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통계프로그램 비교 시리즈/오라클함수 비교(R & Python)

TO_CHAR(number) 오라클 함수 [Oracle, Pandas, R Prog, Dplyr, Sqldf, Pandasql, Data.Table, DuckDB]

by 기서무나구물 2021. 12. 24.

포스팅 목차

* 파이썬 & R 패키지 호출 및 예제 데이터 생성 링크

[ TO_CHAR(number) Oracle Function ]

 

TO_CHAR(number) 함수는 수치형 데이터 값을 사용자가 지정한 number 포맷 형식(fmt)을 따르는 문자형(VARCHAR2) 데이터 타입 문자열로 변환하여 반환한다. 값 n은 NUMBER, BINARY_FLOAT 또는 BINARY_DOUBER 데이터형을 지정할 수 있다. 만약 fmt를 생략하면, n은 유효 자릿수를 유지하기 위해서 충분한 길이의 VARCHAR2로 변환한다.

 

 

1. Oracle(오라클)

 

TO_CHAR() 함수

 

수치형 데이터로 계산된 최소 급여를 문자형으로 변경하여 반환한다.

 

Oracle Programming 
SELECT TO_CHAR(MIN(SAL)) "TO_CHAR_VAR"
FROM   EMP

 

Results 
TO_CHAR_VAR
---------------
800

 

 

2. Python Pandas(파이썬)

 

apply(str)

수치형으로 지정되어 있는 급여(‘sal’) 변수의 속성을 문자형으로 형 변환한다.

 

Python Programming 
withmooc = copy.copy(emp)

withmooc['sal_text'] = withmooc['sal'].apply(str)

display( withmooc.head() )

display( withmooc.info() )

# display( type(withmooc) )

 

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

 

Results
 
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 14 entries, 0 to 13
Data columns (total 9 columns):
 #   Column    Non-Null Count  Dtype  
---  ------    --------------  -----  
 0   empno     14 non-null     int64  
 1   ename     14 non-null     object 
 2   job       14 non-null     object 
 3   mgr       13 non-null     float64
 4   hiredate  14 non-null     object 
 5   sal       14 non-null     int64  
 6   comm      4 non-null      float64
 7   deptno    14 non-null     int64  
 8   sal_text  14 non-null     object 
dtypes: float64(2), int64(3), object(4)
memory usage: 1.1+ KB



None



pandas.core.frame.DataFrame

 

 

 

3. R Programming (R Package)

 

sapply() 함수와 tostring 인수

toString 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R

withmooc <- emp
withmooc['sal_text'] <- sapply(withmooc$sal,toString)

withmooc[1:10, ]

 

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

 

sprintf() 출력 함수

sprintf 함수를 사용하여서 원주율 값을 문자형으로 변환한다.

 

R Programming 
%%R

print(sprintf("%s", pi))
class(sprintf("%s", pi))

 

Results 
[1] "3.14159265358979"
[1] "character"

 

sprintf() 출력 함수

sprintf 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R

withmooc <- emp
withmooc['sal_text'] <- sprintf("%s", withmooc$sal)

withmooc

 

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

 

 

as.character() 함수

as.character 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R
withmooc <- emp
withmooc <- transform(withmooc, sal_text=as.character(sal))  #  z=as.numeric(z)

str(withmooc)

 

Results 
'data.frame':    14 obs. of  9 variables:
 $ empno   : num  7369 7499 7521 7566 7654 ...
 $ ename   : chr  "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr  "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : num  7902 7698 7698 7839 7698 ...
 $ hiredate: Date, format: "1980-12-17" "1981-02-20" ...
 $ sal     : num  800 1600 1250 2975 1250 ...
 $ comm    : num  NA 300 500 NA 1400 NA NA NA NA 0 ...
 $ deptno  : num  20 30 30 20 30 30 10 20 10 30 ...
 $ sal_text: chr  "800" "1600" "1250" "2975" ...

 

 

자동 형 변환 작업 :

  • [참고] Convert type of multiple columns of a dataframe at once  [링크]
  • [참고] Change the class from factor to numeric of many columns in a data frame [링크]

 

모든 변수에 대해 as.character를 사용하여서 문자로 변경 후 type.convert 함수로 자동 형 변환 작업을 수행한다. numeric 형태의 변수는 integer 형태의 변수로 형변환 작업을 수행한다. as.is = TRUE 옵션을 사용하여서 character 형태에 대한 factor로 형 변환하는 것을 제어한다.

