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…
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
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 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).
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