* process large (e.g. 4GB+) data sets in a spreadsheet;
* load GB/32 million-row files in seconds and use them without any crashes;
* 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;
* create and display all popular chart types with millions of data points instantly.
Suggestions for improvements are welcome (and often implemented quite quickly).
* process large (e.g. 4GB+) data sets in a spreadsheet;
* load GB/32 million-row files in seconds and use them without any crashes;
* 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;
* create and display all popular chart types with millions of data points instantly.
Suggestions for improvements are welcome (and often implemented quite quickly).