Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells19590
Missing cells (%)11.5%
Duplicate rows369
Duplicate rows (%)3.7%
Total size in memory1.4 MiB
Average record size in memory150.0 B

Variable types

Categorical3
Numeric5
Text9

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-11534/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 369 (3.7%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 1 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 1 other fieldsHigh correlation
업종명 is highly imbalanced (54.9%)Imbalance
소재지도로명 has 5602 (56.0%) missing valuesMissing
처분기간 has 8998 (90.0%) missing valuesMissing
영업장면적(㎡) has 4877 (48.8%) missing valuesMissing
지도점검일자 is highly skewed (γ1 = -37.17690248)Skewed
위반일자 is highly skewed (γ1 = -37.18094209)Skewed

Reproduction

Analysis started2024-05-11 06:53:59.100357
Analysis finished2024-05-11 06:54:08.588764
Duration9.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3200000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 10000
100.0%

Length

2024-05-11T15:54:08.689451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:08.826662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3270
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20123803
Minimum20010104
Maximum20240509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:54:08.994724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010104
5-th percentile20030704
Q120090522
median20121114
Q320161111
95-th percentile20210414
Maximum20240509
Range230405
Interquartile range (IQR)70589

Descriptive statistics

Standard deviation53779.961
Coefficient of variation (CV)0.0026724552
Kurtosis-0.63778498
Mean20123803
Median Absolute Deviation (MAD)39314.5
Skewness-0.059415199
Sum2.0123803 × 1011
Variance2.8922842 × 109
MonotonicityNot monotonic
2024-05-11T15:54:09.207129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130405 287
 
2.9%
20090522 51
 
0.5%
20231230 50
 
0.5%
20160330 30
 
0.3%
20150112 29
 
0.3%
20130422 25
 
0.2%
20141208 25
 
0.2%
20110418 25
 
0.2%
20160113 24
 
0.2%
20201203 23
 
0.2%
Other values (3260) 9431
94.3%
ValueCountFrequency (%)
20010104 2
< 0.1%
20010111 2
< 0.1%
20010117 4
< 0.1%
20010410 1
 
< 0.1%
20010418 1
 
< 0.1%
20010424 1
 
< 0.1%
20010524 1
 
< 0.1%
20010608 2
< 0.1%
20010704 1
 
< 0.1%
20010708 2
< 0.1%
ValueCountFrequency (%)
20240509 1
 
< 0.1%
20240424 3
< 0.1%
20240416 3
< 0.1%
20240409 1
 
< 0.1%
20240402 1
 
< 0.1%
20240401 1
 
< 0.1%
20240327 2
< 0.1%
20240326 3
< 0.1%
20240325 2
< 0.1%
20240322 3
< 0.1%

교부번호
Text

Distinct5410
Distinct (%)54.1%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:54:09.551092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.464939
Min length1

Characters and Unicode

Total characters104618
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3575 ?
Unique (%)35.8%

Sample

1st row20100094930
2nd row20150094117
3rd row20020094169
4th row20050094423
5th row20010095362
ValueCountFrequency (%)
20080094225 54
 
0.5%
20000094678 31
 
0.3%
19990094152 25
 
0.3%
20030094780 24
 
0.2%
20000094179 23
 
0.2%
19990094162 23
 
0.2%
20040095160 21
 
0.2%
20150094306 21
 
0.2%
20040095092 21
 
0.2%
20010095164 20
 
0.2%
Other values (5400) 9734
97.4%
2024-05-11T15:54:10.127783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 35296
33.7%
9 16696
16.0%
4 11593
 
11.1%
2 11517
 
11.0%
1 9682
 
9.3%
5 4629
 
4.4%
8 3873
 
3.7%
3 3869
 
3.7%
6 3849
 
3.7%
7 3515
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104519
99.9%
Dash Punctuation 99
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35296
33.8%
9 16696
16.0%
4 11593
 
11.1%
2 11517
 
11.0%
1 9682
 
9.3%
5 4629
 
4.4%
8 3873
 
3.7%
3 3869
 
3.7%
6 3849
 
3.7%
7 3515
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104618
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 35296
33.7%
9 16696
16.0%
4 11593
 
11.1%
2 11517
 
11.0%
1 9682
 
9.3%
5 4629
 
4.4%
8 3873
 
3.7%
3 3869
 
3.7%
6 3849
 
3.7%
7 3515
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104618
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 35296
33.7%
9 16696
16.0%
4 11593
 
11.1%
2 11517
 
11.0%
1 9682
 
9.3%
5 4629
 
4.4%
8 3873
 
3.7%
3 3869
 
3.7%
6 3849
 
3.7%
7 3515
 
3.4%

업종명
Categorical

IMBALANCE 

Distinct39
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
6133 
유흥주점영업
1053 
휴게음식점
 
402
숙박업(일반)
 
380
단란주점
 
367
Other values (34)
1665 

Length

Max length23
Median length5
Mean length5.5115
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row즉석판매제조가공업
2nd row즉석판매제조가공업
3rd row일반음식점
4th row일반음식점
5th row즉석판매제조가공업

Common Values

ValueCountFrequency (%)
일반음식점 6133
61.3%
유흥주점영업 1053
 
10.5%
휴게음식점 402
 
4.0%
숙박업(일반) 380
 
3.8%
단란주점 367
 
3.7%
즉석판매제조가공업 349
 
3.5%
건강기능식품일반판매업 238
 
2.4%
식품제조가공업 148
 
1.5%
이용업 147
 
1.5%
제과점영업 130
 
1.3%
Other values (29) 653
 
6.5%

Length

2024-05-11T15:54:10.439430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 6133
60.6%
유흥주점영업 1053
 
10.4%
휴게음식점 402
 
4.0%
숙박업(일반 380
 
3.8%
단란주점 367
 
3.6%
즉석판매제조가공업 349
 
3.4%
건강기능식품일반판매업 238
 
2.4%
식품제조가공업 148
 
1.5%
이용업 147
 
1.5%
제과점영업 130
 
1.3%
Other values (26) 778
 
7.7%

업태명
Text

Distinct85
Distinct (%)0.9%
Missing29
Missing (%)0.3%
Memory size156.2 KiB
2024-05-11T15:54:10.797032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length3.778959
Min length2

Characters and Unicode

Total characters37680
Distinct characters167
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row즉석판매제조가공업
2nd row즉석판매제조가공업
3rd row경양식
4th row통닭(치킨)
5th row즉석판매제조가공업
ValueCountFrequency (%)
한식 2392
23.6%
호프/통닭 996
 
9.8%
룸살롱 869
 
8.6%
분식 709
 
7.0%
기타 638
 
6.3%
중국식 390
 
3.8%
단란주점 367
 
3.6%
즉석판매제조가공업 348
 
3.4%
여관업 333
 
3.3%
경양식 251
 
2.5%
Other values (75) 2851
28.1%
2024-05-11T15:54:11.340691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 4393
 
11.7%
한 2392
 
6.3%
업 1943
 
5.2%
/ 1310
 
3.5%
통 1309
 
3.5%
닭 1200
 
3.2%
호 1013
 
2.7%
프 996
 
2.6%
살 899
 
2.4%
롱 899
 
2.4%
Other values (157) 21326
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35432
94.0%
Other Punctuation 1327
 
3.5%
Close Punctuation 363
 
1.0%
Open Punctuation 363
 
1.0%
Space Separator 173
 
0.5%
Math Symbol 22
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 4393
 
12.4%
한 2392
 
6.8%
업 1943
 
5.5%
통 1309
 
3.7%
닭 1200
 
3.4%
호 1013
 
2.9%
프 996
 
2.8%
살 899
 
2.5%
롱 899
 
2.5%
매 890
 
2.5%
Other values (150) 19498
55.0%
Other Punctuation
ValueCountFrequency (%)
/ 1310
98.7%
, 11
 
