Difference between revisions of "Patent Assignment Data Restructure"
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Postcode should always be at the end of addrline1, addrlin2 or city. Exclude P.O. BOX #. | Postcode should always be at the end of addrline1, addrlin2 or city. Exclude P.O. BOX #. | ||
For example, the SQL code to extract postcode and state from addrline1 is: | For example, the SQL code to extract postcode and state from addrline1 is: | ||
| − | SELECT SUBSTRING(addrline1, '\d{5}') | + | SELECT addrline1, SUBSTRING(addrline1, '\d{5}') postcode_candid, |
| − | SUBSTRING(addrline1, '[,]\s{1,}\w{1,}\s{0,}\w{0,}\d{5}') | + | REPLACE(REPLACE(SUBSTRING(addrline1, '[,]\s{1,}\w{1,}\s{0,}\w{0,}\d{5}'),'\d{5}',''),',','') |
| + | state_candid | ||
FROM ptoassigneend_us_temp2 | FROM ptoassigneend_us_temp2 | ||
| − | WHERE | + | WHERE addrline1 ~* '\d{5}$' |
| − | AND NOT (addrline1 ~* ' | + | AND NOT (addrline1 ~* 'BO') AND NOT (addrline1 ~* 'P[.]O[.]'); |
| − | Examples: | + | Examples: |
| + | 181 METRO DRIVE SUITE 520 SAN JOSE, CA 95110 | 95110 | , CA 95110 | ||
| + | 11065 ROSELLE STREET SAN DIEGO, CALIFORNIA 92121 | 11065 | , CALIFORNIA 92121 | ||
| + | 400 MARGARET STREET, NO. 20 PLATTSBURGH, NEW YORK 12901 | 12901 | | ||
====Clean city & state==== | ====Clean city & state==== | ||
Revision as of 16:58, 27 April 2017
| Patent Assignment Data Restructure | |
|---|---|
| Project Information | |
| Project Title | Patent Data Restructure |
| Owner | Marcela Interiano, Sonia Zhang |
| Start Date | 201701 |
| Deadline | 201705 |
| Keywords | Patent, Data |
| Primary Billing | |
| Notes | |
| Has project status | Active |
| Subsumes: | Patent Data (Wiki Page), Patent Data Cleanup - June 2016, Patent Data Extraction Scripts (Tool), USPTO Bulk Data Processing |
| Copyright © 2016 edegan.com. All Rights Reserved. | |
In order to restructure the current patent dataset, the data requires rigorous cleaning. The primary areas for improvement are:
- 1. Clean ptoassignment table to unique keys.
- 2. Clean ptoproperties to remove nonutility patents. The patent numbers currently include:
- 7 digit patent numbers
- application numbers
- unknown numbers that cannot be matched to patent numbers in the patent table
- 20090108066
- 20100007288
- 20090108066
- 20100110022
- Design and Reissue patents ('%D%' or '%RE%')
- alphanumeric character strings
- 3. Restructure address information in ptoassignee table to extract meaningful information
- 4. Verify that cleaned patent documentids correspond to patent numbers or application numbers in the patent table
- 5. Restructure address information in ptoassignment table
- 6. Transform structure of the dataset
Contents
Semester Plan
The final deliverable for the semester is a table with the following structure:
Reel No | Frame No | Invention Title | Filing Date | Patent No | Application No | Publication No | Match By
The schema of the table will be:
Column | Type | Modifiers -----------------+-----------------------+----------- Reel No | integer | Frame No | integer | Invention Title | character varying(500)| Filing Date | date | Patent No | integer | Application No | integer | Publication No | integer | Match By | integer |
Currently the pto tables contain varying identifiers for one invention title that is involved in a reassignment. The purpose of the table is to have each identifier for an invention title listed in a single row, making it easy to track the invention through various transactions. The Match By column will inform the user which identifier should be used to match to other tables in the patent database.
Data Cleanup Progress
Patent Number Cleanup
The goal is to only have assignment records on utility patents. The patents in ptoproperty include alphanumerics which represent reissue and design patents as well as mistakes in the data input. Additionally, the documentids include application numbers or ids and publication numbers. The ptoproperty table stores the patent ids as character strings.
First the duplicates were dropped from the ptoproperty table creating ptoproperty_cleaned.
SELECT COUNT(*) FROM (SELECT DISTINCT * FROM ptoproperty) As T; --27266638 SELECT COUNT(*) FROM ptoproperty_cleaned; --27266638
Next, the Reissue and Design patents were removed.
SELECT COUNT(*) FROM ptoproperty WHERE documentid LIKE 'RE%'; --38512
SELECT COUNT(*) FROM ptoproperty WHERE documentid LIKE 'D%'; --1128247
Restructure Address Information (First Stage)
Note: This section was worked on by Sonia Zhang
The dbase is patent.
The table is ptoassigneend.
