Overview

Dataset statistics

Number of variables4
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory836.0 B
Average record size in memory38.0 B

Variable types

Categorical1
Text3

Dataset

Description대전광역시 특별사법경찰 수사활동계획 입니다. 수사분야, 기간, 대상이 기재되어 있습니다. 구분은 식품, 공중위생, 환경, 원산지표시, 의약품, 축산, 청소년 보호로 합니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15072681/fileData.do

Reproduction

Analysis started2023-12-12 01:23:28.157200
Analysis finished2023-12-12 01:23:28.926735
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
환경
6 
원산지표시
6 
식품
4 
공중위생
2 
축산
2 
Other values (2)
2 

Length

Max length6
Median length2
Mean length3.4545455
Min length2

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row식품
2nd row식품
3rd row식품
4th row식품
5th row공중위생

Common Values

ValueCountFrequency (%)
환경 6
27.3%
원산지표시 6
27.3%
식품 4
18.2%
공중위생 2
 
9.1%
축산 2
 
9.1%
의약품 1
 
4.5%
청소년보호 1
 
4.5%

Length

2023-12-12T10:23:29.013800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:23:29.173226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경 6
27.3%
원산지표시 6
27.3%
식품 4
18.2%
공중위생 2
 
9.1%
축산 2
 
9.1%
의약품 1
 
4.5%
청소년보호 1
 
4.5%

수사분야
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T10:23:29.431054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length16.5
Mean length14.5
Min length9

Characters and Unicode

Total characters319
Distinct characters89
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row설명절 성수식품 기획수사
2nd row식품접객업 준수사항 기획수사(식중독 예방 등)
3rd row추석명절성수식품기획수사
4th row행락철 주변 식품접객업소 기획수사
5th row미용업소 기획수사
ValueCountFrequency (%)
기획수사 16
25.4%
한우 3
 
4.8%
농수산물 2
 
3.2%
등 2
 
3.2%
원산지표시 2
 
3.2%
쇠고기 2
 
3.2%
축산물 2
 
3.2%
성수식품 2
 
3.2%
여름철 1
 
1.6%
납품업체 1
 
1.6%
Other values (30) 30
47.6%
2023-12-12T10:23:29.912143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
13.2%
수 25
 
7.8%
사 25
 
7.8%
기 23
 
7.2%
획 18
 
5.6%
업 13
 
4.1%
산 9
 
2.8%
품 7
 
2.2%
식 7
 
2.2%
소 6
 
1.9%
Other values (79) 144
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 271
85.0%
Space Separator 42
 
13.2%
Close Punctuation 3
 
0.9%
Open Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 25
 
9.2%
사 25
 
9.2%
기 23
 
8.5%
획 18
 
6.6%
업 13
 
4.8%
산 9
 
3.3%
품 7
 
2.6%
식 7
 
2.6%
소 6
 
2.2%
지 6
 
2.2%
Other values (76) 132
48.7%
Space Separator
ValueCountFrequency (%)
42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 271
85.0%
Common 48
 
15.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 25
 
9.2%
사 25
 
9.2%
기 23
 
8.5%
획 18
 
6.6%
업 13
 
4.8%
산 9
 
3.3%
품 7
 
2.6%
식 7
 
2.6%
소 6
 
2.2%
지 6
 
2.2%
Other values (76) 132
48.7%
Common
ValueCountFrequency (%)
42
87.5%
) 3
 
6.2%
( 3
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 271
85.0%
ASCII 48
 
15.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
87.5%
) 3
 
6.2%
( 3
 
6.2%
Hangul
ValueCountFrequency (%)
수 25
 
9.2%
사 25
 
9.2%
기 23
 
8.5%
획 18
 
6.6%
업 13
 
4.8%
산 9
 
3.3%
품 7
 
2.6%
식 7
 
2.6%
소 6
 
2.2%
지 6
 
2.2%
Other values (76) 132
48.7%

기간
Text

Distinct15
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T10:23:30.132782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters352
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)50.0%