0.8%
. 6
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 363
100.0%
Open Punctuation
ValueCountFrequency (%)
( 363
100.0%
Space Separator
ValueCountFrequency (%)
173
100.0%
Math Symbol
ValueCountFrequency (%)
+ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35432
94.0%
Common 2248
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 4393
 
12.4%
한 2392
 
6.8%
업 1943
 
5.5%
통 1309
 
3.7%
닭 1200
 
3.4%
호 1013
 
2.9%
프 996
 
2.8%
살 899
 
2.5%
롱 899
 
2.5%
매 890
 
2.5%
Other values (150) 19498
55.0%
Common
ValueCountFrequency (%)
/ 1310
58.3%
) 363
 
16.1%
( 363
 
16.1%
173
 
7.7%
+ 22
 
1.0%
, 11
 
0.5%
. 6
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35432
94.0%
ASCII 2248
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 4393
 
12.4%
한 2392
 
6.8%
업 1943
 
5.5%
통 1309
 
3.7%
닭 1200
 
3.4%
호 1013
 
2.9%
프 996
 
2.8%
살 899
 
2.5%
롱 899
 
2.5%
매 890
 
2.5%
Other values (150) 19498
55.0%
ASCII
ValueCountFrequency (%)
/ 1310
58.3%
) 363
 
16.1%
( 363
 
16.1%
173
 
7.7%
+ 22
 
1.0%
, 11
 
0.5%
. 6
 
0.3%

업소명
Text

Distinct5471
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:54:11.787512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length5.2648
Min length1

Characters and Unicode

Total characters52648
Distinct characters1000
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3587 ?
Unique (%)35.9%

Sample

1st row신보상회
2nd row고양한과
3rd row발렌타인
4th row하프앤드
5th row장수식품
ValueCountFrequency (%)
청양센타 54
 
0.5%
신림점 49
 
0.4%
김밥천국 32
 
0.3%
서울대입구역점 31
 
0.3%
주식회사 31
 
0.3%
신림역점 28
 
0.3%
전주삼백식당 28
 
0.3%
만리장성 27
 
0.2%
서울대점 23
 
0.2%
땡큐목장 23
 
0.2%
Other values (5804) 10872
97.1%
2024-05-11T15:54:12.537027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1198
 
2.3%
이 1125
 
2.1%
스 956
 
1.8%
리 849
 
1.6%
점 841
 
1.6%
주 712
 
1.4%
식 639
 
1.2%
) 624
 
1.2%
( 619
 
1.2%
대 596
 
1.1%
Other values (990) 44489
84.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47246
89.7%
Space Separator 1198
 
2.3%
Uppercase Letter 1035
 
2.0%
Lowercase Letter 1008
 
1.9%
Decimal Number 633
 
1.2%
Close Punctuation 624
 
1.2%
Open Punctuation 619
 
1.2%
Other Punctuation 253
 
0.5%
Dash Punctuation 25
 
< 0.1%
Math Symbol 2
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1125
 
2.4%
스 956
 
2.0%
리 849
 
1.8%
점 841
 
1.8%
주 712
 
1.5%
식 639
 
1.4%
대 596
 
1.3%
장 594
 
1.3%
마 499
 
1.1%
비 477
 
1.0%
Other values (910) 39958
84.6%
Lowercase Letter
ValueCountFrequency (%)
e 146
14.5%
o 115
 
11.4%
a 85
 
8.4%
i 78
 
7.7%
n 73
 
7.2%
h 52
 
5.2%
t 47
 
4.7%
l 45
 
4.5%
g 38
 
3.8%
u 38
 
3.8%
Other values (16) 291
28.9%
Uppercase Letter
ValueCountFrequency (%)
S 94
 
9.1%
C 94
 
9.1%
A 74
 
7.1%
B 68
 
6.6%
O 65
 
6.3%
E 63
 
6.1%
N 50
 
4.8%
T 49
 
4.7%
F 46
 
4.4%
L 45
 
4.3%
Other values (16) 387
37.4%
Decimal Number
ValueCountFrequency (%)
2 147
23.2%
0 120
19.0%
1 87
13.7%
3 62
9.8%
4 54
 
8.5%
9 43
 
6.8%
7 42
 
6.6%
8 36
 
5.7%
5 24
 
3.8%
6 18
 
2.8%
Other Punctuation
ValueCountFrequency (%)
. 117
46.2%
& 67
26.5%
, 24
 
9.5%
? 12
 
4.7%
; 12
 
4.7%
! 9
 
3.6%
' 5
 
2.0%
？ 4
 
1.6%
% 2
 
0.8%
# 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1198
100.0%
Close Punctuation
ValueCountFrequency (%)
) 624
100.0%
Open Punctuation
ValueCountFrequency (%)
( 619
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
^ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Other Symbol
ValueCountFrequency (%)
♡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47211
89.7%
Common 3357
 
6.4%
Latin 2045
 
3.9%
Han 35
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1125
 
2.4%
스 956
 
2.0%
리 849
 
1.8%
점 841
 
1.8%
주 712
 
1.5%
식 639
 
1.4%
대 596
 
1.3%
장 594
 
1.3%
마 499
 
1.1%
비 477
 
1.0%
Other values (889) 39923
84.6%
Latin
ValueCountFrequency (%)
e 146
 
7.1%
o 115
 
5.6%
S 94
 
4.6%
C 94
 
4.6%
a 85
 
4.2%
i 78
 
3.8%
A 74
 
3.6%
n 73
 
3.6%
B 68
 
3.3%
O 65
 
3.2%
Other values (43) 1153
56.4%
Common
ValueCountFrequency (%)
1198
35.7%
) 624
18.6%
( 619
18.4%
2 147
 
4.4%
0 120
 
3.6%
. 117
 
3.5%
1 87
 
2.6%
& 67
 
2.0%
3 62
 
1.8%
4 54
 
1.6%
Other values (17) 262
 
7.8%
Han
ValueCountFrequency (%)
秀 6
17.1%
家 4
 
11.4%
女 2
 
5.7%
子 2
 
5.7%
地 2
 
5.7%
球 2
 
5.7%
堂 2
 
5.7%
唐 2
 
5.7%
玄 1
 
2.9%
弘 1
 
2.9%
Other values (11) 11
31.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47203
89.7%
ASCII 5395
 
10.2%
CJK 33
 
0.1%
Compat Jamo 8
 
< 0.1%
None 4
 
< 0.1%
Number Forms 2
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1198
22.2%
) 624
 
11.6%
( 619
 
11.5%
2 147
 
2.7%
e 146
 
2.7%
0 120
 
2.2%
. 117
 
2.2%
o 115
 
2.1%
S 94
 
1.7%
C 94
 
1.7%
Other values (67) 2121
39.3%
Hangul
ValueCountFrequency (%)
이 1125
 
2.4%
스 956
 
2.0%
리 849
 
1.8%
점 841
 
1.8%
주 712
 
1.5%
식 639
 
1.4%
대 596
 
1.3%
장 594
 
1.3%
마 499
 
1.1%
비 477
 
1.0%
Other values (885) 39915
84.6%
CJK
ValueCountFrequency (%)
秀 6
18.2%
家 4
 
12.1%
子 2
 
6.1%
地 2
 
6.1%
球 2
 
6.1%
堂 2
 
6.1%
唐 2
 
6.1%
玄 1
 
3.0%
弘 1
 
3.0%
成 1
 
3.0%
Other values (10) 10
30.3%
None
ValueCountFrequency (%)
？ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
25.0%
ㄱ 2
25.0%
ㄴ 2
25.0%
ㄷ 2
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
女 2
100.0%
Misc Symbols
ValueCountFrequency (%)
♡ 1
100.0%

