Overview

Dataset statistics

Number of variables17
Number of observations8659
Missing cells17533
Missing cells (%)11.9%
Duplicate rows257
Duplicate rows (%)3.0%
Total size in memory1.2 MiB
Average record size in memory142.0 B

Variable types

Categorical3
Numeric5
Text9

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,행정처분취소일자,영업장면적(㎡)
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-2384/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 257 (3.0%) duplicate rowsDuplicates
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
행정처분취소일자 is highly overall correlated with 처분일자 and 2 other fieldsHigh correlation
업종명 is highly imbalanced (55.2%)Imbalance
소재지도로명 has 4573 (52.8%) missing valuesMissing
위반내용 has 161 (1.9%) missing valuesMissing
행정처분취소일자 has 8582 (99.1%) missing valuesMissing
영업장면적(㎡) has 4191 (48.4%) missing valuesMissing

Reproduction

Analysis started2024-05-11 03:21:08.479930
Analysis finished2024-05-11 03:21:29.926222
Duration21.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
3120000
8659 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 8659
100.0%

Length

2024-05-11T03:21:30.090637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:21:30.609465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 8659
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2356
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20126190
Minimum19980713
Maximum20240508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-05-11T03:21:30.962888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980713
5-th percentile20030324
Q120080118
median20120828
Q320181002
95-th percentile20220730
Maximum20240508
Range259795
Interquartile range (IQR)100884

Descriptive statistics

Standard deviation61840.75
Coefficient of variation (CV)0.0030726505
Kurtosis-1.1708983
Mean20126190
Median Absolute Deviation (MAD)50401
Skewness0.026181122
Sum1.7427268 × 1011
Variance3.8242783 × 109
MonotonicityDecreasing
2024-05-11T03:21:31.337260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211101 159
 
1.8%
20050317 156
 
1.8%
20220105 88
 
1.0%
20150909 68
 
0.8%
20210517 61
 
0.7%
20231130 55
 
0.6%
20180108 49
 
0.6%
20030221 38
 
0.4%
20190118 37
 
0.4%
20231124 36
 
0.4%
Other values (2346) 7912
91.4%
ValueCountFrequency (%)
19980713 1
 
< 0.1%
20010720 2
< 0.1%
20010817 1
 
< 0.1%
20010917 1
 
< 0.1%
20010918 2
< 0.1%
20010925 1
 
< 0.1%
20010929 1
 
< 0.1%
20011006 2
< 0.1%
20011009 4
< 0.1%
20011012 1
 
< 0.1%
ValueCountFrequency (%)
20240508 1
 
< 0.1%
20240426 1
 
< 0.1%
20240405 2
 
< 0.1%
20240403 2
 
< 0.1%
20240401 8
0.1%
20240325 2
 
< 0.1%
20240320 1
 
< 0.1%
20240319 3
 
< 0.1%
20240312 1
 
< 0.1%
20240308 2
 
< 0.1%
Distinct4757
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2024-05-11T03:21:31.808219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.480425
Min length1

Characters and Unicode

Total characters90750
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

Unique3126 ?
Unique (%)36.1%

Sample

1st row19930067004
2nd row19930066783
3rd row20050066395
4th row20000066100
5th row20090039341
ValueCountFrequency (%)
20020066805 84
 
1.0%
19820066054 30
 
0.3%
20010067090 28
 
0.3%
19940066854 22
 
0.3%
19990067142 21
 
0.2%
20050066396 20
 
0.2%
20080066348 18
 
0.2%
19860066267 18
 
0.2%
20040066097 18
 
0.2%
19830066194 18
 
0.2%
Other values (4747) 8382
96.8%
2024-05-11T03:21:32.560682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28845
31.8%
6 18767
20.7%
2 9014
 
9.9%
1 8656
 
9.5%
9 8150
 
9.0%
7 3563
 
3.9%
3 3488
 
3.8%
5 3417
 
3.8%
8 3413
 
3.8%
4 3390
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90703
99.9%
Dash Punctuation 47
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28845
31.8%
6 18767
20.7%
2 9014
 
9.9%
1 8656
 
9.5%
9 8150
 
9.0%
7 3563
 
3.9%
3 3488
 
3.8%
5 3417
 
3.8%
8 3413
 
3.8%
4 3390
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90750
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28845
31.8%
6 18767
20.7%
2 9014
 
9.9%
1 8656
 
9.5%
9 8150
 
9.0%
7 3563
 
3.9%
3 3488
 
3.8%
5 3417
 
3.8%
8 3413
 
3.8%
4 3390
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90750
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28845
31.8%
6 18767
20.7%
2 9014
 
9.9%
1 8656
 
9.5%
9 8150
 
9.0%
7 3563
 
3.9%
3 3488
 
3.8%
5 3417
 
3.8%
8 3413
 
3.8%
4 3390
 
3.7%

업종명
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
일반음식점
5573 
휴게음식점
592 
단란주점
 
403
즉석판매제조가공업
 
297
식품제조가공업
 
296
Other values (33)
1498 

Length

Max length23
Median length5
Mean length5.4266082
Min length3

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 5573
64.4%
휴게음식점 592
 
6.8%
단란주점 403
 
4.7%
즉석판매제조가공업 297
 
3.4%
식품제조가공업 296
 
3.4%
유흥주점영업 286
 
3.3%
건강기능식품일반판매업 153
 
1.8%
숙박업(일반) 152
 
1.8%
식품등 수입판매업 113
 
1.3%
목욕장업 102
 
1.2%
Other values (28) 692
 
8.0%

Length

2024-05-11T03:21:33.399100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 5573
63.4%
휴게음식점 592
 
6.7%
단란주점 403
 
4.6%
즉석판매제조가공업 297
 
3.4%
식품제조가공업 296
 
3.4%
유흥주점영업 286
 
3.3%
건강기능식품일반판매업 153
 
1.7%
숙박업(일반 152
 
1.7%
수입판매업 113
 
1.3%
식품등 113
 
1.3%
Other values (25) 808
 
9.2%
Distinct88
Distinct (%)1.0%
Missing11
Missing (%)0.1%
Memory size67.8 KiB
2024-05-11T03:21:34.259785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.3923451
Min length2

Characters and Unicode

Total characters37985
Distinct characters174
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

Unique12 ?
Unique (%)0.1%

Sample

1st row단란주점
2nd row단란주점
3rd row기타
4th row호프/통닭
5th row일식
ValueCountFrequency (%)
한식 2299
25.7%
정종/대포집/소주방 716
 
8.0%
경양식 631
 
7.1%
분식 526
 
5.9%
호프/통닭 517
 
5.8%
기타 443
 
5.0%
단란주점 403
 
4.5%
즉석판매제조가공업 297
 
3.3%
식품제조가공업 296
 
3.3%
커피숍 193
 
2.2%
Other values (79) 2621
29.3%
2024-05-11T03:21:35.625120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4519
 
11.9%
2299
 
6.1%
/ 1949
 
5.1%
1777
 
4.7%
1146
 
3.0%
795
 
2.1%
791
 
2.1%
789
 
2.1%
788
 
2.1%
788
 
2.1%
Other values (164) 22344
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35183
92.6%
Other Punctuation 1968
 
5.2%
Space Separator 294
 
0.8%
Open Punctuation 249
 
0.7%
Close Punctuation 249
 
0.7%
Math Symbol 42
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4519
 
12.8%
2299
 
6.5%
1777
 
5.1%
1146
 
3.3%
795
 
2.3%
791
 
2.2%
789
 
2.2%
788
 
2.2%
788
 
2.2%
772
 
2.2%
Other values (158) 20719
58.9%
Other Punctuation
ValueCountFrequency (%)
/ 1949
99.0%
, 19
 
