Overview

Dataset statistics

Number of variables3
Number of observations113
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)1.8%
Total size in memory2.9 KiB
Average record size in memory26.2 B

Variable types

Text2
Numeric1

Dataset

Description메타관리시스템 기반 공공데이터 개방계획 수립 및 이행을 위한 수상구조사 시스템의 수상안전종합관리 메뉴정보에 관한 데이터로 메뉴설명, 메뉴명, 메뉴순서 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15118342/fileData.do

Alerts

Dataset has 2 (1.8%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 09:00:21.927118
Analysis finished2023-12-12 09:00:22.325665
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

메뉴명칭(MENU_NM)
Text

Distinct106
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T18:00:22.563901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.619469
Min length3

Characters and Unicode

Total characters748
Distinct characters145
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)87.6%

Sample

1st row개인별이력현황
2nd row게시물관리
3rd row게시물등록
4th row게시판관리
5th row게시판속성관리
ValueCountFrequency (%)
권한관리 2
 
1.6%
교육기관현황 2
 
1.6%
자격시험공고 2
 
1.6%
보수교육대상자현황 2
 
1.6%
교육공고 2
 
1.6%
교육이수현황 2
 
1.6%
교육안내 2
 
1.6%
취소현황 1
 
0.8%
일자별접속현황 1
 
0.8%
자격시험일정등록 1
 
0.8%
Other values (107) 107
86.3%
2023-12-12T18:00:23.060096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 41
 
5.5%
자 38
 
5.1%
리 32
 
4.3%
시 31
 
4.1%
현 26
 
3.5%
교 26
 
3.5%
황 26
 
3.5%
육 25
 
3.3%
격 24
 
3.2%
수 20
 
2.7%
Other values (135) 459
61.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 731
97.7%
Space Separator 11
 
1.5%
Other Punctuation 4
 
0.5%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 41
 
5.6%
자 38
 
5.2%
리 32
 
4.4%
시 31
 
4.2%
현 26
 
3.6%
교 26
 
3.6%
황 26
 
3.6%
육 25
 
3.4%
격 24
 
3.3%
수 20
 
2.7%
Other values (130) 442
60.5%
Other Punctuation
ValueCountFrequency (%)
/ 3
75.0%
· 1
 
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 731
97.7%
Common 17
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 41
 
5.6%
자 38
 
5.2%
리 32
 
4.4%
시 31
 
4.2%
현 26
 
3.6%
교 26
 
3.6%
황 26
 
3.6%
육 25
 
3.4%
격 24
 
3.3%
수 20
 
2.7%
Other values (130) 442
60.5%
Common
ValueCountFrequency (%)
11
64.7%
/ 3
 
17.6%
) 1
 
5.9%
( 1
 
5.9%
· 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 731
97.7%
ASCII 16
 
2.1%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 41
 
5.6%
자 38
 
5.2%
리 32
 
4.4%
시 31
 
4.2%
현 26
 
3.6%
교 26
 
3.6%
황 26
 
3.6%
육 25
 
3.4%
격 24
 
3.3%
수 20
 
2.7%
Other values (130) 442
60.5%
ASCII
ValueCountFrequency (%)
11
68.8%
/ 3
 
18.8%
) 1
 
6.2%
( 1
 
6.2%
None
ValueCountFrequency (%)
· 1
100.0%

메뉴설명(MENU_DC)
Text

Distinct104
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T18:00:23.387812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length18
Mean length7.2477876
Min length2

Characters and Unicode

Total characters819
Distinct characters149
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)85.0%

Sample

1st row개인별이력현황
2nd row게시물관리
3rd row게시물관리
4th row게시판관리
5th row게시판속성관리
ValueCountFrequency (%)
조회 4
 
2.7%
교육공고 3
 
2.0%
교육기관 3
 
2.0%
성별 2
 
1.3%
현황 2
 
1.3%
교육기관별 2
 
1.3%
등록 2
 
1.3%
변경 2
 
1.3%
보수교육대상자현황 2
 
1.3%
게시물관리 2
 
1.3%
Other values (121) 126
84.0%
2023-12-12T18:00:24.260208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 43
 
5.3%
37
 
4.5%
자 36
 
4.4%
시 31
 
3.8%
리 30
 
3.7%
교 26
 
3.2%
육 25
 
3.1%
현 24
 
2.9%
황 24
 
2.9%
격 24
 
2.9%
Other values (139) 519
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 774
94.5%
Space Separator 37
 
