freeCodeCamp·1yHow to Build an Analytical Dashboard with Next.js
The post provides a comprehensive guide to building an analytical dashboard using Next.js, Flexmonster, and Highcharts. It includes step-by-step instructions on configuring these tools, creating charts, and setting up a functional user interface. Additionally, it explores real-world survey data on passenger flying etiquette to demonstrate the dashboard's capabilities.
Hacker News·45wkepler.gl
Kepler.gl is a WebGL-powered geospatial data visualization tool designed for analyzing and visualizing large-scale datasets in web browsers. Built with high-performance rendering capabilities, it enables interactive exploration of geographic data. Foursquare Studio extends kepler.gl's framework as a free analytics platform with regular feature updates.
Tech With Tim·1yHow To Automate Your Finances with Python - Full Tutorial (Pandas, Streamlit, Plotly & More)
The post provides a step-by-step tutorial for building a personal finance automation tool using Python with libraries such as Pandas, Streamlit, and Plotly. The tool can upload bank statements in CSV format, categorize transactions, and summarize expenses using visualizations. It also explains how to convert bank statements into a format conducive to analysis and the importance of utilizing structured, project-based learning resources like Data Camp for Python and finance fundamentals.
Tinybird·1yUsing LLMs to generate user-defined real-time data visualizations
Developers are increasingly using Tinybird to track LLM usage, costs, and performance in AI applications. A new app template called the LLM Performance Tracker allows users to generate real-time data visualizations. The core components include a Tinybird datasource, a Tinybird pipe, a React component, and an AI API route. The backend processes user input to generate chart parameters, while the frontend visualizes the data. This approach emphasizes the importance of performant analytics backends and cautious LLM usage for secure and scalable data visualization.
LogRocket·1yBest React chart libraries (2025 update): Features, performance & use cases
The post compares top React chart libraries in 2025, including Recharts, react-chartjs-2, Victory, Nivo, React ApexCharts, Ant Design Charts, Apache ECharts, visx, and MUI X Charts. It evaluates these libraries based on features, documentation, community adoption, and customizability. It also discusses their specific strengths, such as support for real-time data updates, rendering methods, responsiveness, and integration with mobile applications.
Syncfusion·1yTop 5 React Stock Chart Libraries for 2025
Discover key advancements in modern React stock chart libraries, including improved performance, mobile-first design, and advanced customization. The post reviews top libraries like Syncfusion, Highcharts, amCharts, AnyChart, and CanvasJS, detailing their features to help build powerful stock market visualizations in 2025.
80 LEVEL·32wJuicy UI For Pixel Art-Style 4X Game Made With Godot
PLVS VLTRA is a turn-based 4X strategy game built with Godot featuring an economy dashboard that visualizes complex financial data through line graphs, pie charts, and detailed breakdowns. The game integrates UI design with gameplay mechanics, where the dashboard reflects player decisions made through a Laws & Policies system and Imperial Cabinet interactions. The project demonstrates how data visualization can serve as both an informational tool and strategic gameplay element in indie game development.
Towards Data Science·46wBuilding A Modern Dashboard with Python and Taipy
Taipy is a Python web framework designed for data scientists and engineers to build production-ready dashboards without web development expertise. The tutorial demonstrates creating an interactive sales dashboard with filtering capabilities, key metrics display, multiple chart types, and raw data tables using 100,000 synthetic sales records from a CSV file. Taipy excels over Streamlit and Gradio when building complex, high-performance, enterprise-grade applications that require scalability and maintainability.
Grafana Labs·52wDashboards and detergent: How two students monitor laundry machines in a college dorm with Grafana
Two college students developed a system using Grafana and TimescaleDB to track laundry machine usage in dorms. They used internet-connected laundry machines' data, building a real-time dashboard that also records metrics like machine popularity and usage times. This creative approach demonstrates Grafana's versatility beyond typical network monitoring and hints at future integration possibilities with weather data or gamification.
Towards Data Science·1yReal-Time Interactive Sentiment Analysis in Python
The post demonstrates creating a real-time interactive sentiment analysis application using Python. It details setting up the GUI with customtkinter and dynamically visualizes sentiment through a procedurally generated smiley face using OpenCV. Pre-trained transformer models from the transformers library are used for sentiment prediction, and visual updates are processed asynchronously using thread pools to ensure smooth UI performance.
Syncfusion·1yTop 5 React Chart Libraries for 2025
This post compares five popular React chart libraries for 2025: Syncfusion React Charts, React Google Charts, Recharts, react-chartjs-2, and Highcharts. Highlights include enhanced performance, mobile compatibility, extensive customization, and expanded chart types. Each library’s strengths, key benefits, and installation instructions are discussed. The post emphasizes choosing the right library based on project-specific requirements.
Towards Data Science·42wI Analysed 25,000 Hotel Names and Found Four Surprising Truths
A data scientist analyzed 25,000 hotel names worldwide using the Hotel Data API to uncover why hotels are named after cities they're not located in. The study revealed that Paris is the most borrowed city name (1,100+ hotels), followed by Vienna and Rome. Three main reasons emerged: proximity for search visibility, branding to evoke luxury and sophistication, and historical tradition dating back to 18th-century aristocratic travel patterns. The analysis used Python, pandas, and geographic distance calculations to map naming patterns across countries.