1.0%
Space Separator
ValueCountFrequency (%)
294
100.0%
Open Punctuation
ValueCountFrequency (%)
( 249
100.0%
Close Punctuation
ValueCountFrequency (%)
) 249
100.0%
Math Symbol
ValueCountFrequency (%)
+ 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35183
92.6%
Common 2802
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4519
 
12.8%
2299
 
6.5%
1777
 
5.1%
1146
 
3.3%
795
 
2.3%
791
 
2.2%
789
 
2.2%
788
 
2.2%
788
 
2.2%
772
 
2.2%
Other values (158) 20719
58.9%
Common
ValueCountFrequency (%)
/ 1949
69.6%
294
 
10.5%
( 249
 
8.9%
) 249
 
8.9%
+ 42
 
1.5%
, 19
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35183
92.6%
ASCII 2802
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4519
 
12.8%
2299
 
6.5%
1777
 
5.1%
1146
 
3.3%
795
 
2.3%
791
 
2.2%
789
 
2.2%
788
 
2.2%
788
 
2.2%
772
 
2.2%
Other values (158) 20719
58.9%
ASCII
ValueCountFrequency (%)
/ 1949
69.6%
294
 
10.5%
( 249
 
8.9%
) 249
 
8.9%
+ 42
 
1.5%
, 19
 
0.7%
Distinct4850
Distinct (%)56.0%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2024-05-11T03:21:36.650559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length5.1158332
Min length1

Characters and Unicode

Total characters44298
Distinct characters986
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3196 ?
Unique (%)36.9%

Sample

1st row아마죤
2nd row황금매들리
3rd row선인장
4th row비어시티
5th row고기사랑
ValueCountFrequency (%)
한옥집 84
 
0.9%
신촌점 63
 
0.6%
주식회사 50
 
0.5%
마실 37
 
0.4%
석란 30
 
0.3%
이대점 29
 
0.3%
다복식품 20
 
0.2%
유가네기사식당 20
 
0.2%
오성 18
 
0.2%
애란네김밥 18
 
0.2%
Other values (5240) 9410
96.2%
2024-05-11T03:21:37.991755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1124
 
2.5%
1120
 
2.5%
966
 
2.2%
726
 
1.6%
) 645
 
1.5%
641
 
1.4%
( 640
 
1.4%
612
 
1.4%
610
 
1.4%
480
 
1.1%
Other values (976) 36734
82.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39672
89.6%
Space Separator 1120
 
2.5%
Lowercase Letter 890
 
2.0%
Uppercase Letter 766
 
1.7%
Close Punctuation 645
 
1.5%
Open Punctuation 640
 
1.4%
Decimal Number 422
 
1.0%
Other Punctuation 125
 
0.3%
Dash Punctuation 9
 
< 0.1%
Letter Number 6
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1124
 
2.8%
966
 
2.4%
726
 
1.8%
641
 
1.6%
612
 
1.5%
610
 
1.5%
480
 
1.2%
405
 
1.0%
404
 
1.0%
373
 
0.9%
Other values (897) 33331
84.0%
Uppercase Letter
ValueCountFrequency (%)
A 74
 
9.7%
B 68
 
8.9%
I 52
 
6.8%
E 49
 
6.4%
N 47
 
6.1%
C 46
 
6.0%
S 44
 
5.7%
O 44
 
5.7%
T 40
 
5.2%
R 36
 
4.7%
Other values (16) 266
34.7%
Lowercase Letter
ValueCountFrequency (%)
a 114
12.8%
e 99
 
11.1%
o 78
 
8.8%
r 62
 
7.0%
i 55
 
6.2%
s 48
 
5.4%
l 48
 
5.4%
t 46
 
5.2%
c 37
 
4.2%
f 37
 
4.2%
Other values (15) 266
29.9%
Decimal Number
ValueCountFrequency (%)
2 120
28.4%
0 67
15.9%
1 65
15.4%
4 46
 
10.9%
9 36
 
8.5%
3 31
 
7.3%
5 28
 
6.6%
7 14
 
3.3%
6 10
 
2.4%
8 5
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 37
29.6%
& 23
18.4%
, 17
13.6%
' 14
 
11.2%
! 11
 
8.8%
; 10
 
8.0%
? 6
 
4.8%
5
 
4.0%
% 1
 
0.8%
@ 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
1120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 645
100.0%
Open Punctuation
ValueCountFrequency (%)
( 640
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Letter Number
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39668
89.5%
Common 2963
 
6.7%
Latin 1662
 
3.8%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1124
 
2.8%
966
 
2.4%
726
 
1.8%
641
 
1.6%
612
 
1.5%
610
 
1.5%
480
 
1.2%
405
 
1.0%
404
 
1.0%
373
 
0.9%
Other values (894) 33327
84.0%
Latin
ValueCountFrequency (%)
a 114
 
6.9%
e 99
 
6.0%
o 78
 
4.7%
A 74
 
4.5%
B 68
 
4.1%
r 62
 
3.7%
i 55
 
3.3%
I 52
 
3.1%
E 49
 
2.9%
s 48
 
2.9%
Other values (42) 963
57.9%
Common
ValueCountFrequency (%)
1120
37.8%
) 645
21.8%
( 640
21.6%
2 120
 
4.0%
0 67
 
2.3%
1 65
 
2.2%
4 46
 
1.6%
. 37
 
1.2%
9 36
 
1.2%
3 31
 
1.0%
Other values (16) 156
 
5.3%
Han
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39666
89.5%
ASCII 4614
 
10.4%
Number Forms 6
 
< 0.1%
None 6
 
< 0.1%
CJK 5
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1124
 
2.8%
966
 
2.4%
726
 
1.8%
641
 
1.6%
612
 
1.5%
610
 
1.5%
480
 
1.2%
405
 
1.0%
404
 
1.0%
373
 
0.9%
Other values (892) 33325
84.0%
ASCII
ValueCountFrequency (%)
1120
24.3%
) 645
14.0%
( 640
13.9%
2 120
 
2.6%
a 114
 
2.5%
e 99
 
2.1%
o 78
 
1.7%
A 74
 
1.6%
B 68
 
1.5%
0 67
 
1.5%
Other values (66) 1589
34.4%
Number Forms
ValueCountFrequency (%)
6
100.0%
None
ValueCountFrequency (%)
5
83.3%
1
 
16.7%
CJK
ValueCountFrequency (%)
2
40.0%
1
20.0%
1
20.0%
1
20.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

소재지도로명
Text

MISSING 

Distinct2445
Distinct (%)59.8%
Missing4573
Missing (%)52.8%
Memory size67.8 KiB
2024-05-11T03:21:38.680259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length58
Mean length31.315223
Min length23

Characters and Unicode

Total characters127954
Distinct characters303
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1669 ?
Unique (%)40.8%

Sample

1st row서울특별시 서대문구 신촌로 283, (북아현동)
2nd row서울특별시 서대문구 응암로 78, (북가좌동,,15,16)
3rd row서울특별시 서대문구 수색로4가길 14-7, (남가좌동,1층)
4th row서울특별시 서대문구 증가로 116, (남가좌동)
5th row서울특별시 서대문구 충정로4길 26, 1~2층 (충정로3가)
ValueCountFrequency (%)
서울특별시 4086
 
17.7%
서대문구 4086
 
17.7%
창천동 718
 
3.1%
1층 597
 
2.6%
홍제동 385
 
1.7%
연희동 373
 
1.6%
남가좌동 324
 
1.4%
대현동 317
 
1.4%
통일로 294
 
1.3%
신촌로 276
 
1.2%
Other values (1758) 11651
50.4%
2024-05-11T03:21:39.795581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19026
 