소재지도로명
Text

MISSING 

Distinct2508
Distinct (%)57.0%
Missing5602
Missing (%)56.0%
Memory size156.2 KiB
2024-05-11T15:54:13.003246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length56
Mean length29.681219
Min length22

Characters and Unicode

Total characters130538
Distinct characters280
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1625 ?
Unique (%)36.9%

Sample

1st row서울특별시 관악구 남부순환로157길 63, (신림동)
2nd row서울특별시 관악구 남부순환로248길 20, (봉천동)
3rd row서울특별시 관악구 남부순환로248길 24, (봉천동)
4th row서울특별시 관악구 신림로 365, 2층호 (신림동)
5th row서울특별시 관악구 청림3마길 26, 지상1층 (봉천동)
ValueCountFrequency (%)
서울특별시 4398
17.2%
관악구 4398
17.2%
신림동 2266
 
8.8%
봉천동 1428
 
5.6%
1층 1283
 
5.0%
남부순환로 633
 
2.5%
지하1층 391
 
1.5%
신림로 349
 
1.4%
지상1층 320
 
1.2%
봉천로 283
 
1.1%
Other values (1632) 9881
38.6%
2024-05-11T15:54:13.722728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21243
 
16.3%
1 6242
 
4.8%
, 5470
 
4.2%
관 4844
 
3.7%
악 4762
 
3.6%
동 4618
 
3.5%
시 4467
 
3.4%
( 4448
 
3.4%
) 4448
 
3.4%
서 4432
 
3.4%
Other values (270) 65564
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74293
56.9%
Space Separator 21243
 
16.3%
Decimal Number 19895
 
15.2%
Other Punctuation 5476
 
4.2%
Open Punctuation 4448
 
3.4%
Close Punctuation 4448
 
3.4%
Dash Punctuation 576
 
0.4%
Uppercase Letter 118
 
0.1%
Math Symbol 39
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 4844
 
6.5%
악 4762
 
6.4%
동 4618
 
6.2%
시 4467
 
6.0%
서 4432
 
6.0%
구 4417
 
5.9%
울 4414
 
5.9%
특 4402
 
5.9%
별 4398
 
5.9%
로 3711
 
5.0%
Other values (236) 29828
40.1%
Uppercase Letter
ValueCountFrequency (%)
B 63
53.4%
S 10
 
8.5%
T 8
 
6.8%
E 6
 
5.1%
W 6
 
5.1%
D 5
 
4.2%
R 5
 
4.2%
K 5
 
4.2%
O 4
 
3.4%
G 2
 
1.7%
Other values (3) 4
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 6242
31.4%
2 2845
14.3%
3 1941
 
9.8%
6 1638
 
8.2%
5 1548
 
7.8%
4 1334
 
6.7%
0 1295
 
6.5%
9 1052
 
5.3%
7 1004
 
5.0%
8 996
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 5470
99.9%
@ 3
 
0.1%
. 2
 
< 0.1%
/ 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
50.0%
b 1
50.0%
Space Separator
ValueCountFrequency (%)
21243
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4448
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4448
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 576
100.0%
Math Symbol
ValueCountFrequency (%)
~ 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74293
56.9%
Common 56125
43.0%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 4844
 
6.5%
악 4762
 
6.4%
동 4618
 
6.2%
시 4467
 
6.0%
서 4432
 
6.0%
구 4417
 
5.9%
울 4414
 
5.9%
특 4402
 
5.9%
별 4398
 
5.9%
로 3711
 
5.0%
Other values (236) 29828
40.1%
Common
ValueCountFrequency (%)
21243
37.8%
1 6242
 
11.1%
, 5470
 
9.7%
( 4448
 
7.9%
) 4448
 
7.9%
2 2845
 
5.1%
3 1941
 
3.5%
6 1638
 
2.9%
5 1548
 
2.8%
4 1334
 
2.4%
Other values (9) 4968
 
8.9%
Latin
ValueCountFrequency (%)
B 63
52.5%
S 10
 
8.3%
T 8
 
6.7%
E 6
 
5.0%
W 6
 
5.0%
D 5
 
4.2%
R 5
 
4.2%
K 5
 
4.2%
O 4
 
3.3%
G 2
 
1.7%
Other values (5) 6
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74293
56.9%
ASCII 56245
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21243
37.8%
1 6242
 
11.1%
, 5470
 
9.7%
( 4448
 
7.9%
) 4448
 
7.9%
2 2845
 
5.1%
3 1941
 
3.5%
6 1638
 
2.9%
5 1548
 
2.8%
4 1334
 
2.4%
Other values (24) 5088
 
9.0%
Hangul
ValueCountFrequency (%)
관 4844
 
6.5%
악 4762
 
6.4%
동 4618
 
6.2%
시 4467
 
6.0%
서 4432
 
6.0%
구 4417
 
5.9%
울 4414
 
5.9%
특 4402
 
5.9%
별 4398
 
5.9%
로 3711
 
5.0%
Other values (236) 29828
40.1%

소재지지번
Text

Distinct4409
Distinct (%)44.3%
Missing41
Missing (%)0.4%
Memory size156.2 KiB
2024-05-11T15:54:14.311765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length59
Mean length28.060347
Min length21

Characters and Unicode

Total characters279453
Distinct characters268
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2450 ?
Unique (%)24.6%

Sample

1st row서울특별시 관악구 신림동 505번지 1호
2nd row서울특별시 관악구 봉천동 1635번지 18호
3rd row서울특별시 관악구 신림동 1531번지 3호
4th row서울특별시 관악구 남현동 1067번지 23호 지상1층
5th row서울특별시 관악구 봉천동 1635번지 37호
ValueCountFrequency (%)
관악구 9960
18.5%
서울특별시 9959
18.5%
신림동 5731
 
10.6%
봉천동 3709
 
6.9%
지상1층 1300
 
2.4%
1호 977
 
1.8%
2호 627
 
1.2%
지하1층 525
 
1.0%
남현동 519
 
1.0%
4호 457
 
0.8%
Other values (1588) 20110
37.3%
2024-05-11T15:54:15.226447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70323
25.2%
1 15002
 
5.4%
지 12749
 
4.6%
호 10126
 
3.6%
동 10054
 
3.6%
관 10010
 
3.6%
악 10003
 
3.6%
번 9976
 
3.6%
서 9976
 
3.6%
구 9976
 
3.6%
Other values (258) 111258
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 151243
54.1%
Space Separator 70323
25.2%
Decimal Number 56458
 
20.2%
Other Punctuation 523
 
0.2%
Dash Punctuation 326
 
0.1%
Open Punctuation 181
 
0.1%
Close Punctuation 181
 
0.1%
Uppercase Letter 168
 
0.1%
Math Symbol 46
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 12749
 
8.4%
호 10126
 
6.7%
동 10054
 
6.6%
관 10010
 
6.6%
악 10003
 
6.6%
번 9976
 
6.6%
서 9976
 
6.6%
구 9976
 
6.6%
울 9975
 
6.6%
시 9970
 
6.6%
Other values (220) 48428
32.0%
Uppercase Letter
ValueCountFrequency (%)
A 46
27.4%
B 45
26.8%
S 17
 