SQL code and other things are in:
E:/McNair/Projects/PatentAddress
IO files are on the dbase server in:
Z:/PatentAddress
To do
In no particular order:
- Remove city, state, zip, country from addrline1 & addrline2 to get clean addrlines.
- Maybe concatenate addrline1 and addrline to make addrline
- Identify clean data (e.g. City that is a city, zip that is a zip, state that is a state)
- By pattern, length, match to list
- Try some more patterns, perhaps with a slightly higher false positive rate, on the remaining uncleaned data
- Iterate!
Introduction
Currently done:
- Five features (addrline1, addrline2, city, state, postcode) in the table contain address information.
- Features addrline1, addrline2 and city are not cleaned. They can have suite, street, city, state and postcode information, or any combination of these
- The first object of this project is to extract postcode, state and city information from the three features above (Section 2.2.2).
- Then, we summarize the postcode, state and city information in the original table and those extracted from addresses to generate only one postcode, state and city for each record (Section 2.2.3).
- For now, we only focus on American patents.
Extract Address Information
So far these instructions apply to:
- Records identified as US (by zip code or country feature) ~3.5m records
- Those that well-formatted zip code (5-4) in addrline1, addrline2, and city (not postcode, etc) ~5,000 records
To get the record identified as US, we make the table:
- ptoassigneend_allus
This table contains all the U.S. patents extracted from ptoassigneend table. The rule to generate this table is 'country = 'UNITED STATES' ' if any of the features contains U.S. postcode.
Noise exists because of postcode errors.
The ptoassigneend_allus table may miss some U.S. patents which lose postcode records.
SQL code:
CREATE TABLE ptoassigneend_allus AS
SELECT * FROM ptoassigneend
WHERE city ~* '.*\d{5}[-]\d{4}.*' OR addrline1 ~* '.*\d{5}[-]\d{4}.*' OR
addrline2 ~* '.*\d{5}[-]\d{4}.*' OR postcode ~* '.*\d{5}[-]\d{4}.*' OR
country ~* 'UNITED STATES';
SELECT 3572682
Table "public.ptoassigneend_allus" Column | Type | Modifiers ----------| -----------------------|----------- reelno | integer | frameno | integer | name | character varying(500) | addrline1 | character varying(500) | addrline2 | character varying(500) | city | character varying(500) | state | character varying(500) | country | character varying(500) | postcode | character varying(80) |
Postcode
U.S. postcode should follow the pattern five digits - four digits. In this way, U.S. patents can be extracted by searching for postcode with regular expression.
Note: It is too risky to extract just 5 digit postcodes as these might street numbers, or other countries postcodes.
'(^|\s)\d{5}-\d{4}($|\s)'
For example,
city | postcode_extracted --------------------------------------|------------------- NEW YORK, NY 10022-3201 | 10022-3201 BEAVERTON, OREGON 97005-6453 | 97005-6453 SANTA BARBARA, CA 93130-3003 | 93130-3003 NEW YORK NY 10022-3201 | 10022-3201 SUNNYVALE, CA 94088-3453 | 94088-3453 94088-3470 | 94088-3470 CS 46510-35065 RENNES CEDEX | 46510-3506 NEW YORK, NY 10013-2412 | 10013-2412 OALKLAND, CA 94612-3550 | 94612-3550 OXFORD CT 06483-1011 | 06483-1011
The extracted postcode is in table ptoassigneend_us_extracted.
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
State
The following patterns can be used to extract state information.
Note: a,b,c are to be run on city, addrline1, and addrline2. We use city as an example below.
a. ', State Postcode'
The state and postcode are always together, separated by a space. We can extract state information with regular expression
'([,]|[.])\s\w{2,}\s{0,}\w{0,}\s{1,}\d{5}[-]\d{4}'
SQL Code:
WHEN city ~* '([,]|[.])\s\w{2,}\s{0,}\w{0,}\s{1,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(replace(regexp_replace(SUBSTRING(city, '[,]\s\w{2,}\s{0,}\w{0,}\s{1,}\d{5}[-]\d{4}'), '\d{5}-\d{4}', ),',',)))
Examples:
city | state_city --------------------------------------|----------- NEW YORK, NY 10022-3201 | NY BEAVERTON, OREGON 97005-6453 | OREGON SANTA BARBARA, CA 93130-3003 | CA SUNNYVALE, CA 94088-3453 | CA NEW YORK, NY 10013-2412 | NY OALKLAND, CA 94612-3550 | CA SANTA CLARA, CA 95052-8090 | CA PEORIA, IL 61629-6490 | IL MIDVALE, UTAH 84047-1408 | UTAH OAKLAND, CA 94612-3550 | CA HARRISBURG, PA 17105-3608 | PA ROCHESTER, NY 14650-2201 | NY NEW YORK, NY 10013-2412 | NY HOUSTON, TEXAS 77256-6571 | TEXAS BROOKINGS, SOUTH DAKOTA 57006-0128 | SOUTH DAKOTA
b. '\s State(abbreviation) Postcode'
'(^|\s)\w{2}\s{1}\d{5}[-]\d{4}'
SQL code:
WHEN city ~* '(^|\s)\w{2}\s{1}\d{5}[-]\d{4}'
THEN regexp_replace(SUBSTRING(city, '\w{2}\s{1,}\d{5}[-]\d{4}'), '\d{5}-\d{4}', )
Examples:
NEW YORK NY 10022-3201 |NY WAUKEGAN IL 60085-2195 |IL
c. 'D.C.'
