Mito – Excel-like interface for Pandas dataframes in Jupyter notebook

• datasette

  187 8,881 9.2 Python

  An open source multi-tool for exploring and publishing data

Looks like a Datasette[0] clone which runs on top of something (jupyter) which runs on top of Python (ipython). I think I would like to see how much time it takes to open a massive dataset in Mito & in Datasette :P

[0]: https://datasette.io/

• mito

  18 2,210 10.0 Python

  The mitosheet package, trymito.io, and other public Mito code.

  

Mito is open source, but using Pro features does actually require a Pro or enterprise license. You can check out this callout in the license [1], as well as the restrictions on Mito Pro features here [2]. We're in the process of fixing up the upgrade to Pro process a bit... as you can tell... :)

You can of course fork Mito and turn off telemetry as long as you open source your changes! Go for it - happy to hop on a call and help you get set up with the codebase, if you want. Yay open source!

[1] https://github.com/mito-ds/monorepo/blob/974091b455950c6c50e...

• InfluxDB

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• qgrid

  6 3,028 0.0 Python

  An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks

  

I played around with many of these before:

https://github.com/quantopian/qgrid

• dtale

  46 4,539 8.5 TypeScript

  Visualizer for pandas data structures

  

https://github.com/man-group/dtale

I find that I'm actually a lot faster using basic Pandas methods to get the data I want in exactly the form I want it.

If I really want to show everything, I just use:

'''

• pandas-profiling

  1 8,962 8.5 Python

  Discontinued Create HTML profiling reports from pandas DataFrame objects [Moved to: https://github.com/ydataai/pandas-profiling] (by pandas-profiling)

  

For those who are going through the thread finding new tools: pandas-profiling[0] is a library for automatic EDA (part of what bamboolib[1] does).

[0]: https://github.com/pandas-profiling/pandas-profiling

• vegafusion

  2 288 8.7 Rust

  Serverside scaling for Vega and Altair visualizations

  

One cool library I saw recently for helping on the visualisation side is https://github.com/vegafusion/vegafusion

It allows you to use Altair in Python for visualising data, but does the computation in the backend using Arrow DataFusion. Not for 15GB perhaps, but cool nonetheless.

• lux

  6 4,915 2.2 Python

  Automatically visualize your pandas dataframe via a single print! 📊 💡 (by lux-org)

  

• WorkOS

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• Altair

  42 8,892 9.0 Python

  Declarative statistical visualization library for Python

  

If you can write visualisations in Python itself, I am a big fan of Altair's syntax (https://github.com/altair-viz/altair), which is based on vega-lite. A while back, I wrote a brief guide and comparison of the main plotting libraries: https://datapane.com/reports/87NNEJ7/the-ultimate-guide-to-p...

One benefit of having them in actual code is that you can programmatically automate the creation of things like dashboards and reports. For instance, schedule a script to share an interactive plot every Monday morning, or build a live dashboard that updates every 10m. This opens up a lot of possibilities that would be impossible in a traditional drag-and-drop tool.

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