Overview

Dataset statistics

Number of variables17
Number of observations634
Missing cells747
Missing cells (%)6.9%
Duplicate rows28
Duplicate rows (%)4.4%
Total size in memory88.0 KiB
Average record size in memory142.2 B

Variable types

Categorical4
Numeric5
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-9835/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 28 (4.4%) 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
처분기간 is highly overall correlated with 영업장면적(㎡) and 1 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 처분기간High correlation
업종명 is highly overall correlated with 업태명High correlation
업태명 is highly overall correlated with 처분기간 and 1 other fieldsHigh correlation
소재지도로명 has 57 (9.0%) missing valuesMissing
소재지지번 has 13 (2.1%) missing valuesMissing
처분기간 has 612 (96.5%) missing valuesMissing
영업장면적(㎡) has 65 (10.3%) missing valuesMissing
영업장면적(㎡) has 7 (1.1%) zerosZeros

Reproduction

Analysis started2024-05-10 22:58:50.555941
Analysis finished2024-05-10 22:59:01.262557
Duration10.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
3000000
634 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 634
100.0%

Length

2024-05-10T22:59:01.443248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:59:01.675844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 634
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct228
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137338
Minimum20020125
Maximum20240401
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-10T22:59:01.883556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020125
5-th percentile20071228
Q120110329
median20130102
Q320170512
95-th percentile20217945
Maximum20240401
Range220276
Interquartile range (IQR)60183

Descriptive statistics

Standard deviation43620.403
Coefficient of variation (CV)0.0021661454
Kurtosis-0.56524049
Mean20137338
Median Absolute Deviation (MAD)29773
Skewness0.29408984
Sum1.2767072 × 1010
Variance1.9027396 × 109
MonotonicityDecreasing
2024-05-10T22:59:02.321841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150909 40
 
6.3%
20110707 32
 
5.0%
20071228 30
 
4.7%
20180424 24
 
3.8%
20230705 23
 
3.6%
20120628 20
 
3.2%
20121217 14
 
2.2%
20200911 12
 
1.9%
20100527 12
 
1.9%
20140624 11
 
1.7%
Other values (218) 416
65.6%
ValueCountFrequency (%)
20020125 1
 
0.2%
20030218 1
 
0.2%
20060303 1
 
0.2%
20060405 1
 
0.2%
20060807 1
 
0.2%
20060824 8
1.3%
20060830 2
 
0.3%
20070205 1
 
0.2%
20070402 1
 
0.2%
20070420 2
 
0.3%
ValueCountFrequency (%)
20240401 2
 
0.3%
20231025 2
 
0.3%
20230830 1
 
0.2%
20230726 1
 
0.2%
20230705 23
3.6%
20230703 1
 
0.2%
20230619 1
 
0.2%
20230420 1
 
0.2%
20211227 2
 
0.3%
20211206 3
 
0.5%

교부번호
Text

Distinct325
Distinct (%)51.3%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:02.816969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length4
Mean length4.2917981
Min length1

Characters and Unicode

Total characters2721
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)29.5%

Sample

1st row0138
2nd row0036
3rd row2015-00002
4th row0098
5th row432
ValueCountFrequency (%)
0262 10
 
1.6%
561 9
 
1.4%
52 8
 
1.3%
0015 8
 
1.3%
0171 7
 
1.1%
0097 7
 
1.1%
2009-00002 6
 
0.9%
515 6
 
0.9%
263 6
 
0.9%
516 6
 
0.9%
Other values (315) 561
88.5%
2024-05-10T22:59:03.539486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 967
35.5%
1 413
15.2%
2 326
 
12.0%
5 184
 
6.8%
3 174
 
6.4%
4 133
 
4.9%
6 124
 
4.6%
7 121
 
4.4%
8 110
 
4.0%
9 95
 
3.5%
Other values (3) 74
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2647
97.3%
Dash Punctuation 70
 
2.6%
Other Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 967
36.5%
1 413
15.6%
2 326
 
12.3%
5 184
 
7.0%
3 174
 
6.6%
4 133
 
5.0%
6 124
 
4.7%
7 121
 
4.6%
8 110
 
4.2%
9 95
 
3.6%
Other Letter
ValueCountFrequency (%)
제 2
50.0%
호 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2717
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 967
35.6%
1 413
15.2%
2 326
 
12.0%
5 184
 
6.8%
3 174
 
6.4%
4 133
 
4.9%
6 124
 
4.6%
7 121
 
4.5%
8 110
 
4.0%
9 95
 
3.5%
Hangul
ValueCountFrequency (%)
제 2
50.0%
호 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2717
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 967
35.6%
1 413
15.2%
2 326
 
12.0%
5 184
 
6.8%
3 174
 
6.4%
4 133
 
4.9%
6 124
 
4.6%
7 121
 
4.5%
8 110
 
4.0%
9 95
 
3.5%
Hangul
ValueCountFrequency (%)
제 2
50.0%
호 2
50.0%

업종명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
숙박업(일반)
202 
위생관리용역업
113 
이용업
84 
피부미용업
66 
목욕장업
52 
Other values (10)
117 

Length

Max length16
Median length7
Mean length5.5473186
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row숙박업(일반)
2nd row목욕장업
3rd row목욕장업
4th row숙박업(일반)
5th row일반미용업

Common Values

ValueCountFrequency (%)
숙박업(일반) 202
31.9%
위생관리용역업 113
17.8%
이용업 84
13.2%
피부미용업 66
 
10.4%
목욕장업 52
 
8.2%
미용업 39
 
6.2%
일반미용업 23
 
3.6%
세탁업 23
 
3.6%
네일미용업 11
 
1.7%
종합미용업 9
 
1.4%
Other values (5) 12
 
1.9%

Length

2024-05-10T22:59:03.804955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
숙박업(일반 202
31.4%
위생관리용역업 113
17.6%
이용업 84
13.1%
피부미용업 69
 
10.7%
목욕장업 52
 
8.1%
미용업 43
 
6.7%
일반미용업 26
 
4.0%
세탁업 23
 
3.6%
네일미용업 13
 
2.0%
종합미용업 9
 
1.4%
Other values (2) 9
 
1.4%

업태명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
여관업
155 
위생관리용역업
113 
일반이용업
84 
피부미용업
71 
일반미용업
62 
Other values (13)
149 

Length

Max length14
Median length7
Mean length4.9227129
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여관업
2nd row공동탕업
3rd row공동탕업
4th row여관업
5th row일반미용업

Common Values

ValueCountFrequency (%)
여관업 155
24.4%
위생관리용역업 113
17.8%
일반이용업 84
13.2%
피부미용업 71
11.2%
일반미용업 62
 
