[Data literate][m]: Copy and refactor data-literate into minimal template folder
This commit is contained in:
41
examples/data-literate-template/components/DataLiterate.js
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41
examples/data-literate-template/components/DataLiterate.js
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import Layout from './Layout'
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import Head from 'next/head'
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import Excel from './Excel'
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import Table from './Table'
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import TableGrid from './TableGrid'
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import LineChart from './LineChart'
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import MetaData from './Metadata'
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import { MDXProvider } from '@mdx-js/react'
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import { Vega, VegaLite } from 'react-vega'
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// Custom components/renderers to pass to MDX.
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// Since the MDX files aren't loaded by webpack, they have no knowledge of how
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// to handle import statements. Instead, you must include components in scope
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// here.
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const components = {
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Table,
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Excel,
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Vega,
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VegaLite,
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LineChart,
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Head,
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TableGrid,
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MetaData,
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}
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export default function DataLiterate({ children }) {
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const { Component, pageProps } = children
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return (
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<Layout>
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<main>
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<MDXProvider components={components}>
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<div className="prose mx-auto">
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<Component {...pageProps} />
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</div>
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</MDXProvider>
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</main>
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</Layout>
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)
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}
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74
examples/data-literate-template/components/Excel.js
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74
examples/data-literate-template/components/Excel.js
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import axios from 'axios'
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import XLSX from 'xlsx'
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import React, { useEffect, useState } from 'react'
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import Table from './Table'
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export default function Excel ({ src='' }) {
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const [data, setData] = React.useState([])
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const [cols, setCols] = React.useState([])
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const [workbook, setWorkbook] = React.useState(null)
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const [error, setError] = React.useState('')
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const [hasMounted, setHasMounted] = React.useState(0)
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// so this is here so we re-render this in the browser
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// and not just when we build the page statically in nextjs
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useEffect(() => {
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if (hasMounted==0) {
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handleUrl(src)
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}
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setHasMounted(1)
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})
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function handleUrl(url) {
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// if url is external may have CORS issue so we proxy it ...
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if (url.startsWith('http')) {
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const PROXY_URL = window.location.origin + '/api/proxy'
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url = PROXY_URL + '?url=' + encodeURIComponent(url)
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}
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axios.get(url, {
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responseType: 'arraybuffer'
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}).then((res) => {
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let out = new Uint8Array(res.data)
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let workbook = XLSX.read(out, {type: "array"})
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// Get first worksheet
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const wsname = workbook.SheetNames[0]
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const ws = workbook.Sheets[wsname]
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// Convert array of arrays
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const datatmp = XLSX.utils.sheet_to_json(ws, {header:1})
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const colstmp = make_cols(ws['!ref'])
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setData(datatmp)
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setCols(colstmp)
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setWorkbook(workbook)
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}).catch((e) => {
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setError(e.message)
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})
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}
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return (
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<>
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{error &&
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<div>
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There was an error loading the excel file at {src}:
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<p>{error}</p>
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</div>
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}
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{workbook &&
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<ul>
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{workbook.SheetNames.map((value, index) => {
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return <li key={index}>{value}</li>
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})}
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</ul>
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}
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<Table data={data} cols={cols} />
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</>
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)
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}
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/* generate an array of column objects */
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const make_cols = refstr => {
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let o = [], C = XLSX.utils.decode_range(refstr).e.c + 1
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for(var i = 0; i < C; ++i) o[i] = {name:XLSX.utils.encode_col(i), key:i}
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return o
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}
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29
examples/data-literate-template/components/Layout.js
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29
examples/data-literate-template/components/Layout.js
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import Link from 'next/link'
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import Head from 'next/head'
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export default function Layout({ children, title = 'Home' }) {
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return (
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<>
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<Head>
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<title>Portal.JS - {title}</title>
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<link rel="icon" href="/favicon.ico" />
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<meta charSet="utf-8" />
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<meta name="viewport" content="initial-scale=1.0, width=device-width" />
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</Head>
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<div className="mx-auto p-6">
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{children}
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</div>
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<footer className="flex items-center justify-center w-full h-24 border-t">
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<a
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className="flex items-center justify-center"
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href="https://datopian.com/"
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target="_blank"
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rel="noopener noreferrer"
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>
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Built by{' '}
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<img src="/datopian-logo.png" alt="Datopian Logo" className="h-6 ml-2" />
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</a>
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</footer>
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</>
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)
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}
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33
examples/data-literate-template/components/LineChart.js
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33
examples/data-literate-template/components/LineChart.js
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import { Vega, VegaLite } from 'react-vega'
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export default function LineChart( { data=[] }) {
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var tmp = data
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if (Array.isArray(data)) {
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tmp = data.map((r,i) => {
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return { x: r[0], y: r[1] }
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})
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}
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const vegaData = { "table": tmp }
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const spec = {
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"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
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"mark": "line",
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"data": {
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"name": "table"
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},
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"encoding": {
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"x": {
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"field": "x",
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"timeUnit": "year",
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"type": "temporal"
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},
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"y": {
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"field": "y",
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"type": "quantitative"
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}
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}
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}