'D[.]C[.]\s\d{5}-\d{4}'
SQL code:
WHEN city ~* 'D[.]C[.]\s\d{5}-\d{4}'
THEN 'D.C.'
d. 'A CORP.* OF State'
This pattern is not reliable. When 'addrline1' looks this way, 'addrline2' always provide more detailed address information than 'addrline1'. Besides, a great part of state info extracted from 'A CORP.* OF [State]' doesn't match the state extracted from detailed 'addrline2'. In this way, we discard this pattern.
Examples:
addrline1 | addrline2 -----------------------------------------------------------------------------------------|------------------------------------------------------------------------------------- A CORP. OF NEW YORK | ONE LINCOLN FIRST SQUARE, ROCHESTER, NEW YORK, NY 14601-0054 A CORPORATION OF NY | 550 MADISON AVENUE, NEW YORK, NY 10022-3201 A NON-PROFIT CORP. OF WASHINGTON | 4225 ROOSEVELT WAY NE, STE. 303 SEATTLE, WA 98105-6099 A CORP. OF MN | 2611 NORTH SECOND ST., MINNEAPOLIS, MN 55411-1633 A CORPORATION OF DE | 612 WHEELER'S FARM RD. MILFORD, CT 06460-8719 A CORP. OF WA. | 411 FIRST AVENUE SOUTH SEATTLE, WASHINGTON 98104-2871 A CORPORATION OF OREGON | ONE BOWERMAN DRIVE, BEAVERTON, OREGON 97005-6453 A CORPORATION OF | ONE BOWERMAN DRIVE BEAVERTON, OR 97005-6453 A CORP. OF INDIANA | 4810 TECUMSEH LANE, POST OFFICE BOX 15190 EVANSVILLE, INDIANA 47716-0190 A CORPORATION OF PA | 7200 SUTER ROAD, COOPERSBURG, PA 18036-1299 A CORP. OF DE | SCARBORO & BEAR CREEK ROAD, P.O. BOX 2009 OAK RIDGE, TENNESSEE 37831-8014
If you're interested, the SQL code is
WHEN addrline1 ~* 'CORP.*OF(\s|$)' THEN LTRIM(RTRIM(SUBSTRING(regexp_replace(SUBSTRING(addrline1, 'CORP.*OF.*'),'CORP.*OF', ), 1, 18)))
- Summary
The extracted state records are stored in the table ptoassigneend_us_extracted.
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
City
The following patterns can be used to extract city information.
a. '\s{2,} CityName [,] State Postcode'
SQL code:
CASE WHEN addrline1 ~* '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(REPLACE(SUBSTRING(SUBSTRING(addrline1, '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5} [-]\d{4}'),'.*[,]'),',',)))
Examples (in any of addrline1, addrline2, and city):
source |extracted ------------------------------------------------------------------------------------------------|--------------------- 800 CHRYSLER DR. EAST AUBURN HILLS, MICHIGAN 48326-2757 |AUBURN HILLS 550 MADISON AVENUE NEW YORK, NEW YORK 10022-3201 |NEW YORK P.O. BOX 15439 WILMINGTON, DE 19850-5439 |WILMINGTON
Some noise exists (just a little).
