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Augenstein","email":"marius.augenstein@gmail.com"},"license":"ISC","homepage":"https://github.com/maugenst/tabletojson#readme","keywords":["table2json","html","table","convert","json","csv"],"repository":{"url":"git://github.com/maugenst/tabletojson.git","type":"git"},"description":"Convert HTML tables to JSON objects","maintainers":[{"name":"iaincollins","email":"me@iaincollins.com"},{"name":"piranna","email":"piranna@gmail.com"},{"name":"maugenst","email":"marius.augenstein@gmail.com"}],"readme":"# Tabletojson: Converting Table to JSON objects made easy\n\n[![CircleCI](https://circleci.com/gh/maugenst/tabletojson.svg?style=shield)](https://circleci.com/gh/maugenst/tabletojson)\n[![Codacy Badge](https://app.codacy.com/project/badge/Grade/9e26dee5b7774ceea1b3f01dcaa51c41)](https://app.codacy.com/gh/maugenst/tabletojson/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)\n[![Codacy Badge](https://app.codacy.com/project/badge/Coverage/9e26dee5b7774ceea1b3f01dcaa51c41)](https://app.codacy.com/gh/maugenst/tabletojson/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_coverage)\n[![Known Vulnerabilities](https://snyk.io/test/github/maugenst/tabletojson/badge.svg)](https://snyk.io/test/github/maugenst/tabletojson)\n\nConvert local or remote HTML embedded tables into JSON objects.\n\n# Table of Contents\n- [Introduction](#introduction)\n- [Incompatible changes](#incompatible-changes)\n    * [Conversion from version 1.+ to 2.x](#conversion-from-version-1-to-2x)\n    * [Conversion from version 2.0.1 to 3.x](#conversion-from-version-201-to-3x)\n- [Installation](#installation)\n- [Quickstart](#quickstart)\n    * [esm](#esm)\n    * [commonjs](#commonjs)\n    * [Remote (`convertUrl`)](#remote-converturl)\n    * [Local (`convert`)](#local-convert)\n- [Use case examples](#use-case-examples)\n    * [Duplicate column headings](#duplicate-column-headings)\n    * [Tables with rowspan](#tables-with-rowspan)\n    * [Tables with complex rowspan](#tables-with-complex-rowspan)\n    * [Tables with even more complex rowspans](#tables-with-even-more-complex-rowspans)\n    * [Tables with headings in the first column](#tables-with-headings-in-the-first-column)\n    * [Tables with HTML](#tables-with-html)\n    * [Tables with complex headers](#tables-with-complex-headers)\n- [Options](#options)\n    * [fetchOptions (only `convertUrl`)](#fetchoptions-only-converturl)\n    * [headers](#headers)\n    * [stripHtmlFromHeadings](#striphtmlfromheadings)\n    * [stripHtmlFromCells](#striphtmlfromcells)\n    * [forceIndexAsNumber](#forceindexasnumber)\n    * [countDuplicateHeadings](#countduplicateheadings)\n    * [ignoreColumns](#ignorecolumns)\n    * [onlyColumns](#onlycolumns)\n    * [ignoreHiddenRows](#ignorehiddenrows)\n    * [headings](#headings)\n    * [limitrows](#limitrows)\n        + [Huge Table (see test/tables.html)](#huge-table-see-testtableshtml)\n        + [Example output with limitrows: 5](#example-output-with-limitrows-5)\n    * [containsClasses](#containsclasses)\n- [Known issues and limitations](#known-issues-and-limitations)\n- [Usage](#usage)\n    * [Convert an HTML text into an array of all the tables on the page](#convert-an-html-text-into-an-array-of-all-the-tables-on-the-page)\n    * [Fetch a URL and parse all it's tables into JSON, using a callback](#fetch-a-url-and-parse-all-its-tables-into-json-using-a-callback)\n    * [Fetch a URL and parse all it's tables into JSON, using promises](#fetch-a-url-and-parse-all-its-tables-into-json-using-promises)\n    * [Fetch a table from Wikipedia and combine with json2csv to convert to CSV](#fetch-a-table-from-wikipedia-and-combine-with-json2csv-to-convert-to-csv)\n- [Contributing](#contributing)\n    * [Contributors](#contributors)\n\n## Introduction\n\nTabletojson attempts to convert local or remote HTML tables into JSON with a very low footprint. \nCan be passed the markup for a single table as a string, a fragment of HTML or\nan entire page or just a URL (with an optional callback function; promises also\nsupported).\n\nThe response is always an array. Every array entry in the response represents a\ntable found on the page (in same the order they were found in HTML).\n\nAs of version 2.0 tabletojson is completely written in typescript.\n\n## Incompatible changes\n* Version 2 on request.js is not used anymore\n* Version >=2.1.0 got is not used anymore and got replaced by node internal fetch. more information [here](#options)...