Overview

Dataset statistics

Number of variables8
Number of observations116
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory65.1 B

Variable types

Text3
Categorical4
Boolean1

Dataset

Description한국노인인력개발원에서 운영하는 노인일자리 취업연계에서 제공하는 시스템 관리 정보를 제공합니다. 주로 취업연계 공통코드를 제공합니다.
Author한국노인인력개발원
URLhttps://www.data.go.kr/data/15067136/fileData.do

Alerts

수정일 is highly overall correlated with 대분류코드 and 2 other fieldsHigh correlation
등록일 is highly overall correlated with 대분류코드 and 2 other fieldsHigh correlation
대분류코드 is highly overall correlated with 등록일 and 1 other fieldsHigh correlation
사용여부 is highly overall correlated with 등록일 and 1 other fieldsHigh correlation
사용여부 is highly imbalanced (78.4%)Imbalance
코드ID has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:41:42.068429
Analysis finished2023-12-12 02:41:42.929635
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

코드ID
Text

UNIQUE 

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T11:41:43.177634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6034483
Min length1

Characters and Unicode

Total characters650
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)100.0%

Sample

1st row888011
2nd rowE26000
3rd rowE26001
4th rowE26002
5th rowE26003
ValueCountFrequency (%)
888011 1
 
0.9%
60063 1
 
0.9%
is3001 1
 
0.9%
is3002 1
 
0.9%
is4000 1
 
0.9%
is3000 1
 
0.9%
is4002 1
 
0.9%
is4003 1
 
0.9%
is4001 1
 
0.9%
e12011 1
 
0.9%
Other values (106) 106
91.4%
2023-12-12T11:41:43.601959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 292
44.9%
1 54
 
8.3%
S 43
 
6.6%
2 43
 
6.6%
4 42
 
6.5%
3 37
 
5.7%
5 35
 
5.4%
9 27
 
4.2%
6 21
 
3.2%
E 17
 
2.6%
Other values (8) 39
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 574
88.3%
Uppercase Letter 76
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 292
50.9%
1 54
 
9.4%
2 43
 
7.5%
4 42
 
7.3%
3 37
 
6.4%
5 35
 
6.1%
9 27
 
4.7%
6 21
 
3.7%
8 14
 
2.4%
7 9
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
S 43
56.6%
E 17
 
22.4%
I 7
 
9.2%
P 5
 
6.6%
D 1
 
1.3%
Y 1
 
1.3%
N 1
 
1.3%
W 1
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 574
88.3%
Latin 76
 
11.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 292
50.9%
1 54
 
9.4%
2 43
 
7.5%
4 42
 
7.3%
3 37
 
6.4%
5 35
 
6.1%
9 27
 
4.7%
6 21
 
3.7%
8 14
 
2.4%
7 9
 
1.6%
Latin
ValueCountFrequency (%)
S 43
56.6%
E 17
 
22.4%
I 7
 
9.2%
P 5
 
6.6%
D 1
 
1.3%
Y 1
 
1.3%
N 1
 
1.3%
W 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 292
44.9%
1 54
 
8.3%
S 43
 
6.6%
2 43
 
6.6%
4 42
 
6.5%
3 37
 
5.7%
5 35
 
5.4%
9 27
 
4.2%
6 21
 
3.2%
E 17
 
2.6%
Other values (8) 39
 
6.0%

대분류코드
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
S05
16 
60
8 
400
 
7
S04
 
6
991
 
6
Other values (23)
73 

Length

Max length3
Median length3
Mean length2.9137931
Min length2

Unique

Unique7 ?
Unique (%)6.0%

Sample

1st row888
2nd rowE26
3rd rowE26
4th rowE26
5th rowE26

Common Values

ValueCountFrequency (%)
S05 16
 
13.8%
60 8
 
6.9%
400 7
 
6.0%
S04 6
 
5.2%
991 6
 
5.2%
304 6
 
5.2%
E26 5
 
4.3%
E27 5
 
4.3%
115 5
 
4.3%
990 5
 
4.3%
Other values (18) 47
40.5%

Length

2023-12-12T11:41:43.762184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
s05 16
 
13.8%
60 8
 
6.9%
400 7
 
6.0%
s04 6
 
5.2%
991 6
 
5.2%
304 6
 
5.2%
e26 5
 
4.3%
e27 5
 
4.3%
115 5
 
4.3%
990 5
 
4.3%
Other values (18) 47
40.5%

중분류코드
Categorical

Distinct32
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
0
16 
2
15 
1
15 
3
14 
4
12 
Other values (27)
44 

