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Show HN: D-Tale, easy to use pandas GUI
1 project | news.ycombinator.com | 1 Nov 2021
Added visualizations of statsmodels time series analysis functions to the free pandas visualizer, D-Tale
1 project | reddit.com/r/algotrading | 31 Oct 2021
Just added "Time Series Analysis" in v1.60.1 of D-Tale on pypi & conda-forge: pip install -U dtale conda install dtale -c conda-forge This feature provides a quick and easy way to visualize the usage of the following time series analysis function in statsmodels:
Show HN: Open-source pandas dataframe visualizer
1 project | news.ycombinator.com | 5 Aug 2021
For all the python/pandas users out there I just released a bunch of UI updates to the free visualizer, D-Tale
Here is the list of direct dependencies. I think the majority of the packages I'm using are pretty well-known. Maybe some of the plotly dash packages are aren't as well known (like dash-colorscales) and then some calculation-based packages (squarify, ppscore, missingno) might not be widely used. But as far as I can tell they are harmless. We used D-Tale at my company in an enterprise-style way through jupyterhub.
Hope these help & please support open-source by throwing your star on the repo.
Mostly reliant on pandas since this is a tool specifically designed for pandas. That being said it would be really easy for you to write a simple DB loader to that takes any SQL and returns the results in a pandas dataframe and just pass that to D-Tale. Its actually pretty easy to integrate D-Tale into your own flask/django/streamlit apps. Heres documentation about using it in Flask: https://github.com/man-group/dtale/blob/master/docs/EMBEDDED_FLASK.md
The jupyterhub-server-proxy plugin works great with it. Here's some documentation on how to use it: https://github.com/man-group/dtale#jupyterhub-w-jupyter-server-proxy
These are the most engrossing UI changes I've made in a while so please let me know if you run into any issues. You can play around with them on the demo site (please note that the "Github Fork" link covers the close button for the "sliding side panel" but you can close it using your ESC key). If these changes prove to be easier to use then I can start moving more functionality towards the "sliding side panel" rather than the old popup windows/tabs.
Your data is stored in memory so the size of your dataframe is limited to the memory of your machine. That being said we’ve allowed users to swap out the machanism which stores the data so you can use something like Redis or Shelve to allieviate memory. Here’s some documentation: https://github.com/man-group/dtale/blob/master/docs/GLOBAL_STATE.md
When you've created a finalised dataframe, do any of you convert it into an excel document to help you visualise your data, or am I being inefficient in doing this?
2 projects | reddit.com/r/datascience | 7 Apr 2021
What are some alternatives?
PandasGUI - A GUI for Pandas DataFrames
pandas-profiling - Create HTML profiling reports from pandas DataFrame objects
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
sqliteviz - Instant offline SQL-powered data visualisation in your browser
pandastable - Table analysis in Tkinter using pandas DataFrames.
Graphia - A visualisation tool for the creation and analysis of graphs
siuba - Python library for using dplyr like syntax with pandas and SQL
Numba - NumPy aware dynamic Python compiler using LLVM
best-of-generator - 🏆 Generates a ranked list of awesome libraries and tools.
pywsitest - PYthon WebSocket Integration TESTing framework
catwiki - CatWiki is a simple wiki that stores its articles as text files
missingno - Missing data visualization module for Python.