Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells20040
Missing cells (%)11.1%
Duplicate rows834
Duplicate rows (%)8.3%
Total size in memory1.5 MiB
Average record size in memory159.0 B

Variable types

Categorical4
Numeric6
Text8

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡),운영형태
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-10219/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 834 (8.3%) duplicate rowsDuplicates
운영형태 is highly overall correlated with 처분일자 and 5 other fieldsHigh correlation
업종명 is highly overall correlated with 운영형태High correlation
처분일자 is highly overall correlated with 지도점검일자 and 2 other fieldsHigh correlation
교부번호 is highly overall correlated with 운영형태High 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
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
운영형태 is highly imbalanced (98.6%)Imbalance
소재지도로명 has 6302 (63.0%) missing valuesMissing
처분기간 has 8851 (88.5%) missing valuesMissing
영업장면적(㎡) has 4824 (48.2%) missing valuesMissing
위반일자 is highly skewed (γ1 = -25.93382506)Skewed

Reproduction

Analysis started2024-05-18 06:24:32.077881
Analysis finished2024-05-18 06:24:53.703292
Duration21.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3010000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 10000
100.0%

Length

2024-05-18T15:24:53.894897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:24:54.304016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2359
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20108358
Minimum19910605
Maximum20240318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:24:54.722857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19910605
5-th percentile20020626
Q120041209
median20091012
Q320170915
95-th percentile20230627
Maximum20240318
Range329713
Interquartile range (IQR)129706

Descriptive statistics

Standard deviation69601.808
Coefficient of variation (CV)0.0034613372
Kurtosis-1.1584729
Mean20108358
Median Absolute Deviation (MAD)60194.5
Skewness0.35636545
Sum2.0108358 × 1011
Variance4.8444117 × 109
MonotonicityNot monotonic
2024-05-18T15:24:55.404309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021220 152
 
1.5%
20021218 126
 
1.3%
20111115 118
 
1.2%
20040410 110
 
1.1%
20021211 86
 
0.9%
20120102 79
 
0.8%
20090609 72
 
0.7%
20230627 71
 
0.7%
20190909 62
 
0.6%
20180220 56
 
0.6%
Other values (2349) 9068
90.7%
ValueCountFrequency (%)
19910605 1
< 0.1%
19930907 1
< 0.1%
19971125 1
< 0.1%
19990104 1
< 0.1%
19990520 2
< 0.1%
19990721 1
< 0.1%
19990726 1
< 0.1%
19990831 1
< 0.1%
19991230 1
< 0.1%
20000127 1
< 0.1%
ValueCountFrequency (%)
20240318 1
 
< 0.1%
20240312 1
 
< 0.1%
20240308 1
 
< 0.1%
20240229 2
< 0.1%
20240215 2
< 0.1%
20240213 2
< 0.1%
20240205 4
< 0.1%
20240202 2
< 0.1%
20240131 3
< 0.1%
20240130 1
 
< 0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION 

Distinct5084
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9999182 × 1010
Minimum1.9650029 × 1010
Maximum2.0230042 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:24:56.150576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9650029 × 1010
5-th percentile1.9790029 × 1010
Q11.9950029 × 1010
median2.0010029 × 1010
Q32.006003 × 1010
95-th percentile2.016003 × 1010
Maximum2.0230042 × 1010
Range5.8001252 × 108
Interquartile range (IQR)1.1000045 × 108

Descriptive statistics

Standard deviation1.0262252 × 108
Coefficient of variation (CV)0.0051313357
Kurtosis0.54015445
Mean1.9999182 × 1010
Median Absolute Deviation (MAD)59999525
Skewness-0.6324371
Sum1.9999182 × 1014
Variance1.0531381 × 1016
MonotonicityNot monotonic
2024-05-18T15:24:56.878374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19980029330 70
 
0.7%
20000029177 48
 
0.5%
20140029044 37
 
0.4%
20160030050 36
 
0.4%
19920029370 36
 
0.4%
20010029090 34
 
0.3%
20140029422 34
 
0.3%
19990029864 27
 
0.3%
20070029567 25
 
0.2%
19990030704 24
 
0.2%
Other values (5074) 9629
96.3%
ValueCountFrequency (%)
19650029002 1
 
< 0.1%
19660029013 2
 
< 0.1%
19660029015 1
 
< 0.1%
19670029011 1
 
< 0.1%
19670029026 1
 
< 0.1%
19670029039 1
 
< 0.1%
19670029042 1
 
< 0.1%
19670029043 6
0.1%
19670029056 1
 
< 0.1%
19670029083 2
 
< 0.1%
ValueCountFrequency (%)
20230041525 1
 
< 0.1%
20230041202 1
 
< 0.1%
20230040830 1
 
< 0.1%
20230040763 2
< 0.1%
20230040423 4
< 0.1%
20230040184 1
 
< 0.1%
20230040137 1
 
< 0.1%
20220033328 1
 
< 0.1%
20220033254 1
 
< 0.1%
20220033077 1
 
< 0.1%

업종명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
5962 
유흥주점영업
1372 
휴게음식점
 
480
단란주점
 
453
즉석판매제조가공업
 
385
Other values (14)
1348 

Length

Max length13
Median length5
Mean length5.5498
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 5962
59.6%
유흥주점영업 1372
 
13.7%
휴게음식점 480
 
4.8%
단란주점 453
 
4.5%
즉석판매제조가공업 385
 
3.9%
식품소분업 337
 
3.4%
식품제조가공업 252
 
2.5%
식품등 수입판매업 232
 
2.3%
유통전문판매업 148
 
1.5%
건강기능식품일반판매업 136
 
1.4%
Other values (9) 243
 
2.4%

Length

2024-05-18T15:24:57.454946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 5962
58.3%
유흥주점영업 1372
 
13.4%
휴게음식점 480
 
4.7%
단란주점 453
 
4.4%
즉석판매제조가공업 385
 
3.8%
식품소분업 337
 
3.3%
식품제조가공업 252
 
2.5%
식품등 232
 
2.3%
수입판매업 232
 
2.3%
유통전문판매업 148
 
1.4%
Other values (10) 379
 
3.7%

업태명
Text

Distinct61
Distinct (%)0.6%
Missing16
Missing (%)0.2%
Memory size156.2 KiB
2024-05-18T15:24:58.175443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length3.6603566
Min length2

Characters and Unicode

Total characters36545
Distinct characters134
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row한식
2nd row중국식
3rd row한식
4th row전자상거래(통신판매업)
5th row한식
ValueCountFrequency (%)
한식 2739
26.6%
룸살롱 1092
 
10.6%
분식 858
 
8.3%
경양식 829
 
8.0%
기타 481
 
4.7%
단란주점 453
 
4.4%
즉석판매제조가공업 385
 
3.7%
식품소분업 337
 
3.3%
호프/통닭 318
 
3.1%
중국식 308
 
3.0%
Other values (51) 2504
24.3%
2024-05-18T15:24:59.216295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 6070
 
16.6%
한 2739
 
7.5%
업 1669
 
4.6%
분 1195
 
3.3%
롱 1118
 
3.1%
살 1118
 
3.1%
룸 1092
 
3.0%
판 1069
 
2.9%
매 1069
 
2.9%
품 893
 
2.4%
Other values (124) 18513
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35287
96.6%
Other Punctuation 574
 
1.6%
Space Separator 320
 
0.9%
Open Punctuation 182
 
0.5%
Close Punctuation 182
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 6070
 
17.2%
한 2739
 
7.8%
업 1669
 
4.7%
분 1195
 
3.4%
롱 1118
 
3.2%
살 1118
 
3.2%
룸 1092
 
3.1%
판 1069
 
3.0%
매 1069
 
3.0%
품 893
 
2.5%
Other values (118) 17255
48.9%
Other Punctuation
ValueCountFrequency (%)
/ 476
82.9%
, 53
 
