Overview

Dataset statistics

Number of variables8
Number of observations2756
Missing cells1267
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory172.4 KiB
Average record size in memory64.0 B

Variable types

Text5
Boolean1
DateTime2

Dataset

Description한국노인인력개발원에서 운영하는 노인일자리 취업연계에서 제공하는 시스템 관리 정보로 대분류, 중분류, 코드명 등의 항목을 제공합니다.
Author한국노인인력개발원
URLhttps://www.data.go.kr/data/15067132/fileData.do

Alerts

사용여부 is highly imbalanced (85.5%)Imbalance
코드설명 has 1265 (45.9%) missing valuesMissing
코드ID has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:50:45.551100
Analysis finished2023-12-12 10:50:47.719940
Duration2.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

코드ID
Text

UNIQUE 

Distinct2756
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2023-12-12T19:50:49.025753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8185776
Min length1

Characters and Unicode

Total characters16036
Distinct characters31
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

Unique2756 ?
Unique (%)100.0%

Sample

1st row304002
2nd row304005
3rd row304004
4th row304001
5th row304003
ValueCountFrequency (%)
304002 1
 
< 0.1%
931a4 1
 
< 0.1%
131020 1
 
< 0.1%
941a3 1
 
< 0.1%
941a4 1
 
< 0.1%
960000 1
 
< 0.1%
964004 1
 
< 0.1%
967004 1
 
< 0.1%
931a2 1
 
< 0.1%
931a3 1
 
< 0.1%
Other values (2746) 2746
99.6%
2023-12-12T19:50:50.294497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5098
31.8%
1 2026
 
12.6%
2 1495
 
9.3%
4 1392
 
8.7%
3 1218
 
7.6%
9 749
 
4.7%
8 747
 
4.7%
5 691
 
4.3%
T 646
 
4.0%
6 509
 
3.2%
Other values (21) 1465
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14290
89.1%
Uppercase Letter 1746
 
10.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T 646
37.0%
C 298
17.1%
E 201
 
11.5%
W 150
 
8.6%
M 106
 
6.1%
A 94
 
5.4%
S 58
 
3.3%
N 48
 
2.7%
B 40
 
2.3%
P 31
 
1.8%
Other values (11) 74
 
4.2%
Decimal Number
ValueCountFrequency (%)
0 5098
35.7%
1 2026
 
14.2%
2 1495
 
10.5%
4 1392
 
9.7%
3 1218
 
8.5%
9 749
 
5.2%
8 747
 
5.2%
5 691
 
4.8%
6 509
 
3.6%
7 365
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 14290
89.1%
Latin 1746
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 646
37.0%
C 298
17.1%
E 201
 
11.5%
W 150
 
8.6%
M 106
 
6.1%
A 94
 
5.4%
S 58
 
3.3%
N 48
 
2.7%
B 40
 
2.3%
P 31
 
1.8%
Other values (11) 74
 
4.2%
Common
ValueCountFrequency (%)
0 5098
35.7%
1 2026
 
14.2%
2 1495
 
10.5%
4 1392
 
9.7%
3 1218
 
8.5%
9 749
 
5.2%
8 747
 
5.2%
5 691
 
4.8%
6 509
 
3.6%
7 365
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5098
31.8%
1 2026
 
12.6%
2 1495
 
9.3%
4 1392
 
8.7%
3 1218
 
7.6%
9 749
 
4.7%
8 747
 
4.7%
5 691
 
4.3%
T 646
 
4.0%
6 509
 
3.2%
Other values (21) 1465
 
9.1%

대분류코드
Text

Distinct469
Distinct (%)17.0%
Missing1
Missing (%)< 0.1%
Memory size21.7 KiB
2023-12-12T19:50:51.395902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9967332
Min length2

Characters and Unicode

Total characters8256
Distinct characters24
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

Unique40 ?
Unique (%)1.5%

Sample

1st row304
2nd row304
3rd row304
4th row304
5th row304
ValueCountFrequency (%)
c03 54
 
2.0%
214 50
 
1.8%
060 36
 
1.3%
401 34
 
1.2%
w35 34
 
1.2%
816 33
 
1.2%
c01 26
 
0.9%
c05 26
 
0.9%
240 24
 
0.9%
096 23
 
0.8%
Other values (459) 2415
87.7%
2023-12-12T19:50:52.805723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1358
16.4%
1 1146
13.9%
2 815
9.9%
3 635
7.7%
8 625
7.6%
9 613
7.4%
4 594
7.2%
5 449
 