9.8%
공동탕업 31
 
4.9%
일반세탁업 23
 
3.6%
일반호텔 19
 
3.0%
여인숙업 14
 
2.2%
네일아트업 13
 
2.1%
Other values (8) 49
 
7.7%

Length

2024-05-10T22:59:04.049242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여관업 155
24.2%
위생관리용역업 113
17.6%
일반이용업 84
13.1%
피부미용업 71
11.1%
일반미용업 62
 
9.7%
공동탕업 31
 
4.8%
일반세탁업 23
 
3.6%
일반호텔 19
 
3.0%
여인숙업 14
 
2.2%
네일아트업 13
 
2.0%
Other values (8) 56
 
8.7%

업소명
Text

Distinct387
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:04.490336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length5.9069401
Min length1

Characters and Unicode

Total characters3745
Distinct characters403
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique273 ?
Unique (%)43.1%

Sample

1st row테크노모텔
2nd row문화탕
3rd row센츄럴관광호텔 사우나
4th row만남모텔
5th row준오헤어
ValueCountFrequency (%)
주식회사 23
 
2.8%
에스테틱 22
 
2.6%
린 9
 
1.1%
호텔 9
 
1.1%
21세기헤어클럽 8
 
1.0%
게스트하우스 7
 
0.8%
우성 6
 
0.7%
골근위뷰티 6
 
0.7%
명가 6
 
0.7%
약손차이 6
 
0.7%
Other values (447) 732
87.8%
2024-05-10T22:59:05.275170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
 
5.3%
스 172
 
4.6%
주 102
 
2.7%
이 94
 
2.5%
) 85
 
2.3%
( 85
 
2.3%
사 77
 
2.1%
텔 75
 
2.0%
에 66
 
1.8%
리 65
 
1.7%
Other values (393) 2724
72.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3117
83.2%
Space Separator 200
 
5.3%
Uppercase Letter 108
 
2.9%
Close Punctuation 85
 
2.3%
Open Punctuation 85
 
2.3%
Lowercase Letter 80
 
2.1%
Decimal Number 51
 
1.4%
Other Punctuation 18
 
0.5%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 172
 
5.5%
주 102
 
3.3%
이 94
 
3.0%
사 77
 
2.5%
텔 75
 
2.4%
에 66
 
2.1%
리 65
 
2.1%
우 61
 
2.0%
호 53
 
1.7%
대 51
 
1.6%
Other values (338) 2301
73.8%
Uppercase Letter
ValueCountFrequency (%)
N 11
 
10.2%
A 11
 
10.2%
E 9
 
8.3%
M 8
 
7.4%
V 8
 
7.4%
S 7
 
6.5%
F 6
 
5.6%
U 6
 
5.6%
H 6
 
5.6%
I 5
 
4.6%
Other values (12) 31
28.7%
Lowercase Letter
ValueCountFrequency (%)
o 10
12.5%
a 9
11.2%
i 8
10.0%
s 7
8.8%
e 7
8.8%
h 5
 
6.2%
u 5
 
6.2%
l 5
 
6.2%
t 5
 
6.2%
r 4
 
5.0%
Other values (7) 15
18.8%
Decimal Number
ValueCountFrequency (%)
2 15
29.4%
1 12
23.5%
4 9
17.6%
0 7
13.7%
5 5
 
9.8%
3 2
 
3.9%
9 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
？ 8
44.4%
. 5
27.8%
& 3
 
16.7%
; 1
 
5.6%
, 1
 
5.6%
Space Separator
ValueCountFrequency (%)
200
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3117
83.2%
Common 440
 
11.7%
Latin 188
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 172
 
5.5%
주 102
 
3.3%
이 94
 
3.0%
사 77
 
2.5%
텔 75
 
2.4%
에 66
 
2.1%
리 65
 
2.1%
우 61
 
2.0%
호 53
 
1.7%
대 51
 
1.6%
Other values (338) 2301
73.8%
Latin
ValueCountFrequency (%)
N 11
 
5.9%
A 11
 
5.9%
o 10
 
5.3%
E 9
 
4.8%
a 9
 
4.8%
M 8
 
4.3%
i 8
 
4.3%
V 8
 
4.3%
S 7
 
3.7%
s 7
 
3.7%
Other values (29) 100
53.2%
Common
ValueCountFrequency (%)
200
45.5%
) 85
19.3%
( 85
19.3%
2 15
 
3.4%
1 12
 
2.7%
4 9
 
2.0%
？ 8
 
1.8%
0 7
 
1.6%
5 5
 
1.1%
. 5
 
1.1%
Other values (6) 9
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3117
83.2%
ASCII 620
 
16.6%
None 8
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200
32.3%
) 85
13.7%
( 85
13.7%
2 15
 
2.4%
1 12
 
1.9%
N 11
 
1.8%
A 11
 
1.8%
o 10
 
1.6%
E 9
 
1.5%
4 9
 
1.5%
Other values (44) 173
27.9%
Hangul
ValueCountFrequency (%)
스 172
 
5.5%
주 102
 
3.3%
이 94
 
3.0%
사 77
 
2.5%
텔 75
 
2.4%
에 66
 
2.1%
리 65
 
2.1%
우 61
 
2.0%
호 53
 
1.7%
대 51
 
1.6%
Other values (338) 2301
73.8%
None
ValueCountFrequency (%)
？ 8
100.0%

소재지도로명
Text

MISSING 

Distinct346
Distinct (%)60.0%
Missing57
Missing (%)9.0%
Memory size5.1 KiB
2024-05-10T22:59:05.822516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length53
Mean length29.809359
Min length21

Characters and Unicode

Total characters17200
Distinct characters203
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)40.2%

Sample

1st row서울특별시 종로구 돈화문로5길 28-3, (낙원동)
2nd row서울특별시 종로구 돈화문로5길 28-5, (낙원동)
3rd row서울특별시 종로구 청계천로 137, 지하1층 (장사동)
4th row서울특별시 종로구 보문로1길 7-20, (숭인동)
5th row서울특별시 종로구 대학로 132, 3층 (동숭동, ABC마트빌딩)
ValueCountFrequency (%)
서울특별시 577
 
17.9%
종로구 577
 
17.9%
종로 60
 
1.9%
숭인동 59
 
1.8%
낙원동 35
 
1.1%
창신동 34
 
1.1%
자하문로 25
 
0.8%
무악동 23
 
0.7%
삼일대로 22
 
0.7%
지하1층 20
 
0.6%
Other values (589) 1795
55.6%
2024-05-10T22:59:06.873764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2651
 
15.4%
로 1143
 
6.6%
, 789
 
4.6%
종 773
 
4.5%
1 622
 
3.6%
서 592
 
3.4%
) 586
 
3.4%
( 586
 
3.4%
시 585
 
3.4%
구 585
 
3.4%
Other values (193) 8288
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9700
56.4%
Decimal Number 2679
 