9.2%
. 45
 
7.8%
Space Separator
ValueCountFrequency (%)
320
100.0%
Open Punctuation
ValueCountFrequency (%)
( 182
100.0%
Close Punctuation
ValueCountFrequency (%)
) 182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35287
96.6%
Common 1258
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 6070
 
17.2%
한 2739
 
7.8%
업 1669
 
4.7%
분 1195
 
3.4%
롱 1118
 
3.2%
살 1118
 
3.2%
룸 1092
 
3.1%
판 1069
 
3.0%
매 1069
 
3.0%
품 893
 
2.5%
Other values (118) 17255
48.9%
Common
ValueCountFrequency (%)
/ 476
37.8%
320
25.4%
( 182
 
14.5%
) 182
 
14.5%
, 53
 
4.2%
. 45
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35287
96.6%
ASCII 1258
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 6070
 
17.2%
한 2739
 
7.8%
업 1669
 
4.7%
분 1195
 
3.4%
롱 1118
 
3.2%
살 1118
 
3.2%
룸 1092
 
3.1%
판 1069
 
3.0%
매 1069
 
3.0%
품 893
 
2.5%
Other values (118) 17255
48.9%
ASCII
ValueCountFrequency (%)
/ 476
37.8%
320
25.4%
( 182
 
14.5%
) 182
 
14.5%
, 53
 
4.2%
. 45
 
3.6%

업소명
Text

Distinct4866
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T15:24:59.869591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length5.119
Min length1

Characters and Unicode

Total characters51190
Distinct characters941
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3115 ?
Unique (%)31.1%

Sample

1st row불타는다동화로
2nd row송경
3rd row차목원
4th row(주)와이즈머티리얼
5th row마르칸드
ValueCountFrequency (%)
명동점 71
 
0.6%
만선호프 69
 
0.6%
주식회사 57
 
0.5%
동국 37
 
0.3%
본푸드 37
 
0.3%
미래식품 36
 
0.3%
엘본더테이블 36
 
0.3%
둘둘치킨 35
 
0.3%
명동교자 29
 
0.3%
동아물산 27
 
0.2%
Other values (5235) 10989
96.2%
2024-05-18T15:25:01.106858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1433
 
2.8%
주 1109
 
2.2%
이 1063
 
2.1%
스 1043
 
2.0%
( 980
 
1.9%
) 978
 
1.9%
동 851
 
1.7%
점 842
 
1.6%
식 785
 
1.5%
리 745
 
1.5%
Other values (931) 41361
80.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45423
88.7%
Space Separator 1433
 
2.8%
Uppercase Letter 1037
 
2.0%
Open Punctuation 980
 
1.9%
Close Punctuation 978
 
1.9%
Lowercase Letter 702
 
1.4%
Decimal Number 335
 
0.7%
Other Punctuation 262
 
0.5%
Dash Punctuation 34
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1109
 
2.4%
이 1063
 
2.3%
스 1043
 
2.3%
동 851
 
1.9%
점 842
 
1.9%
식 785
 
1.7%
리 745
 
1.6%
아 478
 
1.1%
가 463
 
1.0%
호 450
 
1.0%
Other values (852) 37594
82.8%
Uppercase Letter
ValueCountFrequency (%)
B 82
 
7.9%
A 79
 
7.6%
O 77
 
7.4%
M 62
 
6.0%
C 60
 
5.8%
L 59
 
5.7%
N 58
 
5.6%
S 51
 
4.9%
I 49
 
4.7%
T 41
 
4.0%
Other values (16) 419
40.4%
Lowercase Letter
ValueCountFrequency (%)
a 96
13.7%
e 87
12.4%
o 73
 
10.4%
r 44
 
6.3%
n 38
 
5.4%
c 36
 
5.1%
s 35
 
5.0%
i 29
 
4.1%
t 29
 
4.1%
u 28
 
4.0%
Other values (15) 207
29.5%
Other Punctuation
ValueCountFrequency (%)
. 161
61.5%
& 41
 
15.6%
, 21
 
8.0%
; 13
 
5.0%
? 7
 
2.7%
' 7
 
2.7%
# 5
 
1.9%
! 4
 
1.5%
@ 2
 
0.8%
/ 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 95
28.4%
0 53
15.8%
1 53
15.8%
5 29
 
8.7%
7 24
 
7.2%
8 22
 
6.6%
4 16
 
4.8%
6 15
 
4.5%
3 15
 
4.5%
9 13
 
3.9%
Letter Number
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅱ 1
25.0%
Ⅰ 1
25.0%
Space Separator
ValueCountFrequency (%)
1433
100.0%
Open Punctuation
ValueCountFrequency (%)
( 980
100.0%
Close Punctuation
ValueCountFrequency (%)
) 978
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45405
88.7%
Common 4024
 
7.9%
Latin 1743
 
3.4%
Han 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1109
 
2.4%
이 1063
 
2.3%
스 1043
 
2.3%
동 851
 
1.9%
점 842
 
1.9%
식 785
 
1.7%
리 745
 
1.6%
아 478
 
1.1%
가 463
 
1.0%
호 450
 
1.0%
Other values (843) 37576
82.8%
Latin
ValueCountFrequency (%)
a 96
 
5.5%
e 87
 
5.0%
B 82
 
4.7%
A 79
 
4.5%
O 77
 
4.4%
o 73
 
4.2%
M 62
 
3.6%
C 60
 
3.4%
L 59
 
3.4%
N 58
 
3.3%
Other values (44) 1010
57.9%
Common
ValueCountFrequency (%)
1433
35.6%
( 980
24.4%
) 978
24.3%
. 161
 
4.0%
2 95
 
2.4%
0 53
 
1.3%
1 53
 
1.3%
& 41
 
1.0%
- 34
 
0.8%
5 29
 
0.7%
Other values (15) 167
 
4.2%
Han
ValueCountFrequency (%)
土 6
33.3%
家 4
22.2%
源 2
 
11.1%
高 1
 
5.6%
校 1
 
5.6%
福 1
 
5.6%
三 1
 
5.6%
金 1
 
5.6%
新 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45405
88.7%
ASCII 5763
 
11.3%
CJK 18
 
< 0.1%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1433
24.9%
( 980
17.0%
) 978
17.0%
. 161
 
2.8%
a 96
 
1.7%
2 95
 
1.6%
e 87
 
1.5%
B 82
 
1.4%
A 79
 
1.4%
O 77
 
1.3%
Other values (66) 1695
29.4%
Hangul
ValueCountFrequency (%)
주 1109
 
2.4%
이 1063
 
2.3%
스 1043
 
2.3%
동 851
 
1.9%
점 842
 
1.9%
식 785
 
1.7%
리 745
 
1.6%
아 478
 
1.1%
가 463
 
1.0%
호 450
 
1.0%
Other values (843) 37576
82.8%
CJK
ValueCountFrequency (%)
土 6
33.3%
家 4
22.2%
源 2
 
11.1%
高 1
 
5.6%
校 1
 
5.6%
福 1
 
5.6%
三 1
 
5.6%
金 1
 
5.6%
新 1
 
5.6%
Number Forms
ValueCountFrequency (%)
Ⅲ 2
50.0%
Ⅱ 1
25.0%
Ⅰ 1
25.0%

소재지도로명
Text

MISSING 

Distinct1828
Distinct (%)49.4%
Missing6302
Missing (%)63.0%
Memory size156.2 KiB
2024-05-18T15:25:01.984053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length58
Mean length32.202542
Min length20

Characters and Unicode

Total characters119085
Distinct characters317
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1196 ?
Unique (%)32.3%