14.9%
8281
 
6.5%
, 6140
 
4.8%
5121
 
4.0%
1 4902
 
3.8%
( 4815
 
3.8%
) 4813
 
3.8%
4187
 
3.3%
4156
 
3.2%
4150
 
3.2%
Other values (293) 62363
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74984
58.6%
Space Separator 19026
 
14.9%
Decimal Number 16887
 
13.2%
Other Punctuation 6153
 
4.8%
Open Punctuation 4815
 
3.8%
Close Punctuation 4813
 
3.8%
Dash Punctuation 985
 
0.8%
Uppercase Letter 180
 
0.1%
Math Symbol 65
 
0.1%
Lowercase Letter 40
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8281
 
11.0%
5121
 
6.8%
4187
 
5.6%
4156
 
5.5%
4150
 
5.5%
4098
 
5.5%
4098
 
5.5%
4086
 
5.4%
4074
 
5.4%
3593
 
4.8%
Other values (250) 29140
38.9%
Uppercase Letter
ValueCountFrequency (%)
B 60
33.3%
D 23
 
12.8%
C 21
 
11.7%
A 21
 
11.7%
M 20
 
11.1%
K 13
 
7.2%
S 9
 
5.0%
T 4
 
2.2%
G 4
 
2.2%
L 2
 
1.1%
Other values (3) 3
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 4902
29.0%
2 2464
14.6%
3 1974
11.7%
4 1500
 
8.9%
5 1243
 
7.4%
0 1123
 
6.7%
7 1059
 
6.3%
8 979
 
5.8%
6 901
 
5.3%
9 742
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 12
30.0%
c 5
12.5%
m 5
12.5%
d 5
12.5%
a 4
 
10.0%
s 3
 
7.5%
k 3
 
7.5%
b 3
 
7.5%
Other Punctuation
ValueCountFrequency (%)
, 6140
99.8%
? 4
 
0.1%
& 4
 
0.1%
/ 2
 
< 0.1%
. 2
 
< 0.1%
@ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
19026
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4815
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4813
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 985
100.0%
Math Symbol
ValueCountFrequency (%)
~ 65
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74979
58.6%
Common 52750
41.2%
Latin 220
 
0.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8281
 
11.0%
5121
 
6.8%
4187
 
5.6%
4156
 
5.5%
4150
 
5.5%
4098
 
5.5%
4098
 
5.5%
4086
 
5.4%
4074
 
5.4%
3593
 
4.8%
Other values (249) 29135
38.9%
Common
ValueCountFrequency (%)
19026
36.1%
, 6140
 
11.6%
1 4902
 
9.3%
( 4815
 
9.1%
) 4813
 
9.1%
2 2464
 
4.7%
3 1974
 
3.7%
4 1500
 
2.8%
5 1243
 
2.4%
0 1123
 
2.1%
Other values (12) 4750
 
9.0%
Latin
ValueCountFrequency (%)
B 60
27.3%
D 23
 
10.5%
C 21
 
9.5%
A 21
 
9.5%
M 20
 
9.1%
K 13
 
5.9%
e 12
 
5.5%
S 9
 
4.1%
c 5
 
2.3%
m 5
 
2.3%
Other values (11) 31
14.1%
Han
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74979
58.6%
ASCII 52970
41.4%
CJK 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19026
35.9%
, 6140
 
11.6%
1 4902
 
9.3%
( 4815
 
9.1%
) 4813
 
9.1%
2 2464
 
4.7%
3 1974
 
3.7%
4 1500
 
2.8%
5 1243
 
2.3%
0 1123
 
2.1%
Other values (33) 4970
 
9.4%
Hangul
ValueCountFrequency (%)
8281
 
11.0%
5121
 
6.8%
4187
 
5.6%
4156
 
5.5%
4150
 
5.5%
4098
 
5.5%
4098
 
5.5%
4086
 
5.4%
4074
 
5.4%
3593
 
4.8%
Other values (249) 29135
38.9%
CJK
ValueCountFrequency (%)
5
100.0%
Distinct4253
Distinct (%)49.2%
Missing11
Missing (%)0.1%
Memory size67.8 KiB
2024-05-11T03:21:40.516192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length63
Mean length29.741559
Min length21

Characters and Unicode

Total characters257205
Distinct characters316
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2534 ?
Unique (%)29.3%

Sample

1st row서울특별시 서대문구 북아현동 126번지 44호
2nd row서울특별시 서대문구 북가좌동 300번지 14호 ,15,16
3rd row서울특별시 서대문구 남가좌동 295번지 13호 1층
4th row서울특별시 서대문구 남가좌동 339번지 34호
5th row서울특별시 서대문구 충정로3가 345번지 1,2층 전체
ValueCountFrequency (%)
서울특별시 8648
 
18.0%
서대문구 8648
 
18.0%
창천동 2210
 
4.6%
남가좌동 1253
 
2.6%
홍제동 1061
 
2.2%
지상1층 852
 
1.8%
연희동 767
 
1.6%
대현동 676
 
1.4%
홍은동 625
 
1.3%
지하1층 611
 
1.3%
Other values (1767) 22641
47.2%
2024-05-11T03:21:41.778349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61110
23.8%
17324
 
6.7%
11136
 
4.3%
1 10153
 
3.9%
9592
 
3.7%
8678
 
3.4%
8667
 
3.4%
8663
 
3.4%
8663
 
3.4%
8658
 
3.4%
Other values (306) 104561
40.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145136
56.4%
Space Separator 61110
23.8%
Decimal Number 44588
 
17.3%
Open Punctuation 2044
 
0.8%
Close Punctuation 2043
 
0.8%
Other Punctuation 1360
 
0.5%
Dash Punctuation 597
 
0.2%
Uppercase Letter 232
 
0.1%
Math Symbol 50
 
< 0.1%
Lowercase Letter 45
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17324
 
11.9%
11136
 
7.7%
9592
 
6.6%
8678
 
6.0%
8667
 
6.0%
8663
 
6.0%
8663
 
6.0%
8658
 
6.0%
8654
 
6.0%
8648
 
6.0%
Other values (260) 46453
32.0%
Uppercase Letter
ValueCountFrequency (%)
B 73
31.5%
A 41
17.7%
D 26
 
11.2%
C 22
 
9.5%
M 21
 
9.1%
K 17
 
7.3%
S 12
 
5.2%
T 7
 
3.0%
P 4
 
1.7%
G 4
 
1.7%
Other values (4) 5
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 10153
22.8%
2 6712
15.1%
3 6258
14.0%
5 4095
9.2%
4 3604
 
8.1%
0 3181
 
7.1%
7 2753
 
6.2%
9 2740
 
6.1%
8 2603
 
5.8%
6 2489
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
e 14
31.1%
m 7
15.6%
a 6
13.3%
c 5
 
11.1%
d 5
 
11.1%
b 4
 
8.9%
p 2
 
4.4%
s 1
 
2.2%
k 1
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 1316
96.8%
. 11
 
0.8%
@ 11
 
0.8%
/ 9
 
0.7%
& 5
 
0.4%
? 4
 
0.3%
: 2
 
0.1%
; 2
 
0.1%
Space Separator
ValueCountFrequency (%)
61110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2044
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2043
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 597
100.0%
Math Symbol
ValueCountFrequency (%)
~ 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145130
56.4%
Common 111792
43.5%
Latin 277
 
0.1%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17324
 
11.9%
11136
 
7.7%
9592
 
6.6%
8678
 
6.0%
8667
 
6.0%
8663
 
6.0%
8663
 
6.0%
8658
 
6.0%
8654
 
6.0%
8648
 
6.0%
Other values (259) 46447
32.0%
Common
ValueCountFrequency (%)
61110
54.7%
1 10153
 
