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Which is more popular?
Based on our record, Plotly
seems to be a lot more popular than NVD3.
While we know about 34 links to Plotly,
we've tracked only 1 mention of NVD3.
social mentions
1 vs 34
Charting Libraries popularity
36% vs 64%
alternatives listed
135 vs 240+
Base details
Website, pricing, platforms and company facts side by side.
Reusable Charts NVD3 provides a variety of pre-built chart types that are easy to reuse and customize, saving developers time when creating standard visualization needs.
Based on D3.js Utilizing D3.js ensures a high level of flexibility and the ability to integrate complex data manipulations with aesthetic chart outputs.
Ease of Use NVD3 simplifies the process of generating complex visualizations by providing an intuitive API for interacting with D3.js charts.
Responsive Design Many of the chart components are designed with responsiveness in mind, allowing them to adjust to different screen sizes and devices.
Possible disadvantages
Limited Updates NVD3 is not frequently updated, which may lead to compatibility issues or lack of support for newer web technologies.
Learning Curve While it simplifies some aspects of D3.js, users still need to have a solid understanding of D3.js to fully leverage NVD3's capabilities, which can be steep for new users.
Limited Customization Compared to directly using D3.js, NVD3 offers a more limited range of customization options for charts, potentially restricting designers looking for highly unique visualizations.
Documentation Quality The documentation for NVD3 can be sparse or outdated, making it harder for developers to troubleshoot issues or learn best practices.
Interactivity Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
High-quality visualizations It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
Versatility Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
Python integration Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
Web-based The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
Open-source Plotly offers an open-source version, which allows users to create and share visualizations without any cost.
Possible disadvantages
Performance Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
Learning curve Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
Cost for advanced features While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
Dependency management Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
Complexity For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.
Analysis
An editorial look at what each product does well and who it suits.
NVD3Plotly
Overall verdict
NVD3 is generally a good library if you are seeking convenience and speed in creating standard chart types. However, if your project requires extensive customization and more complex interactive features, sticking directly with D3.js could be more beneficial.
Why this product is good
NVD3 is built on top of D3.js, offering a simplified API for creating various types of charts. It's useful for developers who need to generate data visualizations quickly without delving deep into the complexities of D3. It provides a collection of reusable chart components, saving time in coding from scratch. However, since it's a layer on top of D3.js, it might not offer the same level of customization and flexibility for more unique visualizations.
Recommended for
Developers looking for quick, easy-to-implement charting solutions.
Projects that require standard charts with minimal customization.
Teams that want to leverage D3.js capabilities with a simpler API.
Overall verdict
Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.
Why this product is good
Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.
Recommended for
Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
This project is an attempt to build reusable charts and chart components for d3.js without taking away the power that d3.js gives you. The goal of the project is to keep all your charts neat and customizable. NVD3 is...
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering...
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data...
Recommendations tracked on public social media and blogs since March 2021.
NVD31 mentionPlotly34 mentions
Widely Used Data Display and Analysis Libraries
NVD3 is also on the list of the most popular libraries. Built upon D3.js like the others above, it does have a solid technical base.
- Source: dev.to
/
about 5 years ago
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization.
- Source: dev.to
/
8 months ago
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
/
over 1 year 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...
- Source: dev.to
/
almost 2 years ago
Creating meaningful and aesthetically pleasing data visualizations and incorporating them into your projects is easy with the tools offered by ZoomCharts.
Highcharts
Google Charts
ZoomCharts
RAWGraphs
ZingChart
D3.js
ChartBlocks
Tableau
Bokeh
Chart.js