Length

Max length2
Median length1
Mean length1.1982759
Min length1

Unique

Unique20 ?
Unique (%)17.2%

Sample

1st row11
2nd row0
3rd row1
4th row2
5th row3

Common Values

ValueCountFrequency (%)
0 16
13.8%
2 15
12.9%
1 15
12.9%
3 14
12.1%
4 12
10.3%
5 6
 
5.2%
11 4
 
3.4%
7 3
 
2.6%
6 3
 
2.6%
8 3
 
2.6%
Other values (22) 25
21.6%

Length

2023-12-12T11:41:43.888380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 16
13.8%
1 15
12.9%
2 15
12.9%
3 14
12.1%
4 12
10.3%
5 6
 
5.2%
11 4
 
3.4%
8 3
 
2.6%
10 3
 
2.6%
6 3
 
2.6%
Other values (22) 25
21.6%

코드명
Text

Distinct105
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T11:41:44.125958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length6.3706897
Min length2

Characters and Unicode

Total characters739
Distinct characters215
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)81.9%

Sample

1st row인천
2nd row교육사용자유형(2022년)
3rd row담당자
4th row신규 담당자
5th row실무자
ValueCountFrequency (%)
자원봉사 7
 
4.1%
6
 
3.6%
수료증 4
 
2.4%
신규 4
 
2.4%
실무자 4
 
2.4%
담당자 4
 
2.4%
기타 3
 
1.8%
교육 3
 
1.8%
환수완료 2
 
1.2%
환수진행 2
 
1.2%
Other values (126) 130
76.9%
2023-12-12T11:41:44.513852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53
 
7.2%
0 36
 
4.9%
자 24
 
3.2%
사 22
 
3.0%
수 21
 
2.8%
교 14
 
1.9%
2 14
 
1.9%
육 13
 
1.8%
환 11
 
1.5%
료 11
 
1.5%
Other values (205) 520
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 548
74.2%
Decimal Number 76
 
10.3%
Space Separator 53
 
7.2%
Lowercase Letter 20
 
2.7%
Uppercase Letter 16
 
2.2%
Dash Punctuation 8
 
1.1%
Close Punctuation 6
 
0.8%
Open Punctuation 6
 
0.8%
Other Punctuation 4
 
0.5%
Math Symbol 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 24
 
4.4%
사 22
 
4.0%
수 21
 
3.8%
교 14
 
2.6%
육 13
 
2.4%
환 11
 
2.0%
료 11
 
2.0%
원 9
 
1.6%
증 9
 
1.6%
보 8
 
1.5%
Other values (165) 406
74.1%
Lowercase Letter
ValueCountFrequency (%)
o 4
20.0%
s 3
15.0%
n 2
10.0%
i 2
10.0%
e 2
10.0%
k 1
 
5.0%
r 1
 
5.0%
t 1
 
5.0%
w 1
 
5.0%
j 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
0 36
47.4%
2 14
 
18.4%
1 7
 
9.2%
3 5
 
6.6%
6 3
 
3.9%
7 3
 
3.9%
4 2
 
2.6%
5 2
 
2.6%
8 2
 
2.6%
9 2
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
N 3
18.8%
B 3
18.8%
D 2
12.5%
M 2
12.5%
P 2
12.5%
J 1
 
6.2%
A 1
 
6.2%
I 1
 
6.2%
O 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
· 2
50.0%
, 1
25.0%
/ 1
25.0%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 548
74.2%
Common 155
 
21.0%
Latin 36
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 24
 
4.4%
사 22
 
4.0%
수 21
 
3.8%
교 14
 
2.6%
육 13
 
2.4%
환 11
 
2.0%
료 11
 
2.0%
원 9
 
1.6%
증 9
 
1.6%
보 8
 
1.5%
Other values (165) 406
74.1%
Latin
ValueCountFrequency (%)
o 4
 
11.1%
s 3
 
8.3%
N 3
 
8.3%
B 3
 
8.3%
D 2
 
5.6%
M 2
 
5.6%
n 2
 
5.6%
i 2
 
5.6%
P 2
 
5.6%
e 2
 
5.6%
Other values (11) 11
30.6%
Common
ValueCountFrequency (%)
53
34.2%
0 36
23.2%
2 14
 