Sample

1st row서울특별시 중구 을지로3길 33, (다동,(지상1층))
2nd row서울특별시 중구 필동로 35-18, (필동3가)
3rd row서울특별시 중구 동호로 171, (신당동)
4th row서울특별시 중구 충무로2길 16, (충무로4가)
5th row서울특별시 중구 을지로44길 12, (광희동1가,뉴금호타워 201호)
ValueCountFrequency (%)
서울특별시 3698
 
16.9%
중구 3698
 
16.9%
1층 802
 
3.7%
신당동 382
 
1.7%
2층 240
 
1.1%
지하1층 221
 
1.0%
퇴계로 204
 
0.9%
21 165
 
0.8%
황학동 160
 
0.7%
을지로3가 136
 
0.6%
Other values (1846) 12166
55.6%
2024-05-18T15:25:03.518527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18189
 
15.3%
, 6355
 
5.3%
1 5934
 
5.0%
) 4514
 
3.8%
( 4514
 
3.8%
로 4356
 
3.7%
2 3995
 
3.4%
서 3963
 
3.3%
시 3909
 
3.3%
중 3820
 
3.2%
Other values (307) 59536
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63996
53.7%
Decimal Number 20352
 
17.1%
Space Separator 18189
 
15.3%
Other Punctuation 6411
 
5.4%
Close Punctuation 4514
 
3.8%
Open Punctuation 4514
 
3.8%
Dash Punctuation 809
 
0.7%
Uppercase Letter 214
 
0.2%
Math Symbol 79
 
0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4356
 
6.8%
서 3963
 
6.2%
시 3909
 
6.1%
중 3820
 
6.0%
구 3773
 
5.9%
울 3756
 
5.9%
특 3717
 
5.8%
별 3698
 
5.8%
동 3364
 
5.3%
층 2796
 
4.4%
Other values (265) 26844
41.9%
Uppercase Letter
ValueCountFrequency (%)
B 68
31.8%
A 30
14.0%
C 25
 
11.7%
D 15
 
7.0%
E 10
 
4.7%
H 8
 
3.7%
F 8
 
3.7%
K 8
 
3.7%
T 7
 
3.3%
Y 7
 
3.3%
Other values (9) 28
13.1%
Decimal Number
ValueCountFrequency (%)
1 5934
29.2%
2 3995
19.6%
3 2481
12.2%
4 1547
 
7.6%
5 1325
 
6.5%
0 1270
 
6.2%
6 1034
 
5.1%
8 996
 
4.9%
7 911
 
4.5%
9 859
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 6355
99.1%
. 45
 
0.7%
/ 6
 
0.1%
？ 5
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
p 2
28.6%
m 2
28.6%
a 2
28.6%
e 1
14.3%
Space Separator
ValueCountFrequency (%)
18189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4514
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4514
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 809
100.0%
Math Symbol
ValueCountFrequency (%)
~ 79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63996
53.7%
Common 54868
46.1%
Latin 221
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4356
 
6.8%
서 3963
 
6.2%
시 3909
 
6.1%
중 3820
 
6.0%
구 3773
 
5.9%
울 3756
 
5.9%
특 3717
 
5.8%
별 3698
 
5.8%
동 3364
 
5.3%
층 2796
 
4.4%
Other values (265) 26844
41.9%
Latin
ValueCountFrequency (%)
B 68
30.8%
A 30
13.6%
C 25
 
11.3%
D 15
 
6.8%
E 10
 
4.5%
H 8
 
3.6%
F 8
 
3.6%
K 8
 
3.6%
T 7
 
3.2%
Y 7
 
3.2%
Other values (13) 35
15.8%
Common
ValueCountFrequency (%)
18189
33.2%
, 6355
 
11.6%
1 5934
 
10.8%
) 4514
 
8.2%
( 4514
 
8.2%
2 3995
 
7.3%
3 2481
 
4.5%
4 1547
 
2.8%
5 1325
 
2.4%
0 1270
 
2.3%
Other values (9) 4744
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63996
53.7%
ASCII 55084
46.3%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18189
33.0%
, 6355
 
11.5%
1 5934
 
10.8%
) 4514
 
8.2%
( 4514
 
8.2%
2 3995
 
7.3%
3 2481
 
4.5%
4 1547
 
2.8%
5 1325
 
2.4%
0 1270
 
2.3%
Other values (31) 4960
 
9.0%
Hangul
ValueCountFrequency (%)
로 4356
 
6.8%
서 3963
 
6.2%
시 3909
 
6.1%
중 3820
 
6.0%
구 3773
 
5.9%
울 3756
 
5.9%
특 3717
 
5.8%
별 3698
 
5.8%
동 3364
 
5.3%
층 2796
 
4.4%
Other values (265) 26844
41.9%
None
ValueCountFrequency (%)
？ 5
100.0%

소재지지번
Text

Distinct4493
Distinct (%)44.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-18T15:25:04.460229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length62
Mean length28.370337
Min length19

Characters and Unicode

Total characters283675
Distinct characters353
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2764 ?
Unique (%)27.6%

Sample

1st row서울특별시 중구 다동 128번지 0호 (지상1층)
2nd row서울특별시 중구 을지로4가 310번지 11호 (지상1층)
3rd row서울특별시 중구 필동3가 54번지 0호
4th row서울특별시 중구 신당동 372번지 3호
5th row서울특별시 중구 광희동1가 115번지 0호 지상1층
ValueCountFrequency (%)
서울특별시 9999
 
17.7%
중구 9999
 
17.7%
신당동 1645
 
2.9%
1호 1323
 
2.3%
0호 1157
 
2.0%
1층 1118
 
2.0%
2호 750
 
1.3%
지하1층 701
 
1.2%
지상1층 633
 
1.1%
3호 624
 
1.1%
Other values (2140) 28562
50.5%
2024-05-18T15:25:05.912774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70917
25.0%
지 14622
 
5.2%
1 14558
 
5.1%
서 10256
 
3.6%
중 10231
 
3.6%
시 10114
 
3.6%
울 10077
 
3.6%
구 10066
 
3.5%
특 10021
 
3.5%
별 10005
 
3.5%
Other values (343) 112808
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154341
54.4%
Space Separator 70917
25.0%
Decimal Number 52112
 
18.4%
Close Punctuation 2191
 
0.8%
Open Punctuation 2191
 
0.8%
Other Punctuation 1066
 
0.4%
Dash Punctuation 370
 
0.1%
Uppercase Letter 309
 
0.1%
Math Symbol 170
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 14622
 
9.5%
서 10256
 
6.6%
중 10231
 
6.6%
시 10114
 
6.6%
울 10077
 
6.5%
구 10066
 
6.5%
특 10021
 
6.5%
별 10005
 
6.5%
번 10004
 
6.5%
호 9803
 
6.4%
Other values (300) 49142
31.8%
Uppercase Letter
ValueCountFrequency (%)
B 91
29.4%
A 49
15.9%
C 46
14.9%
D 39
12.6%
E 12
 
3.9%
K 12
 
3.9%
F 9
 
2.9%
S 8
 
2.6%
Y 8
 
2.6%
G 7
 
2.3%
Other values (8) 28
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 14558
27.9%
2 9109
17.5%
3 5566
 
10.7%
0 4166
 
8.0%
5 3922
 
7.5%
4 3871
 
7.4%
6 3083
 
5.9%
9 2682
 
5.1%
8 2650
 
5.1%
7 2505
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 964
90.4%
. 66
 
6.2%
/ 29
 
2.7%
？ 5
 
0.5%
? 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
a 2
25.0%
p 2
25.0%
m 2
25.0%
e 1
12.5%
i 1
12.5%
Space Separator
ValueCountFrequency (%)
70917
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2191
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2191
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 370
100.0%
Math Symbol
ValueCountFrequency (%)
~ 170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154340
54.4%
Common 129017
45.5%
Latin 317
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 14622
 
