Share Your App - Explore Page - December 2023

Thank you for your interest in submitting your Dash app to the Plotly Explore Page platform, visited by thousands of Dash users daily.

Current submissions cycle will run from December 1 to December 31, 2023.

To submit your app, please reply to this thread directly.

Please refer to the following suggestions when building and submitting your app. The more suggestions your app adheres to, the more likely it is to be added to the Explore Page.

  • Apps in the following categories are encouraged: Energy & Utilities, Business, Predictive Analytics & Forecasting, NLP, Connecting to APIs
  • App should look as good or better than the current apps on the platform
  • App should use different data than the other apps and try to cover a unique story
  • Content/story should be neutral or positive
  • App with live data that updates itself is encouraged
  • App that goes beyond exploratory analysis – app that perform advanced analytics
  • App that uses 3rd-party libraries (e.g., SciPy, spaCy, TensorFlow, Scikit-learn)
  • App that solves real-life problems, app that could have practical use cases
  • App content and results should be easy to access (we discourage requiring log-ins or uploading data as a precursor to seeing the full app).

The Plotly Example Apps team will review the apps submitted and update this post with the names of the apps that have been selected.

Happy Dash app building!

I just soft launched a site that I’ve been working on for fun. It access National Weather Service data to show past weather and the forecast together to help decide where to go ice climbing. I have plans to add more data sources and other useful information that ice climbers would care about - and perhaps even some logic for predictions - it’s an MVP right now.

I’ve been lurking in the forum to help answer some of my questions along the way! Thanks for the great community!


Hi @crsaulnier and welcome to the Dash community :slightly_smiling_face:

This site is awesome!

From your “about” page:

…got tired of obsessively watching weather forecasts to decide where to climb on the weekends. This tool weaves together historical weather observations and forecasts to create a single stop for ice conditions forecasting.

I can relate – I also obsessively watch weather forecasts – but it’s for planning flights in small airplanes. This site is useful for not only ice climbing but for anyone planning outdoor activities. It makes it possible to get the “big picture” weather patterns in a glance!


What a great way to showcase weather data. Really nice app, @crsaulnier . Thank you for sharing.

The app is going through a lot of information. Is this all free by the National Weather Service?

Great app! Is the source code available? I’d appreciate a repo, even if not reproducible. I just want to see how you use Dash components and follow your patterns in my work. Thanks!

:slight_smile: mazing application indeed, @crsaulnier .
I am actively building dash applications using plotly and sutff in julia, as a learning endeavour,
can’t wait for the day when my application will be showcased here .:slight_smile:


@adamschroeder - it is all free NWS data. I might add some less free data sources at some point - but there are still plenty of different places within the NWS where I can access other data streams.

@avm23 - I might open source the repo someday but for now it’s closed. I’d be slightly embarrassed at the current state of the codebase - it’s a little messy as I’ve been learning as I went and have defiantly done some things wrong along the way. My structure is just the build in pages capability and a few tricks I’ve picked up from various forum posts - nothing special.


Hello, Dash community!
I have been inspired by a lot of awesome open-source examples, lectures, and documentation in recent months. Thank you for your time and help!

I recently developed and deployed a Dash app for one of my coursework. It utilizes a Kaggle dataset (Two Sigma’s Renthop) to do data analysis, data visualization, customer interest level prediction, rental cost prediction, and an integration of the LLaMA model (HugChat API). I also plan to implement mobile view and continue to work on the LLaMA model (it is simply API calls for now)

This dataset is rich and Dash’s utilities are powerful so there are definitely ways to improve the app. Any feedback regarding the app or analysis is welcome! Thank you for the great community!

Repo: GitHub - mnguyen0226/rental_gpt_dash: Rental app with in-depth data analysis, interactive data visualization, predictive analytics, and chatbot using Dash.

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amazing app with so many features. Thank you for sharing, @minheapolis :pray:

I’m not sure why but I can’t get the Rental Cost Prediction page to work. When I click the button at the very bottom of the page, nothing happens. Do you know what might be the problem?

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Hello @adamschroeder ,
Thank you for your kind words and feedback! Yes, so the predicted values are being shown/updated on the right half of that tab.

I see your confusion now. For this design, I had the left half as tunning and the right half is for displaying results. A pop-up (Modal component) might be a better choice. Let me update the redesigned tab soon!

My Dash app covers cryptocurrency / stock analysis, also using regression models and various types of charts.

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I’m excited to share a project I’ve been working on: the Mental Health App. This project, developed as part of a data science assignment, is a deep dive into the world of mental health data. The goal was to create a Dash app using health data, and we chose to focus on mental health.

Experience the app live here: Mental Health Dash App

Check out our GitHub repo: GitHub Repository

Here are some previews:

I’d love to hear your thoughts and feedback!


Your app looks very clean and neat, but I saw a problem that when hovering on bar chart of Schizophrenia and Eating, it continuously blinking. Do you face with this problem?

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Thank you for your feedback.
Indeed, it’s a bug that I noticed when I started coding the application, then I completely forgot to fix it.

It’s now corrected, thank you again!

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awesome app, @rafalsza
Thanks for sharing.

Did you use Dash Mantine for the layout?
Are you planning to make the code open source?

Also, it’s interesting to see how the volatility of bitcoin is going down as it matures.
What is the correlation heatmap telling us exactly?

Interesting to see how anxiety appears to be going down after 65 years of age. Really cool app that raises awareness on the topic of mental health. Thanks for sharing, @tgy98

The correlation between an anxiety and GDP seems to be minimal. Does this look different with as a logarithmic scale?

I’ve implemented the log scale on the GDP axis, and it indeed presents the data more clearly across the wide range of values. Thanks for the suggestion!

Here with the Depressive disorder:

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Hello :wave:

I created a couple of articles about Dash (more than 1k+ claps on Medium) with their corresponding Dash applications:

All the code can be found here: Data-Visualization/Dash at master · pierpaolo28/Data-Visualization · GitHub

If there is anything else I can do, please just let me know :grinning:



I’ve made a lot of updates to and the layout is much more phone friendly. I’m using dash_breakpoints to have responsive navigation and also added caching of the NWS data to decrease latency. It is now possible to create a user account (using flask-login). If you make an account you can add custom areas to watch.

Unfortunately the NWS has an unplanned outage of their API this week - which they say will be resolved Jan 1st - so the site isn’t working for now as there is no data available - but should be populating with data again soon! is a portal which provides access to concentration data on atmospheric pollutants (sulphur, NOX, particles, etc.) made available by the French government’s OpenData platform.
It is made up of 3 applications which allow real-time visualization of pollutant levels in the air and present data analyses: full dataset, risk map.

This development is made up of technological building blocks, among them: Plotly with its famous RangeSlider component. In addition to graphic capabilities, its power also lies in ability to integrate into a native JS application, the interaction possibilities allowing for a fluid and efficient application despite large quantities of data.

I thank you for providing such efficient components.

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