9.0%
- 8
 
5.2%
1 7
 
4.5%
) 6
 
3.9%
( 6
 
3.9%
3 5
 
3.2%
6 3
 
1.9%
7 3
 
1.9%
Other values (9) 14
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 548
74.2%
ASCII 189
 
25.6%
None 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53
28.0%
0 36
19.0%
2 14
 
7.4%
- 8
 
4.2%
1 7
 
3.7%
) 6
 
3.2%
( 6
 
3.2%
3 5
 
2.6%
o 4
 
2.1%
s 3
 
1.6%
Other values (29) 47
24.9%
Hangul
ValueCountFrequency (%)
자 24
 
4.4%
사 22
 
4.0%
수 21
 
3.8%
교 14
 
2.6%
육 13
 
2.4%
환 11
 
2.0%
료 11
 
2.0%
원 9
 
1.6%
증 9
 
1.6%
보 8
 
1.5%
Other values (165) 406
74.1%
None
ValueCountFrequency (%)
· 2
100.0%

코드설명
Text

Distinct89
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T11:41:44.828749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length30
Mean length11.456897
Min length2

Characters and Unicode

Total characters1329
Distinct characters223
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)62.9%

Sample

1st row인천
2nd row교육지원 사용자의 유형을 관리한다.
3rd row노인일자리 담당자 (구.전담인력)
4th row노인일자리 신규 담당자 (구.전담인력으로 22년 신규 담당자)
5th row노인일자리 실무자 (구.전담인력 제외)
ValueCountFrequency (%)
선택사항 11
 
4.0%
10
 
3.6%
노인일자리 8
 
2.9%
신규 8
 
2.9%
표시(복지,환경,안전,균형/현항,국민편의 6
 
2.2%
5개 6
 
2.2%
자원봉사 6
 
2.2%
관리한다 6
 
2.2%
실무자 6
 
2.2%
구.전담인력 6
 
2.2%
Other values (134) 204
73.6%
2023-12-12T11:41:45.369370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
161
 
12.1%
자 41
 
3.1%
, 40
 
3.0%
사 29
 
2.2%
( 28
 
2.1%
인 24
 
1.8%
) 23
 
1.7%
리 20
 
1.5%
수 20
 
1.5%
항 17
 
1.3%
Other values (213) 926
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 946
71.2%
Space Separator 161
 
12.1%
Other Punctuation 70
 
5.3%
Decimal Number 40
 
3.0%
Open Punctuation 29
 
2.2%
Uppercase Letter 27
 
2.0%
Close Punctuation 24
 
1.8%
Lowercase Letter 20
 
1.5%
Dash Punctuation 6
 
0.5%
Connector Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 41
 
4.3%
사 29
 
3.1%
인 24
 
2.5%
리 20
 
2.1%
수 20
 
2.1%
항 17
 
1.8%
시 17
 
1.8%
실 17
 
1.8%
전 16
 
1.7%
제 16
 
1.7%
Other values (171) 729
77.1%
Lowercase Letter
ValueCountFrequency (%)
o 4
20.0%
s 3
15.0%
i 2
10.0%
n 2
10.0%
e 2
10.0%
k 1
 
5.0%
j 1
 
5.0%
t 1
 
5.0%
r 1
 
5.0%
p 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
2 11
27.5%
5 7
17.5%
4 6
15.0%
1 5
12.5%
6 3
 
7.5%
3 3
 
7.5%
8 2
 
5.0%
7 1
 
2.5%
0 1
 
2.5%
9 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
D 11
40.7%
C 5
18.5%
I 5
18.5%
P 2
 
7.4%
B 2
 
7.4%
J 1
 
3.7%
N 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 40
57.1%
. 15
 
21.4%
/ 6
 
8.6%
: 5
 
7.1%
· 4
 
5.7%
Open Punctuation
ValueCountFrequency (%)
( 28
96.6%
[ 1
 
3.4%
Close Punctuation
ValueCountFrequency (%)
) 23
95.8%
] 1
 
4.2%
Space Separator
ValueCountFrequency (%)
161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 946
71.2%
Common 336
 
