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Startup Metrics in SQL and Python

by LucidPlexus
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Growth, churn, runway and cohorts from monthly startup data, with the check to run before quoting each. Two A4 pages on the measures a portfolio review is built from, written on the monthly records of the 91 funded startups in Worth Backing?…
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Growth, churn, runway and cohorts from monthly startup data, with the check to run before quoting each.

Two A4 pages on the measures a portfolio review is built from, written on the monthly records of the 91 funded startups in Worth Backing? (Lanternfield, USD). Every query and script was run, in DuckDB SQL (the LucidPlexus workbench engine) and in pandas, and its real result is printed under it.

It covers month-over-month growth when a month is missing, portfolio growth against like-for-like growth, the customer identity (end = start + new − lost), churn with its denominator stated and the four numbers it gets quoted as, new, lost and net new customers, burn and runway as of a date, and cohorts by first month counted against the startups old enough to be counted.

The data is the raw teaching copy, and the sheet shows its faults where they change a number: a copied row that makes December's portfolio revenue jump 88.7%, two missing months, a negative count of lost customers, and a 0% churn rate on 15 to 22 customers.

PDF to print, and an HTML version to read on screen.

#cheat-sheet #data-analysis #duckdb #pandas #sql #startups
Type Cheat Sheet
Pages 2
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