4.5%
Lowercase Letter 4
 
0.5%
Other Punctuation 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 43
 
5.6%
자 36
 
4.7%
시 31
 
4.0%
리 30
 
3.9%
교 26
 
3.4%
육 25
 
3.2%
현 24
 
3.1%
황 24
 
3.1%
격 24
 
3.1%
수 21
 
2.7%
Other values (132) 490
63.3%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
r 1
25.0%
t 1
25.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 774
94.5%
Common 41
 
5.0%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 43
 
5.6%
자 36
 
4.7%
시 31
 
4.0%
리 30
 
3.9%
교 26
 
3.4%
육 25
 
3.2%
현 24
 
3.1%
황 24
 
3.1%
격 24
 
3.1%
수 21
 
2.7%
Other values (132) 490
63.3%
Common
ValueCountFrequency (%)
37
90.2%
, 2
 
4.9%
) 1
 
2.4%
( 1
 
2.4%
Latin
ValueCountFrequency (%)
o 2
50.0%
r 1
25.0%
t 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 774
94.5%
ASCII 45
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 43
 
5.6%
자 36
 
4.7%
시 31
 
4.0%
리 30
 
3.9%
교 26
 
3.4%
육 25
 
3.2%
현 24
 
3.1%
황 24
 
3.1%
격 24
 
3.1%
수 21
 
2.7%
Other values (132) 490
63.3%
ASCII
ValueCountFrequency (%)
37
82.2%
, 2
 
4.4%
o 2
 
4.4%
) 1
 
2.2%
r 1
 
2.2%
( 1
 
2.2%
t 1
 
2.2%

메뉴순서(MENU_ORDR)
Real number (ℝ)

Distinct23
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.318584
Minimum1
Maximum96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T18:00:24.411012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile90.4
Maximum96
Range95
Interquartile range (IQR)6

Descriptive statistics

Standard deviation21.647033
Coefficient of variation (CV)2.0978685
Kurtosis11.014224
Mean10.318584
Median Absolute Deviation (MAD)3
Skewness3.5197374
Sum1166
Variance468.59403
MonotonicityNot monotonic
2023-12-12T18:00:24.596957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 21
18.6%
2 16
14.2%
3 13
11.5%
4 10
8.8%
5 8
 
7.1%
7 8
 
7.1%
6 7
 
6.2%
8 6
 
5.3%
11 3
 
2.7%
10 3
 
2.7%
Other values (13) 18
15.9%
ValueCountFrequency (%)
1 21
18.6%
2 16
14.2%
3 13
11.5%
4 10
8.8%
5 8
 
7.1%
6 7
 
6.2%
7 8
 
7.1%
8 6
 
5.3%
9 3
 
2.7%
10 3
 
2.7%
ValueCountFrequency (%)
96 1
0.9%
95 1
0.9%
94 1
0.9%
93 1
0.9%
92 1
0.9%
91 1
0.9%
90 1
0.9%
16 1
0.9%
15 1
0.9%
14 1
0.9%

Interactions

2023-12-12T18:00:22.109174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T18:00:22.219341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:00:22.292859image/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

메뉴명칭(MENU_NM)메뉴설명(MENU_DC)메뉴순서(MENU_ORDR)
0개인별이력현황개인별이력현황8
1게시물관리게시물관리2
2게시물등록게시물관리3
3게시판관리게시판관리94
4게시판속성관리게시판속성관리1
5결격자관리결격자관리10
6결격자일괄등록결격자일괄등록2
7결격자현황결격자조회1
8공지사항공지사항1
9공통상세코드공통상세코드2
메뉴명칭(MENU_NM)메뉴설명(MENU_DC)메뉴순서(MENU_ORDR)
103접속로그접속로그12
104접수내역조회 변경접수내역조회 변경11
105조직도관리조직도관리95
106조직도현황조직도현황1
107지원센터지원센터7
108질의응답질의응답2
109통계관리각종 통계관리12
110프로그램관리프로그램관리1
111합격자승인합격자승인3
112합격자조회합격자조회2

Duplicate rows

Most frequently occurring

메뉴명칭(MENU_NM)메뉴설명(MENU_DC)메뉴순서(MENU_ORDR)# duplicates
0교육기관현황교육기관현황32
1교육이수현황교육이수현황42