UX Planet·45wDashboard That Works: A Step-by-Step Guide for Startups in 2025
A comprehensive 10-step guide for building effective business dashboards that focuses on setting clear goals, assembling the right team, defining user needs, selecting meaningful metrics, and ensuring proper data preparation. The guide emphasizes collaboration between analysts, designers, and developers, warns against template-only approaches, and stresses the importance of user feedback and iterative improvement. Key principles include limiting metrics to 3-5 meaningful ones, avoiding clutter, automating data entry, and designing for specific user roles rather than trying to serve everyone.
Syncfusion·52wSimplify Your Finances with the Flutter Expense Tracker
The Flutter Expense Tracker Sample simplifies financial management by tracking income, expenses, budgets, and savings. Key features include cross-platform support, interactive data visualization, responsive UI, optimized state management, and efficient local storage using reusable Flutter widgets. It offers pages for setup, import, dashboard, transactions, budgets, savings, and settings, ensuring easy navigation and data handling across different devices.
Grafana Labs·26wA Star Wars dashboard deep dive: How to build your next visualization in less than 12 parsecs
A detailed walkthrough of building a Star Wars-themed Grafana dashboard, covering practical techniques like using stat panels for custom text styling, TestData plugin for simulating dynamic data, canvas panels for creating custom visualizations with animations, and styling approaches for visual consistency. Demonstrates how to create gauges, charts, maps, and custom layouts while explaining the technical implementation behind each component.
xkcd·41wxkcd: Bad Map Projection: Interrupted Spheres
An xkcd comic exploring the concept of interrupted spheres as a humorous take on map projection methods. The comic likely satirizes the challenges and compromises involved in representing the Earth's spherical surface on flat maps, highlighting the mathematical and visual trade-offs inherent in cartographic projections.
Towards Data Science·49wBuilding a Modern Dashboard with Python and Gradio
A comprehensive guide to building an interactive sales performance dashboard using Gradio, a Python library for creating web applications. The tutorial covers setting up Gradio, processing CSV data with Pandas, implementing filtering capabilities, generating visualizations with Matplotlib, and creating a responsive interface with key metrics, charts, and data tables. The dashboard allows users to filter by date ranges and product categories while displaying revenue trends, top products, and raw data dynamically.
Grafana Labs·32wTaylor Swift (Grafana’s Version): How to track and visualize data related to pop’s biggest superstar
Grafana Labs built a comprehensive dashboard using Grafana Assistant to visualize Taylor Swift's career data, including album characteristics, Eras Tour analytics, and career milestones. The project demonstrates how Grafana Assistant's AI-powered natural language interface enables users of varying skill levels to create complex dashboards by querying data from sources like BigQuery and Kaggle datasets. The dashboard features four tabs covering profile stats, musical analysis with Spotify API data, tour attendance metrics with geomaps, and album details.
AI·43wI Let AI Be Free, and It Blew My Mind 🤯
A development team at Decipad replaced their traditional chart-building approach with an AI-powered system that generates data visualizations dynamically. The solution uses a multi-agent architecture where one AI fetches and analyzes data while a specialized Chart Agent generates secure, production-ready chart code. Key technical components include Sandpack for secure code execution, automatic error recovery mechanisms, and persistent chart storage. The system allows AI to create custom visualizations using libraries like eCharts without predefined constraints, resulting in more flexible and creative data presentations than traditional fixed chart options.
Linear·31wBest practices for designing Linear Dashboards
Linear's dashboard feature combines data from multiple sources into unified views for monitoring team workflows and resource allocation. Based on usage patterns from thousands of enterprise teams, four key practices emerge: maintain fewer, high-quality dashboards with clear ownership; design dashboards with specific purposes (operational vs strategic); tailor detail level and update frequency to the intended audience; and provide contextual information alongside raw metrics through comparative visualizations and trend analysis.
Product Hunt·46wGitProbe: Analyze and visualize codebases
GitProbe is an intelligent code analysis tool that generates interactive function call graphs and provides comprehensive insights into GitHub repositories. The tool helps developers understand codebase structure and relationships through visual representations.
Data Engineer Things·1yPower BI? Tableau? No Thanks. I’d Rather Use This AI Tool for Charts
Quadratic is an AI-powered tool designed to simplify chart creation for non-technical users across various fields such as marketing, sales, education, and healthcare. It allows users to generate insightful visualizations quickly and effortlessly using natural language prompts, eliminating the need for complex tools and reliance on data analysts.
Faun·1yEssential Python Libraries for Data Science in 2025
Python remains the top choice for data science due to its versatility, simplicity, and strong community support. Essential Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, SciPy, Altair, XGBoost, Statsmodels, and Plotly are highlighted for their key features and use cases, all of which continue to evolve to meet the demands of data science in 2025. Staying current with these libraries is crucial for maintaining efficiency, competitiveness, and innovation in the field.