10.1%
K 14
 
8.3%
T 13
 
7.7%
O 5
 
3.0%
R 5
 
3.0%
D 4
 
2.4%
W 4
 
2.4%
E 4
 
2.4%
Other values (6) 11
 
6.5%
Decimal Number
ValueCountFrequency (%)
1 15002
26.6%
2 6815
12.1%
6 5874
 
10.4%
4 5430
 
9.6%
3 5222
 
9.2%
5 4888
 
8.7%
0 3740
 
6.6%
8 3402
 
6.0%
7 3067
 
5.4%
9 3018
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 500
95.6%
@ 11
 
2.1%
. 9
 
1.7%
/ 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
s 2
50.0%
g 1
25.0%
c 1
25.0%
Space Separator
ValueCountFrequency (%)
70323
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%
Open Punctuation
ValueCountFrequency (%)
( 181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Math Symbol
ValueCountFrequency (%)
~ 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 151243
54.1%
Common 128038
45.8%
Latin 172
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 12749
 
8.4%
호 10126
 
6.7%
동 10054
 
6.6%
관 10010
 
6.6%
악 10003
 
6.6%
번 9976
 
6.6%
서 9976
 
6.6%
구 9976
 
6.6%
울 9975
 
6.6%
시 9970
 
6.6%
Other values (220) 48428
32.0%
Common
ValueCountFrequency (%)
70323
54.9%
1 15002
 
11.7%
2 6815
 
5.3%
6 5874
 
4.6%
4 5430
 
4.2%
3 5222
 
4.1%
5 4888
 
3.8%
0 3740
 
2.9%
8 3402
 
2.7%
7 3067
 
2.4%
Other values (9) 4275
 
3.3%
Latin
ValueCountFrequency (%)
A 46
26.7%
B 45
26.2%
S 17
 
9.9%
K 14
 
8.1%
T 13
 
7.6%
O 5
 
2.9%
R 5
 
2.9%
D 4
 
2.3%
W 4
 
2.3%
E 4
 
2.3%
Other values (9) 15
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 151243
54.1%
ASCII 128210
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70323
54.8%
1 15002
 
11.7%
2 6815
 
5.3%
6 5874
 
4.6%
4 5430
 
4.2%
3 5222
 
4.1%
5 4888
 
3.8%
0 3740
 
2.9%
8 3402
 
2.7%
7 3067
 
2.4%
Other values (28) 4447
 
3.5%
Hangul
ValueCountFrequency (%)
지 12749
 
8.4%
호 10126
 
6.7%
동 10054
 
6.6%
관 10010
 
6.6%
악 10003
 
6.6%
번 9976
 
6.6%
서 9976
 
6.6%
구 9976
 
6.6%
울 9975
 
6.6%
시 9970
 
6.6%
Other values (220) 48428
32.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct3506
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20108490
Minimum200310
Maximum20240317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:54:15.835146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200310
5-th percentile20030527
Q120090328
median20121008
Q320160919
95-th percentile20210218
Maximum20240317
Range20040007
Interquartile range (IQR)70591

Descriptive statistics

Standard deviation529677.09
Coefficient of variation (CV)0.026340968
Kurtosis1394.892
Mean20108490
Median Absolute Deviation (MAD)39409
Skewness-37.176902
Sum2.010849 × 1011
Variance2.8055782 × 1011
MonotonicityNot monotonic
2024-05-11T15:54:16.120462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130308 168
 
1.7%
20130307 87
 
0.9%
20180101 78
 
0.8%
20170101 64
 
0.6%
20141110 48
 
0.5%
20151120 37
 
0.4%
20240119 32
 
0.3%
20130408 30
 
0.3%
20110325 28
 
0.3%
20170601 27
 
0.3%
Other values (3496) 9401
94.0%
ValueCountFrequency (%)
200310 1
 
< 0.1%
200311 1
 
< 0.1%
200401 1
 
< 0.1%
200410 1
 
< 0.1%
200507 3
< 0.1%
20000619 1
 
< 0.1%
20000917 1
 
< 0.1%
20000919 1
 
< 0.1%
20000928 3
< 0.1%
20001011 1
 
< 0.1%
ValueCountFrequency (%)
20240317 2
< 0.1%
20240311 3
< 0.1%
20240309 2
< 0.1%
20240308 1
 
< 0.1%
20240307 3
< 0.1%
20240305 1
 
< 0.1%
20240229 3
< 0.1%
20240227 1
 
< 0.1%
20240226 1
 
< 0.1%
20240222 1
 
< 0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
처분확정
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row처분확정
2nd row처분확정
3rd row처분확정
4th row처분확정
5th row처분확정

Common Values

ValueCountFrequency (%)
처분확정 10000
100.0%

Length

2024-05-11T15:54:16.375150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:54:16.537199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct1386
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:54:16.894341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length74
Mean length8.1205
Min length2

Characters and Unicode

Total characters81205
Distinct characters253
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique935 ?
Unique (%)9.3%

Sample

1st row과태료부과
2nd row영업소폐쇄
3rd row시설개수명령
4th row영업소폐쇄
5th row과태료20만원부과
ValueCountFrequency (%)
과태료부과 1895
 
14.1%
시정명령 1598
 
11.9%
영업소폐쇄 1551
 
11.5%
영업정지 1154
 
8.6%
시설개수명령 956
 
7.1%
부과 309
 
2.3%
과징금부과 241
 
1.8%
및 217
 
1.6%
과징금 210
 
1.6%
갈음 208
 
1.5%
Other values (1381) 5093
37.9%
2024-05-11T15:54:17.678408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7746
 
9.5%
부 4159
 
5.1%
정 3824
 
4.7%
업 3745
 
4.6%
영 3682
 
4.5%
3445
 
4.2%
0 3309
 
4.1%
료 3121
 
3.8%
태 3112
 
3.8%
명 2925
 
3.6%
Other values (243) 42137
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62812
77.3%
Decimal Number 10773
 
13.3%
Space Separator 3445
 
4.2%
Other Punctuation 1559
 
1.9%
Open Punctuation 1187
 
1.5%
Close Punctuation 1180
 
1.5%
Math Symbol 129
 
0.2%
Dash Punctuation 118
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (216) 24740
39.4%
Decimal Number
ValueCountFrequency (%)
0 3309
30.7%
2 2172
20.2%
1 1928
17.9%
3 685
 
6.4%
4 659
 
6.1%
6 610
 
5.7%
5 572
 
5.3%
7 362
 
3.4%
8 278
 
2.6%
9 198
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 905
58.1%
, 445
28.5%
% 142
 
9.1%
: 32
 
2.1%
/ 30
 
1.9%
' 2
 
0.1%
* 2
 
0.1%
？ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1181
99.5%
[ 6
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 1174
99.5%
] 6
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 123
95.3%
+ 6
 
4.7%
Space Separator
ValueCountFrequency (%)
3445
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62812
77.3%
Common 18393
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (216) 24740
39.4%
Common
ValueCountFrequency (%)
3445
18.7%
0 3309
18.0%
2 2172
11.8%
1 1928
10.5%
( 1181
 
6.4%
) 1174
 
6.4%
. 905
 
4.9%
3 685
 
3.7%
4 659
 
3.6%
6 610
 
3.3%
Other values (17) 2325
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62764
77.3%
ASCII 18392
 
22.6%
Compat Jamo 48
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (215) 24692
39.3%
ASCII
ValueCountFrequency (%)
3445
18.7%
0 3309
18.0%
2 2172
11.8%
1 1928
10.5%
( 1181
 
6.4%
) 1174
 
6.4%
. 905
 
4.9%
3 685
 
3.7%
4 659
 
3.6%
6 610
 
3.3%
Other values (16) 2324
12.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 48
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

법적근거
Text

Distinct988
Distinct (%)9.9%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:54:18.129596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length54
Mean length13.94878
Min length3

Characters and Unicode

Total characters139432
Distinct characters180
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)5.3%