9.5%
서 10256
 
6.6%
중 10231
 
6.6%
시 10114
 
6.6%
울 10077
 
6.5%
구 10066
 
6.5%
특 10021
 
6.5%
별 10005
 
6.5%
번 10004
 
6.5%
호 9803
 
6.4%
Other values (299) 49141
31.8%
Latin
ValueCountFrequency (%)
B 91
28.7%
A 49
15.5%
C 46
14.5%
D 39
12.3%
E 12
 
3.8%
K 12
 
3.8%
F 9
 
2.8%
S 8
 
2.5%
Y 8
 
2.5%
G 7
 
2.2%
Other values (13) 36
 
11.4%
Common
ValueCountFrequency (%)
70917
55.0%
1 14558
 
11.3%
2 9109
 
7.1%
3 5566
 
4.3%
0 4166
 
3.2%
5 3922
 
3.0%
4 3871
 
3.0%
6 3083
 
2.4%
9 2682
 
2.1%
8 2650
 
2.1%
Other values (10) 8493
 
6.6%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154340
54.4%
ASCII 129329
45.6%
None 5
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70917
54.8%
1 14558
 
11.3%
2 9109
 
7.0%
3 5566
 
4.3%
0 4166
 
3.2%
5 3922
 
3.0%
4 3871
 
3.0%
6 3083
 
2.4%
9 2682
 
2.1%
8 2650
 
2.0%
Other values (32) 8805
 
6.8%
Hangul
ValueCountFrequency (%)
지 14622
 
9.5%
서 10256
 
6.6%
중 10231
 
6.6%
시 10114
 
6.6%
울 10077
 
6.5%
구 10066
 
6.5%
특 10021
 
6.5%
별 10005
 
6.5%
번 10004
 
6.5%
호 9803
 
6.4%
Other values (299) 49141
31.8%
None
ValueCountFrequency (%)
？ 5
100.0%
CJK
ValueCountFrequency (%)
內 1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2659
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20106769
Minimum19910605
Maximum20240318
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:25:06.516425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19910605
5-th percentile20020502
Q120041109
median20090810
Q320170808
95-th percentile20230405
Maximum20240318
Range329713
Interquartile range (IQR)129699.25

Descriptive statistics

Standard deviation69919.638
Coefficient of variation (CV)0.0034774178
Kurtosis-1.1602661
Mean20106769
Median Absolute Deviation (MAD)60197
Skewness0.36115141
Sum2.0106769 × 1011
Variance4.8887558 × 109
MonotonicityNot monotonic
2024-05-18T15:25:06.967513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021126 163
 
1.6%
20230331 142
 
1.4%
20021128 128
 
1.3%
20081024 102
 
1.0%
20101231 96
 
1.0%
20120102 86
 
0.9%
20230330 85
 
0.9%
20081218 79
 
0.8%
20021202 75
 
0.8%
20091001 62
 
0.6%
Other values (2649) 8982
89.8%
ValueCountFrequency (%)
19910605 1
< 0.1%
19930907 1
< 0.1%
19970601 1
< 0.1%
19971125 1
< 0.1%
19990104 1
< 0.1%
19990520 2
< 0.1%
19990721 1
< 0.1%
19990726 1
< 0.1%
19990813 1
< 0.1%
19991230 1
< 0.1%
ValueCountFrequency (%)
20240318 1
 
< 0.1%
20240228 2
 
< 0.1%
20240226 1
 
< 0.1%
20240221 1
 
< 0.1%
20240216 1
 
< 0.1%
20240213 2
 
< 0.1%
20240201 2
 
< 0.1%
20240131 2
 
< 0.1%
20240130 1
 
< 0.1%
20240124 6
0.1%

행정처분상태
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
처분확정 10000
100.0%

Length

2024-05-18T15:25:07.457218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:25:07.734438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%

처분명
Text

Distinct1285
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T15:25:08.187480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length101
Mean length9.6612
Min length2

Characters and Unicode

Total characters96612
Distinct characters242
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique714 ?
Unique (%)7.1%

Sample

1st row시정명령
2nd row과태료부과(16만원)
3rd row직권말소
4th row영업소폐쇄
5th row영업소폐쇄
ValueCountFrequency (%)
시정명령 1865
 
13.8%
영업소폐쇄 1598
 
11.8%
과태료부과 944
 
7.0%
영업정지 566
 
4.2%
직권말소 501
 
3.7%
시설개수명령 467
 
3.4%
부과 266
 
2.0%
과태료 248
 
1.8%
과징금 180
 
1.3%
원 179
 
1.3%
Other values (1577) 6746
49.7%
2024-05-18T15:25:09.357723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 6509
 
6.7%
0 5417
 
5.6%
정 4489
 
4.6%
업 4226
 
4.4%
영 4201
 
4.3%
3572
 
3.7%
2 3521
 
3.6%
원 2975
 
3.1%
시 2926
 
3.0%
부 2864
 
3.0%
Other values (232) 55912
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68403
70.8%
Decimal Number 17627
 
18.2%
Space Separator 3572
 
3.7%
Other Punctuation 2637
 
2.7%
Close Punctuation 1886
 
2.0%
Open Punctuation 1883
 
1.9%
Math Symbol 319
 
0.3%
Dash Punctuation 285
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.1%
원 2975
 
4.3%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.0%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (207) 31942
46.7%
Decimal Number
ValueCountFrequency (%)
0 5417
30.7%
2 3521
20.0%
1 2857
16.2%
3 1304
 
7.4%
5 1271
 
7.2%
4 845
 
4.8%
6 779
 
4.4%
7 718
 
4.1%
8 585
 
3.3%
9 330
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 2157
81.8%
, 363
 
13.8%
% 51
 
1.9%
/ 40
 
1.5%
: 22
 
0.8%
* 2
 
0.1%
; 1
 
< 0.1%
※ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 310
97.2%
> 5
 
1.6%
→ 4
 
1.3%
Space Separator
ValueCountFrequency (%)
3572
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1886
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1883
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68403
70.8%
Common 28209
29.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.1%
원 2975
 
4.3%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.0%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (207) 31942
46.7%
Common
ValueCountFrequency (%)
0 5417
19.2%
3572
12.7%
2 3521
12.5%
1 2857
10.1%
. 2157
 
7.6%
) 1886
 
6.7%
( 1883
 
6.7%
3 1304
 
4.6%
5 1271
 
4.5%
4 845
 
3.0%
Other values (15) 3496
12.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68246
70.6%
ASCII 28204
29.2%
Compat Jamo 157
 
0.2%
Arrows 4
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.2%
원 2975
 
4.4%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.1%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (206) 31785
46.6%
ASCII
ValueCountFrequency (%)
0 5417
19.2%
3572
12.7%
2 3521
12.5%
1 2857
10.1%
. 2157
 
7.6%
) 1886
 
6.7%
( 1883
 
6.7%
3 1304
 
4.6%
5 1271
 
4.5%
4 845
 
3.0%
Other values (13) 3491
12.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 157
100.0%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

법적근거
Text

Distinct1022
Distinct (%)10.3%
Missing45
Missing (%)0.4%
Memory size156.2 KiB
2024-05-18T15:25:09.945863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length55
Mean length14.960824
Min length1

Characters and Unicode

Total characters148935
Distinct characters158
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique520 ?
Unique (%)5.2%

Sample

1st row법 제71조, 법 제74조 및 법 제75조
2nd row식품위생법제78조,동법시행령56조,동법시행규칙54조
3rd row법 제37조 7항
4th row건강기능식품에 관한 법률 제32조
5th row식품위생법 제36조
ValueCountFrequency (%)
법 6556
23.1%
식품위생법 2355
 
