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 주로(공통 상세 코드)에 대한 데이터입니다.
Author한국노인인력개발원
URLhttps://www.data.go.kr/data/15067128/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 03:57:00.232973
Analysis finished2023-12-12 03:57:01.641596
Duration1.41 second
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
2023-12-12T12:57:02.061851image/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 row110000
2nd row110001
3rd row110002
4th row135002
5th row135000
ValueCountFrequency (%)
110000 1
 
< 0.1%
t48129 1
 
< 0.1%
t48232 1
 
< 0.1%
t48116 1
 
< 0.1%
t48115 1
 
< 0.1%
t48114 1
 
< 0.1%
t48132 1
 
< 0.1%
t48112 1
 
< 0.1%
t48111 1
 
< 0.1%
t48131 1
 
< 0.1%
Other values (2746) 2746
99.6%
2023-12-12T12:57:02.811910image/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
2023-12-12T12:57:03.397704image/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 row110
2nd row110
3rd row110
4th row135
5th row135
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%
c05 26
 
0.9%
c01 26
 
0.9%
240 24
 
0.9%
c12 23
 
0.8%
Other values (459) 2415
87.7%
2023-12-12T12:57:04.217348image/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
2023-12-12T12:57:04.799393image/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 row000
2nd row001
3rd row002
4th row002
5th row000
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%
2023-12-12T12:57:05.542933image/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
2023-12-12T12:57:05.985305image/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 row부적정유형코드
2nd row부적격
3rd row부정수급
4th row시장
5th row보수유형
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%
제조업 25
 
0.6%
Other values (2447) 3797
86.2%
2023-12-12T12:57:06.666589image/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
2023-12-12T12:57:07.028603image/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 row부적정유형코드를 관리한다.
2nd row사업운영 보수유형을 관리한다.
3rd row메뉴유형에 대해 정의합니다.
4th row고친 사용자 등록 유형을 정의 합니다.
5th row메뉴 링크형태에 대해 정의합니다.
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%
2023-12-12T12:57:07.596253image/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%
B 3
 
2.9%
T 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%
5 9
 
6.6%
4 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%
n 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%
t 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%
2023-12-12T12:57:07.756282image/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
2023-12-12T12:57:07.914031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:57:08.066546image/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
2023-12-12T12:57:08.224197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:57:08.419484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Missing values

2023-12-12T12:57:01.164473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:57:01.389985image/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.
2023-12-12T12:57:01.571347image/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
0110000110000부적정유형코드부적정유형코드를 관리한다.Y2016-12-12 14:49:092016-12-12 14:49:09
1110001110001부적격<NA>Y2016-12-12 14:49:092016-12-12 14:49:09
2110002110002부정수급<NA>Y2016-12-12 14:49:092016-12-12 14:49:09
3135002135002시장<NA>Y2016-12-22 13:45:092016-12-22 13:45:09
4135000135000보수유형사업운영 보수유형을 관리한다.Y2016-12-22 13:45:092016-12-22 13:45:09
5135001135001공공<NA>Y2016-12-22 13:45:092016-12-22 13:45:09
6091000091000메뉴유형코드메뉴유형에 대해 정의합니다.Y2016-12-23 14:12:522016-12-23 14:12:52
7091002091002메뉴그룹<NA>Y2016-12-23 14:12:522016-12-23 14:12:52
8884000884000고친등록유형코드고친 사용자 등록 유형을 정의 합니다.Y2016-12-23 14:12:522016-12-23 14:12:52
9092301092301외부URL<NA>Y2016-12-23 14:12:522017-01-24 14:48:25
코드ID대분류코드중분류코드코드명코드설명사용여부등록일수정일
2746E27003E27003실무자노인일자리 실무자 (구.전담인력 제외)Y2023-08-11 16:50:102023-08-11 16:50:10
2747E27000E27000교육사용자유형(2023년)교육지원 사용자의 유형을 관리한다.Y2023-08-11 16:50:102023-08-11 16:50:10
2748E27004E27004신규 실무자노인일자리 신규 실무자 (구.전담인력 제외로 22년 신규 실무자)Y2023-08-11 16:50:102023-08-11 16:50:10
2749E27001E27001담당자노인일자리 담당자 (구.전담인력)Y2023-08-11 16:50:102023-08-11 16:50:10
2750304000304000교육 온라인수료증 검토 반려사유교육 온라인수료증 검토에 대한 반려사유를 관리한다.Y2023-10-04 11:36:112023-10-04 11:36:11
2751304004304004수료증이 열리지 않음<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
2752304002304002타과목 수료증 업로드<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
2753304003304003수료증 정보확인 불가<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
2754304001304001수료증 증빙 파일 없음<NA>Y2023-10-04 11:37:572023-10-04 11:37:57
2755304005304005기타<NA>Y2023-10-04 11:37:572023-10-04 11:37:57