Sample

1st row식품위생법 제101조
2nd row법 제71조, 법 제74조,법 제75조 및 법 제76조
3rd row식품위생법 제36조
4th row식품위생법 제37조
5th row법 제101조제2항제1호
ValueCountFrequency (%)
법 4893
17.5%
식품위생법 4095
 
14.7%
및 2235
 
8.0%
제75조 1533
 
5.5%
제71조 1162
 
4.2%
제101조제2항제1호 978
 
3.5%
제37조 950
 
3.4%
제74조 589
 
2.1%
제67조 561
 
2.0%
영 554
 
2.0%
Other values (690) 10338
37.1%
2024-05-11T15:54:18.841752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17912
12.8%
제 17692
12.7%
조 13838
 
9.9%
법 12248
 
8.8%
1 9424
 
6.8%
위 6925
 
5.0%
생 6518
 
4.7%
7 6316
 
4.5%
품 5959
 
4.3%
식 5958
 
4.3%
Other values (170) 36642
26.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85604
61.4%
Decimal Number 33035
 
23.7%
Space Separator 17912
 
12.8%
Other Punctuation 1628
 
1.2%
Open Punctuation 625
 
0.4%
Close Punctuation 625
 
0.4%
Other Symbol 1
 
< 0.1%
Letter Number 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 17692
20.7%
조 13838
16.2%
법 12248
14.3%
위 6925
 
8.1%
생 6518
 
7.6%
품 5959
 
7.0%
식 5958
 
7.0%
항 2613
 
3.1%
및 2268
 
2.6%
호 1747
 
2.0%
Other values (143) 9838
11.5%
Decimal Number
ValueCountFrequency (%)
1 9424
28.5%
7 6316
19.1%
3 3929
11.9%
2 3614
 
10.9%
4 2766
 
8.4%
5 2185
 
6.6%
6 2152
 
6.5%
0 2044
 
6.2%
8 460
 
1.4%
9 145
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 1574
96.7%
: 35
 
2.1%
. 14
 
0.9%
？ 2
 
0.1%
; 1
 
0.1%
/ 1
 
0.1%
? 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 619
99.0%
[ 5
 
0.8%
「 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 619
99.0%
] 5
 
0.8%
」 1
 
0.2%
Space Separator
ValueCountFrequency (%)
17912
100.0%
Other Symbol
ValueCountFrequency (%)
○ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85604
61.4%
Common 53826
38.6%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 17692
20.7%
조 13838
16.2%
법 12248
14.3%
위 6925
 
8.1%
생 6518
 
7.6%
품 5959
 
7.0%
식 5958
 
7.0%
항 2613
 
3.1%
및 2268
 
2.6%
호 1747
 
2.0%
Other values (143) 9838
11.5%
Common
ValueCountFrequency (%)
17912
33.3%
1 9424
17.5%
7 6316
 
11.7%
3 3929
 
7.3%
2 3614
 
6.7%
4 2766
 
5.1%
5 2185
 
4.1%
6 2152
 
4.0%
0 2044
 
3.8%
, 1574
 
2.9%
Other values (15) 1910
 
3.5%
Latin
ValueCountFrequency (%)
Ⅱ 1
50.0%
X 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85601
61.4%
ASCII 53822
38.6%
None 4
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Geometric Shapes 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17912
33.3%
1 9424
17.5%
7 6316
 
11.7%
3 3929
 
7.3%
2 3614
 
6.7%
4 2766
 
5.1%
5 2185
 
4.1%
6 2152
 
4.0%
0 2044
 
3.8%
, 1574
 
2.9%
Other values (12) 1906
 
3.5%
Hangul
ValueCountFrequency (%)
제 17692
20.7%
조 13838
16.2%
법 12248
14.3%
위 6925
 
8.1%
생 6518
 
7.6%
품 5959
 
7.0%
식 5958
 
7.0%
항 2613
 
3.1%
및 2268
 
2.6%
호 1747
 
2.0%
Other values (140) 9835
11.5%
None
ValueCountFrequency (%)
？ 2
50.0%
「 1
25.0%
」 1
25.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅗ 1
33.3%
ㅈ 1
33.3%
ㄱ 1
33.3%

위반일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct3540
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20108325
Minimum200310
Maximum20240317
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:54:19.077364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200310
5-th percentile20030521
Q120090325
median20121004
Q320160928
95-th percentile20210208
Maximum20240317
Range20040007
Interquartile range (IQR)70603.25

Descriptive statistics

Standard deviation529653.63
Coefficient of variation (CV)0.026340018
Kurtosis1395.0932
Mean20108325
Median Absolute Deviation (MAD)39421
Skewness-37.180942
Sum2.0108325 × 1011
Variance2.8053297 × 1011
MonotonicityNot monotonic
2024-05-11T15:54:19.314131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130308 177
 
1.8%
20130307 87
 
0.9%
20180101 87
 
0.9%
20170101 83
 
0.8%
20190101 56
 
0.6%
20230101 56
 
0.6%
20141110 48
 
0.5%
20160101 47
 
0.5%
20151120 37
 
0.4%
20130408 30
 
0.3%
Other values (3530) 9292
92.9%
ValueCountFrequency (%)
200310 1
 
< 0.1%
200311 1
 
< 0.1%
200401 1
 
< 0.1%
200410 1
 
< 0.1%
200507 3
< 0.1%
19980722 1
 
< 0.1%
20000301 2
< 0.1%
20000619 1
 
< 0.1%
20000623 1
 
< 0.1%
20000703 1
 
< 0.1%
ValueCountFrequency (%)
20240317 2
< 0.1%
20240311 3
< 0.1%
20240309 2
< 0.1%
20240308 1
 
< 0.1%
20240307 3
< 0.1%
20240305 1
 
< 0.1%
20240229 2
< 0.1%
20240227 1
 
< 0.1%
20240226 1
 
< 0.1%
20240222 1
 
< 0.1%

위반내용
Text

Distinct3327
Distinct (%)33.4%
Missing36
Missing (%)0.4%
Memory size156.2 KiB
2024-05-11T15:54:19.944087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length388
Median length146
Mean length16.921718
Min length1

Characters and Unicode

Total characters168608
Distinct characters689
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2201 ?
Unique (%)22.1%

Sample

1st row기존영업자 위생교육 미이수(2012년)
2nd row시설물 멸실
3rd row주방내 환풍기 청소불량
4th row영업시설의 전부철거
5th row2018년 식품위생교육 미이수
ValueCountFrequency (%)
영업시설의 715
 
2.1%
위생교육 662
 
2.0%
영업장외 522
 
1.5%
영업 500
 
1.5%
철거 499
 
1.5%
미필 435
 
1.3%
주방내 430
 
1.3%
건강진단 427
 
1.3%
기존영업자 425
 
1.3%
전부를 412
 
1.2%
Other values (4867) 28731
85.1%
2024-05-11T15:54:20.940981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24441
 
14.5%
업 6552
 
3.9%
영 4528
 
2.7%
미 3470
 
2.1%
1 3461
 
2.1%
위 2926
 
1.7%
2 2686
 
1.6%
) 2591
 
1.5%
( 2540
 
1.5%
기 2513
 
1.5%
Other values (679) 112900
67.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123455
73.2%
Space Separator 24441
 
14.5%
Decimal Number 11737
 
7.0%
Other Punctuation 3298
 
2.0%
Close Punctuation 2596
 
1.5%
Open Punctuation 2545
 
1.5%
Dash Punctuation 339
 
0.2%
Uppercase Letter 74
 
< 0.1%
Lowercase Letter 49
 
< 0.1%
Other Symbol 43
 
< 0.1%
Other values (4) 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6552
 