15.6%
Space Separator 2651
 
15.4%
Other Punctuation 794
 
4.6%
Close Punctuation 586
 
3.4%
Open Punctuation 586
 
3.4%
Dash Punctuation 184
 
1.1%
Uppercase Letter 19
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1143
 
11.8%
종 773
 
8.0%
서 592
 
6.1%
시 585
 
6.0%
구 585
 
6.0%
울 578
 
6.0%
특 577
 
5.9%
별 577
 
5.9%
동 563
 
5.8%
길 347
 
3.6%
Other values (169) 3380
34.8%
Decimal Number
ValueCountFrequency (%)
1 622
23.2%
2 515
19.2%
3 347
13.0%
5 199
 
7.4%
4 196
 
7.3%
0 186
 
6.9%
6 172
 
6.4%
8 151
 
5.6%
7 150
 
5.6%
9 141
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 13
68.4%
D 2
 
10.5%
A 1
 
5.3%
C 1
 
5.3%
K 1
 
5.3%
S 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 789
99.4%
/ 3
 
0.4%
@ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
2651
100.0%
Close Punctuation
ValueCountFrequency (%)
) 586
100.0%
Open Punctuation
ValueCountFrequency (%)
( 586
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9700
56.4%
Common 7481
43.5%
Latin 19
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1143
 
11.8%
종 773
 
8.0%
서 592
 
6.1%
시 585
 
6.0%
구 585
 
6.0%
울 578
 
6.0%
특 577
 
5.9%
별 577
 
5.9%
동 563
 
5.8%
길 347
 
3.6%
Other values (169) 3380
34.8%
Common
ValueCountFrequency (%)
2651
35.4%
, 789
 
10.5%
1 622
 
8.3%
) 586
 
7.8%
( 586
 
7.8%
2 515
 
6.9%
3 347
 
4.6%
5 199
 
2.7%
4 196
 
2.6%
0 186
 
2.5%
Other values (8) 804
 
10.7%
Latin
ValueCountFrequency (%)
B 13
68.4%
D 2
 
10.5%
A 1
 
5.3%
C 1
 
5.3%
K 1
 
5.3%
S 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9700
56.4%
ASCII 7500
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2651
35.3%
, 789
 
10.5%
1 622
 
8.3%
) 586
 
7.8%
( 586
 
7.8%
2 515
 
6.9%
3 347
 
4.6%
5 199
 
2.7%
4 196
 
2.6%
0 186
 
2.5%
Other values (14) 823
 
11.0%
Hangul
ValueCountFrequency (%)
로 1143
 
11.8%
종 773
 
8.0%
서 592
 
6.1%
시 585
 
6.0%
구 585
 
6.0%
울 578
 
6.0%
특 577
 
5.9%
별 577
 
5.9%
동 563
 
5.8%
길 347
 
3.6%
Other values (169) 3380
34.8%

소재지지번
Text

MISSING 

Distinct370
Distinct (%)59.6%
Missing13
Missing (%)2.1%
Memory size5.1 KiB
2024-05-10T22:59:07.362381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length27.00161
Min length20

Characters and Unicode

Total characters16768
Distinct characters192
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)39.6%

Sample

1st row서울특별시 종로구 낙원동 191번지
2nd row서울특별시 종로구 낙원동 190번지
3rd row서울특별시 종로구 장사동 227번지 1호 지하1층
4th row서울특별시 종로구 숭인동 1127번지
5th row서울특별시 종로구 동숭동 1번지 35호 ABC마트빌딩 3층
ValueCountFrequency (%)
서울특별시 621
 
19.0%
종로구 621
 
19.0%
1호 90
 
2.8%
숭인동 81
 
2.5%
창신동 45
 
1.4%
낙원동 38
 
1.2%
관철동 33
 
1.0%
2호 33
 
1.0%
무악동 30
 
0.9%
3호 29
 
0.9%
Other values (461) 1642
50.3%
2024-05-10T22:59:08.422138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4254
25.4%
지 720
 
4.3%
로 696
 
4.2%
종 682
 
4.1%
1 676
 
4.0%
구 634
 
3.8%
서 633
 
3.8%
시 630
 
3.8%
울 622
 
3.7%
별 621
 
3.7%
Other values (182) 6600
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9617
57.4%
Space Separator 4254
25.4%
Decimal Number 2767
 
16.5%
Dash Punctuation 57
 
0.3%
Other Punctuation 27
 
0.2%
Uppercase Letter 25
 
0.1%
Open Punctuation 10
 
0.1%
Close Punctuation 10
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 720
 
7.5%
로 696
 
7.2%
종 682
 
7.1%
구 634
 
6.6%
서 633
 
6.6%
시 630
 
6.6%
울 622
 
6.5%
별 621
 
6.5%
번 621
 
6.5%
특 621
 
6.5%
Other values (157) 3137
32.6%
Decimal Number
ValueCountFrequency (%)
1 676
24.4%
2 465
16.8%
3 315
11.4%
0 248
 
9.0%
4 241
 
8.7%
7 171
 
6.2%
6 170
 
6.1%
9 166
 
6.0%
5 161
 
5.8%
8 154
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 17
68.0%
S 2
 
8.0%
D 2
 
8.0%
G 1
 
4.0%
A 1
 
4.0%
C 1
 
4.0%
K 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 22
81.5%
/ 3
 
11.1%
@ 2
 
7.4%
Space Separator
ValueCountFrequency (%)
4254
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9617
57.4%
Common 7126
42.5%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 720
 
7.5%
로 696
 
7.2%
종 682
 
7.1%
구 634
 
6.6%
서 633
 
6.6%
시 630
 
6.6%
울 622
 
6.5%
별 621
 
6.5%
번 621
 
6.5%
특 621
 
6.5%
Other values (157) 3137
32.6%
Common
ValueCountFrequency (%)
4254
59.7%
1 676
 
9.5%
2 465
 
6.5%
3 315
 
4.4%
0 248
 
3.5%
4 241
 
3.4%
7 171
 
2.4%
6 170
 
2.4%
9 166
 
2.3%
5 161
 
2.3%
Other values (8) 259
 
3.6%
Latin
ValueCountFrequency (%)
B 17
68.0%
S 2
 
8.0%
D 2
 
8.0%
G 1
 
4.0%
A 1
 
4.0%
C 1
 
4.0%
K 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9617
57.4%
ASCII 7151
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4254
59.5%
1 676
 
