dtale-desktop
sweetviz
| dtale-desktop | sweetviz | |
|---|---|---|
| 7 | 1 | |
| 156 | 2,841 | |
| - | - | |
| 2.6 | 6.7 | |
| about 3 years ago | 5 months ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dtale-desktop
- I made a data dashboard web app which you can interactively build by writing python code IN the dashboard. It's available as a python package, and contributors are very welcome! (and I actually need some)
- I made a data dashboard web app which you can interactively build by writing python code IN the dashboard. It's available as a python package, and contributors are welcome!
- Show HN: Dtaledesktop – organize your Python scripts into a data viz dashboard
-
Hi pandas lovers - I released a package for easily converting your python scripts into data visualization dashboards (dtale/fastapi/react)
It can be run both locally and as a web service -- the demo site is actually running on a kubernetes cluster. When run as a web service, it uses websocket connections to push real-time updates, ensuring that all connected users see the same thing. There are a large number of settings which can be used to configure exactly how it behaves, documented [here](https://github.com/phillipdupuis/dtale-desktop#settings).
-
If you use python/pandas/dtale for analysis, I released a free and open-source GUI for organizing your random python scripts into a data visualization dashboard
Also, if you want to you can run it as a web service -- the demo site is actually running on a kubernetes cluster. When run as a web service, it uses websocket connections to push real-time updates, ensuring that all connected users see the same thing. There are a large number of settings which can be used to configure exactly how it behaves, documented here.
-
Need Help to understand importlib module
Inspiration taken from here: https://github.com/phillipdupuis/dtale-desktop/blob/master/dtale_desktop/source_code_tools.py#L20, in that case it's being used to execute text users write in a web browser as python code (text sent to server > server writes it to tempfile, turns the tempfile into a module, executes the code in the module, sends the result of executing that code back)
sweetviz
-
Automated Data Profiling and Attribute Clustering using unsupervised ML techniques
Take a look at this package which computes associations between variables and other viz and can infer some types https://github.com/fbdesignpro/sweetviz
What are some alternatives?
dtale - Visualizer for pandas data structures
dataprep - Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
jupyterlab-autoplot - Magical Plotting in JupyterLab
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
chord - Engaging visualisations, made easy.
popmon - Monitor the stability of a Pandas or Spark dataframe ⚙︎
hyperglass - hyperglass is the network looking glass that tries to make the internet better.
mlgauge - A simple library to benchmark the performance of machine learning methods across different datasets.
Numba - NumPy aware dynamic Python compiler using LLVM
lux - 👾 Fast and simple video download library and CLI tool written in Go