\n* Switched from commonjs to module system. Bumped version to 3.0.0  \n* Providing a \"hybrid\" library to cope with the needs of both esm and commonjs. Bumped version to 4.0.1.\n* Adding support for complex headings as key in the output json object. Bumped version to 4.1.0. \n\n### Conversion from version 1.+ to 2.x\n\n* Require must be changed from ``const tabletojson = require('../lib/tabletojson');`` to either \n``const tabletojson = require('../lib/tabletojson').Tabletojson;`` or\n``const {Tabletojson: tabletojson} = require('../lib/tabletojson');``\n* Replace request options by fetch options. More information [here](#options)...\n\n### Conversion from version 2.0.1 to 3.x\n\n* Tabletojson now uses esm. Use ``import {Tabletojson as tabletojson} from 'tabletojson';`` or ``import {tabletojson} from 'tabletojson';``\n* Added lowercase import ``import {tabletojson} from 'tabletojson';``\n* If you are using Node 18 execute examples by calling:\n```sh\nnpm run build:examples\ncd dist/examples\nnode --experimental-vm-modules --experimental-specifier-resolution=node example-1.js --prefix=dist/examples\n```\n\n## Installation\n\n```sh\nnpm install tabletojson\n```\n\n## Quickstart\n\n### esm\n\n```typescript\nimport {tabletojson} from 'tabletojson';\ntabletojson.convertUrl('https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes', function (tablesAsJson) {\n  console.log(tablesAsJson[1]);\n});\n```\n\n### commonjs\n\n```javascript\nconst {tabletojson} = require('tabletojson');\ntabletojson.convertUrl('https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes', function (tablesAsJson) {\n  console.log(tablesAsJson[1]);\n});\n```\n\n### Remote (`convertUrl`)\n\n```typescript\n// example-1.ts\nimport {tabletojson} from 'tabletojson';\ntabletojson.convertUrl('https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes', function (tablesAsJson) {\n    console.log(tablesAsJson[1]);\n});\n```\n\n### Local (`convert`)\n\nMore examples can be found in examples folder.\n\n```typescript\n// example-6.ts\nimport {tabletojson} from 'tabletojson';\nimport * as fs from 'fs';\nimport * as path from 'path';\nconst html = fs.readFileSync(path.resolve(process.cwd(), '../../test/tables.html'), {\n  encoding: 'utf-8',\n});\nconst converted = tabletojson.convert(html);\nconsole.log(converted);\n```\n\n## Use case examples\n\n### Duplicate column headings\n\nTables with duplicate column headings, subsequent headings are suffixed with a\ncount:\n\n```md\n|| PLACE || VALUE || PLACE || VALUE ||\n|--------|--------|--------|---------|\n| abc    |      1 |    def |      2  |\n```\n\n```json\n[\n  {\n    \"PLACE\": \"abc\",\n    \"VALUE\": \"1\",\n    \"PLACE_2\": \"def\",\n    \"VALUE_2\": \"2\"\n  }\n]\n```\n\n### Tables with rowspan\n\nIn tables with rowspan, the content of the spawned cell must be available in\nthe respective object.\n\n<table id=\"table11\" class=\"table\" style=\"border: solid\">\n    <thead>\n    <tr>\n        <th>Parent</th>\n        <th>Child</th>\n        <th>Age</th>\n    </tr>\n    </thead>\n    <tbody>\n        <tr>\n            <td rowspan=\"3\">Marry</td>\n            <td>Sue</td>\n            <td>15</td>\n        </tr>\n        <tr>\n            <td>Steve</td>\n            <td>12</td>\n        </tr>\n        <tr>\n            <td>Tom</td>\n            <td>3</td>\n        </tr>\n    </tbody>\n</table>\n\n```json\n[\n  {\"Parent\": \"Marry\", \"Child\": \"Tom\", \"Age\": \"3\"},\n  {\"Parent\": \"Marry\", \"Child\": \"Steve\", \"Age\": \"12\"},\n  {\"Parent\": \"Marry\", \"Child\": \"Sue\", \"Age\": \"15\"}\n]\n```\n\n### Tables with complex rowspan\n\nIn tables with complex rowspans, the content of the spawned cell must be available in the respective object.\n\n<table id=\"table12\" class=\"table\" border=\"1\">\n    <thead>\n    <tr>\n        <th>Parent</th>\n        <th>Child</th>\n        <th>Age</th>\n    </tr>\n    </thead>\n    <tbody>\n        <tr>\n            <td rowspan=\"3\">Marry</td>\n            <td>Sue</td>\n            <td>15</td>\n        </tr>\n        <tr>\n            <td>Steve</td>\n            <td>12</td>\n        </tr>\n        <tr>\n            <td rowspan=\"2\">Tom</td>\n            <td rowspan=\"2\">3</td>\n        </tr>\n        <tr>\n            <td rowspan=\"2\">Taylor</td>\n        </tr>\n        <tr>\n            <td>Peter</td>\n            <td>17</td>\n        </tr>\n    </tbody>\n</table>\n\n```json\n[\n  {\"Parent\": \"Marry\", \"Child\": \"Sue\", \"Age\": \"15\"},\n  {\"Parent\": \"Marry\", \"Child\": \"Steve\", \"Age\": \"12\"},\n  {\"Parent\": \"Marry\", \"Child\": \"Tom\", \"Age\": \"3\"},\n  {\"Parent\": \"Taylor\", \"Child\": \"Tom\", \"Age\": \"3\"},\n  {\"Parent\": \"Taylor\", \"Child\": \"Peter\", \"Age\": \"17\"}\n]\n```\n\n### Tables with even more complex rowspans\n\nIn tables with even more complex rowspans, the content of the spawned cell must be available in the respective object.