 

R Programming 
%%R
withmooc <- emp
str(withmooc)
withmooc[] <- lapply(withmooc, function(x) type.convert(as.character(x), as.is = TRUE))

str(withmooc)

 

Results 
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : num [1:14] 7369 7499 7521 7566 7654 ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : num [1:14] 7902 7698 7698 7839 7698 ...
 $ hiredate: Date[1:14], format: "1980-12-17" "1981-02-20" ...
 $ sal     : num [1:14] 800 1600 1250 2975 1250 ...
 $ comm    : num [1:14] NA 300 500 NA 1400 NA NA NA NA 0 ...
 $ deptno  : num [1:14] 20 30 30 20 30 30 10 20 10 30 ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : int [1:14] 7369 7499 7521 7566 7654 7698 7782 7788 7839 7844 ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : int [1:14] 7902 7698 7698 7839 7698 7839 7839 7566 NA 7698 ...
 $ hiredate: chr [1:14] "1980-12-17" "1981-02-20" "1981-02-22" "1981-04-02" ...
 $ sal     : int [1:14] 800 1600 1250 2975 1250 2850 2450 3000 5000 1500 ...
 $ comm    : int [1:14] NA 300 500 NA 1400 NA NA NA NA 0 ...
 $ deptno  : int [1:14] 20 30 30 20 30 30 10 20 10 30 ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )

 

as.character() 

num, chr, Date 형태의 변수를 chr 형태의 변수로 일괄 변환

 

R Programming 
%%R
withmooc <- emp
str(withmooc)
withmooc[] <- apply(withmooc, 2, function(x) (as.character(x)))

str(withmooc)

 

Results 
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : num [1:14] 7369 7499 7521 7566 7654 ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : num [1:14] 7902 7698 7698 7839 7698 ...
 $ hiredate: Date[1:14], format: "1980-12-17" "1981-02-20" ...
 $ sal     : num [1:14] 800 1600 1250 2975 1250 ...
 $ comm    : num [1:14] NA 300 500 NA 1400 NA NA NA NA 0 ...
 $ deptno  : num [1:14] 20 30 30 20 30 30 10 20 10 30 ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : chr [1:14] "7369" "7499" "7521" "7566" ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : chr [1:14] "7902" "7698" "7698" "7839" ...
 $ hiredate: chr [1:14] "1980-12-17" "1981-02-20" "1981-02-22" "1981-04-02" ...
 $ sal     : chr [1:14] " 800" "1600" "1250" "2975" ...
 $ comm    : chr [1:14] NA " 300" " 500" NA ...
 $ deptno  : chr [1:14] "20" "30" "30" "20" ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )

 

 

 

4. R Dplyr Package

 

sapply() 함수와 tostring 인수

toString 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수(리스트)의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R
withmooc <- emp
emp %>%
  dplyr::mutate( sal_text = sapply(withmooc$sal,toString) ) %>%
  head()

 

Results 
# A tibble: 6 x 9
  empno ename  job        mgr hiredate     sal  comm deptno sal_text
  <dbl> <chr>  <chr>    <dbl> <date>     <dbl> <dbl>  <dbl> <chr>   
1  7369 SMITH  CLERK     7902 1980-12-17   800    NA     20 800     
2  7499 ALLEN  SALESMAN  7698 1981-02-20  1600   300     30 1600    
3  7521 WARD   SALESMAN  7698 1981-02-22  1250   500     30 1250    
4  7566 JONES  MANAGER   7839 1981-04-02  2975    NA     20 2975    
5  7654 MARTIN SALESMAN  7698 1981-09-28  1250  1400     30 1250    
6  7698 BLAKE  MANAGER   7839 1981-03-01  2850    NA     30 2850

 

as.character() 함수

as.character 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R
withmooc <- emp
emp %>%
  mutate(sal_text = as.character(sal)) %>%
  head()

 

