sjvisualizer is a data visualization and animation library for Python for time-series data.
Tries to be easy to use. Give it a file of data (the examples given are .xlsx files, can probably use others) and it seems to know what to do if it thinks it's time-series data.
Has an actual website with more detailed and elaborate examples, including background information: https://www.sjdataviz.com/software
Awesome Regex curates the best regular expression tools, tutorials, libraries, and other resources. It covers all major regex flavors, and currently includes especially deep coverage of regular expressions in JavaScript.
Use Python to map a website's external facing links. And then apply D3 to visualize those outbound connections as a network graph.
A Python package on top of matplotlib to create 'cyberpunk' style plots with 3 additional lines of code. After importing the package, the cyberpunk stylesheet (dark background etc.) is available via plt.style.use. The line glow and 'underglow' effects are added via calling add_glow_effects.
Go to their editor. Paste in a well-formed data document. Watch it generate a graph for you out of the data. You can even download the generated image. No API yet.
Setup process:
cd jsoncrack.compnpm installcd srcpnpm buildcd ..
You want to copy the contents of the out/ subdirectory up to your web server because that's where all the business is.
stree is a CLI tool designed to visualize the directory tree structure of an S3 bucket. By inputting an S3 bucket/prefix and utilizing various flags to customize your request, you can obtain a colorized or non-colorized directory tree right in your terminal.
Welcome to PY-SDR v2.0, a powerful real-time spectrum visualization tool built using PyQt5 and Matplotlib. This application leverages the capabilities of RTL-SDR (Software Defined Radio) to provide a dynamic and interactive representation of radio frequency spectra.
Real-Time Spectrum Analysis: Capture and analyze radio frequency spectra in real-time with a customizable FFT size. 3D and 2D Waterfall Views: Visualize the spectrum data in both 3D and 2D waterfall plots for a comprehensive understanding. Set your desired RTL-SDR parameters, including sample rate, center frequency, and gain. Easily adjust the capture duration, FFT size, and other parameters to suit your needs.
An interactive visualization (with simple explanations) of how large language models work.
MesoWx is a real-time HTML front-end for visualizing personal weather station data. It provides a real-time graph and console display, and dynamic graphs of your weather station history allowing you to explore the details of any recorded time period in your data.
MesoWx displays data from a database and does not itself interface with any weather station hardware directly, however, being built upon Meso it supports an HTTP API for remotely adding data, which allows integration with existing weather station software. MesoWx integrates well with Weewx and should support any weather station that it supports.
Requires quite a bit of configuration and background work (like setting up another database for this extension to use exclusively) so read the docs before deciding to set it up.
AKA the "I'm not a climate scientist but I play one on the internet" dashboard.
A curated dynamic collection of websites offer a interesting and interactive experience for users. With real-time data (most of it), engaging maps, and visually stunning data visualizations, this collection is a treasure for enthusiasts of air industry, space, history, world statistics and more!
Open-source, self-hosted alternative to CARTO and Foursquare Studio for data scientists, analysts and engineers. State-of-the art WebGL-powered map visualizations and spatial analysis based on deck.gl. Tested at 100Mb and 1M rows. Efficient query result caching on Amazon S3 or Google Cloud Storage. Side-by-side SQL editor and support for CSV and GeoJSON file uploads.
NiceGUI handles all the web development details for you. So you can focus on writing Python code. Anything from short scripts and dashboards to full robotics projects, IoT solutions, smart home automations and machine learning projects can benefit from having all code in one place. Offers all of the HTML user interface bits you'd expect. Flexible layout by default, supports HTML, CSS and Markdown. Charts, tables, diagrams, 3d visualization, automatic refresh.
Pretty heavy dependencies, but at least pip handles that for you.
A curated list of awesome ASD-B tools, projects, images, resources and other shiny things.
Small program that computes and plots spectrograms, either in a live window or to disk, with support for stdin input. In theory, you can run any data through it and generate a spectrogram. Read the manpage.
In the AUR (but you want specgram-git because specgram has a bug and won't compile!)
Open Infrastructure Map is a view of the world's infrastructure mapped in the OpenStreetMap database. This data isn't exposed on the default OSM map, so I built Open Infrastructure Map to visualise it. If you want to edit the data and you're new to OpenStreetMap, check out learnOSM.
If you already have some OSM experience and want to start tagging infrastructure things, take a look at the tagging guidelines for power and telecoms.
Smashing, the spiritual successor to Dashing, is a Sinatra based framework that lets you build excellent dashboards. It looks especially great on TVs. Use premade widgets, or fully create your own with scss, html, and coffeescript. Has a REST API to push data to the dashboard. Drag and drop interface for building a dashboard.
Install the gem. Run it to create a new dashboard ("project"). Run bundle. Start the server for the project.
Bloxs is a simple python package that helps you display information in an attractive way (formed in blocks). Perfect for building dashboards, reports and apps in the notebook.
It works with Jupyter Notebook, Google Colab, Deepnote, Kaggle Notebook, and Mercury.
An interactive webapp where you can key in an arbitrary message and step through the SHA-256 algorithm to watch how it works.
Dynamic web based reports/dashboards in Python. Write a little bit of code to define the dashboard and populate the layout, and treat the rest like Python. Seems pretty straightforward. Has a built-in DSL to make defining some parts of a dashboard easier to do. Also has a CLI tool that you can use to interactively build dashboards without having to stop and start the server again and again. Even has a REST API that can be used to update the page's widgets in the background, so you can push instead of pull.