\n\n<table id=\"table12-a\" class=\"table\" border=\"1\">\n    <thead>\n    <tr>\n        <th>Department</th>\n        <th>Major</th>\n        <th>Class</th>\n        <th>Instructor</th>\n        <th>Credit</th>\n    </tr>\n    </thead>\n    <tbody>\n        <tr>\n            <td rowspan=\"4\">Engineering</td>\n            <td rowspan=\"3\">Computer Science</td>\n            <td>CS101</td>\n            <td>Kim</td>\n            <td rowspan=\"2\">3</td>\n        </tr>\n        <tr>\n            <td>CS201</td>\n            <td rowspan=\"2\">Garcia</td>\n        </tr>\n        <tr>\n            <td>CS303</td>\n            <td>2</td>\n        </tr>\n        <tr>\n            <td>Electrical Engineering</td>\n            <td>EE101</td>\n            <td>Müller</td>\n            <td>3</td>\n        </tr>\n        <tr>\n            <td rowspan=\"2\">Social Science</td>\n            <td rowspan=\"2\">Economics</td>\n            <td>EC101</td>\n            <td>Nguyen</td>\n            <td rowspan=\"2\">3</td>\n        </tr>\n        <tr>\n            <td>EC401</td>\n            <td>Smith</td>\n        </tr>\n    </tbody>\n</table>\n\n\n```json\n[\n    {\n        \"Department\": \"Engineering\",\n        \"Major\": \"Computer Science\",\n        \"Class\": \"CS101\",\n        \"Instructor\": \"Kim\",\n        \"Credit\": \"3\"\n    },\n    {\n        \"Department\": \"Engineering\",\n        \"Major\": \"Computer Science\",\n        \"Credit\": \"3\",\n        \"Class\": \"CS201\",\n        \"Instructor\": \"Garcia\"\n    },\n    {\n        \"Department\": \"Engineering\",\n        \"Major\": \"Computer Science\",\n        \"Instructor\": \"Garcia\",\n        \"Class\": \"CS303\",\n        \"Credit\": \"2\"\n    },\n    {\n        \"Department\": \"Engineering\",\n        \"Major\": \"Electrical Engineering\",\n        \"Class\": \"EE101\",\n        \"Instructor\": \"Müller\",\n        \"Credit\": \"3\"\n    },\n    {\n        \"Department\": \"Social Science\",\n        \"Major\": \"Economics\",\n        \"Class\": \"EC101\",\n        \"Instructor\": \"Nguyen\",\n        \"Credit\": \"3\"\n    },\n    {\n        \"Department\": \"Social Science\",\n        \"Major\": \"Economics\",\n        \"Credit\": \"3\",\n        \"Class\": \"EC401\",\n        \"Instructor\": \"Smith\"\n    }\n]\n```\n\n### Tables with headings in the first column\n\nIf a table contains headings in the first column you might get an unexpected\nresult, but you can pass a second argument with options with\n`{ useFirstRowForHeadings: true }` to have it treat the first column as it would\nany other cell.\n\n``` javascript\ntabletojson.convertUrl(\n  'https://www.timeanddate.com/holidays/ireland/2017',\n  { useFirstRowForHeadings: true },\n  function(tablesAsJson) {\n    console.log(tablesAsJson);\n  }\n);\n```\n\n### Tables with HTML\n\nThe following options are true by default, which converts all values to plain\ntext to give you an easier more readable object to work with:\n\n* stripHtmlFromHeadings\n* stripHtmlFromCells\n\nIf your table contains HTML you want to parse (for example for links) you can\nset `stripHtmlFromCells` to `false` to treat it as raw text.\n\n``` javascript\ntabletojson.convertUrl(\n  'https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes',\n  { stripHtmlFromCells: false },\n  function(tablesAsJson) {\n    //Print out the 1st row from the 2nd table on the above webpage as JSON\n    console.log(tablesAsJson[1][0]);\n  }\n);\n```\n\nNote: This doesn't work with nested tables, which it will still try to parse.\n\nYou probably don't need to set `stripHtmlFromHeadings` to `false` (and setting\nit to false can make the results hard to parse), but if you do you can also set\nboth at the same time by setting `stripHtml` to `false`.