9.5%
2 465
 
6.5%
3 315
 
4.4%
0 248
 
3.5%
4 241
 
3.4%
7 171
 
2.4%
6 170
 
2.4%
9 166
 
2.3%
5 161
 
2.3%
Other values (15) 284
 
4.0%
Hangul
ValueCountFrequency (%)
지 720
 
7.5%
로 696
 
7.2%
종 682
 
7.1%
구 634
 
6.6%
서 633
 
6.6%
시 630
 
6.6%
울 622
 
6.5%
별 621
 
6.5%
번 621
 
6.5%
특 621
 
6.5%
Other values (157) 3137
32.6%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct236
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20137068
Minimum20011029
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-10T22:59:08.856231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011029
5-th percentile20070927
Q120110101
median20130603
Q320170307
95-th percentile20217716
Maximum20240305
Range229276
Interquartile range (IQR)60206

Descriptive statistics

Standard deviation43389.425
Coefficient of variation (CV)0.0021547043
Kurtosis-0.47289641
Mean20137068
Median Absolute Deviation (MAD)30198
Skewness0.27916436
Sum1.2766901 × 1010
Variance1.8826422 × 109
MonotonicityNot monotonic
2024-05-10T22:59:09.310420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150817 41
 
6.5%
20070927 29
 
4.6%
20120608 25
 
3.9%
20230612 24
 
3.8%
20180320 20
 
3.2%
20160801 17
 
2.7%
20170307 17
 
2.7%
20180516 14
 
2.2%
20121226 14
 
2.2%
20100517 14
 
2.2%
Other values (226) 419
66.1%
ValueCountFrequency (%)
20011029 1
 
0.2%
20020927 1
 
0.2%
20051222 1
 
0.2%
20060216 1
 
0.2%
20060619 8
1.3%
20060620 1
 
0.2%
20061111 1
 
0.2%
20061221 1
 
0.2%
20070109 2
 
0.3%
20070111 1
 
0.2%
ValueCountFrequency (%)
20240305 2
 
0.3%
20230921 1
 
0.2%
20230825 1
 
0.2%
20230801 1
 
0.2%
20230703 1
 
0.2%
20230612 24
3.8%
20230419 1
 
0.2%
20230323 1
 
0.2%
20210927 1
 
0.2%
20210718 1
 
0.2%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
처분확정
634 

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 634
100.0%

Length

2024-05-10T22:59:09.723275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:59:10.028792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 634
100.0%

처분명
Text

Distinct96
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:10.374934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length7.7902208
Min length2

Characters and Unicode

Total characters4939
Distinct characters133
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)10.3%

Sample

1st row개선명령
2nd row영업정지
3rd row영업소폐쇄
4th row영업정지
5th row경고
ValueCountFrequency (%)
과태료부과 246
27.7%
경고 108
12.1%
영업소폐쇄 73
 
8.2%
개선명령 54
 
6.1%
영업정지 44
 
4.9%
과징금부과 38
 
4.3%
및 24
 
2.7%
영업허가ㆍ등록취소 17
 
1.9%
200,000 17
 
1.9%
과태료 15
 
1.7%
Other values (131) 253
28.5%
2024-05-10T22:59:11.116616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 665
 
13.5%
0 381
 
7.7%
부 325
 
6.6%
료 287
 
5.8%
태 284
 
5.8%
255
 
5.2%
업 178
 
3.6%
2 176
 
3.6%
영 169
 
3.4%
1 135
 
2.7%
Other values (123) 2084
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3513
71.1%
Decimal Number 860
 
17.4%
Space Separator 255
 
5.2%
Other Punctuation 174
 
3.5%
Close Punctuation 57
 
1.2%
Open Punctuation 57
 
1.2%
Math Symbol 21
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 665
18.9%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (103) 1190
33.9%
Decimal Number
ValueCountFrequency (%)
0 381
44.3%
2 176
20.5%
1 135
 
15.7%
3 33
 
3.8%
8 30
 
3.5%
9 27
 
3.1%
5 25
 
2.9%
6 23
 
2.7%
7 17
 
2.0%
4 13
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 102
58.6%
, 66
37.9%
% 2
 
1.1%
/ 2
 
1.1%
: 2
 
1.1%
Space Separator
ValueCountFrequency (%)
255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3513
71.1%
Common 1426
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 665
18.9%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (103) 1190
33.9%
Common
ValueCountFrequency (%)
0 381
26.7%
255
17.9%
2 176
12.3%
1 135
 
9.5%
. 102
 
7.2%
, 66
 
4.6%
) 57
 
4.0%
( 57
 
4.0%
3 33
 
2.3%
8 30
 
2.1%
Other values (10) 134
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3496
70.8%
ASCII 1426
28.9%
Compat Jamo 17
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 665
19.0%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (102) 1173
33.6%
ASCII
ValueCountFrequency (%)
0 381
26.7%
255
17.9%
2 176
12.3%
1 135
 
9.5%
. 102
 
7.2%
, 66
 
4.6%
) 57
 
4.0%
( 57
 
4.0%
3 33
 
2.3%
8 30
 
2.1%
Other values (10) 134
 
9.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 17
100.0%

법적근거
Text

Distinct109
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:11.485113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length39
Mean length12.12776
Min length6

Characters and Unicode

Total characters7689
Distinct characters67
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)8.8%

Sample

1st row법 제11조제1항제4호
2nd row법 제11조제1항제4호
3rd row법 제11조제1항제8호
4th row법 제11조제1항제8호
5th row법 제11조제1항제4호
ValueCountFrequency (%)
법 269
21.1%
공중위생관리법 201
15.8%
제17조 159
 
12.5%
제22조제2항제6호 56
 
4.4%
제11조제1항 45
 
3.5%
위반 38
 
3.0%
공중위생관리법제17조제1항 32
 
2.5%
제3조제3항 26
 
2.0%
제1항 20
 
1.6%
공중위생관리법제17조 20
 
1.6%
Other values (107) 408
32.0%
2024-05-10T22:59:12.279794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 1041
13.5%
법 672
 
8.7%
1 671
 
8.7%
659
 
8.6%
조 621
 
8.1%
위 404
 
5.3%
항 396
 
5.2%
중 361
 
4.7%
생 361
 
4.7%
공 361
 
4.7%
Other values (57) 2142
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5383
70.0%
Decimal Number 1579
 
20.5%
Space Separator 659
 
8.6%
Other Punctuation 53
 
0.7%
Uppercase Letter 7
 
0.1%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 1041
19.3%
법 672
12.5%
조 621
11.5%
위 404
 
7.5%
항 396
 
7.4%
중 361
 
6.7%
생 361
 
6.7%
공 361
 
6.7%
관 347
 
6.4%
리 347
 
6.4%
Other values (41) 472
8.8%
Decimal Number
ValueCountFrequency (%)
1 671
42.5%
7 302
19.1%
2 294
18.6%
3 147
 
