←back to thread

Show HN: GS-Calc – A modern spreadsheet with Python integration

(citadel5.com)
94 points jpiech | 4 comments | 25 Apr 25 18:17 UTC | HN request time: 0.274s | source

Process large (e.g. 4GB+) data sets in a spreadsheet.

Load GB/32 million-row files in seconds and use them without any crashes using up to about 500GB RAM.

Load/edit in-place/split/merge/clean CSV/text files with up to 32 million rows and 1 million columns.

Use your Python functions as UDF formulas that can return to GS-Calc images and entire CSV files.

Use a set of statistical pivot data functions.

Solver functions virtually without limits for the number of variables.

Create and display all popular chart types with millions of data points instantly.

Suggestions for improvements are welcome (and often implemented quite quickly).

1. tianqi ◴[25 Apr 25 23:27 UTC] No.43799435[source]▶
It is an interesting tool. I've been struggling with Office Excel's inability to open large files. I always work with csv in python, and if a client must review the data in Excel, I take a random sample to generate a smaller file, then explain to the client that we can't open the whole in Excel. This really doesn't seem like a modern work.

"a slow, old pc with 8GB RAM"

By the way, this struck me like a humour of era. Oh god it has 8GB RAM. Cheers! To the good old days.

replies(2): >>43800204 #>>43801703 #
2. arvindh-manian ◴[26 Apr 25 01:49 UTC] No.43800204[source]▶
I've been using Tad [0] for this purpose, as it streams in the data.

[0] https://www.tadviewer.com

3. samzub ◴[26 Apr 25 07:51 UTC] No.43801703[source]▶
Fully agree, I have found that above 300k rows Excel struggles even on a good laptop. Not even mentioning the Python integration into MS Excel that is so unbearably slow that it is much better performing the calculations outside of Excel first.

I am sold on the website looks and license model!

replies(1): >>43802013 #
4. microflash ◴[26 Apr 25 09:04 UTC] No.43802013[source]▶
These days I use DuckDB to read massive excel files. DuckDB now ships with a nice local UI and it also works beautifully with Datagrip, my preferred database IDE. With SQL, it just becomes a matter of applying old grease to do whatever analysis I want.