dython
dash
dython | dash | |
---|---|---|
2 | 56 | |
490 | 20,583 | |
- | 1.1% | |
7.7 | 9.6 | |
3 months ago | 6 days ago | |
Python | Python | |
MIT License | MIT License |
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dython
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How to interpret scatterplot regarding customer purchasing habits
Make a categorical heatmap instead (example see https://github.com/shakedzy/dython/issues/2)
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Time series prediction problem
to answer question one try just running a simple correlation matrix among your yearly and the average of your daily figures For years 2012+ when you have all four inputs. I frequently use the small convenience library Dython Dython in Github. If your features are very independent then you will not be able to fill in missing values and will need to find other surrogates such as “is my crop largely a fixed percentage of overall exports and are overall exports available for missing years?” If your features are highly dependent then essentially you don’t need them all - both XGBoost and LightGBM have simple fill-in-with-the-mean type imputation of missing values - run across all your data with imputation on and removing low impact features will remove all but one highly interdependent features.
dash
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dash VS solara - a user suggested alternative
2 projects | 13 Oct 2023
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[Python] NiceGUI: Lassen Sie jeden Browser das Frontend für Ihren Python-Code sein
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
- Visualizing parquet in s3 bucket for data analysis?
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Little guidance of a python newbie
You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.
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Launch HN: Pynecone (YC W23) – Web Apps in Pure Python
Useful list. Dash & bokeh as two more in the space
https://github.com/plotly/dash
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Python projects with best practices on Github?
I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.
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4 Streamlit Alternatives for Building Python Data Apps
Plotly is a plotting library, and Dash is their open-source framework for building data apps with Python, R or Julia. (Dash also has an Enterprise version, but we'll focus on the open-source library here.)
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NiceGUI: Let any browser be the frontend for your Python code
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
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Sharing interactive Plotly graphs
looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145
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Containerizing Shiny for Python and Shinylive Applications
Shiny is a framework that makes it easy to build interactive web applications. Shiny was introduced 10 years ago as an R package. In his 10th anniversary keynote speech, Joe Cheng announced Shiny for Python at the 2022 RStudio Conference. Python programmers can now try out Shiny to create interactive data-driven web applications. Shiny comes as an alternative to other frameworks, like Dash, or Streamlit.
What are some alternatives?
RocketPy - Next generation High-Power Rocketry 6-DOF Trajectory Simulation
streamlit - Streamlit — A faster way to build and share data apps.
flopy - A Python package to create, run, and post-process MODFLOW-based models.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Machine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
panel - Panel: The powerful data exploration & web app framework for Python
viper - Simple, expressive pipeline syntax to transform and manipulate data with ease
uvicorn - An ASGI web server, for Python. 🦄
Flask - The Python micro framework for building web applications.
nicegui - Create web-based user interfaces with Python. The nice way.
PyWebIO - Write interactive web app in script way.
reflex - 🕸️ Web apps in pure Python 🐍