8.3%
및 2193
 
7.7%
제75조 1874
 
6.6%
제71조 1623
 
5.7%
제76조 707
 
2.5%
제74조 664
 
2.3%
식품위생법제58조 632
 
2.2%
제37조 623
 
2.2%
7항 582
 
2.1%
Other values (856) 10513
37.1%
2024-05-18T15:25:11.234771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18433
12.4%
제 17152
11.5%
조 15530
 
10.4%
법 14677
 
9.9%
7 8272
 
5.6%
1 7424
 
5.0%
위 7249
 
4.9%
품 6193
 
4.2%
식 6167
 
4.1%
생 6121
 
4.1%
Other values (148) 41717
28.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90092
60.5%
Decimal Number 34520
 
23.2%
Space Separator 18433
 
12.4%
Other Punctuation 3389
 
2.3%
Close Punctuation 1250
 
0.8%
Open Punctuation 1250
 
0.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 17152
19.0%
조 15530
17.2%
법 14677
16.3%
위 7249
8.0%
품 6193
 
6.9%
식 6167
 
6.8%
생 6121
 
6.8%
및 2299
 
2.6%
항 2171
 
2.4%
반 1125
 
1.2%
Other values (128) 11408
12.7%
Decimal Number
ValueCountFrequency (%)
7 8272
24.0%
1 7424
21.5%
5 4600
13.3%
2 3454
10.0%
3 3003
 
8.7%
4 2460
 
7.1%
6 2009
 
5.8%
8 1974
 
5.7%
0 1267
 
3.7%
9 57
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 3362
99.2%
' 14
 
0.4%
? 6
 
0.2%
. 4
 
0.1%
* 2
 
0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
18433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1250
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90092
60.5%
Common 58843
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 17152
19.0%
조 15530
17.2%
법 14677
16.3%
위 7249
8.0%
품 6193
 
6.9%
식 6167
 
6.8%
생 6121
 
6.8%
및 2299
 
2.6%
항 2171
 
2.4%
반 1125
 
1.2%
Other values (128) 11408
12.7%
Common
ValueCountFrequency (%)
18433
31.3%
7 8272
14.1%
1 7424
12.6%
5 4600
 
7.8%
2 3454
 
5.9%
, 3362
 
5.7%
3 3003
 
5.1%
4 2460
 
4.2%
6 2009
 
3.4%
8 1974
 
3.4%
Other values (10) 3852
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90092
60.5%
ASCII 58843
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18433
31.3%
7 8272
14.1%
1 7424
12.6%
5 4600
 
7.8%
2 3454
 
5.9%
, 3362
 
5.7%
3 3003
 
5.1%
4 2460
 
4.2%
6 2009
 
3.4%
8 1974
 
3.4%
Other values (10) 3852
 
6.5%
Hangul
ValueCountFrequency (%)
제 17152
19.0%
조 15530
17.2%
법 14677
16.3%
위 7249
8.0%
품 6193
 
6.9%
식 6167
 
6.8%
생 6121
 
6.8%
및 2299
 
2.6%
항 2171
 
2.4%
반 1125
 
1.2%
Other values (128) 11408
12.7%

위반일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2914
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20094231
Minimum2006102
Maximum29920928
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:25:11.738476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006102
5-th percentile20020404
Q120040814
median20090424
Q320161209
95-th percentile20230330
Maximum29920928
Range27914826
Interquartile range (IQR)120395.25

Descriptive statistics

Standard deviation522276.99
Coefficient of variation (CV)0.02599139
Kurtosis1031.8183
Mean20094231
Median Absolute Deviation (MAD)59798
Skewness-25.933825
Sum2.0094231 × 1011
Variance2.7277325 × 1011
MonotonicityNot monotonic
2024-05-18T15:25:12.155219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20021126 161
 
1.6%
20021128 128
 
1.3%
20101231 100
 
1.0%
20111231 82
 
0.8%
20230330 79
 
0.8%
20021202 75
 
0.8%
20080326 67
 
0.7%
20091001 62
 
0.6%
20110101 48
 
0.5%
20230524 47
 
0.5%
Other values (2904) 9151
91.5%
ValueCountFrequency (%)
2006102 2
< 0.1%
2021126 1
 
< 0.1%
2170302 3
< 0.1%
2170622 1
 
< 0.1%
19651231 1
 
< 0.1%
19861028 1
 
< 0.1%
19861231 1
 
< 0.1%
19870420 1
 
< 0.1%
19891231 1
 
< 0.1%
19900630 1
 
< 0.1%
ValueCountFrequency (%)
29920928 3
< 0.1%
28001230 2
< 0.1%
20240318 1
 
< 0.1%
20240228 2
< 0.1%
20240226 1
 
< 0.1%
20240221 1
 
< 0.1%
20240213 2
< 0.1%
20240206 1
 
< 0.1%
20240201 2
< 0.1%
20240131 2
< 0.1%

위반내용
Text

Distinct3125
Distinct (%)31.3%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-18T15:25:12.786084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length336
Median length172
Mean length19.313831
Min length1

Characters and Unicode

Total characters193119
Distinct characters692
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1855 ?
Unique (%)18.6%

Sample

1st row영업장면적 무단변경
2nd row조리장위생불량(서울시적발)
3rd row사업자등록 폐업
4th row6개월이상 무단휴업
5th row영업장 멸실
ValueCountFrequency (%)
영업시설물 751
 
2.4%
멸실 732
 
2.3%
하지 517
 
1.6%
영업장 515
 
1.6%
489
 
1.5%
건강진단 472
 
1.5%
6개월이상 460
 
1.4%
사업자등록 413
 
1.3%
미이수 401
 
1.3%
미필 396
 
1.2%
Other values (4685) 26756
83.9%
2024-05-18T15:25:14.436585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23887
 
12.4%
업 7737
 
4.0%
영 3916
 
2.0%
0 3708
 
1.9%
미 3647
 
1.9%
시 3361
 
1.7%
2 3290
 
1.7%
1 3283
 
1.7%
- 2980
 
1.5%
) 2938
 
1.5%
Other values (682) 134372
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 140137
72.6%
Space Separator 23887
 
12.4%
Decimal Number 15929
 
8.2%
Other Punctuation 3824
 
2.0%
Close Punctuation 3010
 
1.6%
Open Punctuation 3000
 
1.6%
Dash Punctuation 2980
 
1.5%
Lowercase Letter 178
 
0.1%
Uppercase Letter 134
 
0.1%
Math Symbol 18
 
< 0.1%
Other values (4) 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 7737
 
5.5%
영 3916
 
2.8%
미 3647
 
2.6%
시 3361
 
2.4%
장 2876
 
2.1%
기 2766
 
2.0%
단 2676
 
1.9%
위 2489
 
1.8%
이 2390
 
1.7%
물 2233
 
1.6%
Other values (608) 106046
75.7%
Uppercase Letter
ValueCountFrequency (%)
E 19
14.2%
A 14
10.4%
O 12
 
9.0%
R 12
 
9.0%
L 9
 
6.7%
T 8
 
6.0%
P 8
 
6.0%
S 7
 
5.2%
N 6
 
4.5%
B 5
 
3.7%
Other values (11) 34
25.4%
Lowercase Letter
ValueCountFrequency (%)
g 51
28.7%
o 24
13.5%
m 23
12.9%
l 16
 
9.0%
k 15
 
8.4%
n 10
 
5.6%
i 10
 
5.6%
e 10
 
5.6%
y 5
 
2.8%
u 5
 
2.8%
Other values (3) 9
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 1941
50.8%
/ 719
 
18.8%
, 617
 
16.1%
: 407
 
10.6%
? 50
 
1.3%
' 42
 
1.1%
% 16
 
0.4%
* 15
 
0.4%
; 12
 
0.3%
@ 4
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 3708
23.3%
2 3290
20.7%
1 3283
20.6%
6 1488
9.3%
3 1098
 