9.3%
6 74
 
4.7%
4 71
 
4.5%
8 10
 
0.6%
5 4
 
0.3%
9 3
 
0.2%
0 3
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 43
81.1%
. 10
 
18.9%
Space Separator
ValueCountFrequency (%)
659
100.0%
Uppercase Letter
ValueCountFrequency (%)
I 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5383
70.0%
Common 2299
29.9%
Latin 7
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 1041
19.3%
법 672
12.5%
조 621
11.5%
위 404
 
7.5%
항 396
 
7.4%
중 361
 
6.7%
생 361
 
6.7%
공 361
 
6.7%
관 347
 
6.4%
리 347
 
6.4%
Other values (41) 472
8.8%
Common
ValueCountFrequency (%)
1 671
29.2%
659
28.7%
7 302
13.1%
2 294
12.8%
3 147
 
6.4%
6 74
 
3.2%
4 71
 
3.1%
, 43
 
1.9%
. 10
 
0.4%
8 10
 
0.4%
Other values (5) 18
 
0.8%
Latin
ValueCountFrequency (%)
I 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5383
70.0%
ASCII 2306
30.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 1041
19.3%
법 672
12.5%
조 621
11.5%
위 404
 
7.5%
항 396
 
7.4%
중 361
 
6.7%
생 361
 
6.7%
공 361
 
6.7%
관 347
 
6.4%
리 347
 
6.4%
Other values (41) 472
8.8%
ASCII
ValueCountFrequency (%)
1 671
29.1%
659
28.6%
7 302
13.1%
2 294
12.7%
3 147
 
6.4%
6 74
 
3.2%
4 71
 
3.1%
, 43
 
1.9%
. 10
 
0.4%
8 10
 
0.4%
Other values (6) 25
 
1.1%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct250
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20133912
Minimum20011008
Maximum20240305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-10T22:59:12.751760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011008
5-th percentile20060937
Q120103446
median20121204
Q320170101
95-th percentile20214398
Maximum20240305
Range229297
Interquartile range (IQR)66655.5

Descriptive statistics

Standard deviation43910.779
Coefficient of variation (CV)0.0021809363
Kurtosis-0.49458582
Mean20133912
Median Absolute Deviation (MAD)21051.5
Skewness0.20668902
Sum1.27649 × 1010
Variance1.9281565 × 109
MonotonicityNot monotonic
2024-05-10T22:59:13.202348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20141231 40
 
6.3%
20180101 35
 
5.5%
20221231 24
 
3.8%
20170101 24
 
3.8%
20120607 23
 
3.6%
20121204 19
 
3.0%
20110617 17
 
2.7%
20160101 15
 
2.4%
20190101 14
 
2.2%
20051219 13
 
2.1%
Other values (240) 410
64.7%
ValueCountFrequency (%)
20011008 1
 
0.2%
20020927 1
 
0.2%
20051219 13
2.1%
20051222 1
 
0.2%
20051231 4
 
0.6%
20060209 1
 
0.2%
20060523 1
 
0.2%
20060619 9
1.4%
20060629 1
 
0.2%
20061103 1
 
0.2%
ValueCountFrequency (%)
20240305 2
 
0.3%
20230907 1
 
0.2%
20230825 1
 
0.2%
20230801 1
 
0.2%
20230703 1
 
0.2%
20230419 1
 
0.2%
20230323 1
 
0.2%
20221231 24
3.8%
20210718 1
 
0.2%
20210701 8
 
1.3%

위반내용
Text

Distinct225
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:13.695380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length213
Median length93
Mean length16.219243
Min length5

Characters and Unicode

Total characters10283
Distinct characters264
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)23.0%

Sample

1st row공중위생관리법 제4조(공중위생영업자의 위생관리 의무등) 위반 공중위생관리법 시행규칙 제11조제1항제4호 및 제19조 [별표7]【Ⅱ. 개별기준 1. 숙박업 라. 1).】
2nd row공중위생영업자가 준수해야하는 위생관리기준 등을 위반한 경우 -목욕실 등의 청결을 유지하지 않은 경우
3rd row2023년 9월 7일 19:45경 해당 업소에서는 성명불상의 손님들로부터 8만원에서 20만원의 성매매 대금을 받고 여성종업원으로 하여금 남자 손님들과 성교행위를 하도록 함으로써 성매매알선 등 행위를 하였고, 영업정지 중인 목욕장업 시설인 것을 알고 있음에도 성매매를 하기 위해 출입한 손님들에게 사우나 내 목욕시설을 이용하게 하는 방법으로 목욕장을 영업함
4th row성매매알선 1차 위반
5th row미용 서비스 최종지급가격 내역 미제공
ValueCountFrequency (%)
미이수 246
 
11.7%
위생교육 243
 
11.6%
2014년 42
 
2.0%
2017년 35
 
1.7%
공중위생교육 33
 
1.6%
청소년 33
 
1.6%
위생교육미이수 29
 
1.4%
이성혼숙 29
 
1.4%
장소제공 27
 
1.3%
및 27
 
1.3%
Other values (502) 1350
64.5%
2024-05-10T22:59:14.667757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1516
 
14.7%
위 479
 
4.7%
이 434
 
4.2%
미 398
 
3.9%
2 392
 
3.8%
0 390
 
3.8%
생 385
 
3.7%
수 358
 
3.5%
교 331
 
3.2%
육 327
 
3.2%
Other values (254) 5273
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7211
70.1%
Space Separator 1516
 
14.7%
Decimal Number 1319
 
12.8%
Close Punctuation 77
 
0.7%
Open Punctuation 76
 
0.7%
Other Punctuation 60
 
0.6%
Dash Punctuation 18
 
0.2%
Math Symbol 3
 
< 0.1%
Letter Number 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
위 479
 
6.6%
이 434
 
6.0%
미 398
 
5.5%
생 385
 
5.3%
수 358
 
5.0%
교 331
 
4.6%
육 327
 
4.5%
년 303
 
4.2%
업 207
 
2.9%
소 149
 
2.1%
Other values (226) 3840
53.3%
Decimal Number
ValueCountFrequency (%)
2 392
29.7%
0 390
29.6%
1 242
18.3%
4 63
 
4.8%
6 55
 
4.2%
7 52
 
3.9%
5 45
 
3.4%
9 39
 
3.0%
3 22
 
1.7%
8 19
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 74
96.1%
] 1
 
1.3%
】 1
 
1.3%
』 1
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 73
96.1%
[ 1
 
1.3%
【 1
 
1.3%
『 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 26
43.3%
. 20
33.3%
: 12
20.0%
/ 2
 
