[데이터 출력] 데이터세트(테이블) 출력 - 2

 

2. Display the details of all employees.

 

* 2. Emp 테이블을 출력하시오.

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• 파이썬 & R 패키지 호출 및 예제 데이터 생성 링크

• 데이터세트(테이블) 출력

Oracle : select 구문 파이썬 Pandas : display 구문 R 프로그래밍 : print 구문 R Dplyr Package : print() R sqldf Package : select 구문 Python pandasql Package : select 구문 R data.table Package : Data.table 변환 및 출력 SAS Proc SQL : Select 구문 SAS Data Step : Proc Print Python Dfply Package : display 구문 파이썬 Base 프로그래밍 :

 

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1. 오라클(Oracle)

 

Oracle Programming

select * 
from   emp;

 

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2. 파이썬(Pandas)

 

Python Programming

display(emp)

 

Results

	empno	ename	job	mgr	hiredate	sal	comm	deptno	Tot_salary	annualsal
0	7369	SMITH	CLERK	7902.0	1980/12/17	800	NaN	20	NaN	9600.0
1	7499	ALLEN	SALESMAN	7698.0	1981/02/20	1600	300.0	30	480000.0	19500.0
2	7521	WARD	SALESMAN	7698.0	1981/02/22	1250	500.0	30	625000.0	15500.0
3	7566	JONES	MANAGER	7839.0	1981/04/02	2975	NaN	20	NaN	35700.0
4	7654	MARTIN	SALESMAN	7698.0	1981/09/28	1250	1400.0	30	1750000.0	16400.0
5	7698	BLAKE	MANAGER	7839.0	1981/03/01	2850	NaN	30	NaN	34200.0
6	7782	CLARK	MANAGER	7839.0	1981/01/09	2450	NaN	10	NaN	29400.0
7	7788	SCOTT	ANALYST	7566.0	1982/12/09	3000	NaN	20	NaN	36000.0
8	7839	KING	PRESIDENT	NaN	1981/11/17	5000	NaN	10	NaN	60000.0
9	7844	TURNER	SALESMAN	7698.0	1981/09/08	1500	0.0	30	0.0	18000.0
10	7876	ADAMS	CLERK	7788.0	1983/01/12	1100	NaN	20	NaN	13200.0
11	7900	JAMES	CLERK	7698.0	1981/12/03	950	NaN	30	NaN	11400.0
12	7902	FORD	ANALYST	7566.0	1981/12/03	3000	NaN	20	NaN	36000.0
13	7934	MILLER	CLERK	7782.0	1982/01/23	1300	NaN	10	NaN	15600.0

 

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3. R Programming (R Package)

 

R Programming

%%R

print(emp)

 

Results

# A tibble: 14 x 10
   empno ename job     mgr hiredate     sal  comm deptno Tot_salary
   <dbl> <chr> <chr> <dbl> <date>     <dbl> <dbl>  <dbl>      <dbl>
 1  7369 SMITH CLERK  7902 1980-12-17   800    NA     20         NA
 2  7499 ALLEN SALE~  7698 1981-02-20  1600   300     30     480000
 3  7521 WARD  SALE~  7698 1981-02-22  1250   500     30     625000
 4  7566 JONES MANA~  7839 1981-04-02  2975    NA     20         NA
 5  7654 MART~ SALE~  7698 1981-09-28  1250  1400     30    1750000
 6  7698 BLAKE MANA~  7839 1981-03-01  2850    NA     30         NA
 7  7782 CLARK MANA~  7839 1981-01-09  2450    NA     10         NA
 8  7788 SCOTT ANAL~  7566 1982-12-09  3000    NA     20         NA
 9  7839 KING  PRES~    NA 1981-11-17  5000    NA     10         NA
10  7844 TURN~ SALE~  7698 1981-09-08  1500     0     30          0
11  7876 ADAMS CLERK  7788 1983-01-12  1100    NA     20         NA
12  7900 JAMES CLERK  7698 1981-12-03   950    NA     30         NA
13  7902 FORD  ANAL~  7566 1981-12-03  3000    NA     20         NA
14  7934 MILL~ CLERK  7782 1982-01-23  1300    NA     10         NA
# ... with 1 more variable: annualsal$sal <dbl>

 

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4. R Dplyr Package

 

R Programming

%%R

emp %>% print()

