나는 같은입니다 표 3을 가지고 내가 좋아하는 것입니다 표 2,파이썬을 사용하여 'id'입력을 기반으로 테이블에서 레코드를 검색하는 방법은 무엇입니까?
project_id | energy_type | uses | target | title
------------+-------------------------------------------------------------------------------------------------------------------------+------+----------------------------------+------------------------------
300 | {"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"} | | Target % Better than Median: 75 | About this Property's Design
400 | {"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"} | | Target % Better than Median: 75 | About this Property's Design
이 같은입니다 표,
project_id | metric | design_target | median_property | design_project
------------+----------------------------------------+---------------+-----------------+----------------
300 | ENERGY STAR score (1-100) | Not Available | 50 | Not Available
300 | Source EUI (kBtu/ft\u00b2) | 35.4 | 141.4 | Not Available
300 | Site EUI (kBtu/ft\u00b2) | 15.8 | 63.1 | Not Available
300 | Source Energy Use (kBtu) | 3,536.0 | 14,144.1 | Not Available
300 | Site Energy Use (kBtu) | 1,578.7 | 6,314.9 | Not Available
300 | Energy Cost ($) | 34.61 | 138.44 | Not Available
300 | Total GHG Emissions (Metric Tons CO2e) | 0.2 | 0.6 | 0.0
400 | ENERGY STAR score (1-100) | Not Available | 50 | Not Available
400 | Source EUI (kBtu/ft\u00b2) | 35.4 | 141.4 | Not Available
400 | Site EUI (kBtu/ft\u00b2) | 15.8 | 63.1 | Not Available
400 | Source Energy Use (kBtu) | 3,536.0 | 14,144.1 | Not Available
400 | Site Energy Use (kBtu) | 1,578.7 | 6,314.9 | Not Available
400 | Energy Cost ($) | 34.61 | 138.44 | Not Available
400 | Total GHG Emissions (Metric Tons CO2e) | 0.2 | 0.6 | 0.0
이
project_id | your_design_score
------------+-------------------
300 | N/A
400 | N/A
나는 테이블 기반 프로젝트에 참여하고있다. ct_id = '300'파이썬에서 #declared
PROJECT_ID 지금 PROJECT_ID 입력을 기반으로 레코드를 표시하려고
[('300', 'ENERGY STAR score (1-100)', 'Not Available', '50', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Source EUI (kBtu/ft\\u00b2)', '35.4', '141.4', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Site EUI (kBtu/ft\\u00b2)', '15.8', '63.1', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Source Energy Use (kBtu)', '3,536.0', '14,144.1', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Site Energy Use (kBtu)', '1,578.7', '6,314.9', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Energy Cost ($)', '34.61', '138.44', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('300', 'Total GHG Emissions (Metric Tons CO2e)', '0.2', '0.6', '0.0', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'ENERGY STAR score (1-100)', 'Not Available', '50', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Source EUI (kBtu/ft\\u00b2)', '35.4', '141.4', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Site EUI (kBtu/ft\\u00b2)', '15.8', '63.1', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Source Energy Use (kBtu)', '3,536.0', '14,144.1', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Site Energy Use (kBtu)', '1,578.7', '6,314.9', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Energy Cost ($)', '34.61', '138.44', 'Not Available', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A'), ('400', 'Total GHG Emissions (Metric Tons CO2e)', '0.2', '0.6', '0.0', '{"Energy Not Entered","Assumed Mix Based on State & Property Type:","","Electric - Grid (56.9%)","Natural Gas (43.1%)"}', None, ' Target % Better than Median: 75', "About this Property's Design", 'N/A')]
,
import psycopg2
con = psycopg2.connect(dbname="db",
user="postgres", host="localhost",
password="")
d1 = "select t1.project_id,t1.Metric, t1.Design_Target, t1.Median_Property, t1.Design_Project, t2.Energy_Type, t2.Uses, t2.Target, t2.Title, t3.your_design_score from metric_comparison t1, property_design t2, design_score t3 where t1.project_id = t2.project_id and t2.project_id = t3.project_id"
cursor.execute(d1)
d2 = cursor.fetchall()
print d2
con.commit()
내가 같은 출력을 가지고, 파이썬 사용 코드 PROJECT_ID의 입력을 기반으로 위의 출력에서 레코드를 표시해야합니다.
project_id가 PROJECT_ID와 일치하는 레코드를 표시해야합니다. execute
방법에 paremeter을 통과하는 SQL 측
이 파이썬 특정하지 않습니다. 질문에 대답하려면 t1.project_id = PROJECT_ID를 쿼리하십시오. –
@AmitTripathi, 친구가 작동하지 않았다 – venkat
@AmitTripathi, 내가 했어 t1.project_id = ' "+ str (PROJECT_ID) – venkat