Overview

Dataset statistics

Number of variables6
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory54.0 B

Variable types

Categorical3
Text3

Dataset

Description2021년 특사경 수사(단속) 활동 계획(일정)
Author대전광역시
URLhttps://www.data.go.kr/data/15077565/fileData.do

Alerts

구 분 is highly overall correlated with 2021목표 and 1 other fieldsHigh correlation
2021목표 is highly overall correlated with 구 분High correlation
비고 is highly overall correlated with 구 분High correlation

Reproduction

Analysis started2023-12-12 16:47:42.537753
Analysis finished2023-12-12 16:47:43.081823
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구 분
Categorical

HIGH CORRELATION 

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

Length

Max length6
Median length5
Mean length3.5454545
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%
축산물 2
 
9.1%
의약품 1
 
4.5%
청소년보호 1
 
4.5%

Length

2023-12-13T01:47:43.188406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:43.353921image/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%
축산물 2
 
9.1%
의약품 1
 
4.5%
청소년보호 1
 
4.5%

수사분 야
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T01:47:43.576291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length17.5
Mean length15.090909
Min length9

Characters and Unicode

Total characters332
Distinct characters107
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

Unique20 ?
Unique (%)90.9%

Sample

1st row설명절 성수식품 기획수사
2nd row식품접객업 준수사항 기획수사 (식중독 예방 등)
3rd row추석명절 성수식품기획수사
4th row코로나19 확산차단 식품안전 기획수사
5th row미용업소 기획수사
ValueCountFrequency (%)
기획수사 15
22.4%
한우 3
 
4.5%
농수산물 2
 
3.0%
성수식품 2
 
3.0%
쇠고기 2
 
3.0%
원산지표시 2
 
3.0%
환경오염시설 1
 
1.5%
무허가 1
 
1.5%
유해업소 1
 
1.5%
청소년 1
 
1.5%
Other values (37) 37
55.2%
2023-12-13T01:47:43.986714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47
 
14.2%
사 25
 
7.5%
기 25
 
7.5%
수 24
 
7.2%
획 18
 
5.4%
산 9
 
2.7%
업 9
 
2.7%
식 7
 
2.1%
품 7
 
2.1%
물 5
 
1.5%
Other values (97) 156
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
83.4%
Space Separator 47
 
14.2%
Close Punctuation 3
 
0.9%
Open Punctuation 3
 
0.9%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 25
 
9.0%
기 25
 
9.0%
수 24
 
8.7%
획 18
 
6.5%
산 9
 
3.2%
업 9
 
3.2%
식 7
 
2.5%
품 7
 
2.5%
물 5
 
1.8%
지 5
 
1.8%
Other values (92) 143
51.6%
Decimal Number
ValueCountFrequency (%)
9 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 277
83.4%
Common 55
 
16.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 25
 
9.0%
기 25
 
9.0%
수 24
 
8.7%
획 18
 
6.5%
산 9
 
3.2%
업 9
 
3.2%
식 7
 
2.5%
품 7
 
2.5%
물 5
 
1.8%
지 5
 
1.8%
Other values (92) 143
51.6%
Common
ValueCountFrequency (%)
47
85.5%
) 3
 
5.5%
( 3
 
5.5%
9 1
 
1.8%
1 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 277
83.4%
ASCII 55
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47
85.5%
) 3
 
5.5%
( 3
 
5.5%
9 1
 
1.8%
1 1
 
1.8%
Hangul
ValueCountFrequency (%)
사 25
 
9.0%
기 25
 
9.0%
수 24
 
8.7%
획 18
 
6.5%
산 9
 
3.2%
업 9
 
3.2%
식 7
 
2.5%
품 7
 
2.5%
물 5
 
1.8%
지 5
 
1.8%
Other values (92) 143
51.6%

기 간
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T01:47:44.188827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11.5
Mean length10.545455
Min length9

Characters and Unicode

Total characters232
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row1.4.~2.26.
2nd row3.4.~ 4.30.
3rd row9.1.~10.29.
4th row9.3.~10.29.
5th row5.1.~6.30.
ValueCountFrequency (%)
5.1.~6.30 2
 