\n\n### Tables with complex headers\n\nUse the following rows as keys in the output json object. The values are flattened and concatenated the values with 'concatWith' [default=undefined]\n\nInput:\n\n<table id=\"table15\" class=\"table\" style=\"border:solid\">\n    <tbody>\n    <tr>\n        <td rowspan=\"3\">Industry</td>\n        <td colspan=\"3\">Operating income</td>\n        <td colspan=\"3\">Operating costs</td>\n        <td colspan=\"3\">Total profit</td>\n    </tr>\n    <tr>\n        <td colspan=\"2\">amount (billion)</td>\n        <td rowspan=\"2\">Year-over-year growth (%)</td>\n        <td colspan=\"2\">amount (billion)</td>\n        <td rowspan=\"2\">Year-over-year growth (%)</td>\n        <td colspan=\"2\">amount (billion)</td>\n        <td rowspan=\"2\">Year-over-year growth (%)</td>\n    </tr>\n    <tr>\n        <td>$</td>\n        <td>€<sup>*</sup></td>\n        <td>$</td>\n        <td>€<sup>*</sup></td>\n        <td>$</td>\n        <td>€<sup>*</sup></td>\n    </tr>\n    <tr>\n        <td>total</td>\n        <td>843280,70</td>\n        <td>758952,63</td>\n        <td>-0,30</td>\n        <td>718255,00</td>\n        <td>646429,50</td>\n        <td>0,20</td>\n        <td>46558,20</td>\n        <td>41902,38</td>\n        <td>-11,70</td>\n    </tr>\n    <tr>\n        <td>Coal mining and washing industry</td>\n        <td>22937,30</td>\n        <td>20643,57</td>\n        <td>-13,90</td>\n        <td>14653,70</td>\n        <td>13188,33</td>\n        <td>-7,50</td>\n        <td>5236,90</td>\n        <td>4713,21</td>\n        <td>-26,30</td>\n    </tr>\n    <tr>\n        <td>Oil and gas extraction</td>\n        <td>7605,10</td>\n        <td>6844,59</td>\n        <td>-9,60</td>\n        <td>3863,60</td>\n        <td>3477,24</td>\n        <td>0,10</td>\n        <td>2592,70</td>\n        <td>2333,43</td>\n        <td>-10,80</td>\n    </tr>\n    <tr>\n        <td>Ferrous metal mining and dressing industry</td>\n        <td>3010,70</td>\n        <td>2709,63</td>\n        <td>-4,40</td>\n        <td>2369,10</td>\n        <td>2132,19</td>\n        <td>-4,10</td>\n        <td>326,60</td>\n        <td>293,94</td>\n        <td>-23,80</td>\n    </tr>\n    <tr>\n        <td>Non-ferrous metal mining and dressing industry</td>\n        <td>2180,90</td>\n        <td>1962,81</td>\n        <td>-0,30</td>\n        <td>1394,30</td>\n        <td>1254,87</td>\n        <td>-2,50</td>\n        <td>512,10</td>\n        <td>460,89</td>\n        <td>4,00</td>\n    </tr>\n    <tr>\n        <td>Non-metallic ore mining and dressing industry</td>\n        <td>2244,70</td>\n        <td>2020,23</td>\n        <td>-5,70</td>\n        <td>1612,00</td>\n        <td>1450,80</td>\n        <td>-5,70</td>\n        <td>236,10</td>\n        <td>212,49</td>\n        <td>-7,00</td>\n    </tr>\n    <tr>\n        <td>Mining professional and ancillary activities</td>\n        <td>1537,30</td>\n        <td>1383,57</td>\n        <td>12,70</td>\n        <td>1453,70</td>\n        <td>1308,33</td>\n        <td>11,80</td>\n        <td>2,60</td>\n        <td>2,34</td>\n        <td>-77,00</td>\n    </tr>\n    <tr>\n        <td colspan=\"10\">\n            Note: Some indicators in this table have a situation where the total is not equal to the sum of the sub-items, which is due to rounding of the data and has not been mechanically adjusted.<br>\n            <sup>*</sup> Conversion rate: 1$=0,9€\n        </td>\n    </tr>\n</table>\n\nOutput:\n\n```json\n[\n    {\n        \"Industry\": \"total\",\n        \"Operating income amount (billion) $\": \"843280,70\",\n        \"Operating income amount (billion) €*\": \"758952,63\",\n        \"Operating income Year-over-year growth (%)\": \"-0,30\",\n        \"Operating costs amount (billion) $\": \"718255,00\",\n        \"Operating costs amount (billion) €*\": \"646429,50\",\n        \"Operating costs Year-over-year growth (%)\": \"0,20\",\n        \"Total profit amount (billion) $\": \"46558,20\",\n        \"Total profit amount (billion) €*\": \"41902,38\",\n        \"Total profit Year-over-year growth (%)\": \"-11,70\"\n    },\n    {\n        \"Industry\": \"Coal mining and washing industry\",\n        \"Operating income amount (billion) $\": \"22937,30\",\n        \"Operating income amount (billion) €*\": \"20643,57\",\n        \"Operating income Year-over-year growth (%)\": \"-13,90\",\n        \"Operating costs amount (billion) $\": \"14653,70\",\n        \"Operating costs amount (billion) €*\": \"13188,33\",\n        \"Operating costs Year-over-year growth (%)\": \"-7,50\",\n        \"Total profit amount (billion) $\": \"5236,90\",\n        \"Total profit amount (billion) €*\": \"4713,21\",\n        \"Total profit Year-over-year growth (%)\": \"-26,30\"\n    },\n    {\n        \"Industry\": \"Oil and gas extraction\",\n        \"Operating income amount (billion) $\": \"7605,10\",\n        \"Operating income amount (billion) €*\": \"6844,59\",\n        \"Operating income Year-over-year growth (%)\": \"-9,60\",\n        \"Operating costs amount (billion) $\": \"3863,60\",\n        \"Operating costs amount (billion) €*\": \"3477,24\",\n        \"Operating costs Year-over-year growth (%)\": \"0,10\",\n        \"Total profit amount (billion) $\": \"2592,70\",\n        \"Total profit amount (billion) €*\": \"2333,43\",\n        \"Total profit Year-over-year growth (%)\": \"-10,80\"\n    },\n    {\n        \"Industry\": \"Ferrous metal mining and dressing industry\",\n        \"Operating income amount (billion) $\": \"3010,70\",\n        \"Operating income amount (billion) €*\": \"2709,63\",\n        \"Operating income Year-over-year growth (%)\": \"-4,40\",\n        \"Operating costs amount (billion) $\": \"2369,10\",\n        \"Operating costs amount (billion) €*\": \"2132,19\",\n        \"Operating costs Year-over-year growth (%)\": \"-4,10\",\n        \"Total profit amount (billion) $\": \"326,60\",\n        \"Total profit amount (billion) €*\": \"293,94\",\n        \"Total profit Year-over-year growth (%)\": \"-23,80\"\n    },\n    {\n        \"Industry\": \"Non-ferrous metal mining and dressing industry\",\n        \"Operating income amount (billion) $\": \"2180,90\",\n        \"Operating income amount (billion) €*\": \"1962,81\",\n        \"Operating income Year-over-year growth (%)\": \"-0,30\",\n        \"Operating costs amount (billion) $\": \"1394,30\",\n        \"Operating costs amount (billion) €*\": \"1254,87\",\n        \"Operating costs Year-over-year growth (%)\": \"-2,50\",\n        \"Total profit amount (billion) $\": \"512,10\",\n        \"Total profit amount (billion) €*\": \"460,89\",\n        \"Total profit Year-over-year growth (%)\": \"4,00\"\n    },\n    {\n        \"Industry\": \"Non-metallic ore mining and dressing industry\",\n        \"Operating income amount (billion) $\": \"2244,70\",\n        \"Operating income amount (billion) €*\": \"2020,23\",\n        \"Operating income Year-over-year growth (%)\": \"-5,70\",\n        \"Operating costs amount (billion) $\": \"1612,00\",\n        \"Operating costs amount (billion) €*\": \"1450,80\",\n        \"Operating costs Year-over-year growth (%)\": \"-5,70\",\n        \"Total profit amount (billion) $\": \"236,10\",\n        \"Total profit amount (billion) €*\": \"212,49\",\n        \"Total profit Year-over-year growth (%)\": \"-7,00\"\n    },\n    {\n        \"Industry\": \"Mining professional and ancillary activities\",\n        \"Operating income amount (billion) $\": \"1537,30\",\n        \"Operating income amount (billion) €*\": \"1383,57\",\n        \"Operating income Year-over-year growth (%)\": \"12,70\",\n        \"Operating costs amount (billion) $\": \"1453,70\",\n        \"Operating costs amount (billion) €*\": \"1308,33\",\n        \"Operating costs Year-over-year growth (%)\": \"11,80\",\n        \"Total profit amount (billion) $\": \"2,60\",\n        \"Total profit amount (billion) €*\": \"2,34\",\n        \"Total profit Year-over-year growth (%)\": \"-77,00\"\n    },\n    {\n        \"Industry\": \"Note: Some indicators in this table have a situation where the total is not equal to the sum of the sub-items, which is due to rounding of the data and has not been mechanically adjusted.\\n            * Conversion rate: 1$=0,9€\"\n    }\n]\n```\n\n\n## Options\n\n### fetchOptions (only `convertUrl`)\n\nTabletojson is using fetch api which is available in node from version 17.5.0 onwards to fetch remote HTML pages. See\n[mdn web docs on fetch](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API) for more information. The usage of\nTabletojson should now be the same in node as in browsers.\nSo if you need to get data from a remote server you can call `tabletojson.convertUrl` and pass any\nfetch-options (proxy, headers,...) by adding a RequestInit object to the options\npassed to `convertUrl`. For more information on how to configure request please\nhave a look at [Browser Syntax](https://developer.mozilla.org/en-US/docs/Web/API/fetch#syntax) or [Node fetch](https://nodejs.org/en/blog/announcements/v18-release-announce#fetch-experimental)\n\n``` javascript\ntabletojson.convertUrl('https://www.timeanddate.com/holidays/ireland/2017', {\n    useFirstRowForHeadings: true,\n    fetchOptions: {\n        ...