\dt
4) Perform regular SQL queries
==Incubators in Crunchbase==
\COPY (SELECT uuid, company_name, short_description FROM Organizations WHERE country_code='USA' AND short_description LIKE '%incubat%') TO
'CrunchbaseShortOrgDescsUSAIncubat.txt' WITH DELIMITER AS E'\t' HEADER NULL AS CSV
--466
\COPY (SELECT A.uuid, A.company_name, B.description FROM Organizations AS A JOIN organization_descriptions AS B on A.uuid=B.uuid WHERE
country_code='USA' AND description LIKE '%incubat%') TO 'CrunchbaseLongOrgDescsUSAIncubat.txt' WITH DELIMITER AS E'\t' HEADER NULL AS CSV
--933
The two queries above were run against the Crunchbase database (see [[Ecosystem Organization Classifier]]), then their results were manually reviewed in two xlsx files (CrunchbaseLongOrgDescsUSAIncubat_IncubatorScore and CrunchbaseShortOrgDescsUSAIncubat_IncubatorScore), stored in E:\projects\crunchbase3
These files were then combined into IncubatorsFromCrunchbase.xlsx providing they scored 1 in the Long file or were marked keep and did not score 0 (social impact or virtual) in the Short file. The file has 564 (not necessarily unique) records and the following columns:
uuid company_name description Score Notes Source
RetrievingIncubators.sql was then modified to load this data, locate distinct UUIDs and output Organizational records. The resulting file is CrunchbaseIncubators.txt (456 records, all USA), which has the following fields:
company_name uuid address city state_code region status domain category_list short_description