5.4%
6 379
 
4.6%
M 350
 
4.2%
Other values (14) 1292
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6880
83.3%
Uppercase Letter 1376
 
16.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 350
25.4%
C 276
20.1%
E 197
14.3%
W 149
10.8%
B 137
 
10.0%
N 107
 
7.8%
S 52
 
3.8%
A 47
 
3.4%
P 19
 
1.4%
I 14
 
1.0%
Other values (4) 28
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 1358
19.7%
1 1146
16.7%
2 815
11.8%
3 635
9.2%
8 625
9.1%
9 613
8.9%
4 594
8.6%
5 449
 
6.5%
6 379
 
5.5%
7 266
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 6880
83.3%
Latin 1376
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 350
25.4%
C 276
20.1%
E 197
14.3%
W 149
10.8%
B 137
 
10.0%
N 107
 
7.8%
S 52
 
3.8%
A 47
 
3.4%
P 19
 
1.4%
I 14
 
1.0%
Other values (4) 28
 
2.0%
Common
ValueCountFrequency (%)
0 1358
19.7%
1 1146
16.7%
2 815
11.8%
3 635
9.2%
8 625
9.1%
9 613
8.9%
4 594
8.6%
5 449
 
6.5%
6 379
 
5.5%
7 266
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1358
16.4%
1 1146
13.9%
2 815
9.9%
3 635
7.7%
8 625
7.6%
9 613
7.4%
4 594
7.2%
5 449
 
5.4%
6 379
 
4.6%
M 350
 
4.2%
Other values (14) 1292
15.6%

중분류코드
Text

Distinct673
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
2023-12-12T19:50:53.834747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7750363
Min length1

Characters and Unicode

Total characters7648
Distinct characters29
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

Unique478 ?
Unique (%)17.3%

Sample

1st row002
2nd row005
3rd row004
4th row001
5th row003
ValueCountFrequency (%)
000 289
 
10.5%
001 201
 
7.3%
002 195
 
7.1%
003 164
 
6.0%
004 124
 
4.5%
005 79
 
2.9%
006 44
 
1.6%
10 37
 
1.3%
007 36
 
1.3%
20 35
 
1.3%
Other values (663) 1552
56.3%
2023-12-12T19:50:55.396802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3758
49.1%
1 830
 
10.9%
2 678
 
8.9%
3 558
 
7.3%
4 423
 
5.5%
5 307
 
4.0%
6 229
 
3.0%
9 227
 
3.0%
8 220
 
2.9%
7 195
 
2.5%
Other values (19) 223
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7425
97.1%
Uppercase Letter 223
 
2.9%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 94
42.2%
B 40
17.9%
C 22
 
9.9%
R 18
 
8.1%
P 12
 
5.4%
D 9
 
4.0%
J 5
 
2.2%
F 4
 
1.8%
E 4
 
1.8%
Y 2
 
0.9%
Other values (9) 13
 
5.8%
Decimal Number
ValueCountFrequency (%)
0 3758
50.6%
1 830
 
11.2%
2 678
 
9.1%
3 558
 
7.5%
4 423
 
5.7%
5 307
 
4.1%
6 229
 
3.1%
9 227
 
3.1%
8 220
 
3.0%
7 195
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 7425
97.1%
Latin 223
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 94
42.2%
B 40
17.9%
C 22
 
9.9%
R 18
 
8.1%
P 12
 
5.4%
D 9
 
4.0%
J 5
 
2.2%
F 4
 
1.8%
E 4
 
1.8%
Y 2
 
0.9%
Other values (9) 13
 
5.8%
Common
ValueCountFrequency (%)
0 3758
50.6%
1 830
 
11.2%
2 678
 
9.1%
3 558
 
7.5%
4 423
 
5.7%
5 307
 
4.1%
6 229
 
3.1%
9 227
 
3.1%
8 220
 
3.0%
7 195
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3758
49.1%
1 830
 
10.9%
2 678
 
8.9%
3 558
 
7.3%
4 423
 
5.5%
5 307
 
4.0%
6 229
 
3.0%
9 227
 
3.0%
8 220
 
2.9%
7 195
 
2.5%
Other values (19) 223
 
2.9%

코드명
Text

Distinct2238
Distinct (%)81.2%
Missing1
Missing (%)< 0.1%
Memory size21.7 KiB
2023-12-12T19:50:56.156216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length47
Mean length6.7891107
Min length1

Characters and Unicode

Total characters18704
Distinct characters525
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1949 ?
Unique (%)70.7%

Sample

1st row타과목 수료증 업로드
2nd row기타
3rd row수료증이 열리지 않음
4th row수료증 증빙 파일 없음
5th row수료증 정보확인 불가
ValueCountFrequency (%)
및 200
 