\n    }\n});\n```\n\n### headers\nDefine the rows to be used as keys in the output json object. The values will be concatenated with the given concatWith value. [default=undefined]\n``` javascript\nconst html = fs.readFileSync(path.resolve(process.cwd(), '../test/tables.html'), {\n    encoding: 'utf-8',\n});\nconst converted = tabletojson.convert(html, {\n    id: ['table15'],\n\n    // from (Optional) Start row [default=0]\n    // to End row\n    // concatWith Concatenate the values with this string\n\n    headers: {\n        to: 2,\n        concatWith: ' ',\n    },\n});\nconsole.log(JSON.stringify(converted, null, 2));\n```\n\n\n\n### stripHtmlFromHeadings\n\nStrip any HTML from heading cells. Default is true.\n\n```md\n||KEY || <b>VALUE</b><||\n|-----|----------------|\n| abc |              1 |\n| dev |              2 |\n```\n\nExample output with stripHtmlFromHeadings:true\n```json\n[\n    {\n        \"KEY\": \"abc\", \"VALUE\": \"1\"\n    },\n    {\n        \"KEY\": \"dev\", \"VALUE\": \"2\"\n    }\n]\n```\nExample output with stripHtmlFromHeadings:false\n```json\n[\n    {\n        \"KEY\": \"abc\", \"<b>VALUE</b>\": \"1\"\n    },\n    {\n        \"KEY\": \"dev\", \"<b>VALUE</b>\": \"2\"\n    }\n]\n```\n\n### stripHtmlFromCells\n\nStrip any HTML from tableBody cells. Default is true.\n\n```md\n||KEY ||    VALUE||\n|-----|-----------|\n|abc  |   <i>1</i>|\n|dev  |   <i>2</i>|\n```\n\nExample output with stripHtmlFromHeadings:true\n```json\n[\n    {\n        \"KEY\": \"abc\", \"VALUE\": \"1\"\n    },\n    {\n        \"KEY\": \"dev\", \"VALUE\": \"2\"\n    }\n]\n```\nExample output with stripHtmlFromHeadings:false\n```json\n[\n    {\n        \"KEY\": \"abc\", \"VALUE\": \"<i>1</i>\"\n    },\n    {\n        \"KEY\": \"dev\", \"VALUE\": \"<i>2</i>\"\n    }\n]\n```\n\n### forceIndexAsNumber\n\nInstead of using column text (that sometime re-order the data), force an index as a number (string number).\n\n```json\n{\n  \"0\": \"\",\n  \"1\": \"Ａ会\",\n  \"2\": \"Ｂ会\",\n  \"3\": \"Ｃ会\",\n  \"4\": \"Something\",\n  \"5\": \"Else\",\n  \"6\": \"\"\n}\n```\n\n### countDuplicateHeadings\n\nDefault is `true`. If set to `false`, duplicate headings will not get a trailing\nnumber. The value of the field will be the last value found in the table row:\n```md\n||PLACE || VALUE || PLACE || VALUE||\n|-------|--------|--------|--------|\n|   abc |      1 |    def |     2  |\n|   ghi |      3 |    jkl |     4  |\n```\nExample output with countDuplicateHeadings:false\n```json\n[\n    {\n        \"PLACE\": \"def\", \"VALUE\": \"2\"\n    },\n    {\n        \"PLACE\": \"jkl\", \"VALUE\": \"4\"\n    }\n]\n```\n\n### ignoreColumns\n\nArray of indexes to be ignored, starting with 0. Default is 'null/undefined'.\n```md\n|| NAME || PLACE || WEIGHT || SEX || AGE ||\n|-------|--------|---------|------|-------|\n| Mel   |      1 |      58 |    W |  23   |\n| Bill  |      3 |      92 |    M |  31   |\n| Tom   |      2 |      78 |    M |  54   |\n```\nExample output with ignoreColumns: [2, 3]\n```json\n[\n    {\n        \"NAME\": \"Mel\", \"PLACE\": \"1\", \"AGE\": \"23\"\n    },\n    {\n        \"NAME\": \"Tom\", \"PLACE\": \"2\", \"AGE\": \"54\"\n    },\n    {\n        \"NAME\": \"Bill\", \"PLACE\": \"3\", \"AGE\": \"31\"\n    }\n]\n```\n\n### onlyColumns\n\nArray of indexes that are taken, starting with 0. Default is 'null/undefined'.\nIf given, this option overrides ignoreColumns.\n```md\n|| NAME || PLACE || WEIGHT || SEX || AGE ||\n|-------|--------|---------|------|-------|\n| Mel   |      1 |      58 |    W |     23|\n| Tom   |      2 |      78 |    M |     54|\n| Bill  |      3 |      92 |    M |     31|\n```\nExample output with onlyColumns: [0, 4]\n```json\n[\n    {\n        \"NAME\": \"Mel\", \"AGE\": \"23\"\n    },\n    {\n        \"NAME\": \"Tom\", \"AGE\": \"54\"\n    },\n    {\n        \"NAME\": \"Bill\", \"AGE\": \"31\"\n    }\n]\n```\n\n### ignoreHiddenRows\n\nIndicates if hidden rows (display:none) are ignored. Default is true:\n```md\n|| NAME || PLACE || WEIGHT || SEX || AGE ||\n|-------|--------|---------|------|-------|\n| Mel   |      1 |      58 |    W |     23|\n| Tom   |      2 |      78 |    M |     54|\n| Bill  |      3 |      92 |    M |     31|\n|* Cat  |      4 |       4 |    W |     2*|\n```\nExample