Overview

Dataset statistics

Number of variables3
Number of observations124
Missing cells15
Missing cells (%)4.0%
Duplicate rows2
Duplicate rows (%)1.6%
Total size in memory3.2 KiB
Average record size in memory26.1 B

Variable types

Numeric1
Text2

Dataset

Description공무원연금공단 종합재해보상 표준기안문대분류코드(기안문대분류세부명, 기안문대분류설명 등) 관련 사항을 포함하고 있습니다.
Author공무원연금공단
URLhttps://www.data.go.kr/data/15123823/fileData.do

Alerts

Dataset has 2 (1.6%) duplicate rowsDuplicates
기안문대분류설명 has 15 (12.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:36:03.543306
Analysis finished2023-12-12 04:36:04.021137
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기안문대분류코드
Real number (ℝ)

Distinct11
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3145161
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:36:04.098235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile8
Maximum11
Range10
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4173053
Coefficient of variation (CV)0.72930865
Kurtosis0.58923154
Mean3.3145161
Median Absolute Deviation (MAD)2
Skewness1.1050706
Sum411
Variance5.8433648
MonotonicityNot monotonic
2023-12-12T13:36:04.233181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 36
29.0%
2 25
20.2%
3 17
13.7%
4 12
 
9.7%
5 11
 
8.9%
6 9
 
7.3%
7 5
 
4.0%
8 3
 
2.4%
9 3
 
2.4%
10 2
 
1.6%
ValueCountFrequency (%)
1 36
29.0%
2 25
20.2%
3 17
13.7%
4 12
 
9.7%
5 11
 
8.9%
6 9
 
7.3%
7 5
 
4.0%
8 3
 
2.4%
9 3
 
2.4%
10 2
 
1.6%
ValueCountFrequency (%)
11 1
 
0.8%
10 2
 
1.6%
9 3
 
2.4%
8 3
 
2.4%
7 5
 
4.0%
6 9
 
7.3%
5 11
8.9%
4 12
9.7%
3 17
13.7%
2 25
20.2%

기안문대분류세부명
Text

Distinct115
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T13:36:04.557183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length9.8225806
Min length2

Characters and Unicode

Total characters1218
Distinct characters144
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)87.1%

Sample

1st row공무상요양비(재청구)
2nd row전자심의결과보고
3rd row소송자료이송(요양비)
4th row본인협조(공무상요양비)
5th row소방서협조
ValueCountFrequency (%)
부지급 9
 
3.7%
확정판결 6
 
2.5%
일부정정 6
 
2.5%
승인사항 6
 
2.5%
재심인용 6
 
2.5%
사망조위금 6
 
2.5%
없음 5
 
2.1%
이탈 4
 
1.7%
및 4
 
1.7%
장해등급 4
 
1.7%
Other values (145) 185
76.8%
2023-12-12T13:36:05.011107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
118
 
9.7%
( 40
 
3.3%
) 40
 
3.3%
부 39
 
3.2%
상 37
 
3.0%
보 33
 
2.7%
조 28
 
2.3%
정 27
 
2.2%
인 26
 
2.1%
심 24
 
2.0%
Other values (134) 806
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1017
83.5%
Space Separator 118
 
9.7%
Open Punctuation 40
 
3.3%
Close Punctuation 40
 
3.3%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 39
 
3.8%
상 37
 
3.6%
보 33
 
3.2%
조 28
 
2.8%
정 27
 
2.7%
인 26
 
2.6%
심 24
 
2.4%
사 24
 
2.4%
통 22
 
2.2%
기 21
 
2.1%
Other values (130) 736
72.4%
Space Separator
ValueCountFrequency (%)
118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1017
83.5%
Common 201
 
16.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 39
 
3.8%
상 37
 
3.6%
보 33
 
3.2%
조 28
 
2.8%
정 27
 
2.7%
인 26
 
2.6%
심 24
 
2.4%
사 24
 
2.4%
통 22
 
2.2%
기 21
 
2.1%
Other values (130) 736
72.4%
Common
ValueCountFrequency (%)
118
58.7%
( 40
 
19.9%
) 40
 
19.9%
_ 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1017
83.5%
ASCII 201
 
16.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118
58.7%
( 40
 
19.9%
) 40
 
19.9%
_ 3
 
1.5%
Hangul
ValueCountFrequency (%)
부 39
 
3.8%
상 37
 
3.6%
보 33
 
3.2%
조 28
 
2.8%
정 27
 
2.7%
인 26
 
2.6%
심 24
 
2.4%
사 24
 
2.4%
통 22
 
2.2%
기 21
 
2.1%
Other values (130) 736
72.4%

기안문대분류설명
Text

MISSING 

Distinct105
Distinct (%)96.3%
Missing15
Missing (%)12.1%
Memory size1.1 KiB
2023-12-12T13:36:05.431335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length17.954128
Min length4

