You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 california_schools
【Schema】
# Table: schools
[
(CDSCode:TEXT, Primary Key, Examples: [01100170000000, 01100170109835, 01100170112607]),
(NCESDist:TEXT, Examples: [0691051, 0600002, 0600003]),
(NCESSchool:TEXT, Examples: [10546, 10947, 12283]),
(StatusType:TEXT, Examples: [Active, Closed, Merged]),
(County:TEXT, Examples: [Alameda, Alpine, Amador]),
(District:TEXT),
(School:TEXT, Examples: [FAME Public Charter]),
(Street:TEXT, Examples: [313 West Winton Avenue]),
(StreetAbr:TEXT, Examples: [313 West Winton Ave.]),
(City:TEXT, Examples: [Hayward, Newark, Oakland]),
(Zip:TEXT, Examples: [94544-1136, 94560-5359, 94612-3355]),
(State:TEXT, Examples: [CA]),
(MailStreet:TEXT, Examples: [313 West Winton Avenue]),
(MailStrAbr:TEXT, Examples: [313 West Winton Ave.]),
(MailCity:TEXT, Examples: [Hayward, Newark, Oakland]),
(MailZip:TEXT, Examples: [94544-1136, 94560-5359, 94612]),
(MailState:TEXT, Examples: [CA]),
(Phone:TEXT, Examples: [(510) 887-0152, (510) 596-8901, (510) 686-4131]),
(Ext:TEXT, Examples: [130, 1240, 1200]),
(Website:TEXT, Examples: [www.acoe.org]),
(OpenDate:DATE, Examples: [2005-08-29]),
(ClosedDate:DATE, Examples: [2015-07-31]),
(Charter:INTEGER, Examples: [1, 0]),
(CharterNum:TEXT, Examples: [0728, 0811, 1049]),
(FundingType:TEXT, Examples: [Directly funded]),
(DOC:TEXT, Examples: [00, 31, 34]),
(DOCType:TEXT, Examples: [County Office of Education (COE)]),
(SOC:TEXT, Examples: [65, 66, 60]),
(SOCType:TEXT, Examples: [K-12 Schools (Public)]),
(EdOpsCode:TEXT, Examples: [TRAD, JUV, COMM]),
(EdOpsName:TEXT, Examples: [Traditional]),
(EILCode:TEXT, Examples: [ELEMHIGH, HS, ELEM]),
(EILName:TEXT, Examples: [Elementary-High Combination]),
(GSoffered:TEXT, Examples: [K-12, 9-12, K-8]),
(GSserved:TEXT, Examples: [K-12, 9-12, K-7]),
(Virtual:TEXT, Examples: [P, N, F]),
(Magnet:INTEGER, Examples: [0, 1]),
(Latitude:REAL, Examples: [37.658212, 37.521436, 37.80452]),
(Longitude:REAL, Examples: [-122.09713, -121.99391, -122.26815]),
(AdmFName1:TEXT, Examples: [L Karen, Laura, Clifford]),
(AdmLName1:TEXT, Examples: [Monroe, Robell, Thompson]),
(AdmEmail1:TEXT),
(AdmFName2:TEXT, Examples: [Sau-Lim (Lance), Jennifer, Annalisa]),
(AdmLName2:TEXT, Examples: [Tsang, Koelling, Moore]),
(AdmEmail2:TEXT),
(AdmFName3:TEXT, Examples: [Drew, Irma, Vickie]),
(AdmLName3:TEXT, Examples: [Sarratore, Munoz, Chang]),
(AdmEmail3:TEXT),
(LastUpdate:DATE, Examples: [2015-06-23])
]
# Table: frpm
[
(CDSCode:TEXT, Primary Key, Examples: [01100170109835, 01100170112607, 01100170118489]),
(Academic Year:TEXT, Examples: [2014-2015]),
(County Code:TEXT, Examples: [01, 02, 03]),
(District Code:INTEGER, Examples: [10017, 31609, 31617]),
(School Code:TEXT, Examples: [0109835, 0112607, 0118489]),
(County Name:TEXT, Examples: [Alameda, Alpine, Amador]),
(District Name:TEXT),
(School Name:TEXT, Examples: [FAME Public Charter]),
(District Type:TEXT, Examples: [County Office of Education (COE)]),
(School Type:TEXT, Examples: [K-12 Schools (Public)]),
(Educational Option Type:TEXT, Examples: [Traditional]),
(NSLP Provision Status:TEXT, Examples: [Breakfast Provision 2]),
(Charter School (Y/N):INTEGER, Examples: [1, 0]),
(Charter School Number:TEXT, Examples: [0728, 0811, 1049]),
(Charter Funding Type:TEXT, Examples: [Directly funded]),
(IRC:INTEGER, Examples: [1, 0]),
(Low Grade:TEXT, Examples: [K, 9, 1]),
(High Grade:TEXT, Examples: [12, 8, 5]),
(Enrollment (K-12):REAL, Examples: [1087.0, 395.0, 244.0]),
(Free Meal Count (K-12):REAL, Examples: [565.0, 186.0, 134.0]),
(Percent (%) Eligible Free (K-12):REAL, Examples: [0.519779208831647, 0.470886075949367, 0.549180327868853]),
(FRPM Count (K-12):REAL, Examples: [715.0, 186.0, 175.0]),
(Percent (%) Eligible FRPM (K-12):REAL, Examples: [0.657773689052438, 0.470886075949367, 0.717213114754098]),
(Enrollment (Ages 5-17):REAL, Examples: [1070.0, 376.0, 230.0]),
(Free Meal Count (Ages 5-17):REAL, Examples: [553.0, 182.0, 128.0]),
(Percent (%) Eligible Free (Ages 5-17):REAL, Examples: [0.516822429906542, 0.484042553191489, 0.556521739130435]),
(FRPM Count (Ages 5-17):REAL, Examples: [702.0, 182.0, 168.0]),
(Percent (%) Eligible FRPM (Ages 5-17):REAL, Examples: [0.65607476635514, 0.484042553191489, 0.730434782608696]),
(2013-14 CALPADS Fall 1 Certification Status:INTEGER, Examples: [1])
]
# Table: satscores
[
(cds:TEXT, Primary Key, Examples: [10101080000000, 10101080109991, 10101080111682]),
(rtype:TEXT, Examples: [D, S]),
(sname:TEXT, Examples: [FAME Public Charter]),
(dname:TEXT, Examples: [Alameda County Office of Education]),
(cname:TEXT, Examples: [Alameda, Amador, Butte]),
(enroll12:INTEGER, Examples: [398, 62, 75]),
(NumTstTakr:INTEGER, Examples: [88, 17, 71]),
(AvgScrRead:INTEGER, Examples: [418, 503, 397]),
(AvgScrMath:INTEGER, Examples: [418, 546, 387]),
(AvgScrWrite:INTEGER, Examples: [417, 505, 395]),
(NumGE1500:INTEGER, Examples: [14, 9, 5])
]
【Foreign keys】
frpm.CDSCode=schools.CDSCode
satscores.cds=schools.CDSCode

    【Question】
    What is the total number of schools whose total SAT scores are greater or equal to 1500 whose mailing city is Lakeport? Total SAT scores can be computed by AvgScrRead + AvgScrMath + AvgScrWrite

    【Evidence】
    Total SAT scores can be computed by AvgScrRead + AvgScrMath + AvgScrWrite

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.cds) FROM satscores AS T1 INNER JOIN schools AS T2 ON T1.cds = T2.CDSCode WHERE T2.MailCity = 'Lakeport' AND (T1.AvgScrRead + T1.AvgScrMath + T1.AvgScrWrite) >= 1500