Difference between revisions of "VC Database Rebuild"
Line 121: | Line 121: | ||
FROM (SELECT DISTINCT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)a; | FROM (SELECT DISTINCT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)a; | ||
--44770 | --44770 | ||
− | By looking at the counts you can see that there is still 1 duplicate key in the table. Let's find it another way. | + | By looking at the counts you can see that there is still 1 duplicate key in the table. Let's find it another way. Running the query below finds the key (coname, statecode, datefirstinv) that appears twice in the table. |
+ | SELECT * | ||
+ | FROM (SELECT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)AS key | ||
+ | GROUP BY coname, statecode, datefirstinv | ||
+ | HAVING COUNT(key) > 1; | ||
+ | The output looks like this: | ||
+ | coname | statecode | datefirstinv | ||
+ | ----------------------------+-----------+-------------- | ||
+ | New York Digital Health LLC | NY | 2015-08-13 |
Revision as of 14:30, 17 July 2017
Contents
Plan
Rebuild roundbase, round, geo, ipos, mas from SDC data. Create companybase from roundbase Create round from roundbase. Build stageflags from round.
Clean companybase by putting flags for Undisclosed Company, US location. Check if key (coname, statecode, datefirstinv) is valid. Remove duplicates manually/update command from roundbase. Check if round key is valid. Remove duplicates.
Build statelookup tables and roundlookup tables.
Clean firmbase tables. Clean ipo tables. Clean mas table.
Run matcher on ipos, companybase. Matcher on mas, companybase. Fix duplicate matches.
Join ipos and companybase. Check if count is valid. Fix match as required. Pull ipo key into companybase and companybase key into ipo table first. Then join.
Join mas and companybase. Check if count is valid. Fix match as required. Pull mas key into companybase and companybase key into mas table first. Then join.
Join ipocompanybase with macompanybase to get a table of portcos, ipos and mas.
Calculate exit date based on ipo, ma, datelastinv + 5 years.
Pull in sel flag into companybase and build dead or alive flag.
Match geodata to companybase. Pull geokey into companybase table. Lookup addresses to get geo data as required using geo.py.
Clean fundbase and check valid key (fundname, statecode, firstinvdate)
Clean firmbase and check valid key (firmname, foundingdate)
Loading starting data into database
Database is named vcdb2. It is located in /bulk/VentureCapitalData/SDCVCData. Launch with psql vcdb2. Load the following tables by running the commands below. Make sure the sql scripts and data txt files are all located in the folder. Check that the line numbers copied into your new tables match the line numbers in the Load files.
\i LoadFunds.sql \i LoadIPOs.sql \i LoadRoundbase.sql \i LoadFirms.sql \i LoadGeoData.sql \i LoadLongDescription.sql \i LoadRound.sql
Creating Base Tables
Create the base tables, companybase and round, by running the following scripts. These are the initial tables you will need to clean and join in order to get the master tables.
DROP TABLE companybase; CREATE TABLE companybase AS SELECT DISTINCT coname,updateddate,foundingdate,datelastinv,datefirstinv,investedk,city,description,msa,msacode,nationcode,statecode,addr1,addr2,indclass,indsubgroup3,indminor,url,zip FROM roundbase ORDER BY coname;
DROP TABLE round; CREATE TABLE round AS SELECT DISTINCT coname,statecode,datefirstinv,rounddate,stage1,stage3,rndamtdisck,rndamtestk,roundnum,numinvestors FROM roundbase ORDER BY coname;
Creating Stage Flags Table
Stage flags will be used to later on to determine if a company received seed, early or later stage financing. The growthflag is '1' if either the seed, early or later flags is '1'. The exclude flag is used to exclude all companies that received financing for activities we are not interested in and thus should be excluded from our dataset. Entries like 'Open Market Purchase', 'PIPE', etc are the things that the exclude flag filters out. It is built off the round table.
DROP TABLE stageflags; CREATE TABLE stageflags AS SELECT coname, statecode, datefirstinv, rounddate, stage3, CASE WHEN stage3 = 'Seed' THEN 1::int ELSE 0::int END AS seedflag, CASE WHEN stage3 = 'Early Stage' THEN 1::int ELSE 0::int END AS earlyflag, CASE WHEN stage3 = 'Later Stage' THEN 1::int ELSE 0::int END AS laterflag, CASE WHEN stage3 = 'Seed' OR stage3 = 'Later Stage' OR stage3 = 'Early Stage' THEN 1::int ELSE 0::int END AS growthflag, CASE WHEN stage3 = 'Acq. for Expansion' OR stage3 = 'Acquisition' OR stage3 = 'Bridge Loan' OR stage3 = 'Expansion' OR stage3 = 'Pending Acq' OR stage3 = 'Recap or Turnaround' OR stage3 = 'Mezzanine' THEN 1::int ELSE 0::int END AS transactionflag, CASE WHEN stage3 = 'LBO' OR stage3 = 'MBO' OR stage3 = 'Open Market Purchase' OR stage3 = 'PIPE' OR stage3 = 'Secondary Buyout' OR stage3 = 'Other' OR stage3 = 'VC Partnership' OR stage3 = 'Secondary Purchase' THEN 1::int ELSE 0::int END AS excludeflag FROM round;
Cleaning the Companybase table
Every table will contain some duplicate keys and erroneous entries. We're going to clean the companybase table so that every key (coname, statecode, datefirstinv) is unique. This means that there will be a 1:1 relationship between 1 key and 1 entry. Given an entry you will be able to create a unique key and given a coname, statecode, datefirstinv key you will be able to find exactly 1 entry that the key corresponds to in the companybase table set.
So first check to see if the key is valid on the base data using the following 2 queries.
SELECT COUNT(*) FROM (SELECT coname, statecode, datefirstinv FROM companybase)a; --44774
SELECT COUNT(*) FROM (SELECT DISTINCT coname, statecode, datefirstinv FROM companybase)a; --44771
You can see that they key is not unique because the counts don't match up. There are 44,771 distinct keys but there are 44,774 keys in the companybase table. So 1 key can match to more than one entry in the table. Some of the data in the companybase table contains undisclosed company names and companies that exist in other countries outside the US. So let's build flags for these two events and check the key count again.
DROP TABLE companybase1; CREATE TABLE companybase1 AS SELECT *, CASE WHEN nationcode = 'US' THEN 1::int ELSE 0::int END AS alwaysusflag, CASE WHEN coname = 'Undisclosed Company' THEN 1::int ELSE 0::int END AS undisclosedflag FROM companybase;
SELECT COUNT(*) FROM (SELECT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)a; --44771
SELECT COUNT(*) FROM (SELECT DISTINCT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)a; --44770
By looking at the counts you can see that there is still 1 duplicate key in the table. Let's find it another way. Running the query below finds the key (coname, statecode, datefirstinv) that appears twice in the table.
SELECT * FROM (SELECT coname, statecode, datefirstinv FROM companybase1 WHERE alwaysusflag = 1 AND undisclosedflag = 0)AS key GROUP BY coname, statecode, datefirstinv HAVING COUNT(key) > 1;
The output looks like this:
coname | statecode | datefirstinv ----------------------------+-----------+-------------- New York Digital Health LLC | NY | 2015-08-13