Characters and Unicode

Total characters1957
Distinct characters172
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)92.7%

Sample

1st row소송자료이송(요양비)
2nd row소송자료이송(기간연장)
3rd row건보협조
4th row공무원재해보상연금위원회 심사 인용에 따른 결정 기안(공무상요양비)
5th row기간연장심사결과보고
ValueCountFrequency (%)
불승인 23
 
5.5%
공무상요양 16
 
3.8%
부지급 14
 
3.3%
경우 12
 
2.9%
유족보상금 10
 
2.4%
따른 9
 
2.1%
및 9
 
2.1%
장해등급 7
 
1.7%
결정 7
 
1.7%
기간연장 6
 
1.4%
Other values (190) 308
73.2%
2023-12-12T13:36:06.037242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
317
 
16.2%
상 71
 
3.6%
인 46
 
2.4%
보 45
 
2.3%
부 42
 
2.1%
금 37
 
1.9%
사 37
 
1.9%
급 36
 
1.8%
무 34
 
1.7%
승 31
 
1.6%
Other values (162) 1261
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1581
80.8%
Space Separator 317
 
16.2%
Open Punctuation 28
 
1.4%
Close Punctuation 28
 
1.4%
Connector Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 71
 
4.5%
인 46
 
2.9%
보 45
 
2.8%
부 42
 
2.7%
금 37
 
2.3%
사 37
 
2.3%
급 36
 
2.3%
무 34
 
2.2%
승 31
 
2.0%
요 31
 
2.0%
Other values (158) 1171
74.1%
Space Separator
ValueCountFrequency (%)
317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1581
80.8%
Common 376
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 71
 
4.5%
인 46
 
2.9%
보 45
 
2.8%
부 42
 
2.7%
금 37
 
2.3%
사 37
 
2.3%
급 36
 
2.3%
무 34
 
2.2%
승 31
 
2.0%
요 31
 
2.0%
Other values (158) 1171
74.1%
Common
ValueCountFrequency (%)
317
84.3%
( 28
 
7.4%
) 28
 
7.4%
_ 3
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1581
80.8%
ASCII 376
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317
84.3%
( 28
 
7.4%
) 28
 
7.4%
_ 3
 
0.8%
Hangul
ValueCountFrequency (%)
상 71
 
4.5%
인 46
 
2.9%
보 45
 
2.8%
부 42
 
2.7%
금 37
 
2.3%
사 37
 
2.3%
급 36
 
2.3%
무 34
 
2.2%
승 31
 
2.0%
요 31
 
2.0%
Other values (158) 1171
74.1%

Interactions

2023-12-12T13:36:03.770260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T13:36:03.893001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:36:03.982370image/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

기안문대분류코드기안문대분류세부명기안문대분류설명
02공무상요양비(재청구)<NA>
13전자심의결과보고<NA>
23소송자료이송(요양비)소송자료이송(요양비)
36본인협조(공무상요양비)<NA>
47소방서협조<NA>
55병원협조(공무상요양비)<NA>
62소송자료이송(기간연장)소송자료이송(기간연장)
72건보협조건보협조
86재심인용 (공무상요양비)공무원재해보상연금위원회 심사 인용에 따른 결정 기안(공무상요양비)
92기간연장심사결과보고기간연장심사결과보고
기안문대분류코드기안문대분류세부명기안문대분류설명
1143청구반려(요양비)요양비 청구 반려를 요청할 경우
1157확정판결 (공무상요양비)<NA>
1168사망조위금 부지급 통보(부양입증자료)사망조위금 부지급 통보 부양입증자료 미비 사항
1172승인사항 일부정정 통보(상병일시)<NA>
1183승인사항 일부정정 통보(요양기간)<NA>
1194승인사항 일부정정 통보(제외사유)프로그램 사용 안 함
1205승인사항 일부정정 통보(결정구분)<NA>
1216승인사항 일부정정 통보(가해자유무)<NA>
1229재난부조금 부지급 통보(기타)재난부조금 부지급 통보(기타)
1234명백한부상결과보고명백한부상결과보고

Duplicate rows

Most frequently occurring

기안문대분류코드기안문대분류세부명기안문대분류설명# duplicates
01급여이체위험직무 순직유족급여 지급에 따른 급여 이체 요청2
12전액회수구상관리대상금액을 전액회수한 경우2