echarts
Altair
echarts | Altair | |
---|---|---|
18 | 43 | |
59,130 | 8,972 | |
0.8% | 1.3% | |
8.7 | 9.0 | |
7 days ago | about 7 hours ago | |
TypeScript | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
echarts
- Ask HN: What's the best charting library for customer-facing dashboards?
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A web crawler program for crawling Echarts official website examples implemented by Puppeter
import puppeteer from "puppeteer"; import fs from "node:fs"; import { storiesTpl, storiesArgs, generOptions, generOptionsWithFn, } from "./template.mjs"; const ECHARTS_BASE_URL = "https://echarts.apache.org/examples/en/index.html"; function capitalizeFirstLetter(str) { if (!str || str.length === 0) { return ""; } str = str.toLowerCase(); return str.charAt(0).toUpperCase() + str.slice(1); } (async function () { const browser = await puppeteer.launch(); const page = await browser.newPage(); // Navigate the page to a URL await page.goto(ECHARTS_BASE_URL); // Set screen size await page.setViewport({ width: 1080, height: 1024 }); // Type into search box // const examples = await page.type([".example-list-panel"]); const searchResultSelector = ".example-list-panel > div"; const results = await page.$$(searchResultSelector); for (const element of results) { // gener namespace const ele = await element.$(".chart-type-head"); const title = await ele.evaluate((el) => el.textContent); let namespace = title.split(" ").filter(Boolean); namespace = namespace.slice(0, namespace.length - 1); namespace = namespace .map((item) => item.replace("\n", "").replace("/", "")) .filter(Boolean) .join(""); console.log(`${namespace} start`); const instances = await element.$$(".row .example-list-item"); const components = []; for (const instance of instances) { // title const titleElement = await instance.$(".example-title"); const subTitle = await titleElement.evaluate((el) => el.textContent); const titles = subTitle .split(" ") .filter(Boolean) .map((item) => item .replace(/\+/g, "") .replace(/\(/g, "") .replace(/\)/g, "") .replace(/-/g, "") ); const title = titles.map((item) => capitalizeFirstLetter(item)).join(""); const link = await instance.$(".example-link"); const newPagePromise = new Promise((resolve) => { browser.on("targetcreated", async (target) => { if (target.type() === "page") { const targetPage = await target.page(); const url = await targetPage.url(); if (url.includes("editor")) { resolve(targetPage); } } }); }); await link.click(); const newPage = await newPagePromise; await newPage.setViewport({ width: 40000, height: 20000 }); await newPage.waitForSelector(".ace_text-layer"); await new Promise((resolve) => { setTimeout(() => { resolve(); }, 3000); }); let content = await newPage.evaluate( () => document.querySelector(".ace_text-layer").innerText ); content = content .replace(/\[\]/g, "[] as any") .replace(//g, "") .replace(/var/g, "let"); let options; if (content.includes("myChart")) { options = generOptionsWithFn({ options: content }); } else { options = generOptions({ options: content }); } components.push({ options, title }); await newPage.close(); } const args = components .filter(({ options }) => { if (options.includes("$")) return false; return true; }) .map(({ options, title }) => storiesArgs({ options: options, name: title }) ) .join("\r\n"); const scripts = storiesTpl({ namespace: `Charts/${namespace}`, components: args, }); fs.writeFileSync(`./bots/assests/${namespace}.stories.ts`, scripts); console.log(`${namespace} end`); } })();
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Show HN: Paisa – Open-Source Personal Finance Manager
I want to know where my money goes. I like to look at stacked-area (or column) charts of the categories of spending. To make this work I have some software I made ~20 years ago that does double-entry book-keeping. At the end of the month, I import statements from financial service providers (eg: Wells Fargo, Chase, PayPal, Stripe, etc). Lots of stuff is repeat purchases (eg: Shell Gas) and my software automatically categorises. Some transactions I have to categorise manually. Each category / vendor becomes an expense-account and my banks and CCs exist as assets and liabilities.
Once the import and reconciliation is done I pull up a my column chart that shows where the money went -- and can compare over time -- see a full year of movement. I've been through various charting libraries with it and most recently moved to ECharts[0] -- so I'm planning to expand with Treemap and Sankey style visuals.