6.9%
4 806
 
5.1%
5 698
 
4.4%
7 557
 
3.5%
9 510
 
3.2%
8 491
 
3.1%
Math Symbol
ValueCountFrequency (%)
= 6
33.3%
+ 4
22.2%
→ 3
16.7%
> 2
 
11.1%
~ 2
 
11.1%
< 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 2938
97.6%
] 53
 
1.8%
」 19
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 2935
97.8%
[ 53
 
1.8%
「 12
 
0.4%
Other Symbol
ValueCountFrequency (%)
○ 2
66.7%
㈜ 1
33.3%
Space Separator
ValueCountFrequency (%)
23887
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2980
100.0%
Final Punctuation
ValueCountFrequency (%)
” 8
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 140133
72.6%
Common 52669
 
27.3%
Latin 312
 
0.2%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 7737
 
5.5%
영 3916
 
2.8%
미 3647
 
2.6%
시 3361
 
2.4%
장 2876
 
2.1%
기 2766
 
2.0%
단 2676
 
1.9%
위 2489
 
1.8%
이 2390
 
1.7%
물 2233
 
1.6%
Other values (606) 106042
75.7%
Common
ValueCountFrequency (%)
23887
45.4%
0 3708
 
7.0%
2 3290
 
6.2%
1 3283
 
6.2%
- 2980
 
5.7%
) 2938
 
5.6%
( 2935
 
5.6%
. 1941
 
3.7%
6 1488
 
2.8%
3 1098
 
2.1%
Other values (29) 5121
 
9.7%
Latin
ValueCountFrequency (%)
g 51
16.3%
o 24
 
7.7%
m 23
 
7.4%
E 19
 
6.1%
l 16
 
5.1%
k 15
 
4.8%
A 14
 
4.5%
O 12
 
3.8%
R 12
 
3.8%
n 10
 
3.2%
Other values (24) 116
37.2%
Han
ValueCountFrequency (%)
類 2
40.0%
酒 2
40.0%
人 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 140131
72.6%
ASCII 52928
 
27.4%
None 33
 
< 0.1%
Punctuation 16
 
< 0.1%
CJK 5
 
< 0.1%
Arrows 3
 
< 0.1%
Geometric Shapes 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23887
45.1%
0 3708
 
7.0%
2 3290
 
6.2%
1 3283
 
6.2%
- 2980
 
5.6%
) 2938
 
5.6%
( 2935
 
5.5%
. 1941
 
3.7%
6 1488
 
2.8%
3 1098
 
2.1%
Other values (56) 5380
 
10.2%
Hangul
ValueCountFrequency (%)
업 7737
 
5.5%
영 3916
 
2.8%
미 3647
 
2.6%
시 3361
 
2.4%
장 2876
 
2.1%
기 2766
 
2.0%
단 2676
 
1.9%
위 2489
 
1.8%
이 2390
 
1.7%
물 2233
 
1.6%
Other values (604) 106040
75.7%
None
ValueCountFrequency (%)
」 19
57.6%
「 12
36.4%
㈜ 1
 
3.0%
？ 1
 
3.0%
Punctuation
ValueCountFrequency (%)
” 8
50.0%
“ 8
50.0%
Arrows
ValueCountFrequency (%)
→ 3
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 2
100.0%
CJK
ValueCountFrequency (%)
類 2
40.0%
酒 2
40.0%
人 1
20.0%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
100.0%

처분내용
Text

Distinct1285
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T15:25:15.118428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length101
Mean length9.6612
Min length2

Characters and Unicode

Total characters96612
Distinct characters242
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique714 ?
Unique (%)7.1%

Sample

1st row시정명령
2nd row과태료부과(16만원)
3rd row직권말소
4th row영업소폐쇄
5th row영업소폐쇄
ValueCountFrequency (%)
시정명령 1865
 
13.8%
영업소폐쇄 1598
 
11.8%
과태료부과 944
 
7.0%
영업정지 566
 
4.2%
직권말소 501
 
3.7%
시설개수명령 467
 
3.4%
부과 266
 
2.0%
과태료 248
 
1.8%
과징금 180
 
1.3%
원 179
 
1.3%
Other values (1577) 6746
49.7%
2024-05-18T15:25:16.538326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 6509
 
6.7%
0 5417
 
5.6%
정 4489
 
4.6%
업 4226
 
4.4%
영 4201
 
4.3%
3572
 
3.7%
2 3521
 
3.6%
원 2975
 
3.1%
시 2926
 
3.0%
부 2864
 
3.0%
Other values (232) 55912
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68403
70.8%
Decimal Number 17627
 
18.2%
Space Separator 3572
 
3.7%
Other Punctuation 2637
 
2.7%
Close Punctuation 1886
 
2.0%
Open Punctuation 1883
 
1.9%
Math Symbol 319
 
0.3%
Dash Punctuation 285
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.1%
원 2975
 
4.3%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.0%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (207) 31942
46.7%
Decimal Number
ValueCountFrequency (%)
0 5417
30.7%
2 3521
20.0%
1 2857
16.2%
3 1304
 
7.4%
5 1271
 
7.2%
4 845
 
4.8%
6 779
 
4.4%
7 718
 
4.1%
8 585
 
3.3%
9 330
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 2157
81.8%
, 363
 
13.8%
% 51
 
1.9%
/ 40
 
1.5%
: 22
 
0.8%
* 2
 
0.1%
; 1
 
< 0.1%
※ 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 310
97.2%
> 5
 
1.6%
→ 4
 
1.3%
Space Separator
ValueCountFrequency (%)
3572
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1886
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1883
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68403
70.8%
Common 28209
29.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.1%
원 2975
 
4.3%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.0%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (207) 31942
46.7%
Common
ValueCountFrequency (%)
0 5417
19.2%
3572
12.7%
2 3521
12.5%
1 2857
10.1%
. 2157
 
7.6%
) 1886
 
6.7%
( 1883
 
6.7%
3 1304
 
4.6%
5 1271
 
4.5%
4 845
 
3.0%
Other values (15) 3496
12.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68246
70.6%
ASCII 28204
29.2%
Compat Jamo 157
 
0.2%
Arrows 4
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 6509
 
9.5%
정 4489
 
6.6%
업 4226
 
6.2%
영 4201
 
6.2%
원 2975
 
4.4%
시 2926
 
4.3%
부 2864
 
4.2%
료 2767
 
4.1%
태 2756
 
4.0%
소 2748
 
4.0%
Other values (206) 31785
46.6%
ASCII
ValueCountFrequency (%)
0 5417
19.2%
3572
12.7%
2 3521
12.5%
1 2857
10.1%
. 2157
 
7.6%
) 1886
 
6.7%
( 1883
 
6.7%
3 1304
 
4.6%
5 1271
 
4.5%
4 845
 
3.0%
Other values (13) 3491
12.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 157
100.0%
Arrows
ValueCountFrequency (%)
→ 4
100.0%
Punctuation
ValueCountFrequency (%)
※ 1
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)2.3%
Missing8851
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean11.491732
Minimum0
Maximum45
Zeros59
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:25:16.981817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q315
95-th percentile20
Maximum45
Range45
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.7277954
Coefficient of variation (CV)0.49842752
Kurtosis0.82197775
Mean11.491732
Median Absolute Deviation (MAD)5
Skewness0.16308147
Sum13204
Variance32.807641
MonotonicityNot monotonic
2024-05-18T15:25:17.716637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15 490
 
