Overview

Dataset statistics

Number of variables17
Number of observations7324
Missing cells13278
Missing cells (%)10.7%
Duplicate rows355
Duplicate rows (%)4.8%
Total size in memory1015.8 KiB
Average record size in memory142.0 B

Variable types

Categorical3
Numeric5
Text9

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-2383/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 355 (4.8%) 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
영업장면적(㎡) is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 영업장면적(㎡)High correlation
소재지도로명 has 3234 (44.2%) missing valuesMissing
처분기간 has 6334 (86.5%) missing valuesMissing
영업장면적(㎡) has 3626 (49.5%) missing valuesMissing
영업장면적(㎡) is highly skewed (γ1 = 28.95020315)Skewed
처분기간 has 75 (1.0%) zerosZeros

Reproduction

Analysis started2024-05-17 22:06:07.305625
Analysis finished2024-05-17 22:06:21.735071
Duration14.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
3160000
7324 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 7324
100.0%

Length

2024-05-18T07:06:22.155781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:06:22.493478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 7324
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2199
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124569
Minimum20011012
Maximum20240424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.5 KiB
2024-05-18T07:06:22.982913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011012
5-th percentile20021022
Q120080222
median20130214
Q320171201
95-th percentile20220424
Maximum20240424
Range229412
Interquartile range (IQR)90979

Descriptive statistics

Standard deviation60659.79
Coefficient of variation (CV)0.0030142156
Kurtosis-0.995092
Mean20124569
Median Absolute Deviation (MAD)49848
Skewness-0.031289099
Sum1.4739234 × 1011
Variance3.6796101 × 109
MonotonicityNot monotonic
2024-05-18T07:06:23.465660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230201 57
 
0.8%
20141103 52
 
0.7%
20160129 50
 
0.7%
20191022 48
 
0.7%
20190822 44
 
0.6%
20231123 44
 
0.6%
20111011 41
 
0.6%
20140312 34
 
0.5%
20131008 34
 
0.5%
20130524 33
 
0.5%
Other values (2189) 6887
94.0%
ValueCountFrequency (%)
20011012 2
 
< 0.1%
20011120 1
 
< 0.1%
20011124 4
 
0.1%
20011211 6
0.1%
20011212 1
 
< 0.1%
20011222 5
0.1%
20011226 7
0.1%
20020104 9
0.1%
20020105 1
 
< 0.1%
20020116 11
0.2%
ValueCountFrequency (%)
20240424 1
 
< 0.1%
20240409 2
 
< 0.1%
20240319 1
 
< 0.1%
20240318 2
 
< 0.1%
20240311 10
0.1%
20240227 1
 
< 0.1%
20240223 2
 
< 0.1%
20240215 1
 
< 0.1%
20240214 2
 
< 0.1%
20240208 1
 
< 0.1%
Distinct3561
Distinct (%)48.9%
Missing41
Missing (%)0.6%
Memory size57.3 KiB
2024-05-18T07:06:24.394836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.265138
Min length1

Characters and Unicode

Total characters74761
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2097 ?
Unique (%)28.8%

Sample

1st row002
2nd row25300410700013
3rd row010
4th row006
5th row005
ValueCountFrequency (%)
20120094434 42
 
0.6%
19930080713 33
 
0.5%
20180080042 33
 
0.5%
20050080133 27
 
0.4%
716 24
 
0.3%
19960080459 22
 
0.3%
19950080183 21
 
0.3%
19830080204 21
 
0.3%
20180080803 20
 
0.3%
20160080561 18
 
0.2%
Other values (3551) 7022
96.4%
2024-05-18T07:06:26.000346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29676
39.7%
8 9125
 
12.2%
1 8076
 
10.8%
2 7734
 
10.3%
9 5995
 
8.0%
3 2972
 
4.0%
4 2906
 
3.9%
6 2726
 
3.6%
5 2720
 
3.6%
7 2646
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74576
99.8%
Dash Punctuation 185
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29676
39.8%
8 9125
 
12.2%
1 8076
 
10.8%
2 7734
 
10.4%
9 5995
 
8.0%
3 2972
 
4.0%
4 2906
 
3.9%
6 2726
 
3.7%
5 2720
 
3.6%
7 2646
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74761
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29676
39.7%
8 9125
 
12.2%
1 8076
 
10.8%
2 7734
 
10.3%
9 5995
 
8.0%
3 2972
 
4.0%
4 2906
 
3.9%
6 2726
 
3.6%
5 2720
 
3.6%
7 2646
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29676
39.7%
8 9125
 
12.2%
1 8076
 
10.8%
2 7734
 
10.3%
9 5995
 
8.0%
3 2972
 
4.0%
4 2906
 
3.9%
6 2726
 
3.6%
5 2720
 
3.6%
7 2646
 
3.5%

업종명
Categorical

HIGH CORRELATION 

Distinct43
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
일반음식점
4170 
단란주점
468 
휴게음식점
 
340
식품제조가공업
 
306
즉석판매제조가공업
 
267
Other values (38)
1773 

Length

Max length23
Median length5
Mean length5.5626707
Min length3

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 4170
56.9%
단란주점 468
 
6.4%
휴게음식점 340
 
4.6%
식품제조가공업 306
 
4.2%
즉석판매제조가공업 267
 
3.6%
건강기능식품일반판매업 192
 
2.6%
숙박업(일반) 189
 
2.6%
유흥주점영업 179
 
2.4%
위생관리용역업 159
 
2.2%
유통전문판매업 144
 
2.0%
Other values (33) 910
 
12.4%

Length

2024-05-18T07:06:26.581802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 4170
55.8%
단란주점 468
 