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return (
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<VegaLite data={ vegaData } spec={ spec } />
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)
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}
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18
examples/data-literate-template/components/Metadata.js
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18
examples/data-literate-template/components/Metadata.js
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export default function MetaData({ title, author, description }) {
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return (
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<header>
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<div className="mb-6">
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<h1>{title}</h1>
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{author && (
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<div className="-mt-6"><p className="opacity-60 pl-1">{author}</p></div>
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)}
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{description && (
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<p className="description">{description}</p>
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)}
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</div>
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</header>
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)
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}
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83
examples/data-literate-template/components/Table.js
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83
examples/data-literate-template/components/Table.js
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import axios from 'axios'
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import React, { useEffect, useState } from 'react'
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const papa = require("papaparse")
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/*
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Simple HTML Table
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usage: <OutTable data={data} cols={cols} />
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data:Array<Array<any> >;
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cols:Array<{name:string, key:number|string}>;
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*/
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export default function Table({ data=[], cols=[], csv='', url='' }) {
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if (csv) {
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const out = parseCsv(csv)
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data = out.rows
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cols = out.cols
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}
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const [ourdata, setData] = React.useState(data)
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const [ourcols, setCols] = React.useState(cols)
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const [error, setError] = React.useState('')
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useEffect(() => {
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if (url) {
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loadUrl(url)
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}
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}, [url])
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function loadUrl(path) {
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// HACK: duplicate of Excel code - maybe refactor
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// if url is external may have CORS issue so we proxy it ...
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if (url.startsWith('http')) {
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const PROXY_URL = window.location.origin + '/api/proxy'
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url = PROXY_URL + '?url=' + encodeURIComponent(url)
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}
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axios.get(url).then((res) => {
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const { rows, fields } = parseCsv(res.data)
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setData(rows)
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setCols(fields)
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})
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}
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return (
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<>
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<SimpleTable data={ourdata} cols={ourcols} />
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</>
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)
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}
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/*
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Simple HTML Table
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usage: <OutTable data={data} cols={cols} />
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data:Array<Array<any> >;
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cols:Array<{name:string, key:number|string}>;
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*/
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function SimpleTable({ data=[], cols=[] }) {
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return (
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<div className="table-responsive">
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<table className="table table-striped">
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<thead>
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<tr>{cols.map((c) => <th key={c.key}>{c.name}</th>)}</tr>
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</thead>
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<tbody>
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{data.map((r,i) => <tr key={i}>
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{cols.map(c => <td key={c.key}>{ r[c.key] }</td>)}
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</tr>)}
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</tbody>
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</table>
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</div>
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)
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}
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function parseCsv(csv) {
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csv = csv.trim()
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const rawdata = papa.parse(csv, {header: true})
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const cols = rawdata.meta.fields.map((r,i) => {
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return { key: r, name: r }
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})
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return {
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rows: rawdata.data,
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fields: cols
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}
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}
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81
examples/data-literate-template/components/TableGrid.js
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81
examples/data-literate-template/components/TableGrid.js
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import axios from 'axios'
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import React, { useEffect } from 'react'
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import { Table } from 'portal'
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const papa = require("papaparse")
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/*
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Portaljs Table Grid
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usage: <TableGrid url="" data={data} cols={cols} csv="" />
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*/
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export default function TableGrid({ data = [], cols = [], csv = '', url = '' }) {
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if (csv) {
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const out = parseCsv(csv)
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data = prepareRowsForPortalJsTable(out.rows)
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cols = out.fields
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}
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if (cols) {
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cols = prepareColsForPortalJsTable(cols)
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}
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const [ourdata, setData] = React.useState(data)
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const [ourcols, setCols] = React.useState(cols)
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useEffect(() => {
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if (url) {
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loadUrl(url)
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}
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}, [url])
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function loadUrl(path) {
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// HACK: duplicate of Excel code - maybe refactor
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// if url is external may have CORS issue so we proxy it ...
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if (url.startsWith('http')) {
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const PROXY_URL = window.location.origin + '/api/proxy'
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url = PROXY_URL + '?url=' + encodeURIComponent(url)
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}
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axios.get(url).then((res) => {
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const { rows, fields } = parseCsv(res.data)
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setData(rows)
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setCols(prepareColsForPortalJsTable(fields))
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})
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}
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return (
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<div>
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<Table columns={ourcols} data={ourdata} height={"400px"} />
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</div>
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)
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}
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function prepareColsForPortalJsTable(cols) {
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return cols.map((col) => {
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return {
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field: col.key,
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headerName: col.name,
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flex: true
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}
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})
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}
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function prepareRowsForPortalJsTable(rows) {
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return rows.map((r) => {
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return {
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...r,
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id: r.id || r.key
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}
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})
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}
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function parseCsv(csv) {
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csv = csv.trim()
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const rawdata = papa.parse(csv, { header: true })
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const cols = rawdata.meta.fields.map((r, i) => {
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return { key: r, name: r }
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})
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return {
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rows: rawdata.data,
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fields: cols
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}
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}
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