9.1%
2 6712
 
6.0%
3 6258
 
5.6%
5 4095
 
3.7%
4 3604
 
3.2%
0 3181
 
2.8%
7 2753
 
2.5%
9 2740
 
2.5%
8 2603
 
2.3%
Other values (13) 8583
 
7.7%
Latin
ValueCountFrequency (%)
B 73
26.4%
A 41
14.8%
D 26
 
9.4%
C 22
 
7.9%
M 21
 
7.6%
K 17
 
6.1%
e 14
 
5.1%
S 12
 
4.3%
T 7
 
2.5%
m 7
 
2.5%
Other values (13) 37
13.4%
Han
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145130
56.4%
ASCII 112069
43.6%
CJK 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61110
54.5%
1 10153
 
9.1%
2 6712
 
6.0%
3 6258
 
5.6%
5 4095
 
3.7%
4 3604
 
3.2%
0 3181
 
2.8%
7 2753
 
2.5%
9 2740
 
2.4%
8 2603
 
2.3%
Other values (36) 8860
 
7.9%
Hangul
ValueCountFrequency (%)
17324
 
11.9%
11136
 
7.7%
9592
 
6.6%
8678
 
6.0%
8667
 
6.0%
8663
 
6.0%
8663
 
6.0%
8658
 
6.0%
8654
 
6.0%
8648
 
6.0%
Other values (259) 46447
32.0%
CJK
ValueCountFrequency (%)
6
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2871
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124432
Minimum19980713
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-05-11T03:21:42.237400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980713
5-th percentile20030110
Q120071206
median20120713
Q320180522
95-th percentile20220228
Maximum20240311
Range259598
Interquartile range (IQR)109316.5

Descriptive statistics

Standard deviation61751.797
Coefficient of variation (CV)0.0030684988
Kurtosis-1.1427278
Mean20124432
Median Absolute Deviation (MAD)50309
Skewness0.020970968
Sum1.7425746 × 1011
Variance3.8132844 × 109
MonotonicityNot monotonic
2024-05-11T03:21:42.705049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210829 238
 
2.7%
20050124 156
 
1.8%
20171121 112
 
1.3%
20171017 82
 
0.9%
20210415 69
 
0.8%
20150728 65
 
0.8%
20181207 60
 
0.7%
20190313 44
 
0.5%
20231108 41
 
0.5%
20200227 39
 
0.5%
Other values (2861) 7753
89.5%
ValueCountFrequency (%)
19980713 1
< 0.1%
20001225 1
< 0.1%
20010420 1
< 0.1%
20010516 2
< 0.1%
20010517 1
< 0.1%
20010608 1
< 0.1%
20010610 1
< 0.1%
20010612 1
< 0.1%
20010710 1
< 0.1%
20010712 1
< 0.1%
ValueCountFrequency (%)
20240311 10
0.1%
20240228 2
 
< 0.1%
20240221 3
 
< 0.1%
20240207 6
0.1%
20240131 4
 
< 0.1%
20240129 1
 
< 0.1%
20240126 1
 
< 0.1%
20240123 2
 
< 0.1%
20240119 1
 
< 0.1%
20240105 2
 
< 0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
처분확정
8659 

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 8659
100.0%

Length

2024-05-11T03:21:43.218472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:21:43.477655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 8659
100.0%
Distinct989
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2024-05-11T03:21:44.019925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length55
Mean length8.7105901
Min length2

Characters and Unicode

Total characters75425
Distinct characters268
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique588 ?
Unique (%)6.8%

Sample

1st row영업정지
2nd row영업정지
3rd row영업소폐쇄
4th row영업소폐쇄
5th row시정명령
ValueCountFrequency (%)
과태료부과 1906
 
15.3%
영업소폐쇄 1484
 
11.9%
영업정지 1092
 
8.8%
시정명령 943
 
7.6%
20만원 437
 
3.5%
영업소폐쇄(직권말소 407
 
3.3%
시설개수명령 296
 
2.4%
직권말소 280
 
2.2%
과징금부과 250
 
2.0%
237
 
1.9%
Other values (1009) 5138
41.2%
2024-05-11T03:21:45.161936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6402
 
8.5%
3940
 
5.2%
0 3921
 
5.2%
3908
 
5.2%
3827
 
5.1%
3152
 
4.2%
2922
 
3.9%
2784
 
3.7%
2669
 
3.5%
2655
 
3.5%
Other values (258) 39245
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54457
72.2%
Decimal Number 12157
 
16.1%
Space Separator 3827
 
5.1%
Other Punctuation 1720
 
2.3%
Open Punctuation 1450
 
1.9%
Close Punctuation 1449
 
1.9%
Math Symbol 224
 
0.3%
Dash Punctuation 132
 
0.2%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (228) 20866
38.3%
Decimal Number
ValueCountFrequency (%)
0 3921
32.3%
2 2632
21.7%
1 2033
16.7%
3 850
 
7.0%
5 739
 
6.1%
4 704
 
5.8%
6 526
 
4.3%
7 295
 
2.4%
8 283
 
2.3%
9 174
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 1453
84.5%
, 137
 
8.0%
% 82
 
4.8%
: 27
 
1.6%
14
 
0.8%
/ 4
 
0.2%
* 2
 
0.1%
? 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
c 4
44.4%
t 2
22.2%
v 2
22.2%
k 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 1442
99.4%
[ 8
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 1441
99.4%
] 8
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 222
99.1%
= 2
 
0.9%
Space Separator
ValueCountFrequency (%)
3827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54457
72.2%
Common 20959
 
27.8%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (228) 20866
38.3%
Common
ValueCountFrequency (%)
0 3921
18.7%
3827
18.3%
2 2632
12.6%
1 2033
9.7%
. 1453
 
6.9%
( 1442
 
6.9%
) 1441
 
6.9%
3 850
 
4.1%
5 739
 
3.5%
4 704
 
3.4%
Other values (16) 1917
9.1%
Latin
ValueCountFrequency (%)
c 4
44.4%
t 2
22.2%
v 2
22.2%
k 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54413
72.1%
ASCII 20954
 
27.8%
Compat Jamo 44
 
0.1%
Punctuation 14
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (226) 20822
38.3%
ASCII
ValueCountFrequency (%)
0 3921
18.7%
3827
18.3%
2 2632
12.6%
1 2033
9.7%
. 1453
 
6.9%
( 1442
 
6.9%
) 1441
 
6.9%
3 850
 
4.1%
5 739
 
3.5%
4 704
 
3.4%
Other values (19) 1912
9.1%
Compat Jamo
ValueCountFrequency (%)
43
97.7%
1
 
2.3%
Punctuation
ValueCountFrequency (%)
14
100.0%
Distinct672
Distinct (%)7.8%
Missing4
Missing (%)< 0.1%
Memory size67.8 KiB
2024-05-11T03:21:45.857920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length11.886655
Min length2

Characters and Unicode

Total characters102879
Distinct characters131
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique331 ?
Unique (%)3.8%

Sample

1st row법 제71조 및 법 제75조
2nd row법 제71조 및 법 제75조
3rd row법 제71조, 법 제74조, 법 제75조 및 법 제76조
4th row법 제71조, 법 제74조, 법 제75조 및 법 제76조
5th row법 제71조, 법 제72조 및 법 제75조
ValueCountFrequency (%)
4805
22.7%
식품위생법 2534
 
12.0%
제75조 1293
 
6.1%
1217
 
5.8%
제37조 903
 
4.3%
제71조 841
 
4.0%
7항 821
 
3.9%
제101조제2항제1호 534
 
2.5%
제74조 510
 
2.4%
제44조 343
 
1.6%
Other values (521) 7343
34.7%
2024-05-11T03:21:47.168144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12524
12.2%
12505
12.2%
10312
10.0%
10259
10.0%
1 6083
 