output with ignoreHiddenRows:true\n```json\n[\n  {\n    \"NAME\":\"Mel\",\n    \"PLACE\":\"1\",\n    \"WEIGHT\":\"58\",\n    \"SEX\":\"W\",\n    \"AGE\":\"23\"\n  },\n  {\n    \"NAME\":\"Tom\",\n    \"PLACE\":\"2\",\n    \"WEIGHT\":\"78\",\n    \"SEX\":\"M\",\n    \"AGE\":\"54\"\n  },\n  {\n    \"NAME\":\"Bill\",\n    \"PLACE\":\"3\",\n    \"WEIGHT\":\"92\",\n    \"SEX\":\"M\",\n    \"AGE\":\"31\"\n  }\n]\n```\nExample output with ignoreHiddenRows:false\n```json\n[\n  {\n    \"NAME\":\"Mel\",\n    \"PLACE\":\"1\",\n    \"WEIGHT\":\"58\",\n    \"SEX\":\"W\",\n    \"AGE\":\"23\"\n  },\n  {\n    \"NAME\":\"Tom\",\n    \"PLACE\":\"2\",\n    \"WEIGHT\":\"78\",\n    \"SEX\":\"M\",\n    \"AGE\":\"54\"\n  },\n  {\n    \"NAME\":\"Bill\",\n    \"PLACE\":\"3\",\n    \"WEIGHT\":\"92\",\n    \"SEX\":\"M\",\n    \"AGE\":\"31\"\n  },\n  {\n    \"NAME\":\"Cat\",\n    \"PLACE\":\"4\",\n    \"WEIGHT\":\"4\",\n    \"SEX\":\"W\",\n    \"AGE\":\"2\"\n  }\n]\n```\n\n### headings\n\nArray of Strings to be used as headings. Default is `null`/`undefined`.\n\nIf more headings are given than columns exist the overcounting ones will be ignored. If less headings\nare given than existing values the overcounting values are ignored.\n```md\n|| NAME || PLACE || WEIGHT || SEX || AGE ||\n|-------|--------|---------|------|-------|\n| Mel   |      1 |      58 |    W |     23|\n| Tom   |      2 |      78 |    M |     54|\n| Bill  |      3 |      92 |    M |     31|\n|* Cat  |      4 |       4 |    W |     2*|\n```\nExample output with headings: ['A','B','C','D','E']\n```json\n[\n  {\n    \"A\":\"Mel\",\n    \"B\":\"1\",\n    \"C\":\"58\",\n    \"D\":\"W\",\n    \"E\":\"23\"\n  },\n  {\n    \"A\":\"Tom\",\n    \"B\":\"2\",\n    \"C\":\"78\",\n    \"D\":\"M\",\n    \"E\":\"54\"\n  },\n  {\n    \"A\":\"Bill\",\n    \"B\":\"3\",\n    \"C\":\"92\",\n    \"D\":\"M\",\n    \"E\":\"31\"\n  }\n]\n```\nExample output with headings: ['A','B','C']\n```json\n[\n  {\n    \"A\":\"Mel\",\n    \"B\":\"1\",\n    \"C\":\"58\"\n  },\n  {\n    \"A\":\"Tom\",\n    \"B\":\"2\",\n    \"C\":\"78\"\n  },\n  {\n    \"A\":\"Bill\",\n    \"B\":\"3\",\n    \"C\":\"92\"\n  }\n]\n```\nExample output with headings: ['A','B','C','D','E','F','G','H']\n```json\n[\n  {\n    \"A\":\"Mel\",\n    \"B\":\"1\",\n    \"C\":\"58\",\n    \"D\":\"W\",\n    \"E\":\"23\"\n  },\n  {\n    \"A\":\"Tom\",\n    \"B\":\"2\",\n    \"C\":\"78\",\n    \"D\":\"M\",\n    \"E\":\"54\"\n  },\n  {\n    \"A\":\"Bill\",\n    \"B\":\"3\",\n    \"C\":\"92\",\n    \"D\":\"M\",\n    \"E\":\"31\"\n  }\n]\n```\nExample output with headings: ['A','B','C'] && ignoreColumns: [2, 3]\n```json\n[\n  {\n    \"A\":\"Mel\",\n    \"B\":\"W\",\n    \"C\":\"23\"\n  },\n  {\n    \"A\":\"Tom\",\n    \"B\":\"M\",\n    \"C\":\"54\"\n  },\n  {\n    \"A\":\"Bill\",\n    \"B\":\"M\",\n    \"C\":\"31\"\n  }\n]\n```\n\n### limitrows\n\nNumber of rows to which the resulting object should be limited to. Default is\n`null`/`undefined`.\n\n#### Huge Table (see test/tables.html)\n```md\n|| Roleplayer Number || Name            || Text to say||\n|--------------------|------------------|--------------|\n| 0                  | Raife Parkinson  | re dolor in hendrerit in vulputate ve|\n| 1                  | Hazel Schultz    | usto duo dolores et ea rebum. Ste|\n| 2                  | Montana Delgado  | psum dolor sit amet. Lorem ipsum dolor|\n| 3                  | Dianne Mcbride   | sit ame olor sit amet. Lorem ipsum|\n| 4                  | Xena Lynch       | us est Lorem ipsum dol|\n| 5                  | Najma Holding    | akimata sanctus est Lorem ipsum dolor sit|\n| 6                  | Kiki House       | ame nvidunt ut|\n|...|\n|197                 | Montana Delgado  | lores et ea rebum. Stet clita kasd gu a|\n|198                 | Myrtle Conley    | rebum. Stet clita kasd gubergren, no sea|\n|199                 | Hanna Ellis      | kimata sanctus est Lorem ipsum dolor si|\n```\n#### Example output with limitrows: 5\n\n```json\n[\n  {\n    \"Roleplayer Number\":\"0\",\n    \"Name\":\"Raife Parkinson\",\n    \"Text to say\":\"re dolor in hendrerit in vulputate ve\"\n  },\n  {\n    \"Roleplayer Number\":\"1\",\n    \"Name\":\"Hazel Schultz\",\n    \"Text to say\":\"usto duo dolores et ea rebum. Ste\"\n  },\n  {\n    \"Roleplayer Number\":\"2\",\n    \"Name\":\"Montana Delgado\",\n    \"Text to say\":\"psum dolor sit amet. Lorem ipsum dolor sit ame\"\n  },\n  {\n    \"Roleplayer Number\":\"3\",\n    \"Name\":\"Dianne Mcbride\",\n    \"Text to say\":\"olor sit amet. Lorem ipsum\"\n  },\n  {\n    \"Roleplayer Number\":\"4\",\n    \"Name\":\"Xena Lynch\",\n    \"Text to say\":\"us est Lorem ipsum dol\"\n  }\n]\n```\n\n### containsClasses\n\nArray of classes to find a specific table using this class. Default is `null`/\n`undefined`.