4.5%
기타 135
 
3.1%
조작원 56
 
1.3%
종사원 34
 
0.8%
종사자 34
 
0.8%
전문가 32
 
0.7%
사무원 31
 
0.7%
관리자 30
 
0.7%
기술자 29
 
0.7%
서비스업 25
 
0.6%
Other values (2447) 3797
86.2%
2023-12-12T19:50:57.146299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1655
 
8.8%
사 521
 
2.8%
기 505
 
2.7%
원 476
 
2.5%
· 409
 
2.2%
자 363
 
1.9%
업 279
 
1.5%
시 266
 
1.4%
조 221
 
1.2%
인 218
 
1.2%
Other values (515) 13791
73.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15349
82.1%
Space Separator 1660
 
8.9%
Other Punctuation 554
 
3.0%
Decimal Number 416
 
2.2%
Lowercase Letter 308
 
1.6%
Close Punctuation 154
 
0.8%
Open Punctuation 154
 
0.8%
Uppercase Letter 65
 
0.3%
Dash Punctuation 21
 
0.1%
Math Symbol 15
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 521
 
3.4%
기 505
 
3.3%
원 476
 
3.1%
자 363
 
2.4%
업 279
 
1.8%
시 266
 
1.7%
조 221
 
1.4%
인 218
 
1.4%
구 216
 
1.4%
관 208
 
1.4%
Other values (446) 12076
78.7%
Lowercase Letter
ValueCountFrequency (%)
o 44
14.3%
m 34
11.0%
a 33
10.7%
c 30
9.7%
e 24
 
7.8%
n 19
 
6.2%
h 17
 
5.5%
i 16
 
5.2%
r 16
 
5.2%
l 15
 
4.9%
Other values (12) 60
19.5%
Uppercase Letter
ValueCountFrequency (%)
B 9
13.8%
A 8
12.3%
M 7
10.8%
S 6
9.2%
C 5
 
7.7%
L 4
 
6.2%
N 4
 
6.2%
E 3
 
4.6%
I 3
 
4.6%
Q 2
 
3.1%
Other values (11) 14
21.5%
Decimal Number
ValueCountFrequency (%)
0 127
30.5%
2 78
18.8%
1 71
17.1%
3 34
 
8.2%
9 27
 
6.5%
4 22
 
5.3%
5 20
 
4.8%
6 17
 
4.1%
7 11
 
2.6%
8 9
 
2.2%
Other Punctuation
ValueCountFrequency (%)
· 409
73.8%
, 67
 
12.1%
/ 36
 
6.5%
. 35
 
6.3%
& 6
 
1.1%
: 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1655
99.7%
　 5
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 152
98.7%
] 2
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 152
98.7%
[ 2
 
1.3%
Math Symbol
ValueCountFrequency (%)
~ 12
80.0%
+ 3
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15349
82.1%
Common 2982
 
15.9%
Latin 373
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 521
 
3.4%
기 505
 
3.3%
원 476
 
3.1%
자 363
 
2.4%
업 279
 
1.8%
시 266
 
1.7%
조 221
 
1.4%
인 218
 
1.4%
구 216
 
1.4%
관 208
 
1.4%
Other values (446) 12076
78.7%
Latin
ValueCountFrequency (%)
o 44
 
11.8%
m 34
 
9.1%
a 33
 
8.8%
c 30
 
8.0%
e 24
 
6.4%
n 19
 
5.1%
h 17
 
4.6%
i 16
 
4.3%
r 16
 
4.3%
l 15
 
4.0%
Other values (33) 125
33.5%
Common
ValueCountFrequency (%)
1655
55.5%
· 409
 
13.7%
) 152
 
5.1%
( 152
 
5.1%
0 127
 
4.3%
2 78
 
2.6%
1 71
 
2.4%
, 67
 
2.2%
/ 36
 
1.2%
. 35
 
1.2%
Other values (16) 200
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15338
82.0%
ASCII 2941
 
15.7%
None 414
 
2.2%
Compat Jamo 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1655
56.3%
) 152
 