8.3%
7.1.~8.30 2
 
8.3%
1.4.~2.26 1
 
4.2%
1.18.~1.22 1
 
4.2%
3.1.~4.30 1
 
4.2%
7.5.~8.30 1
 
4.2%
11.1.~12.31 1
 
4.2%
9.17 1
 
4.2%
9.1 1
 
4.2%
5.3.~5.14 1
 
4.2%
Other values (12) 12
50.0%
2023-12-13T01:47:44.541905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 88
37.9%
1 32
 
13.8%
~ 22
 
9.5%
2 19
 
8.2%
3 17
 
7.3%
0 13
 
5.6%
9 8
 
3.4%
5 7
 
3.0%
6 7
 
3.0%
4 7
 
3.0%
Other values (3) 12
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119
51.3%
Other Punctuation 88
37.9%
Math Symbol 22
 
9.5%
Space Separator 3
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
26.9%
2 19
16.0%
3 17
14.3%
0 13
10.9%
9 8
 
6.7%
5 7
 
5.9%
6 7
 
5.9%
4 7
 
5.9%
8 5
 
4.2%
7 4
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 88
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 232
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 88
37.9%
1 32
 
13.8%
~ 22
 
9.5%
2 19
 
8.2%
3 17
 
7.3%
0 13
 
5.6%
9 8
 
3.4%
5 7
 
3.0%
6 7
 
3.0%
4 7
 
3.0%
Other values (3) 12
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 88
37.9%
1 32
 
13.8%
~ 22
 
9.5%
2 19
 
8.2%
3 17
 
7.3%
0 13
 
5.6%
9 8
 
3.4%
5 7
 
3.0%
6 7
 
3.0%
4 7
 
3.0%
Other values (3) 12
 
5.2%

대 상
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T01:47:44.788168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length21
Mean length18.772727
Min length8

Characters and Unicode

Total characters413
Distinct characters115
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 row부적합 식품 제조·가공 또는 유통기한 위변조 등
2nd row복지시설 등 지하수 사용업소
3rd row부적합 식품 제조·가공 또는 유통기한 위변조 등
4th row횟집 및 지하수 사용업소 식품 접객업
5th row미신고 영업, 불법의료행위
ValueCountFrequency (%)
등 9
 
10.0%
행위 4
 
4.4%
사업장 3
 
3.3%
식품 3
 
3.3%
유통기한 3
 
3.3%
및 3
 
3.3%
부적합 2
 
2.2%
지하수 2
 
2.2%
사용업소 2
 
2.2%
판매점(정육점 2
 
2.2%
Other values (53) 57
63.3%
2023-12-13T01:47:45.496603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
17.4%
업 12
 
2.9%
위 11
 
2.7%
사 11
 
2.7%
등 11
 
2.7%
기 10
 
2.4%
매 9
 
2.2%
, 9
 
2.2%
점 8
 
1.9%
물 7
 
1.7%
Other values (105) 253
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 314
76.0%
Space Separator 72
 
17.4%
Other Punctuation 17
 
4.1%
Open Punctuation 5
 
1.2%
Close Punctuation 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 12
 
3.8%
위 11
 
3.5%
사 11
 
3.5%
등 11
 
3.5%
기 10
 
3.2%
매 9
 
2.9%
점 8
 
2.5%
물 7
 
2.2%
판 7
 
2.2%
식 7
 
2.2%
Other values (99) 221
70.4%
Other Punctuation
ValueCountFrequency (%)
, 9
52.9%
· 6
35.3%
? 2
 
11.8%
Space Separator
ValueCountFrequency (%)
72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 314
76.0%
Common 99
 
24.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 12
 
3.8%
위 11
 
3.5%
사 11
 
3.5%
등 11
 
3.5%
기 10
 
3.2%
매 9
 
2.9%
점 8
 
2.5%
물 7
 
2.2%
판 7
 
2.2%
식 7
 
2.2%
Other values (99) 221
70.4%
Common
ValueCountFrequency (%)
72
72.7%
, 9
 
9.1%
· 6
 
6.1%
( 5
 
5.1%
) 5
 
5.1%
? 2
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
75.5%
ASCII 93
 
22.5%
None 6
 
1.5%
Compat Jamo 2
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
77.4%
, 9
 