Results 
# A tibble: 6 x 9
  empno ename  job        mgr hiredate     sal  comm deptno sal_text
  <dbl> <chr>  <chr>    <dbl> <date>     <dbl> <dbl>  <dbl> <chr>   
1  7369 SMITH  CLERK     7902 1980-12-17   800    NA     20 800     
2  7499 ALLEN  SALESMAN  7698 1981-02-20  1600   300     30 1600    
3  7521 WARD   SALESMAN  7698 1981-02-22  1250   500     30 1250    
4  7566 JONES  MANAGER   7839 1981-04-02  2975    NA     20 2975    
5  7654 MARTIN SALESMAN  7698 1981-09-28  1250  1400     30 1250    
6  7698 BLAKE  MANAGER   7839 1981-03-01  2850    NA     30 2850

 

hablar::convert() 함수

 

R Programming 
%%R
withmooc <- emp
library(hablar)

withmooc %>% 
  hablar::convert(chr(sal)) %>%    # int(x, z)
  head()

 

Results 
# A tibble: 6 x 8
  empno ename  job        mgr hiredate   sal    comm deptno
  <dbl> <chr>  <chr>    <dbl> <date>     <chr> <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

 

 

[참고] 자동 형 변환 작업 :

  • 모든 변수에 대해 as.character를 사용하여서 문자로 변경 후 type.convert 함수로 자동 형 변환 작업을 수행한다. numeric 형태의 변수는 integer 형태의 변수로 형변환 작업을 수행한다. as.is = TRUE 옵션을 사용하여서 character 형태에 대한 factor로 형변환하는 것을 제어한다.
  • type_convert 함수 : https://readr.tidyverse.org/reference/type_convert.html
R Programming 
%%R
withmooc <- emp

# str(withmooc)
withmooc <- withmooc %>% mutate_all(funs(type.convert(as.character(.), as.is = TRUE)))

str(withmooc)

 

Results 
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : int [1:14] 7369 7499 7521 7566 7654 7698 7782 7788 7839 7844 ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : int [1:14] 7902 7698 7698 7839 7698 7839 7839 7566 NA 7698 ...
 $ hiredate: chr [1:14] "1980-12-17" "1981-02-20" "1981-02-22" "1981-04-02" ...
 $ sal     : int [1:14] 800 1600 1250 2975 1250 2850 2450 3000 5000 1500 ...
 $ comm    : int [1:14] NA 300 500 NA 1400 NA NA NA NA 0 ...
 $ deptno  : int [1:14] 20 30 30 20 30 30 10 20 10 30 ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )

 

mutate_if() 조건문과 as.character(.)

if 조건문을 사용하여서 변수 형태를 조사 후 형변환 작업을 수행한다. 아래 예제는 수치형 변수를 확인 후 문자형 변수로 형변환 작업을 수행한다.

 

R Programming 
%%R

withmooc <- emp
# str(withmooc)
withmooc <- withmooc %>% mutate_if(is.numeric, ~(as.character(.)))
str(withmooc)

 

Results 
tibble [14 x 8] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ empno   : chr [1:14] "7369" "7499" "7521" "7566" ...
 $ ename   : chr [1:14] "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr [1:14] "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : chr [1:14] "7902" "7698" "7698" "7839" ...
 $ hiredate: Date[1:14], format: "1980-12-17" "1981-02-20" ...
 $ sal     : chr [1:14] "800" "1600" "1250" "2975" ...
 $ comm    : chr [1:14] NA "300" "500" NA ...
 $ deptno  : chr [1:14] "20" "30" "30" "20" ...
 - attr(*, "spec")=
  .. cols(
  ..   empno = col_double(),
  ..   ename = col_character(),
  ..   job = col_character(),
  ..   mgr = col_double(),
  ..   hiredate = col_date(format = ""),
  ..   sal = col_double(),
  ..   comm = col_double(),
  ..   deptno = col_double()
  .. )

 

 

 

5. R sqldf Package

 

cast() 함수

급여 변수의 형태를 text로 변환하고, typeof 함수로 변수 형태를 확인한다.

