LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone and trusted by professionals.
FEATURE HIGHLIGHTS
A full list of features: https://labplot.kde.org/features
Video tutorials: https://www.youtube.com/@LabPlot
Communication channels: https://labplot.kde.org/support
Get it here: https://labplot.kde.org/download
LabPlot provides extensive capabilities for data import and export, along with tools for analysis, curve fitting, nonlinear regression and interactive visualization, including live data support. Users can export graphs in various formats and utilize a built-in plot digitizer to extract data from existing charts. Additionally, if users are familiar with programming languages such as Python or R, they can leverage these within LabPlot's interactive notebooks.
Based on our record, Plotly seems to be more popular. It has been mentiond 33 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.
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / about 1 month ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / 3 months ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 5 months ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 11 months ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
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