1313 N. MARKET STREET HERCULES PLAZAWILMINGTON, DE 19894-0001
b. '[,]\s{1,} CityName [,] State Postcode'
SQL code:
CASE WHEN addrline1 ~* '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(REPLACE(SUBSTRING(SUBSTRING(addrline1, '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'),'.*[,]'),',',)))
Example:
source |extracted ---------------------------------------------------------------------------|--------------------- 920 DISC DRIVE, SCOTTS VALLEY, CA 95067-0360 |SCOTTS VALLEY 550 MADISON AVENUE, NEW YORK, NY 10022-3201 |NEW YORK BALLSTON TOWER ONE 800 NORTH QUINCY STREET, ARLINGTON, VA 22217-5660 |ARLINGTON
c. 'CityName [,] State Postcode' (no leading spaces)
SQL code:
WHEN addrline1 ~* '^\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN REPLACE(SUBSTRING(SUBSTRING(addrline1, '^\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'), '.*[,]'),',', )
Examples:
PHILADELPHIA, PA 19104-3147 |PHILADELPHIA ROCHESTER, NY 14650-2201 |ROCHESTER
d. 'CityName State(abbreviation) Postcode' (no leading spaces)
SQL code:
WHEN addrline1 ~* '^\w{1,}\s{0,}\w{0,}\s{0,}\w{2}\s{0,}\d{5}[-]\d{4}'
THEN regexp_replace(SUBSTRING(addrline1, '^\w{1,}\s{0,1}\w{0,}\s{1,}\w{2}\s{0,}\d{5}[-]\d{4}'), '\w{2}\s\d{5}[-]\d{4}', )
Examples:
TARRYTOWN NY 10591-6706 |TARRYTOWN
e. Special cases
Examples:
BATON, ROUGE, LA 70809-4562 ('BATON ROUGH' is separated by a comma)
ST. PAUL, MIN 55133-3427 ('ST. PAUL' contains a dot)
QUINCY STREETARLINGTON, VA 22217-5660 (no space between street and city name :(
SQL code:
CASE WHEN addrline1 ~* 'BATON[,] ROUGE[,]\s{1}LA'
THEN 'BATON ROUGE'
WHEN addrline1 ~* 'ST[.]\s{1}PAUL'
THEN 'ST. PAUL'
WHEN addrline1 ~* 'ARLINGTON[,]\s{1}VA'
THEN 'ARLINGTON'
Noise:
- CityName State (full name) Postcode' (no leading spaces)
NEW YORK NEW YORK 10022-3201
This pattern can't be identified because of much noise.
- 'CityName Postcode' (no leading spaces)
LITTLE ELM 75068-3787 OAK RIDGE 37831-6498
This pattern can't be identified because of the noise:
MASSACHUSETTS 02780-7319 ('State'+'Postcode')
- no space between street and city name :(
BOX 87703CHICAGO, IL 60680-0703
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
Output (Tables)
- ptoassigneend_us_extracted
Contain all the original features as well as city, state and postcode info extracted from features addrline1, addrline2 and city. See Section 2.2.1 for details.
Table "public.ptoassigneend_us_extracted"
Column | Type | Modifiers
---------------|------------------------|-----------
reelno | integer |
frameno | integer |
name | character varying(500) |
addrline1 | character varying(500) |
addrline2 | character varying(500) |
city | character varying(500) |
state | character varying(500) |
country | character varying(500) |
postcode | character varying(80) |
postqcode_city | text |
postcode_addr1 | text |
postcode_addr2 | text |
state_city | text |
state_addr1 | text |
state_addr2 | text |
city_addr1 | text |
city_addr2 | text |
city_city | text |
- postcode_city is the postcode extracted from 'city'
- postcode_addr1 is the postcode extracted from 'addrline1'
- postcode_addr2 is the postcode extracted from 'addrline2'
- state_city is the state name extracted from 'city'
- state_addr1 is the state name extracted from 'addrline1'
- state_addr2 is the state name extracted from 'addrline2'
- city_city is the city name extracted from 'city'
- city_addr1 is the city name extracted from 'addrline1'
- city_addr2 is the city name extracted from 'addrline2'
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
Clean Address Info (Master Table)
Introduction
As mentioned in Section 2.2.2, city, state and postcode info are extracted from 'addrline1', 'addrline2' and 'city'. Original table also contains 'postcode', 'city' and 'state'. In this way, we have four candidates for city, state and postcode.
Info extracted from addresses and that in the original table are not necessarily consistent.
The object of this section is to pick out the best postcode, city and state for each record, and create a Master Table with original features and cleaned postcode, city, and state.
Postcode
Reminder: 'postcode_city' is the postcodes extracted from 'city'; 'postcode_addr1' is the postcodes extracted from 'addrline1'; 'postcode_addr2' is the postcodes extracted from 'addrline2'.
The 'postcode_city', 'postcode_addr1' and 'postcode_addr2' are all consistent!
Examples:
postcode_addr1 | postcode_addr2 ---------------|--------------- 90401-1708 | 90401-1708 37831-8243 | 37831-8243
The issue is the inconsistency between 'postcode' and ('postcode_city', 'postcode_addr1' and 'postcode_addr2').
- Inconsistency between 'postcode' and 'postcode_addr1'
Case 1: 'postcode_addr1' beats 'postcode' because 'addrline1' is detailed. For example:
addrline1 | postcode_addr1 | postcode -----------------------------------------------------------------------------------------------------------------------------------------------------------|----------------|----------- P.O. BOX 6 / 83707-0006 | 83707-0006 | 83716 BLDG. C01, M.S. A126 P.O. BOX 80028 LOS ANGELES, CA 90080-0028 | 90080-0028 | 90045 P. O. BOX 1407, HOUSTON, TEXAS 77251-1407 | 77251-1407 | 77042 841 3RD, LONGVIEW, WASHINGTON 98632-0189 | 98632-0189 | 95404 2210 W. OAKLAWN, 72762-6999 | 72762-6999 | 72765-2020 BLDG. CO1, M.S. A126, P.O. BOX 80028 LOS ANGELES, CA 90080-0028 | 90080-0028 | 90045 P.O. BOX 6 / 83707-0006 | 83707-0006 | 83716
- Inconsistency between 'postcode' and 'postcode_addr2'
Case 2: 'postcode_addr2' beats 'postcode' because 'addrline2' is detailed.