 

Results

# A tibble: 14 x 8
   empno ename  job         mgr hiredate     sal  comm deptno
   <dbl> <chr>  <chr>     <dbl> <date>     <dbl> <dbl>  <dbl>
 1  7369 SMITH  CLERK      7902 1980-12-17   800    NA     20
 2  7499 ALLEN  SALESMAN   7698 1981-02-20  1600   300     30
 3  7521 WARD   SALESMAN   7698 1981-02-22  1250   500     30
 4  7566 JONES  MANAGER    7839 1981-04-02  2975    NA     20
 5  7654 MARTIN SALESMAN   7698 1981-09-28  1250  1400     30
 6  7698 BLAKE  MANAGER    7839 1981-03-01  2850    NA     30
 7  7782 CLARK  MANAGER    7839 1981-01-09  2450    NA     10
 8  7788 SCOTT  ANALYST    7566 1982-12-09  3000    NA     20
 9  7839 KING   PRESIDENT    NA 1981-11-17  5000    NA     10
10  7844 TURNER SALESMAN   7698 1981-09-08  1500     0     30
11  7876 ADAMS  CLERK      7788 1983-01-12  1100    NA     20
12  7900 JAMES  CLERK      7698 1981-12-03   950    NA     30
13  7902 FORD   ANALYST    7566 1981-12-03  3000    NA     20
14  7934 MILLER CLERK      7782 1982-01-23  1300    NA     10

 

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5. R sqldf Package

 

R Programming

%%R

require(sqldf)
sqldf("select * from emp")

 

Results

   empno  ename       job  mgr   hiredate  sal comm deptno
1   7369  SMITH     CLERK 7902 1980-12-17  800   NA     20
2   7499  ALLEN  SALESMAN 7698 1981-02-20 1600  300     30
3   7521   WARD  SALESMAN 7698 1981-02-22 1250  500     30
4   7566  JONES   MANAGER 7839 1981-04-02 2975   NA     20
5   7654 MARTIN  SALESMAN 7698 1981-09-28 1250 1400     30
6   7698  BLAKE   MANAGER 7839 1981-03-01 2850   NA     30
7   7782  CLARK   MANAGER 7839 1981-01-09 2450   NA     10
8   7788  SCOTT   ANALYST 7566 1982-12-09 3000   NA     20
9   7839   KING PRESIDENT   NA 1981-11-17 5000   NA     10
10  7844 TURNER  SALESMAN 7698 1981-09-08 1500    0     30
11  7876  ADAMS     CLERK 7788 1983-01-12 1100   NA     20
12  7900  JAMES     CLERK 7698 1981-12-03  950   NA     30
13  7902   FORD   ANALYST 7566 1981-12-03 3000   NA     20
14  7934 MILLER     CLERK 7782 1982-01-23 1300   NA     10

 

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6. Python pandasql Package

 

Python Programming

import pandasql as ps

ps.sqldf("select * from emp")

 

Results

	empno	ename	job	mgr	hiredate	sal	comm	deptno
0	7369	SMITH	CLERK	7902.0	1980/12/17	800	NaN	20
1	7499	ALLEN	SALESMAN	7698.0	1981/02/20	1600	300.0	30
2	7521	WARD	SALESMAN	7698.0	1981/02/22	1250	500.0	30
3	7566	JONES	MANAGER	7839.0	1981/04/02	2975	NaN	20
4	7654	MARTIN	SALESMAN	7698.0	1981/09/28	1250	1400.0	30
5	7698	BLAKE	MANAGER	7839.0	1981/03/01	2850	NaN	30
6	7782	CLARK	MANAGER	7839.0	1981/01/09	2450	NaN	10
7	7788	SCOTT	ANALYST	7566.0	1982/12/09	3000	NaN	20
8	7839	KING	PRESIDENT	NaN	1981/11/17	5000	NaN	10
9	7844	TURNER	SALESMAN	7698.0	1981/09/08	1500	0.0	30
10	7876	ADAMS	CLERK	7788.0	1983/01/12	1100	NaN	20
11	7900	JAMES	CLERK	7698.0	1981/12/03	950	NaN	30
12	7902	FORD	ANALYST	7566.0	1981/12/03	3000	NaN	20
13	7934	MILLER	CLERK	7782.0	1982/01/23	1300	NaN	10