 

R Programming 
%%R

sqldf(" select cast(sal as text)         as num_text,
               typeof(cast(sal as text)) as sal_type 
        from emp; ")[1:10, ]

 

Results 
   num_text sal_type
1     800.0     text
2    1600.0     text
3    1250.0     text
4    2975.0     text
5    1250.0     text
6    2850.0     text
7    2450.0     text
8    3000.0     text
9    5000.0     text
10   1500.0     text

 

 

 

6. Python pandasql Package

 

cast() 함수

 

Python Programming 
ps.sqldf(" select cast(sal as text) as num_text,     \
                  typeof(cast(sal as text)) sal_type \
           from emp  ").head()

 

Results 
	num_text	sal_type
0	800		text
1	1600		text
2	1250		text
3	2975		text
4	1250		text

 

 

 

7. R data.table Package

 

sapplyr() 함수와 toString 인수

toString 함수를 사용하여서 수치형으로 지정되어 있는 급여(‘sal’) 변수(리스트)의 속성을 문자형으로 형 변환한다.

 

R Programming 
%%R

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

DT[, sal_text := sapply(withmooc$sal,toString)][1:10, ]

# class(DT)

# str(DT)

 

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

 

[참고] 자동 형 변환 작업

 

R Programming 
%%R

DT          <- data.table(emp)
# str(DT)
DT1 = DT[, lapply(.SD, as.character)]
str(DT1)

 

Results 
Classes 'data.table' and 'data.frame':    14 obs. of  8 variables:
 $ empno   : chr  "7369" "7499" "7521" "7566" ...
 $ ename   : chr  "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr  "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : chr  "7902" "7698" "7698" "7839" ...
 $ hiredate: chr  "1980-12-17" "1981-02-20" "1981-02-22" "1981-04-02" ...
 $ sal     : chr  "800" "1600" "1250" "2975" ...
 $ comm    : chr  NA "300" "500" NA ...
 $ deptno  : chr  "20" "30" "30" "20" ...
 - attr(*, ".internal.selfref")=<externalptr>

 

사용자 정의 함수와 as.character(x)

R Programming 
%%R

DT          <- data.table(emp)

DT = data.table(apply(DT, 2, function(x) as.character(x)))

str(DT)

 

Results 
Classes 'data.table' and 'data.frame':    14 obs. of  8 variables:
 $ empno   : chr  "7369" "7499" "7521" "7566" ...
 $ ename   : chr  "SMITH" "ALLEN" "WARD" "JONES" ...
 $ job     : chr  "CLERK" "SALESMAN" "SALESMAN" "MANAGER" ...
 $ mgr     : chr  "7902" "7698" "7698" "7839" ...
 $ hiredate: chr  "1980-12-17" "1981-02-20" "1981-02-22" "1981-04-02" ...
 $ sal     : chr  " 800" "1600" "1250" "2975" ...
 $ comm    : chr  NA " 300" " 500" NA ...
 $ deptno  : chr  "20" "30" "30" "20" ...
 - attr(*, ".internal.selfref")=<externalptr>

 

8. Python Duckdb의 SQL

 

Python Programming 
%%sql
  SELECT cast(MIN(SAL) as varchar)         as Char_num,
         typeof(cast(MIN(SAL) as varchar)) as char_type
  FROM emp

 

Python Programming 
duckdb.sql(" SELECT cast(MIN(SAL) as varchar)         as Char_num,    \
                    typeof(cast(MIN(SAL) as varchar)) as char_type    \
             FROM emp ").df()

 

Results 
  Char_num char_type
0      800   VARCHAR

 

Python Programming 
%%sql
  select cast(sal as text) as num_text,
         typeof(cast(sal as text)) sal_type
  from   emp
  LIMIT  6

 

Python Programming 
duckdb.sql(" select cast(sal as text) as num_text,          \
                    typeof(cast(sal as text)) sal_type      \
             from   emp                                     \
             LIMIT  6 ").df()

 

Results 
  num_text sal_type
0      800  VARCHAR
1     1600  VARCHAR
2     1250  VARCHAR
3     2975  VARCHAR
4     1250  VARCHAR
5     2850  VARCHAR

 

Dominoes laid out in a background pattern. ( https://unsplash.com/photos/kgRBoAKq-4E )

  --------------------------------------------  

 

 

[Oracle, Pandas, R Prog, Dplyr, Sqldf, Pandasql, Data.Table] 오라클 함수와 R & Python 비교 사전 목록 링크

 

오라클 SQL 함수(Oracle SQL Function) 목록 리스트 링크

 

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