Sample

1st row2022-01-02~02-28
2nd row2022-03-04~04-30
3rd row2022-09-01~10-30
4th row2022-09-01~10-30
5th row2022-05-01~06-30
ValueCountFrequency (%)
2022-09-01~10-30 3
13.6%
2022-05-01~06-30 3
13.6%
2022-07-01~08-30 3
13.6%
2022-01-02~02-28 2
 
9.1%
2022-03-04~04-30 1
 
4.5%
2022-11-01~12-30 1
 
4.5%
2022-01-06~02-28 1
 
4.5%
2022-03-02~04-29 1
 
4.5%
2022-11-02~12-24 1
 
4.5%
2022-01-09~01-17 1
 
4.5%
Other values (5) 5
22.7%
2023-12-12T10:23:30.523619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 93
26.4%
2 87
24.7%
- 66
18.8%
1 33
 
9.4%
~ 22
 
6.2%
3 16
 
4.5%
9 8
 
2.3%
5 6
 
1.7%
8 6
 
1.7%
6 5
 
1.4%
Other values (2) 10
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 264
75.0%
Dash Punctuation 66
 
18.8%
Math Symbol 22
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 93
35.2%
2 87
33.0%
1 33
 
12.5%
3 16
 
6.1%
9 8
 
3.0%
5 6
 
2.3%
8 6
 
2.3%
6 5
 
1.9%
7 5
 
1.9%
4 5
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 93
26.4%
2 87
24.7%
- 66
18.8%
1 33
 
9.4%
~ 22
 
6.2%
3 16
 
4.5%
9 8
 
2.3%
5 6
 
1.7%
8 6
 
1.7%
6 5
 
1.4%
Other values (2) 10
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 93
26.4%
2 87
24.7%
- 66
18.8%
1 33
 
9.4%
~ 22
 
6.2%
3 16
 
4.5%
9 8
 
2.3%
5 6
 
1.7%
8 6
 
1.7%
6 5
 
1.4%
Other values (2) 10
 
2.8%

대상
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-12T10:23:30.820978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20.5
Mean length17.318182
Min length8

Characters and Unicode

Total characters381
Distinct characters110
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)81.8%

Sample

1st row허위제조·가공, 유통기한 위변조 등
2nd row회 및 어패류 취급 식품접객업소
3rd row허위제조·가공, 유통기한 위변조 등
4th row행락지 주변 식품접객업소
5th row미신고 영업, 불법의료행위
ValueCountFrequency (%)
등 9
 
11.4%
식품접객업소 3
 
3.8%
허위제조·가공 2
 
2.5%
취급 2
 
2.5%
유통기한 2
 
2.5%
및 2
 
2.5%
사업장 2
 
2.5%
행위 2
 
2.5%
위변조 2
 
2.5%
쇠고기 2
 
2.5%
Other values (50) 51
64.6%
2023-12-12T10:23:31.352259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
15.5%
업 12
 
3.1%
, 12
 
3.1%
등 11
 
2.9%
위 10
 
2.6%
매 10
 
2.6%
점 8
 
2.1%
사 8
 
2.1%
판 8
 
2.1%
식 7
 
1.8%
Other values (100) 236
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 296
77.7%
Space Separator 59
 
15.5%
Other Punctuation 16
 
4.2%
Open Punctuation 5
 
1.3%
Close Punctuation 5
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 12
 
4.1%
등 11
 
3.7%
위 10
 
3.4%
매 10
 
3.4%
점 8
 
2.7%
사 8
 
2.7%
판 8
 
2.7%
식 7
 
2.4%
공 7
 
2.4%
기 7
 
2.4%
Other values (95) 208
70.3%
Other Punctuation
ValueCountFrequency (%)
, 12
75.0%
· 4
 