4.9%
7 306
 
3.1%
0 59
 
0.6%
10 48
 
0.5%
20 42
 
0.4%
5 26
 
0.3%
3 23
 
0.2%
8 23
 
0.2%
17 18
 
0.2%
2 17
 
0.2%
Other values (17) 97
 
1.0%
(Missing) 8851
88.5%
ValueCountFrequency (%)
0 59
 
0.6%
1 2
 
< 0.1%
2 17
 
0.2%
3 23
 
0.2%
4 5
 
0.1%
5 26
 
0.3%
6 6
 
0.1%
7 306
3.1%
8 23
 
0.2%
10 48
 
0.5%
ValueCountFrequency (%)
45 1
 
< 0.1%
30 8
 
0.1%
29 1
 
< 0.1%
26 1
 
< 0.1%
25 9
 
0.1%
23 2
 
< 0.1%
22 12
 
0.1%
21 5
 
0.1%
20 42
0.4%
19 6
 
0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct2340
Distinct (%)45.2%
Missing4824
Missing (%)48.2%
Infinite0
Infinite (%)0.0%
Mean119.16284
Minimum0
Maximum5251.98
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T15:25:18.188036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.9375
Q136.17
median72.84
Q3116.3375
95-th percentile394.6
Maximum5251.98
Range5251.98
Interquartile range (IQR)80.1675

Descriptive statistics

Standard deviation220.95595
Coefficient of variation (CV)1.8542354
Kurtosis164.00864
Mean119.16284
Median Absolute Deviation (MAD)39.27
Skewness10.208697
Sum616786.84
Variance48821.531
MonotonicityNot monotonic
2024-05-18T15:25:18.831162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.07 36
 
0.4%
19.8 25
 
0.2%
14.5 22
 
0.2%
256.46 22
 
0.2%
33.0 21
 
0.2%
15.0 20
 
0.2%
68.02 17
 
0.2%
101.42 16
 
0.2%
12.87 16
 
0.2%
82.95 16
 
0.2%
Other values (2330) 4965
49.6%
(Missing) 4824
48.2%
ValueCountFrequency (%)
0.0 6
0.1%
0.8 1
 
< 0.1%
1.0 1
 
< 0.1%
1.5 1
 
< 0.1%
1.7 1
 
< 0.1%
2.4 1
 
< 0.1%
2.78 1
 
< 0.1%
2.98 1
 
< 0.1%
3.0 1
 
< 0.1%
3.3 3
< 0.1%
ValueCountFrequency (%)
5251.98 1
 
< 0.1%
4071.92 1
 
< 0.1%
3972.62 4
< 0.1%
2970.0 1
 
< 0.1%
2861.0 1
 
< 0.1%
2297.86 1
 
< 0.1%
1633.33 2
< 0.1%
1609.63 1
 
< 0.1%
1530.0 4
< 0.1%
1349.0 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9980 
(조합)위탁
 
13
직영
 
7

Length

Max length6
Median length4
Mean length4.0012
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 9980
99.8%
(조합)위탁 13
 
0.1%
직영 7
 
0.1%

Length

2024-05-18T15:25:19.569019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T15:25:20.002533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9980
99.8%
조합)위탁 13
 
0.1%
직영 7
 
0.1%

Interactions

2024-05-18T15:24:49.288876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:38.854659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:41.119965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:42.936116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:44.965999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:47.709585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:49.712429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:39.307804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:41.464245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:43.287398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:45.431444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:47.982145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:50.015872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:39.742218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:41.743492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:43.619555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:46.173945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:48.258261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:50.338078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:40.144979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:42.032423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:43.953671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:46.684936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:48.476592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:50.924446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:40.508442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:42.310479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:44.311052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:47.096172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:48.754814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:51.317635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:40.766066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:42.584809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:44.577354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:47.439873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T15:24:49.012261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T15:25:20.325829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.6160.5050.5930.9980.0460.3540.0690.990
교부번호0.6161.0000.4090.6210.6130.0660.3000.1210.650
업종명0.5050.4091.0001.0000.4590.0000.3620.698NaN
업태명0.5930.6211.0001.0000.5530.0000.5060.8440.900
지도점검일자0.9980.6130.4590.5531.0000.0460.4830.1140.990
위반일자0.0460.0660.0000.0000.0461.000NaN0.000NaN
처분기간0.3540.3000.3620.5060.483NaN1.0000.000NaN
영업장면적(㎡)0.0690.1210.6980.8440.1140.0000.0001.000NaN
운영형태0.9900.650NaN0.9000.990NaNNaNNaN1.000
2024-05-18T15:25:20.807941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영형태업종명
운영형태1.0001.000
업종명1.0001.000
2024-05-18T15:25:21.161552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.4470.9980.939-0.256-0.0030.2150.857
교부번호0.4471.0000.4450.466-0.135-0.0520.1660.708
지도점검일자0.9980.4451.0000.944-0.259-0.0050.1900.857
위반일자0.9390.4660.9441.000-0.2600.0230.0001.000
처분기간-0.256-0.135-0.259-0.2601.000-0.1360.1600.000
영업장면적(㎡)-0.003-0.052-0.0050.023-0.1361.0000.3821.000
업종명0.2150.1660.1900.0000.1600.3821.0001.000
운영형태0.8570.7080.8571.0000.0001.0001.0001.000