6.3%
휴게음식점 340
 
4.6%
식품제조가공업 306
 
4.1%
즉석판매제조가공업 267
 
3.6%
건강기능식품일반판매업 192
 
2.6%
숙박업(일반 189
 
2.5%
유흥주점영업 179
 
2.4%
위생관리용역업 159
 
2.1%
유통전문판매업 144
 
1.9%
Other values (27) 1053
 
14.1%
Distinct82
Distinct (%)1.1%
Missing30
Missing (%)0.4%
Memory size57.3 KiB
2024-05-18T07:06:27.256640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.48204
Min length2

Characters and Unicode

Total characters32692
Distinct characters166
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row여인숙업
2nd row여인숙업
3rd row여인숙업
4th row여인숙업
5th row여인숙업
ValueCountFrequency (%)
한식 1533
20.3%
호프/통닭 1423
18.9%
단란주점 468
 
6.2%
식품제조가공업 306
 
4.1%
즉석판매제조가공업 267
 
3.5%
통닭(치킨 262
 
3.5%
중국식 241
 
3.2%
분식 241
 
3.2%
기타 226
 
3.0%
위생관리용역업 159
 
2.1%
Other values (71) 2420
32.1%
2024-05-18T07:06:28.407963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2885
 
8.8%
2073
 
6.3%
1932
 
5.9%
1685
 
5.2%
1533
 
4.7%
/ 1505
 
4.6%
1424
 
4.4%
1423
 
4.4%
831
 
2.5%
830
 
2.5%
Other values (156) 16571
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30212
92.4%
Other Punctuation 1513
 
4.6%
Close Punctuation 353
 
1.1%
Open Punctuation 353
 
1.1%
Space Separator 252
 
0.8%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2885
 
9.5%
2073
 
6.9%
1932
 
6.4%
1685
 
5.6%
1533
 
5.1%
1424
 
4.7%
1423
 
4.7%
831
 
2.8%
830
 
2.7%
656
 
2.2%
Other values (149) 14940
49.5%
Other Punctuation
ValueCountFrequency (%)
/ 1505
99.5%
. 4
 
0.3%
, 4
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 353
100.0%
Open Punctuation
ValueCountFrequency (%)
( 353
100.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30212
92.4%
Common 2480
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2885
 
9.5%
2073
 
6.9%
1932
 
6.4%
1685
 
5.6%
1533
 
5.1%
1424
 
4.7%
1423
 
4.7%
831
 
2.8%
830
 
2.7%
656
 
2.2%
Other values (149) 14940
49.5%
Common
ValueCountFrequency (%)
/ 1505
60.7%
) 353
 
14.2%
( 353
 
14.2%
252
 
10.2%
+ 9
 
0.4%
. 4
 
0.2%
, 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30212
92.4%
ASCII 2480
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2885
 
9.5%
2073
 
6.9%
1932
 
6.4%
1685
 
5.6%
1533
 
5.1%
1424
 
4.7%
1423
 
4.7%
831
 
2.8%
830
 
2.7%
656
 
2.2%
Other values (149) 14940
49.5%
ASCII
ValueCountFrequency (%)
/ 1505
60.7%
) 353
 
14.2%
( 353
 
14.2%
252
 
10.2%
+ 9
 
0.4%
. 4
 
0.2%
, 4
 
0.2%
Distinct3625
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
2024-05-18T07:06:29.242578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length30
Mean length5.4862097
Min length1

Characters and Unicode

Total characters40181
Distinct characters904
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

Unique2155 ?
Unique (%)29.4%

Sample

1st row원선
2nd row충남
3rd row나나
4th row삼화
5th row삼화
ValueCountFrequency (%)
주식회사 85
 
1.0%
떡愛미소식품 42
 
0.5%
roasters 37
 
0.4%
로스터스(around 35
 
0.4%
어라운드 35
 
0.4%
신도림점 33
 
0.4%
오아시스 31
 
0.4%
구로디지털점 30
 
0.3%
치킨 28
 
0.3%
둘둘치킨 26
 
0.3%
Other values (3980) 8336
95.6%
2024-05-18T07:06:30.612725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1395
 
3.5%
889
 
2.2%
869
 
2.2%
803
 
2.0%
) 673
 
1.7%
( 668
 
1.7%
555
 
1.4%
550
 
1.4%
508
 
1.3%
444
 
1.1%
Other values (894) 32827
81.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35459
88.2%
Space Separator 1395
 
3.5%
Lowercase Letter 1029
 
2.6%
Close Punctuation 673
 
1.7%
Open Punctuation 668
 
1.7%
Uppercase Letter 524
 
1.3%
Decimal Number 276
 
0.7%
Other Punctuation 141
 
0.4%
Dash Punctuation 14
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
889
 
2.5%
869
 
2.5%
803
 
2.3%
555
 
1.6%
550
 
1.6%
508
 
1.4%
444
 
1.3%
441
 
1.2%
428
 
1.2%
418
 
1.2%
Other values (818) 29554
83.3%
Uppercase Letter
ValueCountFrequency (%)
B 42
 
