Based on our record, npm should be more popular than Plotly. It has been mentiond 61 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
To begin, you will need to choose a name for your package. Note: Your package name must be unique. Using the exact or similar name of an existing package will return an error when publishing the package to npm. To ensure the uniquenesses of your package name, head over to npmjs.com and search for any existing packages with a similar name. If there’s an exact match or a similar name, consider changing the name... - Source: dev.to / about 1 month ago
By using Fastify, you can quickly get a Node.js application up and running to handle requests. Assuming you have Node.js installed, you’ll start by initializing a new project. We’ll use npm as our package manager. - Source: dev.to / about 1 month ago
It is on this last topic that I want to focus on in this post, and then in particular, how to make working with dependencies a bit safer within the NPM ecosystem. - Source: dev.to / 3 months ago
In modern applications you'll get React and React DOM files from a "package registry" like npm (react and react-dom). - Source: dev.to / 4 months ago
Install the alacritty-themes package globally with npm. - Source: dev.to / 5 months ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 6 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year ago
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... Source: about 1 year ago
I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: about 1 year ago
Plotly Dash is a great framework for developing interactive data dashboards using Python, R, and Javascript. It works alongside Plotly to bring your beautiful visualizations to the masses. - Source: dev.to / over 1 year ago
Webpack - Webpack is a module bundler. Its main purpose is to bundle JavaScript files for usage in a browser, yet it is also capable of transforming, bundling, or packaging just about any resource or asset.
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Yarn - Yarn is a package manager for your code.
Chart.js - Easy, object oriented client side graphs for designers and developers.
Brunch - Brunch builds, lints, compiles, concatenates and shrinks your HTML5 app in an ultra-simple way. No more Grunt / Gulp mess.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application