cheatsheets
d3
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cheatsheets | d3 | |
---|---|---|
126 | 276 | |
7,219 | 107,465 | |
0.9% | 0.3% | |
7.1 | 8.4 | |
23 days ago | 3 days ago | |
Python | Shell | |
BSD 2-clause "Simplified" License | ISC 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.
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
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About to lose access to MATLAB, is Python a realistic replacement for DSP algorithm development?
Edit: recommended libraries A python version of Matlab plotting down to the syntaxes matching.
- What is something you wish there was a Python module for?
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Suggestions for Udemy, Coursera, DataCamp, Pluralsight courses for Pandas and Visualization? So many options out there...project-based ones would be ideal. Or the ones to avoid or overrated courses?
https://matplotlib.org https://seaborn.pydata.org
d3
- Ask HN: Tips to get started on my own server
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Full Stack Web Development Concept map
d3 - very power visualization library enabling dynamic visualizations. docs
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Observable 2.0, a static site generator for data apps
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).
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Using Deno with Jupyter Notebook to build a data dashboard
D3.js: A robust library to visualize your data and create interactive data-driven visualizations.
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What is the technology stack used to create these live charts?
They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.
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How do you implement library types?
When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.
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The top 11 React chart libraries for data visualization
Website: D3.js official site
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Frontend development roadmap
D3js
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How to use Next.js and Recharts to build an information dashboard
Recharts is a composable charting library built on React components and D3.js. It contains API’s which allow you to easily add 11 different highly configurable chart types to your React application. Recharts is one of the most popular React.js charting libraries with over 20k likes on GitHub.
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Best heatmap libraries for React (with demos)
D3.js: The advanced option
What are some alternatives?
echarts - Apache ECharts is a powerful, interactive charting and data visualization library for browser
GoJS, a JavaScript Library for HTML Diagrams - JavaScript diagramming library for interactive flowcharts, org charts, design tools, planning tools, visual languages.
vis
d4 - A friendly reusable charts DSL for D3
svg.js - The lightweight library for manipulating and animating SVG
sigma.js - A JavaScript library aimed at visualizing graphs of thousands of nodes and edges
paper.js - The Swiss Army Knife of Vector Graphics Scripting – Scriptographer ported to JavaScript and the browser, using HTML5 Canvas. Created by @lehni & @puckey
fabric.js - Javascript Canvas Library, SVG-to-Canvas (& canvas-to-SVG) Parser
visx - 🐯 visx | visualization components
vega - A visualization grammar.
Cytoscape.js - Graph theory (network) library for visualisation and analysis
finplot - Performant and effortless finance plotting for Python