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In Dispatch #11
- Version Check
- Plotly’s 10 Year Anniversary
- Dash-ChatGPT App Challenge Winners
- Plotly Blogs
- Component of the Month
- App of the Month
- Things Happen
- Dash Enterprise Platform 5.1 (announcement)
- Dash Open Source Framework 2.12.1 (changelog)
- Plotly.py 5.16.1 (changelog)
- Plotly.js 2.25.2 (changelog)
Plotly was founded in August 2013. Since then, with help from our customers, investors, and the incredible Dash community we’ve empowered data science teams to build ground-breaking data apps and enabled data-driven decision making.
A few fun birthday stats:
- 10 million monthly downloads of Plotly Python library (!!)
- 2 million monthly downloads of Dash
Check out this article to read reflections of the past 10 years of Plotly, from founders and executive team.
Thank you everyone for participating in the Dash-ChatGPT App Challenge. Eleven incredible apps were submitted by the community!
Over the last couple of weeks, a group of Plotly staff judges had the pleasure of reviewing each app and voted for the top three app winners. And the winners are…
This app is astonishing: Upload a dataset and ask the app to visualize things for you. The app will make graphs with Plotly, figure out the variables in your dataset, and generate the code.
A game where you test your ability to distinguish quotes generated by ChatGPT from those written by humans. Can you find the AI?
We loved this app for its creativity, clean design, and fun approach to AI, demonstrating the capabilities of ChatGPT and AI powered chatbots. It quickly captured our attention and played multiple times trying to outsmart the machine.
A great app that shows how sophisticated UI/UX can be built using the Dash framework. This app allows users to ask questions about specific publications and research papers in the field of thyroid cancer.
It simplifies the complex topic of cancer through ChatGPT, and it indicates the number of publications it examined to generate the answer. The Information Retrieval Animation was also unique in that the graph showcased gene regulation and correlations extracted from the literature. Each graph line represents a scientific article connecting two nodes, enabling users to retrieve information by clicking individual lines.
Join us on August 30 to see these winning apps in action. This is a great opportunity to see just how much is possible with open source Dash.
Check out these recent pieces from our new blog page:
- Creating an Interactive Web App with Matplotlib, Python, and Dash
- Build Python Web Apps for scikit-learn Models with Plotly Dash
- Reflections from an Athlete — Dash feat. Strava
- Performance Optimizations for Geospatial Dash Apps
- How Polars Can Help You Build Fast Dash Apps for Large Datasets
- Automating and Streamlining Digital Marketing Workflows with Plotly and Dash
calplot takes a pandas dataframe with a date column and a value column and generates a beautiful calendar heatmap. Get started just
pip install plotly-calplot.
from plotly_calplot import calplot import pandas as pd df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/2016-weather-data-seattle.csv") df.Date = pd.to_datetime(df.Date) df_filtered = df[(df['Date'] > '2012-01-01') & (df['Date'] < '2015-12-31')] fig = calplot(df_filtered, x="Date", y="Max_TemperatureC", title="Seattle Max Temperatures", showscale=True, name='Max temp', colorscale='icefire') fig.show()
Thank you Bruno for creating this library and sharing it with the Plotly Dash community.
This Earthquake Data Visualization app created by Adilet explores the history of earthquakes around the world.
As Adilet explains on the forum, this app allows users to observe and delve into more than 8000+ significant earthquakes (with a magnitude of 6 or higher) recorded from January 1st, 1960, to July 16th, 2023. The data used comes from the US Geological Survey website.
Thank you Adilet for creating this app and submitting it for consideration to be part of the Dash Explore Page.
Github link: GitHub - AdiletBaimyrza/data_visualization: Earthquake Data Visualization Dashbooard WebApp built using Dash low-code framework and Pandas library for data cleaning and preparation in Python Language allows you to observe and analyze more than 8000 earthquakes from 1960 till 2023. Data obtained from United States Geological Survey Website.
See more Dash apps or share your own in the Community Forum’s Show and Tell tag. If you would like your app to be considered for the next edition of the Dash Club newsletter, please message Adam on the Forum.
Congratulating Plotly for our 10 year anniversary and for crossing the 10 million monthly downloads milestone, community member, Danny, gifted us with this awesome app.
Thank you to Sébastien for the incredible contributions to the documentation of our new Dash Ag Grid library, with close to 150 commits in the last 3 months.
The latest stable version of Dash AG Grid 2.3.0 was just released.
Plotly 5.15.0 was recently released adding support for multiple legends, label aliases, dynamic shape annotations, and more.
Plotly at Databricks Summit: Dave, Rick, Rob, Claire, and a few other Plotly staff members had the pleasure of attending the Databricks Data + AI Summit in San Francisco.
Long-time community member, Renaud, built a new Dash component called dash_intersection_observer, which allows the triggering of callbacks when elements of the app become visible in the viewport. Check out the Forum post.
Community member, Snehil, is working on the next version of the famous dash-mantine-components, which will be based on the latest Mantine library (v6), adding a few new helpful components on top of the already existing 75.
Job postings from around the world looking for Dash skills including spots at SpaceX, HP, S&P Global, and more.
Check out our recent video tutorial on Building a Python Front End for Your Scikit Learn Models.
Celebrating our top contributors in July.
Have a great weekend –
Chris & Adam