5.2%
( 152
 
5.2%
0 127
 
4.3%
2 78
 
2.7%
1 71
 
2.4%
, 67
 
2.3%
o 44
 
1.5%
/ 36
 
1.2%
. 35
 
1.2%
Other values (57) 524
 
17.8%
Hangul
ValueCountFrequency (%)
사 521
 
3.4%
기 505
 
3.3%
원 476
 
3.1%
자 363
 
2.4%
업 279
 
1.8%
시 266
 
1.7%
조 221
 
1.4%
인 218
 
1.4%
구 216
 
1.4%
관 208
 
1.4%
Other values (445) 12065
78.7%
None
ValueCountFrequency (%)
· 409
98.8%
　 5
 
1.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%

코드설명
Text

MISSING 

Distinct1299
Distinct (%)87.1%
Missing1265
Missing (%)45.9%
Memory size21.7 KiB
2023-12-12T19:50:57.665315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length33
Mean length10.59222
Min length1

Characters and Unicode

Total characters15793
Distinct characters482
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1199 ?
Unique (%)80.4%

Sample

1st row교육 온라인수료증 검토에 대한 반려사유를 관리한다.
2nd row노인일자리 신규 담당자 (구.전담인력으로 23년 신규 담당자)
3rd row노인일자리 실무자 (구.전담인력 제외)
4th row교육지원 사용자의 유형을 관리한다.
5th row노인일자리 신규 실무자 (구.전담인력 제외로 22년 신규 실무자)
ValueCountFrequency (%)
및 201
 
5.6%
관리한다 110
 
3.1%
기타 89
 
2.5%
조작원 56
 
1.6%
종사원 34
 
0.9%
종사자 32
 
0.9%
전문가 32
 
0.9%
사무원 31
 
0.9%
기술자 29
 
0.8%
관리자 28
 
0.8%
Other values (1673) 2943
82.1%
2023-12-12T19:50:58.542294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2098
 
13.3%
사 459
 
2.9%
원 454
 
2.9%
기 364
 
2.3%
자 320
 
2.0%
· 307
 
1.9%
리 300
 
1.9%
관 284
 
1.8%
및 201
 
1.3%
업 193
 
1.2%
Other values (472) 10813
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12162
77.0%
Space Separator 2103
 
13.3%
Other Punctuation 665
 
4.2%
Lowercase Letter 393
 
2.5%
Decimal Number 137
 
0.9%
Open Punctuation 107
 
0.7%
Uppercase Letter 104
 
0.7%
Close Punctuation 102
 
0.6%
Math Symbol 8
 
0.1%
Connector Punctuation 6
 
< 0.1%
Other values (2) 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 459
 
3.8%
원 454
 
3.7%
기 364
 
3.0%
자 320
 
2.6%
리 300
 
2.5%
관 284
 
2.3%
및 201
 
1.7%
업 193
 
1.6%
조 183
 
1.5%
의 167
 
1.4%
Other values (405) 9237
75.9%
Lowercase Letter
ValueCountFrequency (%)
e 80
20.4%
s 56
14.2%
t 33
8.4%
a 28
 
7.1%
o 26
 
6.6%
p 24
 
6.1%
l 21
 
5.3%
r 19
 
4.8%
n 17
 
4.3%
u 15
 
3.8%
Other values (12) 74
18.8%
Uppercase Letter
ValueCountFrequency (%)
C 22
21.2%
R 17
16.3%
A 15
14.4%
D 15
14.4%
P 8
 
7.7%
J 7
 
6.7%
I 6
 
5.8%
T 3
 
2.9%
B 3
 
2.9%
F 2
 
1.9%
Other values (6) 6
 
5.8%
Decimal Number
ValueCountFrequency (%)
2 48
35.0%
0 24
17.5%
1 18
 
13.1%
8 11
 
8.0%
4 9
 
6.6%
5 9
 
6.6%
3 7
 
5.1%
9 6
 
4.4%
7 3
 
2.2%
6 2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
· 307
46.2%
. 169
25.4%
, 150
22.6%
/ 30
 
4.5%
: 5
 
0.8%
' 2
 
0.3%
？ 1
 
0.2%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
2098
99.8%
　 5
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 74
69.2%
[ 33
30.8%
Close Punctuation
ValueCountFrequency (%)
) 69
67.6%
] 33
32.4%
Other Symbol
ValueCountFrequency (%)
△ 1
50.0%
○ 1
50.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12162
77.0%
Common 3134
 
19.8%
Latin 497
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 459
 
3.8%
원 454
 
3.7%
기 364
 
3.0%
자 320
 
2.6%
리 300
 
2.5%
관 284
 
2.3%
및 201
 
1.7%
업 193
 
1.6%
조 183
 
1.5%
의 167
 
1.4%
Other values (405) 9237
75.9%
Latin
ValueCountFrequency (%)
e 80
16.1%
s 56
 
11.3%
t 33
 
6.6%
a 28
 
5.6%
o 26
 
5.2%
p 24
 
4.8%
C 22
 
4.4%
l 21
 
4.2%
r 19
 
3.8%
R 17
 
3.4%
Other values (28) 171
34.4%
Common
ValueCountFrequency (%)
2098
66.9%
· 307
 
9.8%
. 169
 
5.4%
, 150
 
4.8%
( 74
 
2.4%
) 69
 
2.2%
2 48
 
1.5%
[ 33
 
1.1%
] 33
 
1.1%
/ 30
 
1.0%
Other values (19) 123
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12151
76.9%
ASCII 3315
 