3.3%
Space Separator
ValueCountFrequency (%)
1516
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7211
70.1%
Common 3071
29.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
위 479
 
6.6%
이 434
 
6.0%
미 398
 
5.5%
생 385
 
5.3%
수 358
 
5.0%
교 331
 
4.6%
육 327
 
4.5%
년 303
 
4.2%
업 207
 
2.9%
소 149
 
2.1%
Other values (226) 3840
53.3%
Common
ValueCountFrequency (%)
1516
49.4%
2 392
 
12.8%
0 390
 
12.7%
1 242
 
7.9%
) 74
 
2.4%
( 73
 
2.4%
4 63
 
2.1%
6 55
 
1.8%
7 52
 
1.7%
5 45
 
1.5%
Other values (17) 169
 
5.5%
Latin
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7208
70.1%
ASCII 3065
29.8%
None 4
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Punctuation 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1516
49.5%
2 392
 
12.8%
0 390
 
12.7%
1 242
 
7.9%
) 74
 
2.4%
( 73
 
2.4%
4 63
 
2.1%
6 55
 
1.8%
7 52
 
1.7%
5 45
 
1.5%
Other values (11) 163
 
5.3%
Hangul
ValueCountFrequency (%)
위 479
 
6.6%
이 434
 
6.0%
미 398
 
5.5%
생 385
 
5.3%
수 358
 
5.0%
교 331
 
4.6%
육 327
 
4.5%
년 303
 
4.2%
업 207
 
2.9%
소 149
 
2.1%
Other values (224) 3837
53.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
66.7%
ㅖ 1
33.3%
None
ValueCountFrequency (%)
【 1
25.0%
】 1
25.0%
『 1
25.0%
』 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

처분내용
Text

Distinct96
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size5.1 KiB
2024-05-10T22:59:15.077025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length7.7902208
Min length2

Characters and Unicode

Total characters4939
Distinct characters133
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)10.3%

Sample

1st row개선명령
2nd row영업정지
3rd row영업소폐쇄
4th row영업정지
5th row경고
ValueCountFrequency (%)
과태료부과 246
27.7%
경고 108
12.1%
영업소폐쇄 73
 
8.2%
개선명령 54
 
6.1%
영업정지 44
 
4.9%
과징금부과 38
 
4.3%
및 24
 
2.7%
영업허가ㆍ등록취소 17
 
1.9%
200,000 17
 
1.9%
과태료 15
 
1.7%
Other values (131) 253
28.5%
2024-05-10T22:59:15.812532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 665
 
13.5%
0 381
 
7.7%
부 325
 
6.6%
료 287
 
5.8%
태 284
 
5.8%
255
 
5.2%
업 178
 
3.6%
2 176
 
3.6%
영 169
 
3.4%
1 135
 
2.7%
Other values (123) 2084
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3513
71.1%
Decimal Number 860
 
17.4%
Space Separator 255
 
5.2%
Other Punctuation 174
 
3.5%
Close Punctuation 57
 
1.2%
Open Punctuation 57
 
1.2%
Math Symbol 21
 
0.4%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 665
18.9%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (103) 1190
33.9%
Decimal Number
ValueCountFrequency (%)
0 381
44.3%
2 176
20.5%
1 135
 
15.7%
3 33
 
3.8%
8 30
 
3.5%
9 27
 
3.1%
5 25
 
2.9%
6 23
 
2.7%
7 17
 
2.0%
4 13
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 102
58.6%
, 66
37.9%
% 2
 
1.1%
/ 2
 
1.1%
: 2
 
1.1%
Space Separator
ValueCountFrequency (%)
255
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3513
71.1%
Common 1426
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 665
18.9%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (103) 1190
33.9%
Common
ValueCountFrequency (%)
0 381
26.7%
255
17.9%
2 176
12.3%
1 135
 
9.5%
. 102
 
7.2%
, 66
 
4.6%
) 57
 
4.0%
( 57
 
4.0%
3 33
 
2.3%
8 30
 
2.1%
Other values (10) 134
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3496
70.8%
ASCII 1426
28.9%
Compat Jamo 17
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 665
19.0%
부 325
 
9.3%
료 287
 
8.2%
태 284
 
8.1%
업 178
 
5.1%
영 169
 
4.8%
고 118
 
3.4%
경 116
 
3.3%
소 99
 
2.8%
폐 82
 
2.3%
Other values (102) 1173
33.6%
ASCII
ValueCountFrequency (%)
0 381
26.7%
255
17.9%
2 176
12.3%
1 135
 
9.5%
. 102
 
7.2%
, 66
 
4.6%
) 57
 
4.0%
( 57
 
4.0%
3 33
 
2.3%
8 30
 
2.1%
Other values (10) 134
 
9.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 17
100.0%

처분기간
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing612
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum0
Maximum29
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-10T22:59:16.048292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q15
median10
Q315
95-th percentile24.8
Maximum29
Range29
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.6764947
Coefficient of variation (CV)0.66752128
Kurtosis-0.26081888
Mean11.5
Median Absolute Deviation (MAD)5
Skewness0.6919825
Sum253
Variance58.928571
MonotonicityNot monotonic
2024-05-10T22:59:16.237132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5 8
 
1.3%
15 6
 
0.9%
10 2
 
0.3%
21 2
 
0.3%
7 1
 
0.2%
29 1
 
0.2%
0 1
 
0.2%
25 1
 
0.2%
(Missing) 612
96.5%
ValueCountFrequency (%)
0 1
 
0.2%
5 8
1.3%
7 1
 
0.2%
10 2
 
0.3%
15 6
0.9%
21 2
 
0.3%
25 1
 
0.2%
29 1
 
0.2%
ValueCountFrequency (%)
29 1
 
0.2%
25 1
 
0.2%
21 2
 
0.3%
15 6
0.9%
10 2
 
0.3%
7 1
 
0.2%
5 8
1.3%
0 1
 
0.2%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct311
Distinct (%)54.7%
Missing65
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean302.21448
Minimum0
Maximum6979.56
Zeros7
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2024-05-10T22:59:16.538183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.08
Q134.71
median84.7
Q3235.7
95-th percentile1438.8
Maximum6979.56
Range6979.56
Interquartile range (IQR)200.99

Descriptive statistics

Standard deviation697.60862
Coefficient of variation (CV)2.3083229
Kurtosis41.286262
Mean302.21448
Median Absolute Deviation (MAD)64.96
Skewness5.5721152
Sum171960.04
Variance486657.79
MonotonicityNot monotonic
2024-05-10T22:59:16.849554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.0 11
 