5.9%
7 5543
 
5.4%
5515
 
5.4%
5184
 
5.0%
4880
 
4.7%
4856
 
4.7%
Other values (121) 25218
24.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63846
62.1%
Decimal Number 25229
 
24.5%
Space Separator 12505
 
12.2%
Other Punctuation 1092
 
1.1%
Open Punctuation 102
 
0.1%
Close Punctuation 100
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12524
19.6%
10312
16.2%
10259
16.1%
5515
8.6%
5184
8.1%
4880
 
7.6%
4856
 
7.6%
2747
 
4.3%
1260
 
2.0%
1160
 
1.8%
Other values (100) 5149
8.1%
Decimal Number
ValueCountFrequency (%)
1 6083
24.1%
7 5543
22.0%
2 2629
10.4%
4 2571
10.2%
3 2563
10.2%
5 2178
 
8.6%
0 1409
 
5.6%
6 1206
 
4.8%
8 757
 
3.0%
9 290
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 1079
98.8%
. 12
 
1.1%
: 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 95
95.0%
] 4
 
4.0%
1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 94
92.2%
[ 7
 
6.9%
1
 
1.0%
Space Separator
ValueCountFrequency (%)
12505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63846
62.1%
Common 39033
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12524
19.6%
10312
16.2%
10259
16.1%
5515
8.6%
5184
8.1%
4880
 
7.6%
4856
 
7.6%
2747
 
4.3%
1260
 
2.0%
1160
 
1.8%
Other values (100) 5149
8.1%
Common
ValueCountFrequency (%)
12505
32.0%
1 6083
15.6%
7 5543
14.2%
2 2629
 
6.7%
4 2571
 
6.6%
3 2563
 
6.6%
5 2178
 
5.6%
0 1409
 
3.6%
6 1206
 
3.1%
, 1079
 
2.8%
Other values (11) 1267
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63844
62.1%
ASCII 39031
37.9%
Compat Jamo 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12524
19.6%
10312
16.2%
10259
16.1%
5515
8.6%
5184
8.1%
4880
 
7.6%
4856
 
7.6%
2747
 
4.3%
1260
 
2.0%
1160
 
1.8%
Other values (98) 5147
8.1%
ASCII
ValueCountFrequency (%)
12505
32.0%
1 6083
15.6%
7 5543
14.2%
2 2629
 
6.7%
4 2571
 
6.6%
3 2563
 
6.6%
5 2178
 
5.6%
0 1409
 
3.6%
6 1206
 
3.1%
, 1079
 
2.8%
Other values (9) 1265
 
3.2%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2968
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122827
Minimum19900709
Maximum20240311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-05-11T03:21:47.635426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19900709
5-th percentile20030107
Q120071011
median20120425
Q320180209
95-th percentile20211124
Maximum20240311
Range339602
Interquartile range (IQR)109198

Descriptive statistics

Standard deviation61379.879
Coefficient of variation (CV)0.0030502612
Kurtosis-1.0910539
Mean20122827
Median Absolute Deviation (MAD)50308
Skewness0.014957149
Sum1.7424356 × 1011
Variance3.7674895 × 109
MonotonicityNot monotonic
2024-05-11T03:21:48.162090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20210401 170
 
2.0%
20050124 156
 
1.8%
20171121 111
 
1.3%
20171017 82
 
0.9%
20210415 69
 
0.8%
20211124 64
 
0.7%
20200227 50
 
0.6%
20150728 49
 
0.6%
20181207 46
 
0.5%
20181206 46
 
0.5%
Other values (2958) 7816
90.3%
ValueCountFrequency (%)
19900709 1
 
< 0.1%
19900831 1
 
< 0.1%
19930630 1
 
< 0.1%
19950603 1
 
< 0.1%
19961228 1
 
< 0.1%
19961231 1
 
< 0.1%
19980629 1
 
< 0.1%
19980630 1
 
< 0.1%
19981231 3
< 0.1%
20000410 1
 
< 0.1%
ValueCountFrequency (%)
20240311 8
0.1%
20240301 2
 
< 0.1%
20240228 2
 
< 0.1%
20240207 3
 
< 0.1%
20240206 6
0.1%
20240131 1
 
< 0.1%
20240130 4
< 0.1%
20240123 3
 
< 0.1%
20240119 1
 
< 0.1%
20240118 1
 
< 0.1%

위반내용
Text

MISSING 

Distinct3635
Distinct (%)42.8%
Missing161
Missing (%)1.9%
Memory size67.8 KiB
2024-05-11T03:21:48.899237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length329
Median length185
Mean length22.144152
Min length1

Characters and Unicode

Total characters188181
Distinct characters734
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2615 ?
Unique (%)30.8%

Sample

1st row2023.8.12. 22:52경 아마죤 단란주점의 업주 정00는 유흥주점 영업허가를 받지 않은 채 위 단란주점에서 여성 접객원 이00, 김00으로 하여금 성명을 알수 없는 남성 손님이 술을 마시는 자리에 합석하여 함께 술을 마시는 등의 접객 행위를 하도록 함으로써 식품접객업자 준수사항을 위반함
2nd row2023.10.28. 18:00~21:45경 영업자가 고용한 피의자 김00를 손님들과 유흥접객행위하도록 하여 영업자 준수사항을 위반함
3rd row영업시설물 멸실
4th row영업시설물 멸실
5th row조리된 식품에서 이물이 혼입된 사실을 확인함(돌솥뚝배기 파편)
ValueCountFrequency (%)
미필 762
 
2.1%
건강진단 623
 
1.8%
멸실 531
 
1.5%
위생교육 498
 
1.4%
496
 
1.4%
사업자등록 440
 
1.2%
영업주 438
 
1.2%
영업시설물 412
 
1.2%
직권말소 402
 
1.1%
폐업 378
 
1.1%
Other values (6365) 30540
86.0%
2024-05-11T03:21:50.102121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27961
 
14.9%
0 7613
 
4.0%
6880
 
3.7%
. 6649
 
3.5%
2 6518
 
3.5%
1 6314
 
3.4%
3591
 
1.9%
2910
 
1.5%
( 2883
 
1.5%
) 2876
 
1.5%
Other values (724) 113986
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114681
60.9%
Decimal Number 28493
 
15.1%
Space Separator 27964
 
14.9%
Other Punctuation 9634
 
5.1%
Open Punctuation 2908
 
1.5%
Close Punctuation 2901
 
1.5%
Dash Punctuation 645
 
0.3%
Lowercase Letter 432
 
0.2%
Uppercase Letter 264
 
0.1%
Control 98
 
0.1%
Other values (4) 161
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6880
 
6.0%
3591
 
3.1%
2910
 
2.5%
2374
 
2.1%
2131
 
1.9%
2091
 
1.8%
2056
 
1.8%
1962
 
1.7%
1886
 
1.6%
1862
 
1.6%
Other values (628) 86938
75.8%
Uppercase Letter
ValueCountFrequency (%)
U 42
15.9%
C 38
14.4%
F 35
13.3%
L 32
12.1%
T 18
 
6.8%
N 13
 
4.9%
O 10
 
3.8%
D 9
 
3.4%
S 8
 
3.0%
M 8
 
3.0%
Other values (14) 51
19.3%
Lowercase Letter
ValueCountFrequency (%)
m 61
14.1%
g 50
11.6%
a 46
10.6%
e 42
9.7%
l 35
8.1%
c 34
7.9%
o 30
 
