GS-Calc – A modern spreadsheet with Python integration
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…
GS-Calc – A modern spreadsheet with Python integration launched on April 25, 2025 with 112 votes, #435 of 7,818 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
GS-Calc is a spreadsheet application designed for processing large datasets, supporting files up to 32 million rows and 1 million columns that load in seconds. It integrates Python functions as custom formulas capable of returning images and CSV files, includes statistical pivot functions and a solver with virtually unlimited variables, and renders charts with millions of data points instantly. The tool is built for data analysts and developers who need to handle gigabyte-scale data without crashes while maintaining full in-place editing and file manipulation capabilities.
written from the facts on this page · September 2026
From the sources
GS-Calc - a spreadsheet with 12 million rows and 16K columns that will let you make the best of your hardware. Load e.g. 4GB+ workbooks with 0.5B cells in half a minute. Execute 12M vlookups searching 12M rows in seconds using up to 64 processor cores.
GS-Calc is a modern spreadsheet with unique capabilities for handling large datasets. You can edit large CSV files with millions of rows, and handle XLSX files beyond Excel's 1-million-row limit, automatically split and merged to match GS-Calc's native 32-million-row worksheets. With GS-Calc you can build complex data models containing, for example, millions of binary look-up formulas in a file that is opened, saved and updated almost instantly. Videos created on Intel Core i5-7500 @3.40GHz / 16GB RAM; CPU benchmark 8K [ vs 60K for Intel Core i9-13900K ] Using a 2.37GB workbook file with i5, 16GB RAM & HDD: 32 million formulas and 300 million random number/text cells. Using MonteCarlo…from citadel5.com
In the maker’s words, at launch
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…
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