25.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 296
77.7%
Common 85
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 12
 
4.1%
등 11
 
3.7%
위 10
 
3.4%
매 10
 
3.4%
점 8
 
2.7%
사 8
 
2.7%
판 8
 
2.7%
식 7
 
2.4%
공 7
 
2.4%
기 7
 
2.4%
Other values (95) 208
70.3%
Common
ValueCountFrequency (%)
59
69.4%
, 12
 
14.1%
( 5
 
5.9%
) 5
 
5.9%
· 4
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
77.4%
ASCII 81
 
21.3%
None 4
 
1.0%
Compat Jamo 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
72.8%
, 12
 
14.8%
( 5
 
6.2%
) 5
 
6.2%
Hangul
ValueCountFrequency (%)
업 12
 
4.1%
등 11
 
3.7%
위 10
 
3.4%
매 10
 
3.4%
점 8
 
2.7%
사 8
 
2.7%
판 8
 
2.7%
식 7
 
2.4%
공 7
 
2.4%
기 7
 
2.4%
Other values (94) 207
70.2%
None
ValueCountFrequency (%)
· 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

Correlations

2023-12-12T10:23:31.475272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분수사분야기간대상
구분1.0001.0000.0001.000
수사분야1.0001.0000.9480.949
기간0.0000.9481.0000.880
대상1.0000.9490.8801.000

Missing values

2023-12-12T10:23:28.777488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:23:28.891774image/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

구분수사분야기간대상
0식품설명절 성수식품 기획수사2022-01-02~02-28허위제조·가공, 유통기한 위변조 등
1식품식품접객업 준수사항 기획수사(식중독 예방 등)2022-03-04~04-30회 및 어패류 취급 식품접객업소
2식품추석명절성수식품기획수사2022-09-01~10-30허위제조·가공, 유통기한 위변조 등
3식품행락철 주변 식품접객업소 기획수사2022-09-01~10-30행락지 주변 식품접객업소
4공중위생미용업소 기획수사2022-05-01~06-30미신고 영업, 불법의료행위
5공중위생공중위생업소 기획수사2022-11-01~12-30음용수 검사의뢰, 무신고영업행위
6환경미세먼지발생사업장 기획수사2022-01-06~02-28분진 배출시설 등 대기배출사업장
7환경비산먼지발생사업장 기획수사2022-03-02~04-29토목ㆍ건설공사장, 토사운반 차랑 등
8환경폐기물배출업체 기획수사2022-05-01~06-30불법 폐기물처리시설운영 사업장
9환경운수장비업체 기획수사2022-07-01~08-30자동차공업사, 자동차 외형복원업체 등
구분수사분야기간대상
12원산지표시쇠고기 한우 유전자검사2022-01-09~01-17쇠고기 판매점(정육점)
13원산지표시원산지합동단속(농관원)2022-01-20~01-22농산물·축산물 취급 음식점
14원산지표시농수산물 원산지표시 기획수사2022-05-01~06-30요양원, 요양병원 집단급식소 및 식품접객업소
15원산지표시농수산물 원산지표시 기획수사2022-11-02~12-31수산물 판매업소
16원산지표시한우 유전자 검사2022-05-06~05-29쇠고기판매점(음식점)
17원산지표시쇠고기 한우 유전자검사(하반기)2022-09-17~09-25쇠고기 판매점(정육점)
18의약품의약품 판매업소 기획수사2022-07-01~08-30의약품 판매점(약국,도매상 등)
19축산학교급식 축산물 납품업체 기획수사2022-03-01~04-30허위표시 유통판매, 냉동육 냉장육으로 위조 판매등
20축산여름철 성수식품 축산물 기획수사2022-07-01~08-30부정불량식품 원료 사용 제조가공 행위 등
21청소년보호신학기 청소년 유해업소 등 기획수사2022-01-02~02-28주류,담배,유해매체물 판매(대여)업소 등