6.9%
k 18
 
4.2%
w 17
 
3.9%
t 15
 
3.5%
Other values (13) 84
19.4%
Decimal Number
ValueCountFrequency (%)
0 7613
26.7%
2 6518
22.9%
1 6314
22.2%
3 1629
 
5.7%
9 1301
 
4.6%
6 1150
 
4.0%
7 1035
 
3.6%
4 1023
 
3.6%
5 984
 
3.5%
8 926
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 6649
69.0%
: 1123
 
11.7%
/ 773
 
8.0%
, 723
 
7.5%
* 224
 
2.3%
' 52
 
0.5%
? 39
 
0.4%
% 26
 
0.3%
; 24
 
0.2%
1
 
< 0.1%
Other Number
ValueCountFrequency (%)
² 13
41.9%
3
 
9.7%
3
 
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
Other Symbol
ValueCountFrequency (%)
60
75.0%
10
 
12.5%
8
 
10.0%
1
 
1.2%
1
 
1.2%
Math Symbol
ValueCountFrequency (%)
~ 34
85.0%
= 3
 
7.5%
+ 2
 
5.0%
1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 2883
99.1%
[ 20
 
0.7%
5
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 2876
99.1%
] 20
 
0.7%
5
 
0.2%
Space Separator
ValueCountFrequency (%)
27961
> 99.9%
  3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 645
100.0%
Control
ValueCountFrequency (%)
98
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114681
60.9%
Common 72804
38.7%
Latin 696
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6880
 
6.0%
3591
 
3.1%
2910
 
2.5%
2374
 
2.1%
2131
 
1.9%
2091
 
1.8%
2056
 
1.8%
1962
 
1.7%
1886
 
1.6%
1862
 
1.6%
Other values (628) 86938
75.8%
Common
ValueCountFrequency (%)
27961
38.4%
0 7613
 
10.5%
. 6649
 
9.1%
2 6518
 
9.0%
1 6314
 
8.7%
( 2883
 
4.0%
) 2876
 
4.0%
3 1629
 
2.2%
9 1301
 
1.8%
6 1150
 
1.6%
Other values (39) 7910
 
10.9%
Latin
ValueCountFrequency (%)
m 61
 
8.8%
g 50
 
7.2%
a 46
 
6.6%
U 42
 
6.0%
e 42
 
6.0%
C 38
 
5.5%
F 35
 
5.0%
l 35
 
5.0%
c 34
 
4.9%
L 32
 
4.6%
Other values (37) 281
40.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114661
60.9%
ASCII 73371
39.0%
CJK Compat 70
 
< 0.1%
None 29
 
< 0.1%
Compat Jamo 20
 
< 0.1%
Enclosed Alphanum 18
 
< 0.1%
Geometric Shapes 9
 
< 0.1%
Punctuation 1
 
< 0.1%
Arrows 1
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27961
38.1%
0 7613
 
10.4%
. 6649
 
9.1%
2 6518
 
8.9%
1 6314
 
8.6%
( 2883
 
3.9%
) 2876
 
3.9%
3 1629
 
2.2%
9 1301
 
1.8%
6 1150
 
1.6%
Other values (66) 8477
 
11.6%
Hangul
ValueCountFrequency (%)
6880
 
6.0%
3591
 
3.1%
2910
 
2.5%
2374
 
2.1%
2131
 
1.9%
2091
 
1.8%
2056
 
1.8%
1962
 
1.7%
1886
 
1.6%
1862
 
1.6%
Other values (623) 86918
75.8%
CJK Compat
ValueCountFrequency (%)
60
85.7%
10
 
14.3%
Compat Jamo
ValueCountFrequency (%)
15
75.0%
2
 
10.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
None
ValueCountFrequency (%)
² 13
44.8%
5
 
17.2%
5
 
17.2%
  3
 
10.3%
Ø 3
 
10.3%
Geometric Shapes
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
Enclosed Alphanum
ValueCountFrequency (%)
3
16.7%
3
16.7%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
2
11.1%
Punctuation
ValueCountFrequency (%)
1
100.0%
Arrows
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Distinct989
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size67.8 KiB
2024-05-11T03:21:50.772975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length55
Mean length8.7105901
Min length2

Characters and Unicode

Total characters75425
Distinct characters268
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique588 ?
Unique (%)6.8%

Sample

1st row영업정지
2nd row영업정지
3rd row영업소폐쇄
4th row영업소폐쇄
5th row시정명령
ValueCountFrequency (%)
과태료부과 1906
 
15.3%
영업소폐쇄 1484
 
11.9%
영업정지 1092
 
8.8%
시정명령 943
 
7.6%
20만원 437
 
3.5%
영업소폐쇄(직권말소 407
 
3.3%
시설개수명령 296
 
2.4%
직권말소 280
 
2.2%
과징금부과 250
 
2.0%
237
 
1.9%
Other values (1009) 5138
41.2%
2024-05-11T03:21:52.278013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6402
 
8.5%
3940
 
5.2%
0 3921
 
5.2%
3908
 
5.2%
3827
 
5.1%
3152
 
4.2%
2922
 
3.9%
2784
 
3.7%
2669
 
3.5%
2655
 
3.5%
Other values (258) 39245
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54457
72.2%
Decimal Number 12157
 
16.1%
Space Separator 3827
 
5.1%
Other Punctuation 1720
 
2.3%
Open Punctuation 1450
 
1.9%
Close Punctuation 1449
 
1.9%
Math Symbol 224
 
0.3%
Dash Punctuation 132
 
0.2%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (228) 20866
38.3%
Decimal Number
ValueCountFrequency (%)
0 3921
32.3%
2 2632
21.7%
1 2033
16.7%
3 850
 
7.0%
5 739
 
6.1%
4 704
 
5.8%
6 526
 
4.3%
7 295
 
2.4%
8 283
 
2.3%
9 174
 
1.4%
Other Punctuation
ValueCountFrequency (%)
. 1453
84.5%
, 137
 
8.0%
% 82
 
4.8%
: 27
 
1.6%
14
 
0.8%
/ 4
 
0.2%
* 2
 
0.1%
? 1
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
c 4
44.4%
t 2
22.2%
v 2
22.2%
k 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 1442
99.4%
[ 8
 
0.6%
Close Punctuation
ValueCountFrequency (%)
) 1441
99.4%
] 8
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 222
99.1%
= 2
 
0.9%
Space Separator
ValueCountFrequency (%)
3827
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54457
72.2%
Common 20959
 
27.8%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (228) 20866
38.3%
Common
ValueCountFrequency (%)
0 3921
18.7%
3827
18.3%
2 2632
12.6%
1 2033
9.7%
. 1453
 
6.9%
( 1442
 
6.9%
) 1441
 
6.9%
3 850
 
4.1%
5 739
 
3.5%
4 704
 
3.4%
Other values (16) 1917
9.1%
Latin
ValueCountFrequency (%)
c 4
44.4%
t 2
22.2%
v 2
22.2%
k 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54413
72.1%
ASCII 20954
 
27.8%
Compat Jamo 44
 
0.1%
Punctuation 14
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6402
 
11.8%
3940
 
7.2%
3908
 
7.2%
3152
 
5.8%
2922
 
5.4%
2784
 
5.1%
2669
 
4.9%
2655
 
4.9%
2606
 
4.8%
2553
 
4.7%
Other values (226) 20822
38.3%
ASCII
ValueCountFrequency (%)
0 3921
18.7%
3827
18.3%
2 2632
12.6%
1 2033
9.7%
. 1453
 