9.7%
( 5
 
5.4%
) 5
 
5.4%
? 2
 
2.2%
Hangul
ValueCountFrequency (%)
업 12
 
3.8%
위 11
 
3.5%
사 11
 
3.5%
등 11
 
3.5%
기 10
 
3.2%
매 9
 
2.9%
점 8
 
2.6%
물 7
 
2.2%
판 7
 
2.2%
식 7
 
2.2%
Other values (98) 219
70.2%
None
ValueCountFrequency (%)
· 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

2021목표
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
5
6 
4
6 
-
4 
6
3 
9
1 
Other values (2)
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row5
2nd row5
3rd row6
4th row5
5th row9

Common Values

ValueCountFrequency (%)
5 6
27.3%
4 6
27.3%
- 4
18.2%
6 3
13.6%
9 1
 
4.5%
8 1
 
4.5%
3 1
 
4.5%

Length

2023-12-13T01:47:45.651154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:45.768375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 6
27.3%
4 6
27.3%
4
18.2%
6 3
13.6%
9 1
 
4.5%
8 1
 
4.5%
3 1
 
4.5%

비고
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
1반
9 
2반
6 
3반
6 
1 반
1 

Length

Max length3
Median length2
Mean length2.0454545
Min length2

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row2반
2nd row1반
3rd row2반
4th row1반
5th row2반

Common Values

ValueCountFrequency (%)
1반 9
40.9%
2반 6
27.3%
3반 6
27.3%
1 반 1
 
4.5%

Length

2023-12-13T01:47:45.912794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:47:46.031096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1반 9
39.1%
2반 6
26.1%
3반 6
26.1%
1 1
 
4.3%
반 1
 
4.3%

Correlations

2023-12-13T01:47:46.107723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분수사분 야기 간대 상2021목표비고
구 분1.0001.0000.9181.0000.8940.943
수사분 야1.0001.0000.9830.9491.0001.000
기 간0.9180.9831.0000.9490.0000.834
대 상1.0000.9490.9491.0000.9601.000
2021목표0.8941.0000.0000.9601.0000.153
비고0.9431.0000.8341.0000.1531.000
2023-12-13T01:47:46.241309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2021목표구 분비고
2021목표1.0000.5140.000
구 분0.5141.0000.852
비고0.0000.8521.000
2023-12-13T01:47:46.332758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구 분2021목표비고
구 분1.0000.5140.852
2021목표0.5141.0000.000
비고0.8520.0001.000

Missing values

2023-12-13T01:47:42.916359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:47:43.038241image/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

구 분수사분 야기 간대 상2021목표비고
0식품설명절 성수식품 기획수사1.4.~2.26.부적합 식품 제조·가공 또는 유통기한 위변조 등52반
1식품식품접객업 준수사항 기획수사 (식중독 예방 등)3.4.~ 4.30.복지시설 등 지하수 사용업소51반
2식품추석명절 성수식품기획수사9.1.~10.29.부적합 식품 제조·가공 또는 유통기한 위변조 등62반
3식품코로나19 확산차단 식품안전 기획수사9.3.~10.29.횟집 및 지하수 사용업소 식품 접객업51반
4공중위생미용업소 기획수사5.1.~6.30.미신고 영업, 불법의료행위92반
5공중위생공중위생업소 기획수사11.1.~12.30.음용수 검사의뢰, 무신고영업행위52반
6환경겨울철 미세먼지대응 기획수사1.6.~2.28.금속분말, 주물사 등 미세먼지 유발사업장63반
7환경봄철 비산먼지발생사업장 기획수사3.2.~4.29.토목ㆍ건설공사장, 토사운반 차랑 등83반
8환경폐기물 불법처리 기획수사5.1.~6.30.불법 폐기물처리시설운영 사업장63반
9환경하절기 악취배출사업장 기획수사7.1.~8.30.공단·도심지 악취배출시설 사업장 등53반
구 분수사분 야기 간대 상2021목표비고
12원산지표시쇠고기 한우 유전자검사1.18.~1.22.쇠고기 판매점(정육점)-1반
13원산지표시원산지합동단속(농관원)2.1.~2.5.농산물·축산물 취급 음식점-1반
14원산지표시농수산물 원산지표시 기획수사5.3.~6.30.요양원, 요양병원 집단급식소 및 식품접객업소41반
15원산지표시한우 유전자 검사5.3.~5.14.쇠고기판매점(음식점)-1반
16원산지표시쇠고기 한우 유전자검사(하반기)9.1.~ 9.17.쇠고기 판매점(정육점)-1반
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