21.0%
None 314
 
2.0%
Compat Jamo 11
 
0.1%
Geometric Shapes 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2098
63.3%
. 169
 
5.1%
, 150
 
4.5%
e 80
 
2.4%
( 74
 
2.2%
) 69
 
2.1%
s 56
 
1.7%
2 48
 
1.4%
[ 33
 
1.0%
] 33
 
1.0%
Other values (51) 505
 
15.2%
Hangul
ValueCountFrequency (%)
사 459
 
3.8%
원 454
 
3.7%
기 364
 
3.0%
자 320
 
2.6%
리 300
 
2.5%
관 284
 
2.3%
및 201
 
1.7%
업 193
 
1.6%
조 183
 
1.5%
의 167
 
1.4%
Other values (404) 9226
75.9%
None
ValueCountFrequency (%)
· 307
97.8%
　 5
 
1.6%
？ 1
 
0.3%
Ｘ 1
 
0.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%
Geometric Shapes
ValueCountFrequency (%)
△ 1
50.0%
○ 1
50.0%

사용여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
True
2699 
False
 
57
ValueCountFrequency (%)
True 2699
97.9%
False 57
 
2.1%
2023-12-12T19:50:58.787277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일
Date

Distinct400
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
Minimum2016-12-12 14:49:09
Maximum2023-10-04 11:37:57
2023-12-12T19:50:59.007500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:50:59.327917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일
Date

Distinct429
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size21.7 KiB
Minimum2016-12-12 14:49:09
Maximum2023-10-04 11:37:57
2023-12-12T19:50:59.648565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:50:59.973652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2023-12-12T19:50:47.074674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:50:47.357941image/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.
2023-12-12T19:50:47.593951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

코드ID대분류코드중분류코드코드명코드설명사용여부등록일수정일
0304002304002타과목 수료증 업로드<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
1304005304005기타<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
2304004304004수료증이 열리지 않음<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
3304001304001수료증 증빙 파일 없음<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
4304003304003수료증 정보확인 불가<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
5304000304000교육 온라인수료증 검토 반려사유교육 온라인수료증 검토에 대한 반려사유를 관리한다.Y2023-10-04 11:36:112023-10-04 11:36:11
6E27002E27002신규 담당자노인일자리 신규 담당자 (구.전담인력으로 23년 신규 담당자)Y2023-08-11 16:50:102023-08-11 16:50:10
7E27003E27003실무자노인일자리 실무자 (구.전담인력 제외)Y2023-08-11 16:50:102023-08-11 16:50:10
8E27000E27000교육사용자유형(2023년)교육지원 사용자의 유형을 관리한다.Y2023-08-11 16:50:102023-08-11 16:50:10
9E27004E27004신규 실무자노인일자리 신규 실무자 (구.전담인력 제외로 22년 신규 실무자)Y2023-08-11 16:50:102023-08-11 16:50:10
코드ID대분류코드중분류코드코드명코드설명사용여부등록일수정일
2746092201092201통합게시판<NA>Y2016-12-23 14:12:522017-01-24 14:48:25
2747092301092301외부URL<NA>Y2016-12-23 14:12:522017-01-24 14:48:25
2748884000884000고친등록유형코드고친 사용자 등록 유형을 정의 합니다.Y2016-12-23 14:12:522016-12-23 14:12:52
2749092101092101개별프로그램<NA>Y2016-12-23 14:12:522017-01-24 14:48:25
2750135002135002시장<NA>Y2016-12-22 13:45:092016-12-22 13:45:09
2751135000135000보수유형사업운영 보수유형을 관리한다.Y2016-12-22 13:45:092016-12-22 13:45:09
2752135001135001공공<NA>Y2016-12-22 13:45:092016-12-22 13:45:09
2753110000110000부적정유형코드부적정유형코드를 관리한다.Y2016-12-12 14:49:092016-12-12 14:49:09
2754110001110001부적격<NA>Y2016-12-12 14:49:092016-12-12 14:49:09
2755110002110002부정수급<NA>Y2016-12-12 14:49:092016-12-12 14:49:09