6.9%
( 1442
 
6.9%
) 1441
 
6.9%
3 850
 
4.1%
5 739
 
3.5%
4 704
 
3.4%
Other values (19) 1912
9.1%
Compat Jamo
ValueCountFrequency (%)
43
97.7%
1
 
2.3%
Punctuation
ValueCountFrequency (%)
14
100.0%

행정처분취소일자
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct49
Distinct (%)63.6%
Missing8582
Missing (%)99.1%
Infinite0
Infinite (%)0.0%
Mean20122814
Minimum20020603
Maximum20231228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-05-11T03:21:52.883281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020603
5-th percentile20071103
Q120080828
median20110704
Q320150722
95-th percentile20222200
Maximum20231228
Range210625
Interquartile range (IQR)69894

Descriptive statistics

Standard deviation49801.683
Coefficient of variation (CV)0.0024748867
Kurtosis-0.17672565
Mean20122814
Median Absolute Deviation (MAD)30013
Skewness0.42874114
Sum1.5494566 × 109
Variance2.4802076 × 109
MonotonicityNot monotonic
2024-05-11T03:21:53.545806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
20080828 10
 
0.1%
20110704 6
 
0.1%
20141203 4
 
< 0.1%
20080701 3
 
< 0.1%
20080401 2
 
< 0.1%
20230526 2
 
< 0.1%
20121105 2
 
< 0.1%
20130411 2
 
< 0.1%
20140117 2
 
< 0.1%
20150722 2
 
< 0.1%
Other values (39) 42
 
0.5%
(Missing) 8582
99.1%
ValueCountFrequency (%)
20020603 1
< 0.1%
20021202 2
< 0.1%
20071005 1
< 0.1%
20071127 1
< 0.1%
20071128 1
< 0.1%
20071211 1
< 0.1%
20071220 1
< 0.1%
20080401 2
< 0.1%
20080425 1
< 0.1%
20080603 1
< 0.1%
ValueCountFrequency (%)
20231228 1
< 0.1%
20230526 2
< 0.1%
20230524 1
< 0.1%
20220119 1
< 0.1%
20210616 1
< 0.1%
20210115 1
< 0.1%
20200820 1
< 0.1%
20181218 2
< 0.1%
20180326 1
< 0.1%
20171212 2
< 0.1%

영업장면적(㎡)
Real number (ℝ)

MISSING 

Distinct1947
Distinct (%)43.6%
Missing4191
Missing (%)48.4%
Infinite0
Infinite (%)0.0%
Mean118.50493
Minimum0
Maximum3606.89
Zeros43
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size76.2 KiB
2024-05-11T03:21:54.148877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.207
Q133.2875
median63.98
Q3106.17
95-th percentile383.5005
Maximum3606.89
Range3606.89
Interquartile range (IQR)72.8825

Descriptive statistics

Standard deviation239.4919
Coefficient of variation (CV)2.0209447
Kurtosis84.486127
Mean118.50493
Median Absolute Deviation (MAD)33.595
Skewness7.8420065
Sum529480.02
Variance57356.372
MonotonicityNot monotonic
2024-05-11T03:21:55.156597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 46
 
0.5%
33.0 44
 
0.5%
0.0 43
 
0.5%
66.0 36
 
0.4%
23.1 35
 
0.4%
29.7 33
 
0.4%
97.24 32
 
0.4%
49.5 24
 
0.3%
42.9 24
 
0.3%
16.5 24
 
0.3%
Other values (1937) 4127
47.7%
(Missing) 4191
48.4%
ValueCountFrequency (%)
0.0 43
0.5%
1.3 2
 
< 0.1%
2.0 1
 
< 0.1%
2.52 1
 
< 0.1%
2.84 1
 
< 0.1%
3.0 1
 
< 0.1%
3.43 1
 
< 0.1%
3.5 1
 
< 0.1%
4.95 5
 
0.1%
5.0 4
 
< 0.1%
ValueCountFrequency (%)
3606.89 6
0.1%
2457.59 5
0.1%
2412.3 2
 
< 0.1%
2114.32 3
< 0.1%
1991.0 1
 
< 0.1%
1952.87 1
 
< 0.1%
1810.75 1
 
< 0.1%
1712.41 1
 
< 0.1%
1650.0 1
 
< 0.1%
1643.27 1
 
< 0.1%

Interactions

2024-05-11T03:21:26.756221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:19.737041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:21.289104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:23.194519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:25.079904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:27.049424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:20.052854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:21.657644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:23.595846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:25.431690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:27.331771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:20.399681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:22.030954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:24.004840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:25.762942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:27.628847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:20.725008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:22.557467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:24.381206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:26.140268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:27.872895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:20.949892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:22.882913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:24.622897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:21:26.430243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T03:21:55.578320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자행정처분취소일자영업장면적(㎡)
처분일자1.0000.4640.5500.9780.9130.9490.087
업종명0.4641.0000.9980.4650.4530.7590.612
업태명0.5500.9981.0000.5490.5370.8380.757
지도점검일자0.9780.4650.5491.0000.9690.9350.087
위반일자0.9130.4530.5370.9691.0000.9770.054
행정처분취소일자0.9490.7590.8380.9350.9771.0000.146
영업장면적(㎡)0.0870.6120.7570.0870.0540.1461.000
2024-05-11T03:21:56.009893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자행정처분취소일자영업장면적(㎡)업종명
처분일자1.0000.9990.9710.998-0.0350.177
지도점검일자0.9991.0000.9710.990-0.0360.180
위반일자0.9710.9711.0000.990-0.0180.174
행정처분취소일자0.9980.9900.9901.000-0.2700.419
영업장면적(㎡)-0.035-0.036-0.018-0.2701.0000.288
업종명0.1770.1800.1740.4190.2881.000

Missing values

2024-05-11T03:21:28.352634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T03:21:29.075156image/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.
2024-05-11T03:21:29.562591image/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