8.0%
C 42
 
8.0%
K 40
 
7.6%
S 34
 
6.5%
N 34
 
6.5%
A 33
 
6.3%
M 28
 
5.3%
T 28
 
5.3%
L 26
 
5.0%
O 26
 
5.0%
Other values (16) 191
36.5%
Lowercase Letter
ValueCountFrequency (%)
r 136
13.2%
a 132
12.8%
o 126
12.2%
e 108
10.5%
s 91
8.8%
n 65
 
6.3%
t 53
 
5.2%
u 53
 
5.2%
d 45
 
4.4%
f 32
 
3.1%
Other values (13) 188
18.3%
Decimal Number
ValueCountFrequency (%)
2 60
21.7%
1 42
15.2%
0 36
13.0%
7 28
10.1%
5 27
9.8%
9 23
 
8.3%
8 18
 
6.5%
3 16
 
5.8%
6 14
 
5.1%
4 11
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 58
41.1%
& 25
17.7%
14
 
9.9%
; 11
 
7.8%
, 11
 
7.8%
' 8
 
5.7%
? 4
 
2.8%
! 4
 
2.8%
/ 3
 
2.1%
: 2
 
1.4%
Space Separator
ValueCountFrequency (%)
1395
100.0%
Close Punctuation
ValueCountFrequency (%)
) 673
100.0%
Open Punctuation
ValueCountFrequency (%)
( 668
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35395
88.1%
Common 3169
 
7.9%
Latin 1553
 
3.9%
Han 64
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
889
 
2.5%
869
 
2.5%
803
 
2.3%
555
 
1.6%
550
 
1.6%
508
 
1.4%
444
 
1.3%
441
 
1.2%
428
 
1.2%
418
 
1.2%
Other values (800) 29490
83.3%
Latin
ValueCountFrequency (%)
r 136
 
8.8%
a 132
 
8.5%
o 126
 
8.1%
e 108
 
7.0%
s 91
 
5.9%
n 65
 
4.2%
t 53
 
3.4%
u 53
 
3.4%
d 45
 
2.9%
B 42
 
2.7%
Other values (39) 702
45.2%
Common
ValueCountFrequency (%)
1395
44.0%
) 673
21.2%
( 668
21.1%
2 60
 
1.9%
. 58
 
1.8%
1 42
 
1.3%
0 36
 
1.1%
7 28
 
0.9%
5 27
 
0.9%
& 25
 
0.8%
Other values (17) 157
 
5.0%
Han
ValueCountFrequency (%)
42
65.6%
4
 
6.2%
2
 
3.1%
2
 
3.1%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Other values (8) 8
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35395
88.1%
ASCII 4707
 
11.7%
CJK 64
 
0.2%
None 15
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1395
29.6%
) 673
14.3%
( 668
14.2%
r 136
 
2.9%
a 132
 
2.8%
o 126
 
2.7%
e 108
 
2.3%
s 91
 
1.9%
n 65
 
1.4%
2 60
 
1.3%
Other values (64) 1253
26.6%
Hangul
ValueCountFrequency (%)
889
 
2.5%
869
 
2.5%
803
 
2.3%
555
 
1.6%
550
 
1.6%
508
 
1.4%
444
 
1.3%
441
 
1.2%
428
 
1.2%
418
 
1.2%
Other values (800) 29490
83.3%
CJK
ValueCountFrequency (%)
42
65.6%
4
 
6.2%
2
 
3.1%
2
 
3.1%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Other values (8) 8
 
12.5%
None
ValueCountFrequency (%)
14
93.3%
1
 
6.7%

소재지도로명
Text

MISSING 

Distinct2010
Distinct (%)49.1%
Missing3234
Missing (%)44.2%
Memory size57.3 KiB
2024-05-18T07:06:31.229966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length57
Mean length33.557457
Min length22

Characters and Unicode

Total characters137250
Distinct characters362
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

Unique1168 ?
Unique (%)28.6%

Sample

1st row서울특별시 구로구 구로동로22길 5-14, (구로동)
2nd row서울특별시 구로구 구로동로26길 55-8, (구로동)
3rd row서울특별시 구로구 경인로15길 8-6, (오류동)
4th row서울특별시 구로구 구로동로35길 13, (구로동)
5th row서울특별시 구로구 구로동로35길 13, (구로동)
ValueCountFrequency (%)
서울특별시 4090
 
16.4%
구로구 4090
 
16.4%
구로동 1638
 
6.6%
1층 617
 
2.5%
개봉동 437
 
1.8%
경인로 376
 
1.5%
오류동 351
 
1.4%
고척동 340
 
1.4%
신도림동 238
 
1.0%
가리봉동 183
 
0.7%
Other values (2023) 12579
50.4%
2024-05-18T07:06:32.714609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20862
 
15.2%
11096
 
8.1%
11014
 
8.0%
1 6077
 
4.4%
, 6043
 
4.4%
4908
 
3.6%
) 4326
 
3.2%
( 4325
 
3.2%
4262
 
3.1%
4163
 
3.0%
Other values (352) 60174
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77953
56.8%
Decimal Number 22441
 
16.4%
Space Separator 20862
 
15.2%
Other Punctuation 6063
 
4.4%
Close Punctuation 4328
 
3.2%
Open Punctuation 4327
 
3.2%
Dash Punctuation 888
 
0.6%
Uppercase Letter 356
 
0.3%
Math Symbol 15
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11096
14.2%
11014
14.1%
4908
 
6.3%
4262
 
5.5%
4163
 
5.3%
4097
 
5.3%
4091
 
5.2%
4090
 
5.2%
2574
 
3.3%
1666
 
2.1%
Other values (303) 25992
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 147
41.3%
A 59
16.6%
S 26
 
