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Based on our record, Pandas seems to be a lot more popular than Recharts. While we know about 198 links to Pandas, we've tracked only 16 mentions of Recharts. 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.
Chartjs looks great, but I've never used it so can't recommend personally. I've used https://recharts.org a lot with success. - Source: Hacker News / 7 days ago
We first build the dashboard page where we present stats for relevant KPIs in cards, charts and a table. We use the React-based Recharts library for plotting our data. - Source: dev.to / 6 months ago
For the charts a heavily customized version of recharts (https://recharts.org/) and for the globe threejs (https://threejs.org). - Source: Hacker News / 8 months ago
Recharts is another React charting library that simplifies creating charts by providing a wide range of chart components out of the box. It is built on top of D3.js but abstracts away the complexities, making it easier for React developers to create interactive and visually appealing charts and graphs. Recharts leverage the power of SVG (Scalable Vector Graphics) for rendering, allowing charts to be scalable and... - Source: dev.to / 9 months ago
Recharts is a charting library that allows you to create attractive and informative data visualizations. - Source: dev.to / about 1 year ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 15 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 9 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Chart.js - Easy, object oriented client side graphs for designers and developers.
NumPy - NumPy is the fundamental package for scientific computing with Python
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
OpenCV - OpenCV is the world's biggest computer vision library