The import process, which I do monthly takes maybe an hour. I'm importing from like 5 bank accounts, 3 payment processors, 4 CC providers. The part that takes the longest is signing into their slow sites, navigating past pop-up/interstitial, getting to their download page and waiting for it to download. Loads of these sites (WF, Chase) have been "modernised" and have some real bullshit UI/UX going on -- lags, no keyboard, elements jump around, forms can't remember state, ctrl+click won't open in a new page cause that damned link isn't actually a link but some nested monster of DIVs with 19 event listeners on each one -- and somehow still all wrong.
I think the most-best feature would be to have some tool automatically get all my transactions from all these providers into one common format. Gimmee some JSON with like 10 commonly-named fields for the normal stuff and then 52 other BS fields that each provider likes to add (see a PayPal CSV for example). Does that exist and I just don't know?
[0] https://echarts.apache.org/
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Personal Sträva Activity Statistics
Coded mainly in Perl and Gnuplot, recently extended by Python Pandas and JavaScript Tabulator and ECharts
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Build complex SPAs quickly with vue-element-admin
Dashboards have a lot of charts for different forms and data. This is another common requirement. This template recommends Apache ECharts, a powerful, easy-to-use, and flexible JavaScript visualization library.
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Using Apache ECharts in React Native - wrn-echarts
We have developed an open source graphics library for react native APP, which is based on Apache ECharts and uses RNSVG or RNSkia for rendering in a way that is almost identical to using it in the web, and can satisfy most graphics situations. The project source code is available at https://github.com/wuba/wrn-echarts .
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Best practice for UI design in scientific app
apache-echarts for charting system (it has 3d chart anyway)
- [OC] The crude birth rate in European Union from 1960 to 2020
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Use types (which import other types that reference the DOM) inside a web-worker!
How are you importing the definition? Assuming you are using "apache/echarts" and not some other lib named "echarts", you should be able to import DatasetModel directly and let tree shaking trim out what you're not using.
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Pulling and visualizing data from a database client side
ECharts -- open source js lib for enterprise-grade charts
Altair
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Ask HN: What's the best charting library for customer-facing dashboards?
I like Vega-Lite: https://vega.github.io/vega-lite/
It’s built by folks from the same lab as D3, but designed as “a higher-level visual specification language on top of D3” [https://vega.github.io/vega/about/vega-and-d3/]
My favorite way to prototype a dashboard is to use Streamlit to lay things out and serve it and then use Altair [https://altair-viz.github.io/] to generate the Vega-Lite plots in Python. Then if you need to move to something besides Python to productionize, you can produce the same Vega-Lite definitions using the framework of your choice.
- FLaNK AI Weekly 18 March 2024
- FLaNK AI for 11 March 2024
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Vega-Altair: Declarative Visualization in Python
Feel free to open an issue to let us know which parts of the documentation you find obscure and if you have suggestions for how to improve them. We did a larger overhaul a few months back and are always open to feedback on how to improve it further! https://altair-viz.github.io/
(disclaimer: I'm a co-maintainer of Altair)
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Gnuplotlib: Non-Painful Plotting for NumPy
Vega-Altair is pretty great as well. It uses a grammar of graphics that’s slightly different from ggplot, but has most of the same advantages.
https://altair-viz.github.io/
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Altair - Declarative statistical visualization library for Python.
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Top 10 growing data visualization libraries in Python in 2023
Github: Altair
- What python library you are using for interactive visualisation?(other than plotly)
- Libs para gráficos
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If you had to pick a library from another language (Rust, JS, etc.) that isn’t currently available in Python and have it instantly converted into Python for you to use, what would it be?
Yeah, that's one of the main reasons I like altair. It has 10M downloads per month and the newest Git update is from two days ago.
What are some alternatives?
Chart.js - Simple HTML5 Charts using the <canvas> tag
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
bokeh - Interactive Data Visualization in the browser, from Python
Highcharts JS - Highcharts JS, the JavaScript charting framework
seaborn - Statistical data visualization in Python
vega - A visualization grammar.
ggplot - ggplot port for python
Frappe Gantt - Open Source Javascript Gantt
plotnine - A Grammar of Graphics for Python
apexcharts.js - 📊 Interactive JavaScript Charts built on SVG
matplotlib - matplotlib: plotting with Python