Example:
addrline2 | postcode_addr2 | postcode ------------------------------------------------------------------------------------------------------|----------------|---------- P.O. BOX 6 / 83707-0006 | 83707-0006 | 83716-9632 P.O. BOX 5800 - MS0161, ALBUQUERQUE, NEW MEXICO 87185-0161 | 87185-0161 | 87123-0161 P.O. BOX 674412, HOUSTON, TEXAS 77267-4412 | 77267-4412 | 77002 WASHINGTON, DC 20250-1400 | 20250-1400 | 61604 BOX 10076, HATTIESBURGH, MISSISSIPPI 39406-0076 | 39406-0076 | 39402 P.O. BOX 674412, HOUSTON, TEXAS 77267-4412 | 77267-4412 | 77032 P.O. BOX 6 / 83707-0006 | 83707-0006 | 83716-9632 P.O. BOX 6 / 83707-0006 | 83707-0006 | 83716-9632 P.O. BOX 27115-4191 | 27115-4191 | 27105-4191 P.O. BOX 674412, HOUSTON, TX 77267-4412 | 77267-4412 | 77002
Besides, I randomly picked some records and googled address and postcode. The results support 'postcode_addr2'.
Examples:
Micron Technology, Inc. 8000 South Federal Way Post Office Box 6 Boise 83707-0006 USA Tel: Ph: 208-368-4000
WebsterBank, NA 50 Kennedy Plaza 11th Floor Suite 110 (Mail Stop: PR-105) Providence, RI 02903
- Inconsistency between 'postcode' and 'postcode_city'
Case 3: 'postcode_city' beats 'postcode'.
city | state | postcode_city | postcode ----------------------|----------|---------------|---------- HAUPPAUGE, 11788-8847 | NEW YORK | 11788-8847 | 78759
- Output
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
For records of which 'addrline1', 'addrline2' and 'city' don't contain postcode info, just clean the 'postcode' as the 'postcode_cleaned'
All the cleaned postcodes for U.S. patents are stored in ptoassigneend_us_cleaned (see feature postcode_cleaned).
State
Reminder: 'state_city' is the states extracted from 'city'; 'state_addr1' is the states extracted from 'addrline1'; 'state_addr2' is the states extracted from 'addrline2'.
The 'state_city', 'state_addr1' and 'state_addr2' are consistent.
Examples:
state_addr2 | state_city ------------|----------- ILLINOIS | ILLINOIS IL | IL IL | IL CT | CT MN | MN CA | CA
One reason for the inconsistency between 'state' and ('state_city', 'state_addr1' and 'state_addr2') is the co-existence of abbreviation and full form. So they are the same actually. Otherwise, 'state_city', 'state_addr1' and 'state_addr2' beat 'state' because they are detailed.
For records of which 'addrline1', 'addrline2' and 'city' don't contain state info, just take 'state' as the 'state_cleaned'.
- Output
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
All the cleaned states for U.S. patents are stored in ptoassigneend_us_cleaned (see feature state_cleaned).
Note: We might want to convert state names to standard codes.
City
Reminder: 'city_city' is the city info extracted from 'city'; 'city_addr1' is the city info extracted from 'addrline1'; 'city_addr2' is the city info extracted from 'addrline2'.
The 'city_city', 'city_addr1' and 'city_addr2' are consistent.
Examples:
city_addr2 | city_city -------------|-------------- BOISE | BOISE THOMASVILLE | THOMASVILLE CARROLLTON | CARROLLTON CINCINNATI | CINCINNATI CINCINNATI | CINCINNATI PEORIA | PEORIA OAK RIDGE | OAK RIDGE CARROLLTON | CARROLLTON
'city_city', 'city_addr1' and 'city_addr2' beat 'city' because they are detailed.
For records of which 'addrline1', 'addrline2' and 'city' don't contain city info, just keep 'city' as the 'city_cleaned'.
