Notice
														
												
											
												
												
													Recent Posts
													
											
												
												
													Recent Comments
													
											
												
												
													Link
													
											
									| 일 | 월 | 화 | 수 | 목 | 금 | 토 | 
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | |||
| 5 | 6 | 7 | 8 | 9 | 10 | 11 | 
| 12 | 13 | 14 | 15 | 16 | 17 | 18 | 
| 19 | 20 | 21 | 22 | 23 | 24 | 25 | 
| 26 | 27 | 28 | 29 | 30 | 31 | 
													Tags
													
											
												
												- kaggle
- Labor Management System
- pandas profiling
- oracle
- tensorflow
- 신경쓰기의 기술
- Gaimification
- TensorFlowGPU
- eda
- 코딩테스트연습
- 코딩테스트
- 딥러닝
- 당신의 인생이 왜 힘들지 않아야 한다고 생각하십니까
- 피그마인디언
- forecast
- 웨어하우스 보관 최적화
- 데이터분석
- 파이썬
- ABC Analysis
- 프로그래머스
- leetcode
- HackerRank
- SKU Consolidation
- Product Demand
- MySQL
- Inventory Optimization
- SQL
- MS SQL Server
- ProfileReport
- ModelCheckPoint
													Archives
													
											
												
												- Today
- Total
오늘도 배운다
Average Population of Each Continent / HackerRank, SQL, MySQL 본문
			코딩테스트연습(SQL)
			
		Average Population of Each Continent / HackerRank, SQL, MySQL
LearnerToRunner 2022. 12. 27. 18:46문제
Given the CITY and COUNTRY tables, query the names of all the continents (COUNTRY.Continent) and their respective average city populations (CITY.Population) rounded down to the nearest integer.
Note: CITY.CountryCode and COUNTRY.Code are matching key columns.

제출답안(MySQL)
SELECT continent, FLOOR(AVG(ct.population))
FROM city as ct JOIN country ctr ON ct.countrycode = ctr.code
GROUP BY continent
문제 바로가기(MySQL)
728x90
    
    
  '코딩테스트연습(SQL)' 카테고리의 다른 글
| New Companies / HackerRank, SQL, MySQL (0) | 2023.01.03 | 
|---|---|
| The Report / HackerRank, SQL, MySQL (0) | 2022.12.28 | 
| Weather Observation Station 20 / HackerRank, SQL, MySQL (0) | 2022.12.27 | 
| Weather Observation Station 19 / HackerRank, SQL, MySQL (0) | 2022.12.26 | 
| Weather Observation Station 18 / HackerRank, SQL, MySQL (0) | 2022.12.26 | 
			  Comments
			
		
	
               
           
					
					
					
					
					
					
				 
								 
								 
								