7.3%
K 25
 
7.0%
E 13
 
3.7%
I 11
 
3.1%
C 11
 
3.1%
T 10
 
2.8%
F 10
 
2.8%
L 7
 
2.0%
Other values (11) 37
 
10.4%
Decimal Number
ValueCountFrequency (%)
1 6077
27.1%
2 3756
16.7%
3 2593
11.6%
0 2188
 
9.8%
6 1493
 
6.7%
7 1476
 
6.6%
5 1378
 
6.1%
4 1316
 
5.9%
8 1206
 
5.4%
9 958
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
b 4
30.8%
e 3
23.1%
k 2
15.4%
z 1
 
7.7%
i 1
 
7.7%
n 1
 
7.7%
j 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 6043
99.7%
. 11
 
0.2%
/ 9
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4326
> 99.9%
] 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4325
> 99.9%
[ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20862
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 888
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77951
56.8%
Common 58928
42.9%
Latin 369
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11096
14.2%
11014
14.1%
4908
 
6.3%
4262
 
5.5%
4163
 
5.3%
4097
 
5.3%
4091
 
5.2%
4090
 
5.2%
2574
 
3.3%
1666
 
2.1%
Other values (301) 25990
33.3%
Latin
ValueCountFrequency (%)
B 147
39.8%
A 59
16.0%
S 26
 
7.0%
K 25
 
6.8%
E 13
 
3.5%
I 11
 
3.0%
C 11
 
3.0%
T 10
 
2.7%
F 10
 
2.7%
L 7
 
1.9%
Other values (18) 50
 
13.6%
Common
ValueCountFrequency (%)
20862
35.4%
1 6077
 
10.3%
, 6043
 
10.3%
) 4326
 
7.3%
( 4325
 
7.3%
2 3756
 
6.4%
3 2593
 
4.4%
0 2188
 
3.7%
6 1493
 
2.5%
7 1476
 
2.5%
Other values (11) 5789
 
9.8%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77951
56.8%
ASCII 59293
43.2%
CJK Compat 4
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20862
35.2%
1 6077
 
10.2%
, 6043
 
10.2%
) 4326
 
7.3%
( 4325
 
7.3%
2 3756
 
6.3%
3 2593
 
4.4%
0 2188
 
3.7%
6 1493
 
2.5%
7 1476
 
2.5%
Other values (38) 6154
 
10.4%
Hangul
ValueCountFrequency (%)
11096
14.2%
11014
14.1%
4908
 
6.3%
4262
 
5.5%
4163
 
5.3%
4097
 
5.3%
4091
 
5.2%
4090
 
5.2%
2574
 
3.3%
1666
 
2.1%
Other values (301) 25990
33.3%
CJK Compat
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct3077
Distinct (%)42.1%
Missing13
Missing (%)0.2%
Memory size57.3 KiB
2024-05-18T07:06:33.632191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length60
Mean length29.697989
Min length20

Characters and Unicode

Total characters217122
Distinct characters378
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1636 ?
Unique (%)22.4%

Sample

1st row서울특별시 구로구 구로동 733번지 35호
2nd row서울특별시 구로구 구로동 730번지 29호
3rd row서울특별시 구로구 오류동 6번지 114호
4th row서울특별시 구로구 구로동 414번지 30호
5th row서울특별시 구로구 구로동 414번지 30호
ValueCountFrequency (%)
구로구 7323
 
17.7%
서울특별시 7311
 
17.7%
구로동 3591
 
8.7%
개봉동 1006
 
2.4%
고척동 862
 
2.1%
오류동 682
 
1.6%
1호 542
 
1.3%
신도림동 494
 
1.2%
가리봉동 441
 
1.1%
1층 388
 
0.9%
Other values (2168) 18757
45.3%
2024-05-18T07:06:35.328387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52510
24.2%
18484
 
8.5%
11173
 
5.1%
1 10535
 
4.9%
8310
 
3.8%
7637
 
3.5%
7450
 
3.4%
7350
 
3.4%
7336
 
3.4%
7320
 
3.4%
Other values (368) 79017
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120437
55.5%
Space Separator 52510
24.2%
Decimal Number 41254
 
19.0%
Dash Punctuation 845
 
0.4%
Uppercase Letter 543
 
0.3%
Other Punctuation 529
 
0.2%
Close Punctuation 483
 
0.2%
Open Punctuation 482
 
0.2%
Math Symbol 22
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18484
15.3%
11173
 
9.3%
8310
 
6.9%
7637
 
6.3%
7450
 
6.2%
7350
 
6.1%
7336
 
6.1%
7320
 
6.1%
7319
 
6.1%
7314
 
6.1%
Other values (315) 30744
25.5%
Uppercase Letter
ValueCountFrequency (%)
B 194
35.7%
A 93
17.1%
K 59
 
10.9%
S 48
 
8.8%
D 26
 
4.8%
C 23
 
4.2%
E 20
 
3.7%
F 18
 
3.3%
I 13
 
2.4%
T 12
 
2.2%
Other values (11) 37
 
6.8%
Decimal Number
ValueCountFrequency (%)
1 10535
25.5%
2 5756
14.0%
3 4825
11.7%
0 3864
 
9.4%
4 3654
 
8.9%
5 3145
 
7.6%
7 2990
 
7.2%
6 2387
 
5.8%
8 2353
 
5.7%
9 1745
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
k 4
26.7%
e 3
20.0%
b 2
13.3%
s 2
13.3%
i 1
 
