惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

aimingoo的专栏
aimingoo的专栏
宝玉的分享
宝玉的分享
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
WordPress大学
WordPress大学
V
V2EX
Apple Machine Learning Research
Apple Machine Learning Research
J
Java Code Geeks
腾讯CDC
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Engineering at Meta
Engineering at Meta
L
LangChain Blog
Jina AI
Jina AI
博客园 - 叶小钗
B
Blog RSS Feed
Recent Announcements
Recent Announcements
H
Help Net Security
小众软件
小众软件
大猫的无限游戏
大猫的无限游戏
B
Blog
云风的 BLOG
云风的 BLOG
Blog — PlanetScale
Blog — PlanetScale
D
DataBreaches.Net
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
罗磊的独立博客

Hugging Face - Blog

Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs ALTK‑Evolve: On‑the‑Job Learning for AI Agents Safetensors is Joining the PyTorch Foundation Holo3: Breaking the Computer Use Frontier Any Custom Frontend with Gradio's Backend A New Framework for Evaluating Voice Agents (EVA) Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations One-Shot Any Web App with Gradio's gr.HTML CUGA on Hugging Face: Democratizing Configurable AI Agents New in llama.cpp: Model Management Building Deep Research: How we Achieved State of the Art OVHcloud on Hugging Face Inference Providers 🔥 20x Faster TRL Fine-tuning with RapidFire AI Building for an Open Future - our new partnership with Google Cloud Aligning to What? Rethinking Agent Generalization in MiniMax M2 Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac Sentence Transformers is joining Hugging Face! Unlock the power of images with AI Sheets Supercharge your OCR Pipelines with Open Models Google Cloud C4 Brings a 70% TCO improvement on GPT OSS with Intel and Hugging Face Get your VLM running in 3 simple steps on Intel CPUs Nemotron-Personas-India: Synthesized Data for Sovereign AI Introducing RTEB: A New Standard for Retrieval Evaluation Accelerating Qwen3-8B Agent on Intel® Core™ Ultra with Depth-Pruned Draft Models VibeGame: Exploring Vibe Coding Games Nemotron-Personas-Japan: ソブリン AI のための合成データセット Swift Transformers Reaches 1.0 – and Looks to the Future Smol2Operator: Post-Training GUI Agents for Computer Use SyGra: The One-Stop Framework for Building Data for LLMs and SLMs Gaia2 and ARE: Empowering the community to study agents
Introducing Gradio's new Dataframe!
hannah, Abubakar Abid · 2025-03-24 · via Hugging Face - Blog

Back to Articles

hannah's avatar

Abubakar Abid's avatar

Gradio’s gr.Dataframe component is one of our most popular components, we've seen it used in a variety of awesome apps, like leaderboards, dashboards, and interactive visualisations. Although we hadn't made any changes to the dataframe in quite some time, our backlog of issues had been growing, and some improvements had been in demand for a while.

Well — we’re now super excited to release a host of new updates to Gradio’s dataframe component. Over the last 6 weeks, we’ve closed over 70 dataframe issues - including bugs, improvements and enhancements.

1. Multi-Cell Selection

You can select multiple cells at once! Copy or delete values across your selection with ease.

2. Row Numbers & Column Pinning

Add row number columns and keep critical columns in view while navigating wide datasets using the pinned_columns parameter. No more losing track of what you're looking at!

3. Copy Button and Full Screen Button

Easily copy cell values into a comma-separated format with our new copy button. Need a better view? The full screen button gives you interactivity without distractions and can be enabled with the show_full_screen parameter.

4. Scroll to Top Button

Look at all that data! Now we can just scroll to the top.

5. Accessibility Upgrade and Enhanced Styling

Improved keyboard navigation makes gr.Dataframe more accessible than ever. You can also take control of your dataframe’s look with a dedicated styler parameter and enhance the user experience of your app.

6. Row and Column Selection

Access entire row data in select events for more intuitive interactivity and data manipulation.

7. Static Columns

Customise the interactivity of your dataframe by specifying non-editable columns using the static_columns parameter.

8. Search functionality

Quickly find the data you need with our powerful search feature by setting the show_search parameter to "search".

9. Filter functionality

Narrow down your dataset to focus on exactly what you need with flexible filtering options with show_search set to "filter".

10. Improved cell selection

Experience smoother, more intuitive cell selection that behaves the way you expect.

What’s next?

With over 70 issues closed, we’ve made huge improvements, but there’s always more for us to work on. Looking ahead, we still have more ideas to implement and we’re excited to keep refining accessibility, performance, and integration. Look out for some cool demos on our socials using the dataframe on Gradio’s X.

Try it yourself!

The updated dataframe is live in the latest Gradio release. Update your installation with pip install --upgrade gradio.

import gradio as gr

df_headers = ["Name", "Population", "Size (min cm)", "Size (max cm)", "Weight (min kg)", "Weight (max kg)", "Lifespan (min years)", "Lifespan (max years)"]
df_data = [
    ["Irish Red Fox", 185000, 48, 92, 4.2, 6.8, 3, 5],
    ["Irish Badger", 95000, 62, 88, 8.5, 13.5, 6, 8],
    ["Irish Otter", 13500, 58, 98, 5.5, 11.5, 9, 13]
]

with gr.Blocks() as demo:
    df = gr.Dataframe(
        label="Irish Wildlife",
        value=df_data,
        headers=df_headers,
        interactive=True,
        show_search="search",
        show_copy_button=True,
        show_fullscreen_button=True,
        show_row_numbers=True,
        pinned_columns=1,
        static_columns=[0],
        column_widths=["300px"]
    )

demo.launch()

Check out the Gradio documentation for examples and tutorials to get started with these new features. We’re eager to see what you create! Got thoughts or suggestions? Share them by raising an issue in our GitHub repo.

Happy building!