Tad, a desktop application for viewing and analyzing tabular data | Hacker News Reader

Tad, a desktop application for viewing and analyzing tabular data

github.com

78 pointstosh17 comments

Try visidata.org for a lightweight and full featured command line application.

Thanks I remember liking this tool and then totally forgetting what it was called and failing to google it.

visidata (vd) is awesome.

I would also recommend dtale [0] for those who work with python, it is one pip install away. Demo is [1] make sure to check the play button in the top left corner.

[0]https://towardsdatascience.com/introduction-to-d-tale-5eddd8...

[1]http://alphatechadmin.pythonanywhere.com/dtale/main/1

People would pay good money for this if you could (1) put it in a Jupyter notebook, (2) create gui bindings for matplotlib.

The single biggest time-sink for me outside of research is back-and-forth with management about how results get presented to project sponsors.

An intuitive interface like this would allow me to pass off raw research to people who refine it for external consumption (people who care about ridiculous things like color schemes).

> Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook, care of PivotTable.js

-- https://github.com/nicolaskruchten/jupyter_pivottablejs

Great effort in visualizing the Pivot breakdown. Excel is amazing at what it does, though where it fails is when you have > 1 Million rows. R comes in handy in those situations. Recently came across http://pivottabler.org.uk/index.html which is fantastic and makes me not miss Excel!

Interesting fact: Although pivot table is a generic term, Microsoft trademarked PivotTable in the United States in 1994 (canceled in 2020).

https://en.wikipedia.org/wiki/Pivot_table

Why would I want this over Excel?

Maybe for users who don't pay for Office / Excel (This seems like a free alternative in this regard?)

Libre office has pivot tables although when I used them last, and that was a while ago, they weren't anywhere near as slick to use as excel's.

My question exactly. Looking at the screenshot: perhaps it's quicker to use if your use-case matches-or-is-simpler of what the program can do.

Better for programmers. We typically prefer working with csv files rather than Excel files. Most of our processing would be in code anyway so the extra features of Excel is just in the way.

I have actually personally never understood the point of Excel. Writing code in Excel is just more hassle than real code anyway IMHO.

I think because it's faster and simpler if you don't need the extra features of Excel. Like if you just want to look at a CSV as a table.

At least in my case, I looked at this app before because I needed to look at a lot of CSV files. Numbers (Excel equivalent on macOS) takes a longer time to open, and it's really bloated if you're just looking at a table

Electron.

In this case I wonder how well it handles big documents, that was always terrible for me in Atom, and only sort of workable in VS Code. Not that Excel can do really huge ones either, to be fair.

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