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용행정처분취소일자영업장면적(㎡)
031200002024050819930067004단란주점단란주점아마죤서울특별시 서대문구 신촌로 283, (북아현동)서울특별시 서대문구 북아현동 126번지 44호20231128처분확정영업정지법 제71조 및 법 제75조202308122023.8.12. 22:52경 아마죤 단란주점의 업주 정00는 유흥주점 영업허가를 받지 않은 채 위 단란주점에서 여성 접객원 이00, 김00으로 하여금 성명을 알수 없는 남성 손님이 술을 마시는 자리에 합석하여 함께 술을 마시는 등의 접객 행위를 하도록 함으로써 식품접객업자 준수사항을 위반함영업정지<NA><NA>
131200002024042619930066783단란주점단란주점황금매들리서울특별시 서대문구 응암로 78, (북가좌동,,15,16)서울특별시 서대문구 북가좌동 300번지 14호 ,15,1620240129처분확정영업정지법 제71조 및 법 제75조202310282023.10.28. 18:00~21:45경 영업자가 고용한 피의자 김00를 손님들과 유흥접객행위하도록 하여 영업자 준수사항을 위반함영업정지<NA><NA>
231200002024040520050066395일반음식점기타선인장서울특별시 서대문구 수색로4가길 14-7, (남가좌동,1층)서울특별시 서대문구 남가좌동 295번지 13호 1층20240207처분확정영업소폐쇄법 제71조, 법 제74조, 법 제75조 및 법 제76조20240206영업시설물 멸실영업소폐쇄<NA>13.2
331200002024040520000066100일반음식점호프/통닭비어시티서울특별시 서대문구 증가로 116, (남가좌동)서울특별시 서대문구 남가좌동 339번지 34호20240207처분확정영업소폐쇄법 제71조, 법 제74조, 법 제75조 및 법 제76조20240206영업시설물 멸실영업소폐쇄<NA><NA>
431200002024040320090039341일반음식점일식고기사랑서울특별시 서대문구 충정로4길 26, 1~2층 (충정로3가)서울특별시 서대문구 충정로3가 345번지 1,2층 전체20240228처분확정시정명령법 제71조, 법 제72조 및 법 제75조20240228조리된 식품에서 이물이 혼입된 사실을 확인함(돌솥뚝배기 파편)시정명령<NA><NA>
531200002024040320090039341일반음식점일식고기사랑서울특별시 서대문구 충정로4길 26, 1~2층 (충정로3가)서울특별시 서대문구 충정로3가 345번지 1,2층 전체20240228처분확정시정명령법 제71조, 법 제72조 및 법 제75조20240228조리된 식품에서 이물이 혼입된 사실을 확인함(돌솥뚝배기 파편)시정명령<NA>96.0
631200002024040120210067221즉석판매제조가공업즉석판매제조가공업싱싱회포장센터서울특별시 서대문구 수색로2길 14, 1층 (남가좌동)서울특별시 서대문구 남가좌동 102번지 19호20240311처분확정직권말소법 제37조 7항20240311사업자등록 폐업 직권말소직권말소<NA><NA>
731200002024040120220080211즉석판매제조가공업즉석판매제조가공업소문난 대박간장게장서울특별시 서대문구 연희로39길 41-16, 103호 (홍은동, 힐튼타운)서울특별시 서대문구 홍은동 265번지 90호 힐튼타운-10320240311처분확정직권말소법 제37조 7항20240311사업자등록 폐업 직권말소직권말소<NA><NA>
831200002024040120200066672즉석판매제조가공업즉석판매제조가공업이화김치서울특별시 서대문구 거북골로 211, 1층 3호 (북가좌동)서울특별시 서대문구 북가좌동 366번지 18호20240311처분확정직권말소법 제37조 7항20240311사업자등록 폐업 직권말소직권말소<NA><NA>
931200002024040120180066990유통전문판매업유통전문판매업리퓨어생명과학주식회사서울특별시 서대문구 연세로 50, 연세대학교 공학원 지하1층 B187L호 (신촌동)서울특별시 서대문구 신촌동 134번지 연세대학교 공학원-B187L20240311처분확정직권말소법 제37조 7항20240311사업자등록 폐업 직권말소직권말소<NA><NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용행정처분취소일자영업장면적(㎡)
864931200002001100619990066991일반음식점정종/대포집/소주방제우스<NA>서울특별시 서대문구 창천동 52번지 72호20010902처분확정영업정지2월(2001.10.8-2001.12.7)식품위생법제58조20011109청소년주류제공영업정지2월(2001.10.8-2001.12.7)<NA>122.98
865031200002001092920000066347일반음식점분식큐치킨센타<NA>서울특별시 서대문구 연희동 188번지 57호20010420처분확정영업정지1월식품위생법제58조20011109청소년주류제공영업정지1월<NA><NA>
865131200002001092519840066056일반음식점경양식파트너<NA>서울특별시 서대문구 남가좌동 260번지 173호20010925처분확정영업정지3월(2001.10.5-2002.1.4)식품위생법제58조20010925유흥접객행위영업정지3월(2001.10.5-2002.1.4)<NA>18.15
865231200002001091820010066168일반음식점한식리버풀<NA>서울특별시 서대문구 창천동 53번지 6호 53 -620010809처분확정과태료50만원식품위생법제78조20010809건강진단미필과태료50만원<NA><NA>
865331200002001091820010066090일반음식점정종/대포집/소주방마포24시껍데기집<NA>서울특별시 서대문구 창천동 49번지 5호20010918처분확정영업장폐쇄식품위생법제62조20010918영업정지중영업영업장폐쇄<NA><NA>
865431200002001091704100430100041이용업일반이용업상록<NA>서울특별시 서대문구 충정로3가 95번지 1호20010817처분확정영업정지2월 및 업무정지2월공중위생관리법제11조20010817음란행위(1차)영업정지2월 및 업무정지2월<NA>30.2
865531200002001081719990067203일반음식점정종/대포집/소주방해피데이<NA>서울특별시 서대문구 창천동 33번지 55호20010612처분확정영업소폐쇄식품위생법제62조20011110청소년주류제공3차영업소폐쇄<NA>85.85
865631200002001072019860066243일반음식점한식너스레<NA>서울특별시 서대문구 대현동 101번지 4호20010610처분확정업종미표시식품위생법제55조20020124업종미표시업종미표시<NA>54.57
865731200002001072020010066364일반음식점한식비바체<NA>서울특별시 서대문구 북아현동 142번지 2호20010608처분확정시설개수명령식품위생법제57조20010608비상유동등미설치시설개수명령<NA><NA>
865831200001998071319890066075식품제조가공업식품제조가공업엄마손도시락<NA>서울특별시 서대문구 홍제동 157번지 73호19980713처분확정영업소폐쇄식품위생법19980629시설물멸실영업소폐쇄<NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용행정처분취소일자영업장면적(㎡)# duplicates
1631200002004051720010066691식품제조가공업식품제조가공업용인김밥<NA>서울특별시 서대문구 현저동 885번지 ,(104-5)20040419처분확정시정명령식위20030501<NA>시정명령<NA><NA>4
4931200002006112420050066027일반음식점한식옥돌구이<NA>서울특별시 서대문구 남가좌동 258번지 67호20061102처분확정과징금56만원(영업정지7일)식품위생법 제21조20061102영업장 무단확장과징금56만원(영업정지7일)<NA>24.04
5031200002006112420050066027일반음식점한식옥돌구이<NA>서울특별시 서대문구 남가좌동 258번지 67호20061102처분확정과징금56만원(영업정지7일)식품위생법 제21조20061124영업장 무단확장과징금56만원(영업정지7일)<NA>24.04
7131200002007072019940066078일반음식점한식꼴통<NA>서울특별시 서대문구 남가좌동 324번지 10호20070702처분확정영업정지 2월식품위생법제31조20070702청소년주류제공영업정지 2월<NA><NA>4
7631200002007083119940066078일반음식점한식꼴통<NA>서울특별시 서대문구 남가좌동 324번지 10호20070702처분확정과징금부과식품위생법제31조20070702청소년주류제공과징금부과<NA><NA>4
7831200002007083119940066078일반음식점한식꼴통<NA>서울특별시 서대문구 남가좌동 324번지 10호20070702처분확정영업정지 1개월식품위생법제31조20070702청소년주류제공영업정지 1개월<NA><NA>4
12431200002011051720070066172식품등 수입판매업식품등 수입판매업주식회사 케이쿼크<NA>서울특별시 서대문구 연희동 334번지 29호 (2층)20110310처분확정영업소폐쇄식품위생법 74조20110310영업시설물 전부를 철거영업소폐쇄<NA><NA>4
14731200002012111420050066484건강기능식품수입업건강기능식품수입업목민ASSOCIATION<NA>서울특별시 서대문구 충정로2가 191번지 골든타워-131420121030처분확정영업소폐쇄건강기능식품에관한법률제32조제1항9호20121030정당한 사유없이 계속하여 6월이상 휴업영업소폐쇄<NA><NA>4
16931200002015060819990067046일반음식점한식봉구비어(신촌명물거리점) 2호점서울특별시 서대문구 명물길 41, (창천동)서울특별시 서대문구 창천동 2번지 33호20150518처분확정시정명령식품위생법제71조20150518영업장외 영업시정명령<NA>63.04
19831200002020012219990067046일반음식점한식봉구비어(신촌명물거리점) 2호점서울특별시 서대문구 명물길 41, (창천동)서울특별시 서대문구 창천동 2번지 33호20191128처분확정영업정지법 제71조 및 법 제75조201911282019.11.28. 합동점검 시 마요네즈 유통기한 경과제품 보관영업정지<NA>63.04