Missing values

2024-05-18T15:24:51.942752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T15:24:52.755638image/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.
2024-05-18T15:24:53.397426image/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(㎡)운영형태
353430100002015042320060029155일반음식점한식불타는다동화로서울특별시 중구 을지로3길 33, (다동,(지상1층))서울특별시 중구 다동 128번지 0호 (지상1층)20150326처분확정시정명령법 제71조, 법 제74조 및 법 제75조20150326영업장면적 무단변경시정명령<NA>477.76<NA>
540030100002009091020060030022일반음식점중국식송경<NA>서울특별시 중구 을지로4가 310번지 11호 (지상1층)20090623처분확정과태료부과(16만원)식품위생법제78조,동법시행령56조,동법시행규칙54조20090623조리장위생불량(서울시적발)과태료부과(16만원)<NA><NA><NA>
77230100002023052619980029580일반음식점한식차목원서울특별시 중구 필동로 35-18, (필동3가)서울특별시 중구 필동3가 54번지 0호20230215처분확정직권말소법 제37조 7항20230215사업자등록 폐업직권말소<NA>82.86<NA>
397730100002012113020090029142건강기능식품일반판매업전자상거래(통신판매업)(주)와이즈머티리얼서울특별시 중구 동호로 171, (신당동)서울특별시 중구 신당동 372번지 3호20121025처분확정영업소폐쇄건강기능식품에 관한 법률 제32조201210256개월이상 무단휴업영업소폐쇄<NA><NA><NA>
527130100002009112020000030138일반음식점한식마르칸드<NA>서울특별시 중구 광희동1가 115번지 0호 지상1층20091030처분확정영업소폐쇄식품위생법 제36조20091030영업장 멸실영업소폐쇄<NA>21.0<NA>
28230100002023082219860029004유흥주점영업스텐드바팡팡노래짱서울특별시 중구 충무로2길 16, (충무로4가)서울특별시 중구 충무로4가 150번지 0호20230816처분확정과태료부과법 제71조 및 법 제75조20230816유흥접객원 명부 미작성과태료부과<NA>98.1<NA>
563430100002009060919760029234유흥주점영업룸살롱랑데즈<NA>서울특별시 중구 남대문로5가 12번지 38호20090224처분확정과태료부과(20만원)식품위생법제78조,동법시행령제56조,동법시행규칙제54조200902242008년도 기존영업자 위생교육 미필과태료부과(20만원)<NA>144.6<NA>
419430100002012010220070029260식품등 수입판매업식품등 수입판매업파워우먼서울특별시 중구 을지로44길 12, (광희동1가,뉴금호타워 201호)서울특별시 중구 광희동1가 143번지 2호 뉴금호타워 201호20120102처분확정과태료부과식품위생법 제41조20111231기존영업자 식품위생교육 미이수과태료부과<NA><NA><NA>
361230100002014121619950029600유통전문판매업유통전문판매업롯데쇼핑(주)서울특별시 중구 남대문로 81, (소공동)서울특별시 중구 소공동 1번지20141008처분확정시정명령식품위생법 제10조및제13조20141008유통전문판매원 대상제품이 아님에도 유통전문판매원:롯데쇼핑(주) 을 표시 해당제품 : 롯데마트 DREAM SET시정명령<NA>1081.0<NA>
690130100002007040420000030042유흥주점영업룸살롱아이앤유(I&you)<NA>서울특별시 중구 충무로2가 62번지 9호20070306처분확정영업정지식품위생법 제25조 및 제31조20070306상호표기위반(2차),지위승계미이행영업정지7144.13<NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
939030100002002122019940029703일반음식점분식장충분식<NA>서울특별시 중구 신당동 386번지 75호20021202처분확정영업소폐쇄식품위생법제58조20021202정당한사유없이 6개월이상 장기휴업및 시설물철거-직권폐쇄영업소폐쇄<NA>17.2<NA>
860530100002003120419850029206일반음식점경양식신라주점<NA>서울특별시 중구 신당동 368번지 58호20031110처분확정시설개수명령(1차)식품위생법제21조20031110노래방기기설치(객실)-자체단속시설개수명령(1차)<NA>101.12<NA>
635530100002008041519980029462일반음식점한식달빛머무는곳<NA>서울특별시 중구 을지로6가 18번지 37호20071115처분확정영업정지(45일-2차적발)식품위생법제31조(영업자등의 준수사항)위반, 동법 제58조(허가의 취소등)규정에 의거20071115청소년에게 주류제공(2007.11.15 서울시 합동단속)영업정지(45일-2차적발)15140.21<NA>
863330100002003111720000029289유흥주점영업룸살롱귀빈<NA>서울특별시 중구 수표동 62번지 4호20031015처분확정시정명령식품위생법제55조20031015업종혼돈표기-자체단속시정명령<NA>56.4<NA>
123130100002020122320030029942일반음식점한식가나안서울특별시 중구 다산로 131, (신당동,(지상1층))서울특별시 중구 신당동 374번지 10호 (지상1층)20190613처분확정영업정지법 제75조201905092019.5.9. 청소년을 대상으로 유해약물 등을 판매 (82,000원상당) 서울중부경찰서 적발영업정지<NA>114.22<NA>
613930100002008071120070029576일반음식점기타스모키살룬<NA>서울특별시 중구 순화동 151번지 외1필지(지상1층)20081024처분확정시정명령법제21조, 제22조, 제55조20080618영업장외 영업(옥외 테이블 설치)시정명령<NA><NA><NA>
1029830100002002040819980029559일반음식점경양식친구<NA>서울특별시 중구 신당동 374번지 17호20020318처분확정과태료 50만원식품위생법제26조20020318종업원 건강진단 미필(5명중 2명)과태료 50만원<NA>74.0<NA>
716630100002006092820000030382유흥주점영업룸살롱모델라인<NA>서울특별시 중구 북창동 3번지 1호 성원빌딩지하1층20060905처분확정시정명령식품위생법 제31조20060905유통기한경과제품보관시정명령<NA>89.91<NA>
501730100002010052420000029010일반음식점기타태능갈비<NA>서울특별시 중구 신당동 142번지 1호20100426처분확정과태료부과(감면액 24만원 완납)법제40조(건강진단)20100426종업원 건강진단 미필(2명)과태료부과(감면액 24만원 완납)<NA>14.5<NA>
190130100002019040820070029186일반음식점경양식파티오(한식당)서울특별시 중구 을지로 164, (을지로4가,외2필지(지상2층,지하1층))서울특별시 중구 을지로4가 310번지 외2필지(지상2층,지하1층)20190315처분확정시설개수명령법 제71조, 법 제74조,법 제75조 및 법 제76조20190315조리장내 음식물 쓰레기통 덮개 미비치시설개수명령<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
69230100002019110120160030050일반음식점외국음식전문점(인도,태국등)엘본더테이블 명동점서울특별시 중구 남대문로 81, (소공동, 롯데백화점 14층)서울특별시 중구 소공동 1번지 롯데백화점 14층20191029처분확정과태료부과법 제101조제2항제1호20191029종업원 건강진단결과서 미필과태료부과<NA><NA><NA>20
69130100002019110120160030050일반음식점외국음식전문점(인도,태국등)엘본더테이블 명동점서울특별시 중구 남대문로 81, (소공동, 롯데백화점 14층)서울특별시 중구 소공동 1번지 롯데백화점 14층20191029처분확정과태료부과법 제101조제2항제1호20191029위생모 미착용과태료부과<NA><NA><NA>11
29630100002008052919960029616일반음식점일식일식어가<NA>서울특별시 중구 을지로6가 17번지 2호 11층25호20081024처분확정영업소폐쇄식품위생법제21조(시설기준)위반20080508영업시설물 전부멸실영업소폐쇄<NA>72.02<NA>9
41830100002012010220060030041식품등 수입판매업식품등 수입판매업제이.아이.프로모션서울특별시 중구 동호로 352, (을지로5가,동신빌딩 601, 602, 203, 103호)서울특별시 중구 을지로5가 275번지 5호 동신빌딩 601, 602, 203, 103호20120102처분확정과태료부과식품위생법 제41조20111231기존영업자 식품위생교육 미이수과태료부과<NA><NA><NA>9
55230100002017101120100029747일반음식점한식엉터리 생고기 무한리필(명동점)서울특별시 중구 명동4길 23, (명동2가,(2층, 3층, 4층))서울특별시 중구 명동2가 54번지 32호 (2층, 3층, 4층)20170906처분확정시설개수명령법 제71조, 법 제74조,법 제75조 및 법 제76조20170906조리장내 내수성뚜껑 미사용시설개수명령<NA><NA><NA>8
60930100002018041820000030145일반음식점분식리슈 동까쭈서울특별시 중구 장충단로 249-28, (을지로6가,(지상2층))서울특별시 중구 을지로6가 18번지 82호 (지상2층)20180124처분확정영업소폐쇄 2018.4.18법 제20조제4항제2호20180124영업시설물 멸실영업소폐쇄 2018.4.18<NA><NA><NA>7
83030100002024010520170029257일반음식점한식광화문 국밥서울특별시 중구 세종대로21길 53, (정동, 1층)서울특별시 중구 정동 1번지 48호 1층20240102처분확정과태료부과법 제101조제3항제1호20240102종사자 건강진단 미실시과태료부과<NA><NA><NA>7
60330100002018040419980029330일반음식점분식만선호프서울특별시 중구 을지로13길 19, (을지로3가,,2호(지상1층))서울특별시 중구 을지로3가 95번지 1호 ,2호(지상1층)20180308처분확정시정명령법 제71조, 법 제74조 및 법 제75조20180308영업장 면적을 변경하고 변경신고를 하지 않음.시정명령<NA>99.07<NA>6
60630100002018040419980029330일반음식점분식만선호프서울특별시 중구 을지로13길 19, (을지로3가,,2호(지상1층))서울특별시 중구 을지로3가 95번지 1호 ,2호(지상1층)20180308처분확정시정명령(18.4.4)법 제71조, 법 제74조 및 법 제75조20180308영업장 면적을 변경하고 변경신고를 하지 않음.시정명령(18.4.4)<NA>99.07<NA>6
61030100002018041820080029915일반음식점한식리슈(얼음보숭)서울특별시 중구 장충단로 249-28, (을지로6가,(지상3층))서울특별시 중구 을지로6가 18번지 82호 (지상3층)20180124처분확정영업소폐쇄 2018.4.18법 제20조제4항제2호20180124영업시설물 멸실영업소폐쇄 2018.4.18<NA><NA><NA>6