25.3%
Latin 47
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 41
 
4.3%
사 29
 
3.1%
인 24
 
2.5%
리 20
 
2.1%
수 20
 
2.1%
항 17
 
1.8%
시 17
 
1.8%
실 17
 
1.8%
전 16
 
1.7%
제 16
 
1.7%
Other values (171) 729
77.1%
Common
ValueCountFrequency (%)
161
47.9%
, 40
 
11.9%
( 28
 
8.3%
) 23
 
6.8%
. 15
 
4.5%
2 11
 
3.3%
5 7
 
2.1%
/ 6
 
1.8%
4 6
 
1.8%
- 6
 
1.8%
Other values (13) 33
 
9.8%
Latin
ValueCountFrequency (%)
D 11
23.4%
C 5
10.6%
I 5
10.6%
o 4
 
8.5%
s 3
 
6.4%
P 2
 
4.3%
B 2
 
4.3%
i 2
 
4.3%
n 2
 
4.3%
e 2
 
4.3%
Other values (9) 9
19.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 946
71.2%
ASCII 379
28.5%
None 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
161
42.5%
, 40
 
10.6%
( 28
 
7.4%
) 23
 
6.1%
. 15
 
4.0%
D 11
 
2.9%
2 11
 
2.9%
5 7
 
1.8%
/ 6
 
1.6%
4 6
 
1.6%
Other values (31) 71
18.7%
Hangul
ValueCountFrequency (%)
자 41
 
4.3%
사 29
 
3.1%
인 24
 
2.5%
리 20
 
2.1%
수 20
 
2.1%
항 17
 
1.8%
시 17
 
1.8%
실 17
 
1.8%
전 16
 
1.7%
제 16
 
1.7%
Other values (171) 729
77.1%
None
ValueCountFrequency (%)
· 4
100.0%

사용여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size248.0 B
True
112 
False
 
4
ValueCountFrequency (%)
True 112
96.6%
False 4
 
3.4%
2023-12-12T11:41:45.513067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2022-06-10 16:54
20 
2022-08-10 12:52
16 
2022-11-24 18:19
8 
2023-01-04 21:15
7 
2023-10-04 11:37
 
5
Other values (28)
60 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique16 ?
Unique (%)13.8%

Sample

1st row2022-01-05 16:19
2nd row2022-01-12 13:41
3rd row2022-01-12 13:42
4th row2022-01-12 13:42
5th row2022-01-12 13:43

Common Values

ValueCountFrequency (%)
2022-06-10 16:54 20
17.2%
2022-08-10 12:52 16
13.8%
2022-11-24 18:19 8
 
6.9%
2023-01-04 21:15 7
 
6.0%
2023-10-04 11:37 5
 
4.3%
2023-01-18 18:00 5
 
4.3%
2022-11-08 17:44 5
 
4.3%
2023-01-26 16:56 5
 
4.3%
2022-05-10 13:34 5
 
4.3%
2023-08-11 16:50 5
 
4.3%
Other values (23) 35
30.2%

Length

2023-12-12T11:41:45.674243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-06-10 20
 
8.6%
16:54 20
 
8.6%
2022-08-10 16
 
6.9%
12:52 16
 
6.9%
2022-11-24 8
 
3.4%
18:19 8
 
3.4%
2023-01-04 8
 
3.4%
21:15 7
 
3.0%
2023-10-04 6
 
2.6%
2022-11-08 6
 
2.6%
Other values (50) 117
50.4%

수정일
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2022-06-10 16:54
20 
2022-08-10 12:52
16 
2022-11-24 18:19
8 
2023-01-04 21:15
7 
2022-05-13 11:19
6 
Other values (28)
59 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique17 ?
Unique (%)14.7%

Sample

1st row2022-01-05 16:19
2nd row2022-01-12 13:41
3rd row2022-01-12 13:42
4th row2022-01-12 13:42
5th row2022-01-12 13:43

Common Values

ValueCountFrequency (%)
2022-06-10 16:54 20
17.2%
2022-08-10 12:52 16
13.8%
2022-11-24 18:19 8
 
6.9%
2023-01-04 21:15 7
 
6.0%
2022-05-13 11:19 6
 
5.2%
2022-05-10 13:34 5
 
4.3%
2022-11-30 15:45 5
 
4.3%
2023-01-18 18:00 5
 
4.3%
2023-01-26 16:56 5
 
4.3%
2023-10-04 11:37 5
 
4.3%
Other values (23) 34
29.3%

Length

2023-12-12T11:41:45.822446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022-06-10 20
 