5.3%
영 4528
 
3.7%
미 3470
 
2.8%
위 2926
 
2.4%
기 2513
 
2.0%
소 2415
 
2.0%
장 2275
 
1.8%
시 2121
 
1.7%
주 1993
 
1.6%
이 1880
 
1.5%
Other values (610) 92782
75.2%
Uppercase Letter
ValueCountFrequency (%)
T 10
13.5%
C 9
12.2%
O 8
10.8%
U 8
10.8%
V 6
8.1%
F 5
6.8%
L 5
6.8%
S 4
 
5.4%
R 4
 
5.4%
N 3
 
4.1%
Other values (8) 12
16.2%
Lowercase Letter
ValueCountFrequency (%)
g 16
32.7%
c 7
14.3%
l 6
 
12.2%
m 6
 
12.2%
w 3
 
6.1%
k 3
 
6.1%
v 2
 
4.1%
o 2
 
4.1%
i 1
 
2.0%
t 1
 
2.0%
Other values (2) 2
 
4.1%
Other Punctuation
ValueCountFrequency (%)
. 1695
51.4%
, 709
21.5%
: 633
 
19.2%
/ 213
 
6.5%
? 25
 
0.8%
% 11
 
0.3%
？ 4
 
0.1%
* 3
 
0.1%
' 2
 
0.1%
※ 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 3461
29.5%
2 2686
22.9%
0 2509
21.4%
3 781
 
6.7%
5 547
 
4.7%
4 469
 
4.0%
6 457
 
3.9%
7 334
 
2.8%
9 278
 
2.4%
8 215
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 2591
99.8%
] 3
 
0.1%
」 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 2540
99.8%
[ 3
 
0.1%
「 2
 
0.1%
Other Symbol
ValueCountFrequency (%)
○ 29
67.4%
㎡ 13
30.2%
● 1
 
2.3%
Math Symbol
ValueCountFrequency (%)
~ 17
70.8%
→ 6
 
25.0%
+ 1
 
4.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Space Separator
ValueCountFrequency (%)
24441
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 339
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123449
73.2%
Common 45026
 
26.7%
Latin 127
 
0.1%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6552
 
5.3%
영 4528
 
3.7%
미 3470
 
2.8%
위 2926
 
2.4%
기 2513
 
2.0%
소 2415
 
2.0%
장 2275
 
1.8%
시 2121
 
1.7%
주 1993
 
1.6%
이 1880
 
1.5%
Other values (608) 92776
75.2%
Common
ValueCountFrequency (%)
24441
54.3%
1 3461
 
7.7%
2 2686
 
6.0%
) 2591
 
5.8%
( 2540
 
5.6%
0 2509
 
5.6%
. 1695
 
3.8%
3 781
 
1.7%
, 709
 
1.6%
: 633
 
1.4%
Other values (27) 2980
 
6.6%
Latin
ValueCountFrequency (%)
g 16
 
12.6%
T 10
 
7.9%
C 9
 
7.1%
O 8
 
6.3%
U 8
 
6.3%
c 7
 
5.5%
V 6
 
4.7%
l 6
 
4.7%
m 6
 
4.7%
F 5
 
3.9%
Other values (22) 46
36.2%
Han
ValueCountFrequency (%)
麗 3
50.0%
駙 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123380
73.2%
ASCII 45087
 
26.7%
Compat Jamo 69
 
< 0.1%
Geometric Shapes 30
 
< 0.1%
CJK Compat 13
 
< 0.1%
None 8
 
< 0.1%
Arrows 6
 
< 0.1%
Punctuation 5
 
< 0.1%
Number Forms 4
 
< 0.1%
CJK Compat Ideographs 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24441
54.2%
1 3461
 
7.7%
2 2686
 
6.0%
) 2591
 
5.7%
( 2540
 
5.6%
0 2509
 
5.6%
. 1695
 
3.8%
3 781
 
1.7%
, 709
 
1.6%
: 633
 
1.4%
Other values (47) 3041
 
6.7%
Hangul
ValueCountFrequency (%)
업 6552
 
5.3%
영 4528
 
3.7%
미 3470
 
2.8%
위 2926
 
2.4%
기 2513
 
2.0%
소 2415
 
2.0%
장 2275
 
1.8%
시 2121
 
1.7%
주 1993
 
1.6%
이 1880
 
1.5%
Other values (599) 92707
75.1%
Compat Jamo
ValueCountFrequency (%)
ㅇ 57
82.6%
ㆍ 3
 
4.3%
ㅂ 2
 
2.9%
ㅌ 2
 
2.9%
ㅏ 1
 
1.4%
ㄱ 1
 
1.4%
ㄹ 1
 
1.4%
ㅁ 1
 
1.4%
ㄴ 1
 
1.4%
Geometric Shapes
ValueCountFrequency (%)
○ 29
96.7%
● 1
 
3.3%
CJK Compat
ValueCountFrequency (%)
㎡ 13
100.0%
Arrows
ValueCountFrequency (%)
→ 6
100.0%
None
ValueCountFrequency (%)
？ 4
50.0%
「 2
25.0%
」 2
25.0%
CJK Compat Ideographs
ValueCountFrequency (%)
麗 3
100.0%
CJK
ValueCountFrequency (%)
駙 3
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅰ 2
50.0%
Punctuation
ValueCountFrequency (%)
“ 2
40.0%
※ 2
40.0%
” 1
20.0%

처분내용
Text

Distinct1386
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:54:21.397173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length93
Median length74
Mean length8.1205
Min length2

Characters and Unicode

Total characters81205
Distinct characters253
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique935 ?
Unique (%)9.3%

Sample

1st row과태료부과
2nd row영업소폐쇄
3rd row시설개수명령
4th row영업소폐쇄
5th row과태료20만원부과
ValueCountFrequency (%)
과태료부과 1895
 
14.1%
시정명령 1598
 
11.9%
영업소폐쇄 1551
 
11.5%
영업정지 1154
 
8.6%
시설개수명령 956
 
7.1%
부과 309
 
2.3%
과징금부과 241
 
1.8%
및 217
 
1.6%
과징금 210
 
1.6%
갈음 208
 
1.5%
Other values (1381) 5093
37.9%
2024-05-11T15:54:22.038139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 7746
 
9.5%
부 4159
 
5.1%
정 3824
 
4.7%
업 3745
 
4.6%
영 3682
 
4.5%
3445
 
4.2%
0 3309
 
4.1%
료 3121
 
3.8%
태 3112
 
3.8%
명 2925
 
3.6%
Other values (243) 42137
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62812
77.3%
Decimal Number 10773
 
13.3%
Space Separator 3445
 
4.2%
Other Punctuation 1559
 
1.9%
Open Punctuation 1187
 
1.5%
Close Punctuation 1180
 
1.5%
Math Symbol 129
 
0.2%
Dash Punctuation 118
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (216) 24740
39.4%
Decimal Number
ValueCountFrequency (%)
0 3309
30.7%
2 2172
20.2%
1 1928
17.9%
3 685
 
6.4%
4 659
 
6.1%
6 610
 
5.7%
5 572
 
5.3%
7 362
 
3.4%
8 278
 
2.6%
9 198
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 905
58.1%
, 445
28.5%
% 142
 
9.1%
: 32
 
2.1%
/ 30
 
1.9%
' 2
 
0.1%
* 2
 
0.1%
？ 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1181
99.5%
[ 6
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 1174
99.5%
] 6
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 123
95.3%
+ 6
 
4.7%
Space Separator
ValueCountFrequency (%)
3445
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62812
77.3%
Common 18393
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (216) 24740
39.4%
Common
ValueCountFrequency (%)
3445
18.7%
0 3309
18.0%
2 2172
11.8%
1 1928
10.5%
( 1181
 