1.7%
56.1 9
 
1.4%
0.0 7
 
1.1%
75.0 6
 
0.9%
19.3 6
 
0.9%
2556.61 6
 
0.9%
18.1 6
 
0.9%
62.7 6
 
0.9%
169.54 6
 
0.9%
165.0 6
 
0.9%
Other values (301) 500
78.9%
(Missing) 65
 
10.3%
ValueCountFrequency (%)
0.0 7
1.1%
6.0 5
0.8%
8.1 1
 
0.2%
8.23 1
 
0.2%
9.1 1
 
0.2%
9.21 2
 
0.3%
10.0 4
0.6%
11.48 1
 
0.2%
11.56 1
 
0.2%
12.0 4
0.6%
ValueCountFrequency (%)
6979.56 2
 
0.3%
6309.22 1
 
0.2%
3739.93 1
 
0.2%
3027.26 1
 
0.2%
2758.16 2
 
0.3%
2680.52 3
0.5%
2556.61 6
0.9%
2384.87 2
 
0.3%
1996.7 1
 
0.2%
1985.64 2
 
0.3%

Interactions

2024-05-10T22:58:59.156907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:53.839017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:55.129679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:56.497903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:57.752075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:59.357765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:54.101639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:55.398183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:56.700634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:57.989688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:59.597692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:54.318156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:55.739860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:56.976770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:58.237462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:59.864685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:54.590503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:56.000426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:57.236706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:58.477652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:59:00.109215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:54.839085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:56.243600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:57.477351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:58:58.723081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T22:59:17.143010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자처분명위반일자처분내용처분기간영업장면적(㎡)
처분일자1.0000.5610.5660.9940.9140.9970.9140.7940.274
업종명0.5611.0000.9690.5030.3800.5190.3800.7040.163
업태명0.5660.9691.0000.5940.0000.5320.0000.9560.709
지도점검일자0.9940.5030.5941.0000.8960.9960.8960.7940.313
처분명0.9140.3800.0000.8961.0000.8941.0000.9150.797
위반일자0.9970.5190.5320.9960.8941.0000.8940.7680.264
처분내용0.9140.3800.0000.8961.0000.8941.0000.9150.797
처분기간0.7940.7040.9560.7940.9150.7680.9151.0000.000
영업장면적(㎡)0.2740.1630.7090.3130.7970.2640.7970.0001.000
2024-05-10T22:59:17.375685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명업태명
업종명1.0000.794
업태명0.7941.000
2024-05-10T22:59:17.631840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명업태명
처분일자1.0000.9830.993-0.022-0.0720.2450.255
지도점검일자0.9831.0000.978-0.032-0.0640.2120.273
위반일자0.9930.9781.0000.104-0.0670.2210.235
처분기간-0.022-0.0320.1041.0000.5270.4700.656
영업장면적(㎡)-0.072-0.064-0.0670.5271.0000.0740.410
업종명0.2450.2120.2210.4700.0741.0000.794
업태명0.2550.2730.2350.6560.4100.7941.000

Missing values

2024-05-10T22:59:00.469714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T22:59:00.896101image/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.
2024-05-10T22:59:01.147061image/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(㎡)
03000000202404010138숙박업(일반)여관업테크노모텔서울특별시 종로구 돈화문로5길 28-3, (낙원동)서울특별시 종로구 낙원동 191번지20240305처분확정개선명령법 제11조제1항제4호20240305공중위생관리법 제4조(공중위생영업자의 위생관리 의무등) 위반 공중위생관리법 시행규칙 제11조제1항제4호 및 제19조 [별표7]【Ⅱ. 개별기준 1. 숙박업 라. 1).】개선명령<NA>209.42
13000000202404010036목욕장업공동탕업문화탕서울특별시 종로구 돈화문로5길 28-5, (낙원동)서울특별시 종로구 낙원동 190번지20240305처분확정영업정지법 제11조제1항제4호20240305공중위생영업자가 준수해야하는 위생관리기준 등을 위반한 경우 -목욕실 등의 청결을 유지하지 않은 경우영업정지10281.11
23000000202310252015-00002목욕장업공동탕업센츄럴관광호텔 사우나서울특별시 종로구 청계천로 137, 지하1층 (장사동)서울특별시 종로구 장사동 227번지 1호 지하1층20230921처분확정영업소폐쇄법 제11조제1항제8호202309072023년 9월 7일 19:45경 해당 업소에서는 성명불상의 손님들로부터 8만원에서 20만원의 성매매 대금을 받고 여성종업원으로 하여금 남자 손님들과 성교행위를 하도록 함으로써 성매매알선 등 행위를 하였고, 영업정지 중인 목욕장업 시설인 것을 알고 있음에도 성매매를 하기 위해 출입한 손님들에게 사우나 내 목욕시설을 이용하게 하는 방법으로 목욕장을 영업함영업소폐쇄<NA>193.04
33000000202310250098숙박업(일반)여관업만남모텔서울특별시 종로구 보문로1길 7-20, (숭인동)서울특별시 종로구 숭인동 1127번지20230801처분확정영업정지법 제11조제1항제8호20230801성매매알선 1차 위반영업정지<NA>143.77
4300000020230830432일반미용업일반미용업준오헤어서울특별시 종로구 대학로 132, 3층 (동숭동, ABC마트빌딩)서울특별시 종로구 동숭동 1번지 35호 ABC마트빌딩 3층20230825처분확정경고법 제11조제1항제4호20230825미용 서비스 최종지급가격 내역 미제공경고<NA>192.76
53000000202307262015-00002목욕장업공동탕업센츄럴관광호텔 사우나서울특별시 종로구 청계천로 137, 지하1층 (장사동)서울특별시 종로구 장사동 227번지 1호 지하1층20230612처분확정과태료부과 60만원법 제22조제2항제6호202212312022년 공중위생교육 미이수과태료부과 60만원<NA>193.04
6300000020230705324숙박업(일반)일반호텔(주)호텔리안서울특별시 종로구 수표로18길 26, (관수동)<NA>20230612처분확정과태료부과법 제22조제2항제6호202212312022년 공중위생교육 미이수 과태료 60만원과태료부과<NA>2556.61
73000000202307052020-00012숙박업(일반)관광호텔호스텔코리아서울특별시 종로구 돈화문로 85, (와룡동)서울특별시 종로구 와룡동 140번지20230612처분확정과태료부과법 제22조제2항제6호202212312022년 공중위생교육 미이수 과태료 60만원과태료부과<NA><NA>
8300000020230705324숙박업(일반)일반호텔(주)호텔리안서울특별시 종로구 수표로18길 26, (관수동)<NA>20230612처분확정과태료부과법 제22조제2항제6호202212312022년 공중위생교육 미이수 과태료 60만원과태료부과<NA>2556.61
93000000202307052021-12화장ㆍ분장 미용업메이크업업라라홍 메이크업서울특별시 종로구 삼봉로 81, 두산위브파빌리온 2층 219호 (수송동)서울특별시 종로구 수송동 58번지 두산위브파빌리온20230612처분확정과태료부과 60만원법 제22조제2항제6호202212312022년 공중위생교육 미이수과태료부과 60만원<NA>33.3
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
6243000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정개선명령공중위생관리법제4조제4항및제7항20060619미용요금표미게시개선명령<NA>97.0
6253000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정개선명령공중위생관리법제4조제4항및제7항20060619미용요금표미게시개선명령<NA>97.0
6263000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정과태료부과 50만원공중위생관리법제4조제4항및제7항20060619미용요금표미게시과태료부과 50만원<NA>97.0
6273000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정과태료부과 50만원공중위생관리법제4조제4항및제7항20060619미용요금표미게시과태료부과 50만원<NA>97.0
6283000000200608240350일반미용업일반미용업박승철헤어스투디오서울특별시 종로구 우정국로2길 8, (관철동,쎄븐빌딩2,3층)서울특별시 종로구 관철동 260번지 쎄븐빌딩2,3층20060619처분확정개선명령공중위생관리법제4조제4항및제7항20060619미용요금표미게시개선명령<NA>89.0
6293000000200608070137숙박업(일반)여관업부전서울특별시 종로구 창신1길 9, (창신동)서울특별시 종로구 창신동 580번지 32호20141212처분확정영업정지 2개월에 갈음하는 과징금 1,800,000원공중위생관리법 제11조제1항20060629청소년 이성혼숙 장소제공영업정지 2개월에 갈음하는 과징금 1,800,000원<NA>94.4
6303000000200604050037목욕장업한증막업한일사우나서울특별시 종로구 종로 199, (종로4가)서울특별시 종로구 종로4가 5번지20051222처분확정영업정지공중위생관리법제11조20051222업장내 도박 방조영업정지151074.51
631300000020060303139이용업일반이용업대광이용원서울특별시 종로구 통일로 156, (교남동)서울특별시 종로구 교남동 30번지 0호20060216처분확정개선명령공중위생관리법제3조제1항20060209커튼, 칸막이 그 밖의 유사한 장애물 설치개선명령<NA>41.87
6323000000200302180041숙박업(일반)여관업세림여관서울특별시 종로구 인사동길 37-11, (관훈동)서울특별시 종로구 관훈동 192번지 17호20020927처분확정영업정지(조정권고안 수용)2003.03.14~04.07윤락행위방지법20020927윤락행위방지법위반 2003.04.04---서울행정법원(조정권고)-- 영업정지25일 2003.04.18---서울고등검찰청(조정권고안 수용여부 지휘 품신) ---조정권고안 수용(4.11) 2003.04.17---행정처분 변경처분 : 영업정지25일(처분)영업정지(조정권고안 수용)2003.03.14~04.0725178.01
63330000002002012501100410600113숙박업(일반)여관업신영서울특별시 종로구 세검정로 238, (홍지동)서울특별시 종로구 홍지동 92번지 4호20011029처분확정영업정지공중위생관리법 제11조, 같은법 시행규칙 제19조 위반20011008청소년 남,여 혼숙 장소제공 (2001.10.8.23:00경, 미성년자 박은진(여,14세)과 이우진(남,21세) 혼숙 장소제공으로 서대문경찰서에 적발 통보됨)영업정지<NA>561.19