8.6%
16:54 20
 
8.6%
2022-08-10 16
 
6.9%
12:52 16
 
6.9%
2022-11-24 8
 
3.4%
18:19 8
 
3.4%
2023-01-04 8
 
3.4%
21:15 7
 
3.0%
2022-05-13 6
 
2.6%
11:19 6
 
2.6%
Other values (51) 117
50.4%

Correlations

2023-12-12T11:41:45.929744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류코드중분류코드코드설명사용여부등록일수정일
대분류코드1.0000.0000.9830.5140.9950.995
중분류코드0.0001.0000.9680.0000.0000.000
코드설명0.9830.9681.0001.0000.9880.988
사용여부0.5140.0001.0001.0000.9240.776
등록일0.9950.0000.9880.9241.0001.000
수정일0.9950.0000.9880.7761.0001.000
2023-12-12T11:41:46.084688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수정일대분류코드중분류코드사용여부등록일
수정일1.0000.8660.0000.5800.981
대분류코드0.8661.0000.0000.3580.866
중분류코드0.0000.0001.0000.0000.000
사용여부0.5800.3580.0001.0000.730
등록일0.9810.8660.0000.7301.000
2023-12-12T11:41:46.206083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류코드중분류코드사용여부등록일수정일
대분류코드1.0000.0000.3580.8660.866
중분류코드0.0001.0000.0000.0000.000
사용여부0.3580.0001.0000.7300.580
등록일0.8660.0000.7301.0000.981
수정일0.8660.0000.5800.9811.000

Missing values

2023-12-12T11:41:42.747714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:41:42.877223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

코드ID대분류코드중분류코드코드명코드설명사용여부등록일수정일
088801188811인천인천Y2022-01-05 16:192022-01-05 16:19
1E26000E260교육사용자유형(2022년)교육지원 사용자의 유형을 관리한다.Y2022-01-12 13:412022-01-12 13:41
2E26001E261담당자노인일자리 담당자 (구.전담인력)Y2022-01-12 13:422022-01-12 13:42
3E26002E262신규 담당자노인일자리 신규 담당자 (구.전담인력으로 22년 신규 담당자)Y2022-01-12 13:422022-01-12 13:42
4E26003E263실무자노인일자리 실무자 (구.전담인력 제외)Y2022-01-12 13:432022-01-12 13:43
5E26004E264신규 실무자노인일자리 신규 실무자 (구.전담인력 제외로 21년 신규 실무자)Y2022-01-12 13:432022-01-12 13:43
6P01008P018hoperoothoperootN2022-01-18 10:372022-01-18 10:37
74000004000자원봉사 - 교육종류교육종류를 관리한다.Y2022-02-17 20:222022-02-17 20:22
84000024002자원봉사 - 사전교육자원봉사 - 사전교육N2022-02-17 20:222022-05-13 11:19
94000034003자원봉사 -기타(외부교육등)자원봉사 -기타(외부교육등)N2022-02-17 20:222022-05-13 11:19
코드ID대분류코드중분류코드코드명코드설명사용여부등록일수정일
106E27003E273실무자노인일자리 실무자 (구.전담인력 제외)Y2023-08-11 16:502023-08-11 16:50
107E27000E270교육사용자유형(2023년)교육지원 사용자의 유형을 관리한다.Y2023-08-11 16:502023-08-11 16:50
108E27004E274신규 실무자노인일자리 신규 실무자 (구.전담인력 제외로 22년 신규 실무자)Y2023-08-11 16:502023-08-11 16:50
109E27001E271담당자노인일자리 담당자 (구.전담인력)Y2023-08-11 16:502023-08-11 16:50
1103040003040교육 온라인수료증 검토 반려사유교육 온라인수료증 검토에 대한 반려사유를 관리한다.Y2023-10-04 11:362023-10-04 11:36
1113040043044수료증이 열리지 않음수료증이 열리지 않음Y2023-10-04 11:372023-10-04 11:37
1123040023042타과목 수료증 업로드타과목 수료증 업로드Y2023-10-04 11:372023-10-04 11:37
1133040033043수료증 정보확인 불가수료증 정보확인 불가Y2023-10-04 11:372023-10-04 11:37
1143040013041수료증 증빙 파일 없음수료증 증빙 파일 없음Y2023-10-04 11:372023-10-04 11:37
1153040053045기타기타Y2023-10-04 11:372023-10-04 11:37