6.7%
z 1
 
6.7%
n 1
 
6.7%
j 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 487
92.1%
. 30
 
5.7%
/ 10
 
1.9%
? 1
 
0.2%
1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 481
99.6%
] 2
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 480
99.6%
[ 2
 
0.4%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
52510
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 845
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120435
55.5%
Common 96125
44.3%
Latin 560
 
0.3%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18484
15.3%
11173
 
9.3%
8310
 
6.9%
7637
 
6.3%
7450
 
6.2%
7350
 
6.1%
7336
 
6.1%
7320
 
6.1%
7319
 
6.1%
7314
 
6.1%
Other values (313) 30742
25.5%
Latin
ValueCountFrequency (%)
B 194
34.6%
A 93
16.6%
K 59
 
10.5%
S 48
 
8.6%
D 26
 
4.6%
C 23
 
4.1%
E 20
 
3.6%
F 18
 
3.2%
I 13
 
2.3%
T 12
 
2.1%
Other values (21) 54
 
9.6%
Common
ValueCountFrequency (%)
52510
54.6%
1 10535
 
11.0%
2 5756
 
6.0%
3 4825
 
5.0%
0 3864
 
4.0%
4 3654
 
3.8%
5 3145
 
3.3%
7 2990
 
3.1%
6 2387
 
2.5%
8 2353
 
2.4%
Other values (12) 4106
 
4.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120435
55.5%
ASCII 96682
44.5%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52510
54.3%
1 10535
 
10.9%
2 5756
 
6.0%
3 4825
 
5.0%
0 3864
 
4.0%
4 3654
 
3.8%
5 3145
 
3.3%
7 2990
 
3.1%
6 2387
 
2.5%
8 2353
 
2.4%
Other values (40) 4663
 
4.8%
Hangul
ValueCountFrequency (%)
18484
15.3%
11173
 
9.3%
8310
 
6.9%
7637
 
6.3%
7450
 
6.2%
7350
 
6.1%
7336
 
6.1%
7320
 
6.1%
7319
 
6.1%
7314
 
6.1%
Other values (313) 30742
25.5%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2815
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122285
Minimum20001218
Maximum20240228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.5 KiB
2024-05-18T07:06:35.888153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001218
5-th percentile20020826
Q120080110
median20121017
Q320170928
95-th percentile20220108
Maximum20240228
Range239010
Interquartile range (IQR)90818

Descriptive statistics

Standard deviation60651.576
Coefficient of variation (CV)0.0030141496
Kurtosis-0.97218868
Mean20122285
Median Absolute Deviation (MAD)49800
Skewness-0.033130485
Sum1.4737561 × 1011
Variance3.6786137 × 109
MonotonicityNot monotonic
2024-05-18T07:06:36.441570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190102 65
 
0.9%
20221124 61
 
0.8%
20230417 55
 
0.8%
20190730 51
 
0.7%
20231020 45
 
0.6%
20140101 37
 
0.5%
20210526 34
 
0.5%
20191002 33
 
0.5%
20140701 31
 
0.4%
20130205 30
 
0.4%
Other values (2805) 6882
94.0%
ValueCountFrequency (%)
20001218 1
< 0.1%
20010222 1
< 0.1%
20010226 2
< 0.1%
20010302 2
< 0.1%
20010310 2
< 0.1%
20010313 1
< 0.1%
20010316 1
< 0.1%
20010404 1
< 0.1%
20010407 1
< 0.1%
20010411 1
< 0.1%
ValueCountFrequency (%)
20240228 1
 
< 0.1%
20240220 1
 
< 0.1%
20240213 2
 
< 0.1%
20240208 1
 
< 0.1%
20240205 3
< 0.1%
20240202 6
0.1%
20240201 4
0.1%
20240116 1
 
< 0.1%
20240108 1
 
< 0.1%
20231230 1
 
< 0.1%

행정처분상태
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
처분확정
7324 

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 7324
100.0%

Length

2024-05-18T07:06:37.040335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T07:06:37.530645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 7324
100.0%
Distinct832
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
2024-05-18T07:06:38.234870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length66
Mean length7.9722829
Min length2

Characters and Unicode

Total characters58389
Distinct characters247
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

Unique477 ?
Unique (%)6.5%

Sample

1st row영업정지 2월(2009.6.2~8.2)
2nd row영업정지
3rd row과징금부과
4th row영업정지
5th row영업정지 1월
ValueCountFrequency (%)
영업정지 1553
14.7%
시정명령 1471
 
13.9%
과태료부과 1341
 
12.7%
영업소폐쇄 666
 
6.3%
부과 407
 
3.8%
과태료 369
 
3.5%
283
 
2.7%
과징금부과 279
 
2.6%
과징금 269
 
2.5%
시설개수명령 207
 
2.0%
Other values (833) 3752
35.4%
2024-05-18T07:06:39.782624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5524
 
9.5%
3793
 
6.5%
3275
 
5.6%
0 2795
 
4.8%
2780
 
4.8%
2765
 
4.7%
2759
 
4.7%
2198
 
3.8%
2172
 
3.7%
2145
 
3.7%
Other values (237) 28183
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42920
73.5%
Decimal Number 8697
 