\n\n## Known issues and limitations\n\n* Tables needs to be \"well formatted\" to be convertable.\n* Tables in tables are not processed.\n* Only supports parsing basic tables with horizontal set of\n`<th></th>` headings and corresponding `<td></td>` cells, but also \ntaking care of rowspan and colspan. It can give useless or weird results \non tables that have complex structures\n(such as nested tables) or multiple headers (such as on both X and Y axis).\n* You'll need to handle tables to parse and (in most cases) clean up the data. \nYou might want to combine it with modules like json2csv or CsvToMarkdownTable.\n* You might want to use it with a module like 'cheerio' if you want to parse\nspecific tables identified by id or class (i.e. select them with cheerio and\npass the HTML of them as a string).\n\n## Usage\n\nFind here a list of examples on how to use the library. More examples can be found in the examples folder or \nin the test folder\n\n### Convert an HTML text into an array of all the tables on the page\n```typescript\nimport {tabletojson} from 'tabletojson';\nconst tablesAsJson = tabletojson.convert(html);\nconst firstTableAsJson = tablesAsJson[0];\nconst secondTableAsJson = tablesAsJson[1];\n```\n\n### Fetch a URL and parse all it's tables into JSON, using a callback\n```typescript\nimport {tabletojson} from 'tabletojson';\ntabletojson.convertUrl('https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes', function (tablesAsJson) {\n  console.log(tablesAsJson[1]);\n});\n```\n\n### Fetch a URL and parse all it's tables into JSON, using promises\n\n```typescript\nimport {tabletojson} from 'tabletojson';\nconst url = 'http://en.wikipedia.org/wiki/List_of_countries_by_credit_rating';\ntabletojson.convertUrl(url)\n.then(function(tablesAsJson) {\n  const standardAndPoorRatings = tablesAsJson[1];\n  const fitchRatings = tablesAsJson[2];\n});\n```\n### Fetch a table from Wikipedia and combine with json2csv to convert to CSV\n```typescript\nimport {tabletojson} from 'tabletojson';\nimport {Parser} from 'json2csv';\nconst url = 'http://en.wikipedia.org/wiki/List_of_countries_by_credit_rating';\ntabletojson.convertUrl(url).then(function (tablesAsJson) {\n  const fitchRatings = tablesAsJson[2];\n  const json2csvParser = new Parser({\n    fields: ['Country/Region', 'Outlook'],\n  });\n  const csv = json2csvParser.parse(fitchRatings);\n  console.log(csv);\n  /* Example output\n        \"Country/Region\",\"Outlook\"\n        \"Abu Dhabi, UAE\",\"Stable\"\n        \"Albania\",\"Stable\"\n        \"Andorra\",\"Negative\"\n        \"Angola\",\"Stable\"\n        \"Argentina\",\"Negative\"\n        \"Aruba\",\"Stable\"\n        \"Australia\",\"Stable\"\n        \"Austria\",\"Negative\"\n        \"Azerbaijan\",\"Positive\"\n        ...\n      */\n});\n```\n\n## Contributing\n\nImprovements, fixes and suggestions are welcome.\n\nYou can find basic tests in the test folder. The library has been implemented \nto be used straight forward way. Nonetheless there are some edge cases that\nneed to be tested and I would like to ask for support here. Feel free to fork\nand create PRs here. Every bit of help is appreciated.\n\nFor more usage examples have a look in the examples folder that shows usage and would be a good start.\n\nIf you submit a pull request, please add an example for your use case, so I can\nunderstand what you want it to do (as I want to get around to writing tests for\nthis and want to understand the sort of use cases people have).\n\n### Contributors\n\n* Marius Augenstein (@maugenst)\n* Iain Collins (@iaincollins)\n* Rory O'Kelly (@roryok)\n* Nordes Ménard-Lamarre (@Nordes)\n* Max Thyen (@maxthyen)\n* Thor Jacobsen (@twjacobsen)\n* Michael Keller (@mhkeller)\n* Jesús Leganés-Combarro (@piranna)\n* João Otávio Ferreira Barbosa (@joaobarbosa)\n* Stefano Fadda (@StefanoF)\n* Michael Telatynski (@t3chguy)\n* @mherzhoff\n* Dooho Hyung (@dooho-h)\n","readmeFilename":"README.md","users":{"dees":true,"rurri":true,"sedmonds":true,"shubham54":true,"danielo515":true,"jugaltheshah":true,"diegorbaquero":true,"nimblemachine":true,"flaviomarcioti":true}}