- Output
SQL code is in:
E:/McNair/Projects/PatentAddress/Functions.sql
All the cleaned cities for U.S. patents are stored in ptoassigneend_us_cleaned. (see feature city_cleaned)
Output (Table)
- ptoassigneend_us_cleaned
Table "public.ptoassigneend_us_cleaned"
Column | Type | Modifiers
--------------------|------------------------|-----------
reelno | integer |
frameno | integer |
name | character varying(500) |
addrline1 | character varying(500) |
addrline2 | character varying(500) |
city | character varying(500) |
state | character varying(500) |
country | character varying(500) |
postcode | character varying(80) |
postcode_addr1 | text |
postcode_addr2 | text |
postcode_city | text |
state_addr1 | text |
state_addr2 | text |
state_city | text |
city_addr1 | text |
city_addr2 | text |
city_city | text |
postcode_cleaned | text |
postcode_f5_cleaned | text |
state_cleaned | text |
city_cleaned | text |
Feature postcode_cleaned, postcode_f5_cleaned (first five digits), state_cleaned and city_cleaned are cleaned postcode, state and city info.
Functions to Simplify SQL Code
Extraction
- Postcode
SQL function:
CREATE OR REPLACE FUNCTION ExtractPostcode(adr text) RETURNS text AS $$
BEGIN
RETURN SUBSTRING(adr, '\d{5}[-]\d{4}');
END;
$$ LANGUAGE plpgsql;
Explanation:
adr is the feature from which you want to extract postcode.
- State
SQL function:
CREATE OR REPLACE FUNCTION ExtractState(adr text) RETURNS text AS $$
SELECT
CASE WHEN adr ~* '([,]|[.])\s\w{2,}\s{0,}\w{0,}\s{1,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(replace(regexp_replace(SUBSTRING(adr, '[,]\s\w{2,}\s{0,}\w{0,}\s{1,}\d{5}[-]\d{4}'), '\d{5}-\d{4}', ),',',)))
WHEN adr ~* '(^|\s)\w{2}\s{1}\d{5}[-]\d{4}'
THEN regexp_replace(SUBSTRING(adr, '\w{2}\s{1,}\d{5}[-]\d{4}'), '\d{5}-\d{4}', )
WHEN adr ~* 'D[.]C[.]\s\d{5}-\d{4}'
THEN 'D.C.'
ELSE NULL END AS result;
$$ LANGUAGE SQL;
Explanation:
adr is the feature from which you want to extract state.
- City
SQL function:
CREATE OR REPLACE FUNCTION ExtractCity(adr text) RETURNS text AS $$
SELECT
CASE WHEN adr ~* '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(REPLACE(SUBSTRING(SUBSTRING(adr, '\s{2,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'),'.*[,]'),',',)))
WHEN adr ~* '[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN LTRIM(RTRIM(REPLACE(SUBSTRING(SUBSTRING(adr, '[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'),'[,].*[,]'),',',)))
WHEN adr ~* '^\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'
THEN REPLACE(SUBSTRING(SUBSTRING(adr, '^\w{1,}\s{0,}\w{0,}\s{0,}[,]\s{0,}\w{1,}\s{0,}\w{0,}\s{0,}\d{5}[-]\d{4}'), '.*[,]'),',', )
WHEN adr ~* '^\w{1,}\s{0,}\w{0,}\s{0,}\w{2}\s{0,}\d{5}[-]\d{4}'
THEN regexp_replace(SUBSTRING(adr, '^\w{1,}\s{0,1}\w{0,}\s{1,}\w{2}\s{0,}\d{5}[-]\d{4}'), '\w{2}\s\d{5}[-]\d{4}', )
WHEN adr ~* 'BATON[,] ROUGE[,]\s{1}LA'
THEN 'BATON ROUGE'
WHEN adr ~* 'ST[.]\s{1}PAUL'
THEN 'ST. PAUL'
WHEN adr ~* 'ARLINGTON[,]\s{1}VA'
THEN 'ARLINGTON'
ELSE NULL END AS result;
$$ LANGUAGE SQL;
Explanation:
adr is the feature from which you want to extract city.
With these functions, we can generate ptoassigneend_us_extracted, which is the final output in Section 2.2.1, with the following code:
CREATE TABLE ptoassigneend_us_extracted AS SELECT *, ExtractPostcode(city) postcode_city, ExtractPostcode(addrline1) postcode_addr1, ExtractPostcode(addrline2) postcode_addr2, ExtractState(city) state_city, ExtractState(addrline1) state_addr1, ExtractState(addrline2) state_addr2, ExtractCity(city) city_city, ExtractCity(addrline1) city_addr1, ExtractCity(addrline2) city_addr2 FROM ptoassigneend_missus;
All the SQL is in:
E:/McNair/Projects/PatentAddress/Functions.sql
Cleaning
- Clean Postcode
SQL function:
CREATE OR REPLACE FUNCTION PostcodeClean (text,text,text,text) RETURNS text AS $$
$pri1=$_[0];
$pri2=$_[1];
$pri3=$_[2];
$postcode=$_[3];
if ($pri1) {return $pri1;}
if ($pri2) {return $pri2;}
if ($pri3) {return $pri3;}
if ($postcode) {
if ($postcode = ~ '\d{5}-\d{4}') {return $postcode}
if ($postcode = ~ '\d{5}') {return $postcode}
}
return undef;
$$ LANGUAGE plperl;
Explanation:
$pri1 is the feature with the highest priority, which in this case (see Section 2.2.2.1 is postcode_addr1) $pri2 is the feature with the second highest priority, which in this case (see Section 2.2.2.1 is postcode_addr2) $pri3 is the feature with the third highest priority, which in this case (see Section 2.2.2.1 is postcode_city) $postcode is the feature postcode.