14.9%
Space Separator 3275
 
5.6%
Other Punctuation 1304
 
2.2%
Open Punctuation 960
 
1.6%
Close Punctuation 955
 
1.6%
Math Symbol 198
 
0.3%
Dash Punctuation 80
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (210) 14909
34.7%
Decimal Number
ValueCountFrequency (%)
0 2795
32.1%
2 2143
24.6%
1 1329
15.3%
5 566
 
6.5%
3 486
 
5.6%
4 468
 
5.4%
6 363
 
4.2%
7 206
 
2.4%
8 182
 
2.1%
9 159
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 1019
78.1%
, 221
 
16.9%
: 20
 
1.5%
% 18
 
1.4%
17
 
1.3%
* 6
 
0.5%
/ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 160
80.8%
> 27
 
13.6%
= 7
 
3.5%
4
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 959
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 954
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42920
73.5%
Common 15469
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (210) 14909
34.7%
Common
ValueCountFrequency (%)
3275
21.2%
0 2795
18.1%
2 2143
13.9%
1 1329
8.6%
. 1019
 
6.6%
( 959
 
6.2%
) 954
 
6.2%
5 566
 
3.7%
3 486
 
3.1%
4 468
 
3.0%
Other values (17) 1475
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42894
73.5%
ASCII 15448
 
26.5%
Compat Jamo 26
 
< 0.1%
Punctuation 17
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (209) 14883
34.7%
ASCII
ValueCountFrequency (%)
3275
21.2%
0 2795
18.1%
2 2143
13.9%
1 1329
8.6%
. 1019
 
6.6%
( 959
 
6.2%
) 954
 
6.2%
5 566
 
3.7%
3 486
 
3.1%
4 468
 
3.0%
Other values (15) 1454
9.4%
Compat Jamo
ValueCountFrequency (%)
26
100.0%
Punctuation
ValueCountFrequency (%)
17
100.0%
Arrows
ValueCountFrequency (%)
4
100.0%
Distinct561
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
2024-05-18T07:06:40.635596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length53
Mean length14.972146
Min length3

Characters and Unicode

Total characters109656
Distinct characters135
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique248 ?
Unique (%)3.4%

Sample

1st row공중위생관리법제11조제1항
2nd row공중위생관리법11조1항
3rd row공중위생관리법 제11조제1항
4th row풍속영업의규제에관한법률
5th row공중위생관리법 제11조 1항
ValueCountFrequency (%)
4104
17.8%
식품위생법 2959
 
12.8%
2074
 
9.0%
제75조 1717
 
7.4%
제71조 1317
 
5.7%
공중위생관리법 619
 
2.7%
제31조 584
 
2.5%
제74조 457
 
2.0%
제22조 453
 
2.0%
제101조제2항제1호 421
 
1.8%
Other values (417) 8400
36.4%
2024-05-18T07:06:42.356447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15827
14.4%
14357
13.1%
10975
10.0%
9695
 
8.8%
1 7623
 
7.0%
7 5513
 
5.0%
5192
 
4.7%
4885
 
4.5%
4157
 
3.8%
4156
 
3.8%
Other values (125) 27276
24.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65712
59.9%
Decimal Number 26495
24.2%
Space Separator 15827
 
14.4%
Other Punctuation 1544
 
1.4%
Open Punctuation 38
 
< 0.1%
Close Punctuation 38
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14357
21.8%
10975
16.7%
9695
14.8%
5192
 
7.9%
4885
 
7.4%
4157
 
6.3%
4156
 
6.3%
2943
 
4.5%
2092
 
3.2%
1046
 
1.6%
Other values (105) 6214
9.5%
Decimal Number
ValueCountFrequency (%)
1 7623
28.8%
7 5513
20.8%
2 3818
14.4%
5 2559
 
9.7%
4 2349
 
8.9%
3 1791
 
6.8%
0 1171
 
4.4%
6 992
 
3.7%
8 585
 
2.2%
9 94
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 1516
98.2%
. 19
 
1.2%
? 8
 
0.5%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 35
92.1%
[ 3
 
7.9%
Close Punctuation
ValueCountFrequency (%)
) 35
92.1%
] 3
 
7.9%
Space Separator
ValueCountFrequency (%)
15827
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65711
59.9%
Common 43942
40.1%
Latin 2
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14357
21.8%
10975
16.7%
9695
14.8%
5192
 
7.9%
4885
 
7.4%
4157
 
6.3%
4156
 
6.3%
2943
 
4.5%
2092
 
3.2%
1046
 
1.6%
Other values (104) 6213
9.5%
Common
ValueCountFrequency (%)
15827
36.0%
1 7623
17.3%
7 5513
 
12.5%
2 3818
 
8.7%
5 2559
 
5.8%
4 2349
 
5.3%
3 1791
 
4.1%
, 1516
 
3.5%
0 1171
 
2.7%
6 992
 
2.3%
Other values (9) 783
 
1.8%
Latin
ValueCountFrequency (%)
2
100.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65709
59.9%
ASCII 43941
40.1%
Compat Jamo 2
 
< 0.1%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15827
36.0%
1 7623
17.3%
7 5513
 
