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=Towards unique names= Steps:#Put all the names in one text file (done)#Sort the file and removed exact dups using textpad (done)#Run the matcher on that file in mode 2 (rerun)#Clean that match file manually for idiosyncractic issues (rerun - only 2 problems)#Load all 7 base files into a dbase#Load the matchfile into the dbase#Use SQL to get the unique names for each entry in a base file (7 queries)#Assemble all of the common variables together taking the best available (somewhat subjective) in SQL, and add the extra vars.#Output the new master file to work with!  =Startup Map= '''Total Unique Startup Names: 14181451'''
'''Total Unique Accelerator Names: 13'''
'''Houston Startup Sources:'''
*AngelList500**Joined 396393**Signal 437394**Total Raised 207204***Total Raised is actually made Redundant by the other 2 Angel List Pulls
*HoustonStartupsList 283
*StartupBlinkMap 381379
*Startups-Accelerators 292
*SDC VC Houston Port Cos 494493*CrunchBase 116*StartHouston 27
*Cohort of accelerator
*Industry
 
=To Do=
 
Nexp Steps:
*Standardize names
*Match up SQL tables
*Use URLs to find missing addresses
**Does it matter if website now reroutes to new URL?
*Remove non Houston Startups
*Import into Individual Wiki Pages
*Import into Map
*Repeat Process with:
**Accelerators
**Angels
**Incubators
**Angel Groups
**Venture Capital
**Service Firms
**Co-Working Spaces
**Event Spaces
 
=Future=
 
Possible Expansions:
*Calendar that correlates with the map
*Proximity measures & Microgeography
*Weak/Strong Areas in Houston for Entrepreneurship
*Comparing accelerators based on funding
**https://www.propublica.org/
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