- Clean State
SQL function:
CREATE OR REPLACE FUNCTION StateClean (text,text,text,text) RETURNS text AS $$
$pri1=$_[0];
$pri2=$_[1];
$pri3=$_[2];
$state=$_[3];
if ($pri1) {return $pri1;}
if ($pri2) {return $pri2;}
if ($pri3) {return $pri3;}
if ($state) {return $state;}
return undef;
$$ LANGUAGE plperl;
Explanation:
$pri1 is the feature with the highest priority, which in this case (see Section 2.2.2.2 is state_addr1) $pri2 is the feature with the second highest priority, which in this case (see Section 2.2.2.2 is state_addr2) $pri3 is the feature with the third highest priority, which in this case (see Section 2.2.2.2 is state_city) $state is the feature state.
- Clean City
SQL function:
CREATE OR REPLACE FUNCTION CityClean (text,text,text,text) RETURNS text AS $$
$pri1=$_[0];
$pri2=$_[1];
$pri3=$_[2];
$city=$_[3];
if ($pri1) {return $pri1;}
if ($pri2) {return $pri2;}
if ($pri3) {return $pri3;}
if ($city) {return $city;}
return undef;
$$ LANGUAGE plperl;
Explanation:
$pri1 is the feature with the highest priority, which in this case (see Section 2.2.2.3 is city_addr1) $pri2 is the feature with the second highest priority, which in this case (see Section 2.2.2.3 is city_addr2) $pri3 is the feature with the third highest priority, which in this case (see Section 2.2.2.3 is city_city) $city is the feature city.
Issues
- Inconsistency between 'addrline' and 'country'
Example:
addrline2 | city | country
2882 SAND HILL ROAD MENLO PARK, CALIFORNIA 94025-7022 | TOKYO | JAPAN
2801 CENTERVILLE ROAD, P.O. BOX 15439 WILMINGTON, DE 19850-5439 | TOKYO | JAPAN
1-6, UCHISAIWAI-CHO 1-CHOME | CHIYODA-KU, TOKYO | JAPAN
MENLO PARK, CA 94025-7022 | TOKYO | JAPAN
| MINATO-KU, TOKYO 10585-8518 | JAPAN
1225 NORTH HIGHWAY 169, MINNEAPOLIS, MINNESOTA 55441-5058 | TOKYO | JAPAN
2882 SAND HILL ROAD MENLO PARK, CA 94025-7022 | TOKYO | JAPAN
3001 ORCHARD PARKWAY SAN JOSE, CALIFORNIA 95134-2088 | TOKYO 107 | JAPAN
3001 ORCHARD PARKWAY SAN JOSE, CA 95134-2088 | MINATO-KU, TOKYO 107 | JAPAN
3001 ORCHARD PARKWAY SAN JOSE, CALIFORNIA 95134-2088 | TOKYO 107 | JAPAN
3001 ORCHARD PARKWAY SAN JOSE, CA 95134-2088 | MINATO-KU, TOKYO 107 | JAPAN
- The post code and zip regex for other countries besides U.S. can be found here:
http://stackoverflow.com/questions/578406/what-is-the-ultimate-postal-code-and-zip-regex
Example:
"US", "\d{5}([ \-]\d{4})?"
"CA", "[ABCEGHJKLMNPRSTVXY]\d[ABCEGHJ-NPRSTV-Z][ ]?\d[ABCEGHJ-NPRSTV-Z]\d"
"DE", "\d{5}"
"JP", "\d{3}-\d{4}"
"FR", "\d{2}[ ]?\d{3}"
- The city feature needs to be standardized. For example, 'GRAND CAYMAN, CAYMAN ISLAND' and 'GRAND CAYMAN' indicate the same city.
- Both state name and its abbreviation exist.
Restructure Address Information (Second Stage)
Note: This section was worked on by Sonia Zhang
The dbase is patent.
The table is ptoassigneend.
SQL code and other things are in:
E:/McNair/Projects/PatentAddress/Cleaning_Step2.sql
IO files are on the dbase server in:
Z:/PatentAddress
To do
In no particular order:
- Remove city, state, zip, country from addrline1 & addrline2 to get clean addrlines.