12.5%
2 3818
 
8.7%
5 2559
 
5.8%
4 2349
 
5.3%
3 1791
 
4.1%
, 1516
 
3.5%
0 1171
 
2.7%
6 992
 
2.3%
Other values (8) 782
 
1.8%
Hangul
ValueCountFrequency (%)
14357
21.8%
10975
16.7%
9695
14.8%
5192
 
7.9%
4885
 
7.4%
4157
 
6.3%
4156
 
6.3%
2943
 
4.5%
2092
 
3.2%
1046
 
1.6%
Other values (103) 6211
9.5%
Compat Jamo
ValueCountFrequency (%)
2
100.0%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2819
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20122124
Minimum20001218
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.5 KiB
2024-05-18T07:06:42.997199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001218
5-th percentile20020823
Q120080110
median20121024
Q320170922
95-th percentile20220108
Maximum20240222
Range239004
Interquartile range (IQR)90812

Descriptive statistics

Standard deviation60585.309
Coefficient of variation (CV)0.0030108804
Kurtosis-0.9702898
Mean20122124
Median Absolute Deviation (MAD)49796.5
Skewness-0.033680216
Sum1.4737444 × 1011
Variance3.6705797 × 109
MonotonicityNot monotonic
2024-05-18T07:06:43.670758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190102 64
 
0.9%
20221124 61
 
0.8%
20230417 55
 
0.8%
20190730 51
 
0.7%
20231020 45
 
0.6%
20050715 38
 
0.5%
20140101 37
 
0.5%
20191002 33
 
0.5%
20140701 31
 
0.4%
20130205 30
 
0.4%
Other values (2809) 6879
93.9%
ValueCountFrequency (%)
20001218 1
 
< 0.1%
20010126 1
 
< 0.1%
20010222 1
 
< 0.1%
20010226 2
< 0.1%
20010310 2
< 0.1%
20010316 1
 
< 0.1%
20010403 1
 
< 0.1%
20010404 1
 
< 0.1%
20010408 3
< 0.1%
20010410 1
 
< 0.1%
ValueCountFrequency (%)
20240222 1
 
< 0.1%
20240220 1
 
< 0.1%
20240213 2
 
< 0.1%
20240208 1
 
< 0.1%
20240205 3
< 0.1%
20240202 6
0.1%
20240201 4
0.1%
20240116 1
 
< 0.1%
20240103 1
 
< 0.1%
20231230 1
 
< 0.1%
Distinct2196
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
2024-05-18T07:06:44.443310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length218
Median length128
Mean length16.608001
Min length4

Characters and Unicode

Total characters121637
Distinct characters581
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1308 ?
Unique (%)17.9%

Sample

1st row성매매알선등
2nd row 윤락행위알선
3rd row청소년 이성혼숙
4th row윤락행위알선제공
5th row윤락행위알선장소제공
ValueCountFrequency (%)
위생교육 806
 
3.4%
미이수 678
 
2.8%
1차 482
 
2.0%
건강진단 390
 
1.6%
352
 
1.5%
전부 292
 
1.2%
영업시설물 286
 
1.2%
영업장외 278
 
1.2%
미필 257
 
1.1%
영업 226
 
0.9%
Other values (2780) 19764
83.0%
2024-05-18T07:06:45.730028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17452
 
14.3%
4398
 
3.6%
1 3861
 
3.2%
) 3310
 
2.7%
( 3285
 
2.7%
3184
 
2.6%
2762
 
2.3%
2678
 
2.2%
2216
 
1.8%
2075
 
1.7%
Other values (571) 76416
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87067
71.6%
Space Separator 17452
 
14.3%
Decimal Number 8483
 
7.0%
Close Punctuation 3315
 
2.7%
Open Punctuation 3290
 
2.7%
Other Punctuation 1578
 
1.3%
Dash Punctuation 230
 
0.2%
Uppercase Letter 122
 
0.1%
Lowercase Letter 54
 
< 0.1%
Math Symbol 15
 
< 0.1%
Other values (5) 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4398
 
5.1%
3184
 
3.7%
2762
 
3.2%
2678
 
3.1%
2216
 
2.5%
2075
 
2.4%
1777
 
2.0%
1488
 
1.7%
1441
 
1.7%
1388
 
1.6%
Other values (506) 63660
73.1%
Uppercase Letter
ValueCountFrequency (%)
A 18
14.8%
U 11
9.0%
O 11
9.0%
E 10
8.2%
N 10
8.2%
Y 9
 
7.4%
B 8
 
6.6%
P 8
 
6.6%
G 8
 
6.6%
S 6
 
4.9%
Other values (9) 23
18.9%
Lowercase Letter
ValueCountFrequency (%)
o 11
20.4%
g 8
14.8%
t 5
9.3%
p 4
 
7.4%
i 4
 
7.4%
n 4
 
7.4%
k 4
 
7.4%
w 3
 
5.6%
b 3
 
5.6%
x 3
 
5.6%
Other values (4) 5
9.3%
Decimal Number
ValueCountFrequency (%)
1 3861
45.5%
2 1971
23.2%
0 1337
 
15.8%
3 358
 
4.2%
4 207
 
2.4%
8 184
 
2.2%
5 179
 
2.1%
7 149
 
1.8%
6 124
 
1.5%
9 113
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 1012
64.1%
. 190
 
12.0%
: 168
 
10.6%
/ 158
 
10.0%
% 29
 
1.8%
? 17
 
1.1%
' 4
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3310
99.8%
] 4
 
0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3285
99.8%
[ 4
 
0.1%
1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 8
53.3%
+ 7
46.7%
Space Separator
ValueCountFrequency (%)
17452
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 230
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Initial Punctuation
ValueCountFrequency (%)
8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87067
71.6%
Common 34394
 
