Examples](https://vega.github.io/vega-lite/examples/)\n\n![Screenshot of Vega-Lite Examples](docResources/img/vegaLiteExamplesSm.png)\n\n## Create a Data Driven Map\n\n([See the Data Driven Maps Tutorial for More](https://jupyter-ijavascript-utils.onrender.com/tutorial-vega_choroplethLong.html))\n\n![Screenshot of choropleth](docResources/img/choropleth_workingFull.svg)\n\n## Render Maps\n\n([See the Leaflet module for more](https://jupyter-ijavascript-utils.onrender.com/module-leaflet.html))\n\n![Screenshot of Leaflet](docResources/img/leafletRenderMarkers.png)\n\n## Generate Text Driven Diagrams\n\n([See the PlantUML module for more](https://jupyter-ijavascript-utils.onrender.com/module-plantuml.html))\n\n![Screenshot of PlantUML](docResources/img/plantumlSequence.png)\n\n## Render Other Libraries\n\n([See the Html Script Tutorial for more](https://jupyter-ijavascript-utils.onrender.com/tutorial-htmlScript.html))\n\n```\nutils.ijs.htmlScript({\n    scripts: ['https://cdnjs.cloudflare.com/ajax/libs/qrcodejs/1.0.0/qrcode.min.js'],\n    height: '100%',\n    onReady: ({rootEl}) => {\n        new QRCode(rootEl, \"https://jupyter-ijavascript-utils.onrender.com/\");\n    }\n});\n```\n\n![Screenshot of QR Code](docResources/img/htmlScript_qrCode.png)\n\n## Create Animations\n\n(See the [Noise Visualization Tutorial](https://jupyter-ijavascript-utils.onrender.com/tutorial-noiseVisualization.html) or [SVG Module](file:///Users/proth/Documents/notebooks/jupyter-ijavascript-utils/docs/module-svg.html) for more)\n\n[![Screenshot of dark animation](docResources/img/noiseVisualization_wavesDark.svg)](docResources/img/svgAnimation2Dark.gif)\n\n[![Screenshot of light animation](docResources/img/noiseVisualization_wavesLight.svg)](docResources/img/svgAnimation2Light.gif)\n\n(click the image to play the gif animation)\n\n# License\n\nSee [License](https://jupyter-ijavascript-utils.onrender.com/LICENSE) (MIT License).\n\n# Issues\n\nIf you have any questions first file it on [issues](https://github.com/paulroth3d/jupyter-ijavascript-utils/issues) before contacting authors.\n\n## Toubleshooting\n\niJavaScript does not currently support AMD Modules, due to open issues with nodejs [see iJavaScript issue #210 for more](https://github.com/n-riesco/ijavascript/issues/210)\n\n# Contributions\n\nYour contributions are welcome: both by reporting issues on [GitHub issues](https://github.com/paulroth3d/jupyter-ijavascript-utils/issues) or pull-requesting patches.\n\nIf you want to implement any additional features, to be added to JSforce to our master branch, which may or may not be merged please first check current [opening issues](https://github.com/paulroth3d/jupyter-ijavascript-utils/issues?q=is%3Aopen) with milestones and confirm whether the feature is on road map or not.\n\nIf your feature implementation is brand-new or fixing unsupposed bugs in the library's test cases, please include addtional test codes in the `src/__tests__/` directory.\n\n\n## Further Reading\n\n* [JSDoc Templates](https://cancerberosgx.github.io/jsdoc-templates-demo/demo/)\n* [DocDash Template](http://clenemt.github.io/docdash/)\n* [DocDash Example Code](http://clenemt.github.io/docdash/base_chains.js.html)\n* [Gist creating JSDoc to MD](https://gist.github.com/slorber/0bf8c8c8001505f0f99a062ac55bf442)\n* [JSDoc Documentation](https://jsdoc.app/index.html)\n* [D3 Grouping / Data Transformation](https://observablehq.com/@d3/d3-group)\n* [Danfo](https://danfo.jsdata.org/api-reference/plotting/tables)\n* [DataFrame-js](https://github.com/Gmousse/dataframe-js)\n* [ES21 array](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/flat)\n","readmeFilename":"README.md"}