6.4%
) 1174
 
6.4%
. 905
 
4.9%
3 685
 
3.7%
4 659
 
3.6%
6 610
 
3.3%
Other values (17) 2325
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62764
77.3%
ASCII 18392
 
22.6%
Compat Jamo 48
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 7746
 
12.3%
부 4159
 
6.6%
정 3824
 
6.1%
업 3745
 
6.0%
영 3682
 
5.9%
료 3121
 
5.0%
태 3112
 
5.0%
명 2925
 
4.7%
령 2909
 
4.6%
시 2849
 
4.5%
Other values (215) 24692
39.3%
ASCII
ValueCountFrequency (%)
3445
18.7%
0 3309
18.0%
2 2172
11.8%
1 1928
10.5%
( 1181
 
6.4%
) 1174
 
6.4%
. 905
 
4.9%
3 685
 
3.7%
4 659
 
3.6%
6 610
 
3.3%
Other values (16) 2324
12.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 48
100.0%
None
ValueCountFrequency (%)
？ 1
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)2.7%
Missing8998
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean11.345309
Minimum0
Maximum60
Zeros86
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:54:22.319178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q315
95-th percentile20
Maximum60
Range60
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.3952813
Coefficient of variation (CV)0.56369387
Kurtosis7.0099238
Mean11.345309
Median Absolute Deviation (MAD)5
Skewness1.0097272
Sum11368
Variance40.899623
MonotonicityNot monotonic
2024-05-11T15:54:22.531908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15 456
 
4.6%
7 262
 
2.6%
0 86
 
0.9%
10 64
 
0.6%
20 31
 
0.3%
3 18
 
0.2%
5 17
 
0.2%
22 15
 
0.1%
13 8
 
0.1%
29 6
 
0.1%
Other values (17) 39
 
0.4%
(Missing) 8998
90.0%
ValueCountFrequency (%)
0 86
 
0.9%
1 5
 
0.1%
2 3
 
< 0.1%
3 18
 
0.2%
4 2
 
< 0.1%
5 17
 
0.2%
6 5
 
0.1%
7 262
2.6%
8 1
 
< 0.1%
10 64
 
0.6%
ValueCountFrequency (%)
60 2
 
< 0.1%
40 3
 
< 0.1%
31 2
 
< 0.1%
30 1
 
< 0.1%
29 6
 
0.1%
28 2
 
< 0.1%
25 1
 
< 0.1%
24 2
 
< 0.1%
23 1
 
< 0.1%
22 15
0.1%

영업장면적(㎡)
Real number (ℝ)

MISSING 

Distinct2230
Distinct (%)43.5%
Missing4877
Missing (%)48.8%
Infinite0
Infinite (%)0.0%
Mean145.44268
Minimum0
Maximum4963.42
Zeros11
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:54:22.731106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.004
Q139.6
median75.9
Q3127.1
95-th percentile483.087
Maximum4963.42
Range4963.42
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation287.23334
Coefficient of variation (CV)1.9748903
Kurtosis104.64718
Mean145.44268
Median Absolute Deviation (MAD)42.58
Skewness8.1758721
Sum745102.85
Variance82502.991
MonotonicityNot monotonic
2024-05-11T15:54:22.963161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 45
 
0.4%
66.0 41
 
0.4%
99.0 28
 
0.3%
49.5 26
 
0.3%
23.1 22
 
0.2%
82.5 21
 
0.2%
45.0 20
 
0.2%
52.88 20
 
0.2%
26.4 19
 
0.2%
55.0 18
 
0.2%
Other values (2220) 4863
48.6%
(Missing) 4877
48.8%
ValueCountFrequency (%)
0.0 11
0.1%
2.0 1
 
< 0.1%
3.0 1
 
< 0.1%
3.3 2
 
< 0.1%
3.36 1
 
< 0.1%
3.97 1
 
< 0.1%
5.0 2
 
< 0.1%
5.16 1
 
< 0.1%
5.5 1
 
< 0.1%
5.6 1
 
< 0.1%
ValueCountFrequency (%)
4963.42 6
0.1%
2785.57 1
 
< 0.1%
2466.5 1
 
< 0.1%
2347.46 3
< 0.1%
2278.15 1
 
< 0.1%
2126.35 3
< 0.1%
1980.0 3
< 0.1%
1922.7 1
 
< 0.1%
1912.75 6
0.1%
1877.72 2
 
< 0.1%

Interactions

2024-05-11T15:54:06.692762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:03.259926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.096295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.984106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:05.805931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:06.883460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:03.402809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.284063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:05.159854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:06.029438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:07.070383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:03.643718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.472603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:05.338643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:06.196195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:07.244548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:03.812617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.650362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:05.515803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:06.361858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:07.430321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:03.974473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:04.812379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:05.663486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:54:06.526751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T15:54:23.106152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.4220.5260.0740.0740.3300.086
업종명0.4221.0000.9980.1280.1280.5340.631
업태명0.5260.9981.0000.1170.1170.7200.849
지도점검일자0.0740.1280.1171.0000.991NaN0.148
위반일자0.0740.1280.1170.9911.000NaN0.148
처분기간0.3300.5340.720NaNNaN1.0000.088
영업장면적(㎡)0.0860.6310.8490.1480.1480.0881.000
2024-05-11T15:54:23.286439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명
처분일자1.0000.9990.998-0.122-0.1210.159
지도점검일자0.9991.0000.999-0.126-0.1280.118
위반일자0.9980.9991.000-0.123-0.1250.118
처분기간-0.122-0.126-0.1231.000-0.0020.269
영업장면적(㎡)-0.121-0.128-0.125-0.0021.0000.292
업종명0.1590.1180.1180.2690.2921.000

Missing values

2024-05-11T15:54:07.695892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T15:54:08.101904image/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.
2024-05-11T15:54:08.413330image/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