- Maybe concatenate addrline1 and addrline to make addrline
- Identify clean data (e.g. City that is a city, zip that is a zip, state that is a state)
- By pattern, length, match to list
- Try some more patterns, perhaps with a slightly higher false positive rate, on the remaining uncleaned data
- Iterate!
Identify Clean Data
As mentioned, the ptoassigneend_us_extracted is cleaned. This section works on the remaining records which are stored in ptoassigneend_us_temp.
First, filter out records with city that is a city, zip that is a zip, state that is a state. Note: The consistency between city and state or city and postcode is not checked in this section.
zip that is a zip
Match the pattern 5-4 or 5 digits.
state that is a state
Select distinct state records with
SELECT DISTINCT state FROM ptoassigneend_us_temp;
The output shows that all the records not null or not spaces are valid state names.
city that is a city
Select distinct city records in ptoassigneend_us_extracted and store them in ptoassigneend_us_citylist (775).
Since the city list is not long, I briefly cleaned the list by hand, and still stored in ptoassigneend_us_citylist (730).
The safest method to identify clean city is to find records with feature city in ptoassigneend_us_citylist.
SQL Code:
SELECT city
FROM ptoassigneend_us_temp
WHERE city IN (
SELECT citylist
FROM ptoassigneend_us_citylist);
-- SELECT 2603422
Output: ptoassigneend_us_identify1
This table stores records that meet all the requirements above: zip with 5-4 or 5 digits, state not null or not spaces, and city in ptoasigneend_us_citylist.
SQL Code:
CREATE TABLE ptoassigneend_us_identify1 AS
SELECT *
FROM ptoassigneend_us_temp
WHERE city IN (
SELECT citylist
FROM ptoassigneend_us_citylist) AND
state IS NOT NULL AND state != AND
postcode ~* '\d{5}';
SELECT 2511356
Clean Address: more patterns
Clean postcode & state
Postcode should always be at the end of addrline1, addrlin2 or city. Exclude P.O. BOX #. For example, the SQL code to extract postcode and state from addrline1 is:
SELECT addrline1, SUBSTRING(addrline1, '\d{5}') postcode_candid,
REPLACE(REPLACE(SUBSTRING(addrline1, '[,]\s{1,}\w{1,}\s{0,}\w{0,}\d{5}'),'\d{5}',),',',)
state_candid
FROM ptoassigneend_us_temp2
WHERE addrline1 ~* '\d{5}$'
AND NOT (addrline1 ~* 'BO') AND NOT (addrline1 ~* 'P[.]O[.]');
Examples:
181 METRO DRIVE SUITE 520 SAN JOSE, CA 95110 | 95110 | , CA 95110 11065 ROSELLE STREET SAN DIEGO, CALIFORNIA 92121 | 11065 | , CALIFORNIA 92121 400 MARGARET STREET, NO. 20 PLATTSBURGH, NEW YORK 12901 | 12901 |
Clean city & state
- Pattern 1: 'city' contains punctuation
Remove punctuation marks. Then match city with ptoassigneend_us_citylist.
CREATE TABLE ptoassigneend_us_temp3 AS SELECT *, replace(city, ',', ) clean_city FROM ptoassigneend_us_temp2;
Output: ptoassigneend_us_identify2
CREATE TABLE ptoassigneend_us_identify2 AS
SELECT *
FROM ptoassigneend_us_temp3
WHERE clean_city IN (
SELECT citylist
FROM ptoassigneend_us_citylist) AND
state IS NOT NULL AND state != AND
postcode ~* '\d{5}';
# SELECT 14508
- Pattern 2: 'city' is like 'city name, state ID'
Extract city and state info with SQL code:
SELECT REPLACE(SUBSTRING(city, '.*[,]'),',',) city_candid,
REPLACE(SUBSTRING(city, '[,].*'),',',) state_candid
FROM ptoassigneend_us_temp3
WHERE city ~* '[,]\s{1,}\w{2}' OR city ~* '[,]\s{1,}\w{1}[.]\w{1}[.]'
;
#SELECT 1254
- Pattern 3: 'city' is like 'city name, state postcode (5 digits)'
Extract city and state info with SQL code:
SELECT
REPLACE(SUBSTRING(city, '.*[,]'),',',) city_candid,
REPLACE(REPLACE(SUBSTRING(city, '[,].*\d{5}$'),',',), '\d{5}', ) state_candid
FROM ptoassigneend_us_temp3
WHERE city ~* '[,].*\d{5}$';
#SELECT 624
- Feature city is null or spaces (Not Clean)
-- SELECT 51050
SELECT 847
- city, state postcode(5)
'.*[,].*\d{5}'
- city, state code
'.*[,]\s{0,}\w{2}$'
-- 284
- city, state code
'.*[,]\s{0,}\w{2}\s'
- IS NOT NULL AND city != \'\' AND city !~* '([,]|[.])'
Problem: can't identify cities
-- 23501
