GS

GS-Calc – A modern spreadsheet with Python integration

Hacker News

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

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

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