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
1259532000002015030220100094930즉석판매제조가공업즉석판매제조가공업신보상회서울특별시 관악구 남부순환로157길 63, (신림동)서울특별시 관악구 신림동 505번지 1호20141110처분확정과태료부과식품위생법 제101조20141110기존영업자 위생교육 미이수(2012년)과태료부과<NA><NA>
1266832000002015103020150094117즉석판매제조가공업즉석판매제조가공업고양한과서울특별시 관악구 남부순환로248길 20, (봉천동)서울특별시 관악구 봉천동 1635번지 18호20151007처분확정영업소폐쇄법 제71조, 법 제74조,법 제75조 및 법 제76조20151007시설물 멸실영업소폐쇄<NA><NA>
476232000002012122120020094169일반음식점경양식발렌타인<NA>서울특별시 관악구 신림동 1531번지 3호20121213처분확정시설개수명령식품위생법 제36조20121213주방내 환풍기 청소불량시설개수명령<NA><NA>
607432000002011070820050094423일반음식점통닭(치킨)하프앤드<NA>서울특별시 관악구 남현동 1067번지 23호 지상1층20110607처분확정영업소폐쇄식품위생법 제37조20110607영업시설의 전부철거영업소폐쇄<NA><NA>
1239232000002020021920010095362즉석판매제조가공업즉석판매제조가공업장수식품서울특별시 관악구 남부순환로248길 24, (봉천동)서울특별시 관악구 봉천동 1635번지 37호20191231처분확정과태료20만원부과법 제101조제2항제1호201801012018년 식품위생교육 미이수과태료20만원부과<NA><NA>
244132000002011111719960094424일반음식점한식유천칡냉면<NA>서울특별시 관악구 봉천동 895번지 24호20111114처분확정시설개수명령식품위생법 제36조(시설기준)20111114조리장바닥 타일 파손시설개수명령<NA>85.8
988232000002006091120000094058유흥주점영업룸살롱헤라<NA>서울특별시 관악구 봉천동 868번지 25호20060821처분확정영업허가취소(시설물 무단철거)식품위생법 제22조 제5항 후단20060821영업시설물 무단 철거영업허가취소(시설물 무단철거)<NA>81.61
1089432000002016040420120094180유흥주점영업룸살롱옹달샘서울특별시 관악구 신림로 365, 2층호 (신림동)서울특별시 관악구 신림동 1431번지 7호 -2층20160315처분확정과태료부과법 제101조제2항제1호20160101기존영업자 위생교육 미수료과태료부과<NA><NA>
1211532000002010081720000094505식품제조가공업식품제조가공업(주)해심원<NA>서울특별시 관악구 신림동 566번지 2호20100713처분확정품목제조정지 1개월식품위생법 제31조제1항20100713자가품질검사 미실시(전항목) - 제품명 : 청다시마품목제조정지 1개월<NA><NA>
270332000002013081919970094731일반음식점호프/통닭버블캐슬<NA>서울특별시 관악구 봉천동 1636번지 2호20130711처분확정과태료부과식품위생법 제101조20130711건강진단 미필(영업주1명)과태료부과<NA>24.3
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
687632000002009070220070094641일반음식점한식김밥마을<NA>서울특별시 관악구 신림동 1436번지 17호 지상1층20090608처분확정영업정지15일 및 당해 음식물 폐기식품위생법 제7조 위반20090512수거검사결과 대장균 검출영업정지15일 및 당해 음식물 폐기15<NA>
320532000002011052019990094709일반음식점호프/통닭모아호프<NA>서울특별시 관악구 신림동 608번지 38호 지상2층20110310처분확정영업정지2월에서 불문처리(혐의없음(범죄인정안됨) 통보)식품위생법 제44조20110310청소년주류제공영업정지2월에서 불문처리(혐의없음(범죄인정안됨) 통보)<NA>31.54
143932000002016032119870094154일반음식점한식돼지고기 한주먹 주먹대장서울특별시 관악구 신림로 391, 1층 (신림동)서울특별시 관악구 신림동 1429번지 1호 지상1층20160310처분확정과태료부과 20만원(의견제출기간 20%경감)법 제101조제2항제1호201601012015년 기존영업자 위생교육 미수료과태료부과 20만원(의견제출기간 20%경감)<NA>38.46
631332000002009100620060094084일반음식점호프/통닭캔디<NA>서울특별시 관악구 신림동 1525번지 10호 지상2층20090824처분확정과태료부과 및 시설개수명령식품위생법제40조, 동법제36조 위반20090824건강진단 미필(종업원 4명중 1명) 주방 미개방(커텐 설치) (2009. 8. 24. 21:49경 관악구 적발)과태료부과 및 시설개수명령<NA><NA>
988732000002018011620000094065유흥주점영업룸살롱황제비지니스클럽서울특별시 관악구 남부순환로 1486, 지하1층 (신림동)서울특별시 관악구 신림동 1569번지 12호20171214처분확정영업소폐쇄법 제71조, 법 제74조 및 법 제75조20171214영업시설의 전부 철거영업소폐쇄<NA>124.99
908232000002017080720160094616일반음식점한식술이남서울특별시 관악구 신림동길 5, 2층 201호 (신림동)서울특별시 관악구 신림동 1431번지 43호20170401처분확정과징금부과(1,240만원)법 제75조20170401청소년에게 주류를 제공하는 행위과징금부과(1,240만원)40<NA>
347832000002018080120000094140일반음식점분식김밥나라서울특별시 관악구 신림로 359, (신림동)서울특별시 관악구 신림동 1431번지 16호20180724처분확정과태료부과(240000)법 제18조제1항제1호20180724원산지 미표시(돼지고기)과태료부과(240000)<NA>22.52
923532000002019050820170094934일반음식점한식국제시장서울특별시 관악구 신림로 317, (신림동)서울특별시 관악구 신림동 1638번지 17호20190402처분확정시정명령 및 과태료부과법 제101조제2항제1호 및 영 제67조20190402원료보관실, 조리실 등 청소불량시정명령 및 과태료부과<NA><NA>
422932000002018052320010095089일반음식점한식오사카부르스서울특별시 관악구 청룡2길 1, (봉천동)서울특별시 관악구 봉천동 914번지 1호20180323처분확정과징금부과법 제75조20180211청소년 주류제공(1차)과징금부과<NA>89.46
151732000002017101719890094236일반음식점한식낙지마을해물구이서울특별시 관악구 봉천로 469-1, 1-2층 (봉천동)서울특별시 관악구 봉천동 860번지 37호 지상1,2층20170919처분확정과태료부과법 제101조제2항제1호20170919종업원 건강진단미필(1/3)과태료부과<NA>128.29

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
10432000002007120620070094102유흥주점영업고고(디스코)클럽골든벨중년나이트메들리<NA>서울특별시 관악구 신림동 529번지 4호 외 3필지(지하1층)20071108처분확정시정명령식품위생법26조,31조20071108종업원명부미비치,건강진단미필(3명중1명)시정명령<NA><NA>6
19432000002011092320100094373건강기능식품일반판매업방문판매인석물산<NA>서울특별시 관악구 봉천동 26번지 (지하)20110920처분확정시정명령건강기능식품에 관한 법률 위반 제10조20110920판매사례품 경품제공 등 사행심조장시정명령<NA><NA>4
29632000002017070320030094780일반음식점기타조개천하서울특별시 관악구 신림로 258, (신림동)서울특별시 관악구 신림동 808번지 372호20170530처분확정시정명령법 제71조, 법 제74조 및 법 제75조20170530영업장외 영업시정명령<NA><NA>4
432000002002121020010094048유흥주점영업룸살롱홍콩<NA>서울특별시 관악구 신림동 1513번지 2호20021111처분확정과태료부과 30만원부과식품위생법 제26조20021106건강진단미필과태료부과 30만원부과<NA><NA>3
832000002003061420010094048유흥주점영업룸살롱홍콩<NA>서울특별시 관악구 신림동 1513번지 2호20030612처분확정시정명령식품위생법제31조20030612종업원명부미비치시정명령<NA><NA>3
3532000002005080120040095092일반음식점기타포차홈피<NA>서울특별시 관악구 신림동 517번지 57호20050622처분확정70만원 과태료부과식품위생법 제26조20050622영업주 1명, 종업원2명중 2명 건강진단미필70만원 과태료부과<NA><NA>3
3632000002005080120040095092일반음식점기타포차홈피<NA>서울특별시 관악구 신림동 517번지 57호20050622처분확정70만원 과태료부과식품위생법 제31조20050622유통기간 경과제품 보관70만원 과태료부과<NA><NA>3
3732000002005080120040095092일반음식점기타포차홈피<NA>서울특별시 관악구 신림동 517번지 57호20050622처분확정시정명령식품위생법 제26조20050622영업주 1명, 종업원2명중 2명 건강진단미필시정명령<NA><NA>3
3932000002005080120040095092일반음식점기타포차홈피<NA>서울특별시 관악구 신림동 517번지 57호20050622처분확정시정명령식품위생법제31조20050622출입검사기록부 미비치시정명령<NA><NA>3
4232000002005081219990094162일반음식점한식땡큐목장<NA>서울특별시 관악구 봉천동 883번지 17호20050628처분확정과태료20만원부과식품위생법제31조20050628유통기한경과제품조리목적보관 냉면육수성상부적합과태료20만원부과<NA>394.23