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
03000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정개선명령공중위생관리법제4조제4항및제7항20060619미용요금표미게시개선명령<NA>97.02
13000000200608240035미용업일반미용업리안종로5가점<NA>서울특별시 종로구 종로5가 120번지 8호20060619처분확정과태료부과 50만원공중위생관리법제4조제4항및제7항20060619미용요금표미게시과태료부과 50만원<NA>97.02
23000000200608240350일반미용업일반미용업박승철헤어스투디오서울특별시 종로구 우정국로2길 8, (관철동,쎄븐빌딩2,3층)서울특별시 종로구 관철동 260번지 쎄븐빌딩2,3층20060619처분확정개선명령공중위생관리법제4조제4항및제7항20060619미용요금표미게시개선명령<NA>89.02
33000000200608240350일반미용업일반미용업박승철헤어스투디오서울특별시 종로구 우정국로2길 8, (관철동,쎄븐빌딩2,3층)서울특별시 종로구 관철동 260번지 쎄븐빌딩2,3층20060619처분확정과태료부과 50만원공중위생관리법제4조제4항및제7항20060619미용요금표미게시과태료부과 50만원<NA>89.02
43000000201105160072목욕장업공동탕업백상대중탕서울특별시 종로구 인사동7길 12, (관훈동,백상빌딩 지하2층)서울특별시 종로구 관훈동 197번지 28호 백상빌딩 지하2층20110411처분확정개선명령공중위생관리법 제4조제7항20110411숙박목적 침구류 비치개선명령<NA>1430.02
53000000201105160072목욕장업공동탕업백상대중탕서울특별시 종로구 인사동7길 12, (관훈동,백상빌딩 지하2층)서울특별시 종로구 관훈동 197번지 28호 백상빌딩 지하2층20110411처분확정과태료부과(과태료 50만원, 업주 자진납부:감경액 20%인 40만원)공중위생관리법 제4조제7항20110411숙박목적 침구류 비치과태료부과(과태료 50만원, 업주 자진납부:감경액 20%인 40만원)<NA>1430.02
6300000020110705515피부미용업피부미용업명가서울특별시 종로구 종로 344, (숭인동,외 3필지 종로대우디오빌 4층 403호)서울특별시 종로구 숭인동 310번지 외 3필지 종로대우디오빌 4층 403호20110101처분확정경고법제17조제1항20110101법제17조제1항경고<NA>62.72
7300000020110705515피부미용업피부미용업명가서울특별시 종로구 종로 344, (숭인동,외 3필지 종로대우디오빌 4층 403호)서울특별시 종로구 숭인동 310번지 외 3필지 종로대우디오빌 4층 403호20110101처분확정과태료부과법제17조제1항20110101법제17조제1항과태료부과<NA>62.72
8300000020120406139이용업일반이용업대광이용원서울특별시 종로구 통일로 156, (교남동)서울특별시 종로구 교남동 30번지 0호20120315처분확정개선명령공중위생관리법 제3조 제1항20120315칸막이 설치개선명령<NA>41.872
93000000201509090015위생관리용역업위생관리용역업(주)우리종합써비스서울특별시 종로구 종로 1, 17층 (종로1가, 교보생명빌딩)서울특별시 종로구 종로1가 1번지 교보생명빌딩 17층20150817처분확정경고법 제17조201412312014년 위생교육 미이수경고<NA><NA>2