 

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7. R data.table Package

 

R Programming

%%R

DT          <- data.table(emp)
dept_DT     <- data.table(dept)

DT

 

Results

    empno  ename       job  mgr   hiredate  sal comm deptno
 1:  7369  SMITH     CLERK 7902 1980-12-17  800   NA     20
 2:  7499  ALLEN  SALESMAN 7698 1981-02-20 1600  300     30
 3:  7521   WARD  SALESMAN 7698 1981-02-22 1250  500     30
 4:  7566  JONES   MANAGER 7839 1981-04-02 2975   NA     20
 5:  7654 MARTIN  SALESMAN 7698 1981-09-28 1250 1400     30
 6:  7698  BLAKE   MANAGER 7839 1981-03-01 2850   NA     30
 7:  7782  CLARK   MANAGER 7839 1981-01-09 2450   NA     10
 8:  7788  SCOTT   ANALYST 7566 1982-12-09 3000   NA     20
 9:  7839   KING PRESIDENT   NA 1981-11-17 5000   NA     10
10:  7844 TURNER  SALESMAN 7698 1981-09-08 1500    0     30
11:  7876  ADAMS     CLERK 7788 1983-01-12 1100   NA     20
12:  7900  JAMES     CLERK 7698 1981-12-03  950   NA     30
13:  7902   FORD   ANALYST 7566 1981-12-03 3000   NA     20
14:  7934 MILLER     CLERK 7782 1982-01-23 1300   NA     10

 

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8. SAS Proc SQL

 

SAS Programming

%%SAS sas

proc sql inobs=5;
  select *
  from   emp;
quit;

 

Results

empno	ename	job	mgr	hiredate	sal	comm	deptno
7369	SMITH	CLERK	7902	1980-12-17	800	.	20
7499	ALLEN	SALESMAN	7698	1981-02-20	1600	300	30
7521	WARD	SALESMAN	7698	1981-02-22	1250	500	30
7566	JONES	MANAGER	7839	1981-04-02	2975	.	20
7654	MARTIN	SALESMAN	7698	1981-09-28	1250	1400	30

 

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9. SAS Data Step

 

SAS Programming

%%SAS sas

proc print data=emp;
run;

 

Results

OBS	empno	ename	job	mgr	hiredate	sal	comm	deptno
1	7369	SMITH	CLERK	7902	1980-12-17	800	.	20
2	7499	ALLEN	SALESMAN	7698	1981-02-20	1600	300	30
3	7521	WARD	SALESMAN	7698	1981-02-22	1250	500	30
4	7566	JONES	MANAGER	7839	1981-04-02	2975	.	20
5	7654	MARTIN	SALESMAN	7698	1981-09-28	1250	1400	30
6	7698	BLAKE	MANAGER	7839	1981-03-01	2850	.	30
7	7782	CLARK	MANAGER	7839	1981-01-09	2450	.	10
8	7788	SCOTT	ANALYST	7566	1982-12-09	3000	.	20
9	7839	KING	PRESIDEN	.	1981-11-17	5000	.	10
10	7844	TURNER	SALESMAN	7698	1981-09-08	1500	0	30
11	7876	ADAMS	CLERK	7788	1983-01-12	1100	.	20
12	7900	JAMES	CLERK	7698	1981-12-03	950	.	30
13	7902	FORD	ANALYST	7566	1981-12-03	3000	.	20
14	7934	MILLER	CLERK	7782	1982-01-23	1300	.	10

 

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10. Python Dfply Package

 

Python Programming

display(emp >> head(5))

 

Results

	empno	ename	job	mgr	hiredate	sal	comm	deptno
0	7369	SMITH	CLERK	7902.0	1980/12/17	800	NaN	20
1	7499	ALLEN	SALESMAN	7698.0	1981/02/20	1600	300.0	30
2	7521	WARD	SALESMAN	7698.0	1981/02/22	1250	500.0	30
3	7566	JONES	MANAGER	7839.0	1981/04/02	2975	NaN	20
4	7654	MARTIN	SALESMAN	7698.0	1981/09/28	1250	1400.0	30

 

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[SQL, Pandas, R Prog, Dplyr, SQLDF, PANDASQL, DATA.TABLE]   SQL EMP 예제로 만나는 테이블 데이터 처리 방법 리스트