28.3%
Latin 176
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4398
 
5.1%
3184
 
3.7%
2762
 
3.2%
2678
 
3.1%
2216
 
2.5%
2075
 
2.4%
1777
 
2.0%
1488
 
1.7%
1441
 
1.7%
1388
 
1.6%
Other values (506) 63660
73.1%
Latin
ValueCountFrequency (%)
A 18
 
10.2%
U 11
 
6.2%
o 11
 
6.2%
O 11
 
6.2%
E 10
 
5.7%
N 10
 
5.7%
Y 9
 
5.1%
g 8
 
4.5%
B 8
 
4.5%
P 8
 
4.5%
Other values (23) 72
40.9%
Common
ValueCountFrequency (%)
17452
50.7%
1 3861
 
11.2%
) 3310
 
9.6%
( 3285
 
9.6%
2 1971
 
5.7%
0 1337
 
3.9%
, 1012
 
2.9%
3 358
 
1.0%
- 230
 
0.7%
4 207
 
0.6%
Other values (22) 1371
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87053
71.6%
ASCII 34549
 
28.4%
Punctuation 16
 
< 0.1%
Compat Jamo 14
 
< 0.1%
Geometric Shapes 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17452
50.5%
1 3861
 
11.2%
) 3310
 
9.6%
( 3285
 
9.5%
2 1971
 
5.7%
0 1337
 
3.9%
, 1012
 
2.9%
3 358
 
1.0%
- 230
 
0.7%
4 207
 
0.6%
Other values (50) 1526
 
4.4%
Hangul
ValueCountFrequency (%)
4398
 
5.1%
3184
 
3.7%
2762
 
3.2%
2678
 
3.1%
2216
 
2.5%
2075
 
2.4%
1777
 
2.0%
1488
 
1.7%
1441
 
1.7%
1388
 
1.6%
Other values (505) 63646
73.1%
Compat Jamo
ValueCountFrequency (%)
14
100.0%
Punctuation
ValueCountFrequency (%)
8
50.0%
8
50.0%
Geometric Shapes
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct832
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size57.3 KiB
2024-05-18T07:06:46.552059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length66
Mean length7.9722829
Min length2

Characters and Unicode

Total characters58389
Distinct characters247
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

Unique477 ?
Unique (%)6.5%

Sample

1st row영업정지 2월(2009.6.2~8.2)
2nd row영업정지
3rd row과징금부과
4th row영업정지
5th row영업정지 1월
ValueCountFrequency (%)
영업정지 1553
14.7%
시정명령 1471
 
13.9%
과태료부과 1341
 
12.7%
영업소폐쇄 666
 
6.3%
부과 407
 
3.8%
과태료 369
 
3.5%
283
 
2.7%
과징금부과 279
 
2.6%
과징금 269
 
2.5%
시설개수명령 207
 
2.0%
Other values (833) 3752
35.4%
2024-05-18T07:06:48.270854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5524
 
9.5%
3793
 
6.5%
3275
 
5.6%
0 2795
 
4.8%
2780
 
4.8%
2765
 
4.7%
2759
 
4.7%
2198
 
3.8%
2172
 
3.7%
2145
 
3.7%
Other values (237) 28183
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42920
73.5%
Decimal Number 8697
 
14.9%
Space Separator 3275
 
5.6%
Other Punctuation 1304
 
2.2%
Open Punctuation 960
 
1.6%
Close Punctuation 955
 
1.6%
Math Symbol 198
 
0.3%
Dash Punctuation 80
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (210) 14909
34.7%
Decimal Number
ValueCountFrequency (%)
0 2795
32.1%
2 2143
24.6%
1 1329
15.3%
5 566
 
6.5%
3 486
 
5.6%
4 468
 
5.4%
6 363
 
4.2%
7 206
 
2.4%
8 182
 
2.1%
9 159
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 1019
78.1%
, 221
 
16.9%
: 20
 
1.5%
% 18
 
1.4%
17
 
1.3%
* 6
 
0.5%
/ 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 160
80.8%
> 27
 
13.6%
= 7
 
3.5%
4
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 959
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 954
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
3275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42920
73.5%
Common 15469
 
26.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (210) 14909
34.7%
Common
ValueCountFrequency (%)
3275
21.2%
0 2795
18.1%
2 2143
13.9%
1 1329
8.6%
. 1019
 
6.6%
( 959
 
6.2%
) 954
 
6.2%
5 566
 
3.7%
3 486
 
3.1%
4 468
 
3.0%
Other values (17) 1475
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42894
73.5%
ASCII 15448
 
26.5%
Compat Jamo 26
 
< 0.1%
Punctuation 17
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5524
 
12.9%
3793
 
8.8%
2780
 
6.5%
2765
 
6.4%
2759
 
6.4%
2198
 
5.1%
2172
 
5.1%
2145
 
5.0%
1941
 
4.5%
1934
 
4.5%
Other values (209) 14883
34.7%
ASCII
ValueCountFrequency (%)
3275
21.2%
0 2795
18.1%
2 2143
13.9%
1 1329
8.6%
. 1019
 
6.6%
( 959
 
6.2%
) 954
 
6.2%
5 566
 
3.7%
3 486
 
3.1%
4 468
 
3.0%
Other values (15) 1454
9.4%
Compat Jamo
ValueCountFrequency (%)
26
100.0%
Punctuation
ValueCountFrequency (%)
17
100.0%
Arrows
ValueCountFrequency (%)
4
100.0%

처분기간
Real number (ℝ)

MISSING  ZEROS 

Distinct26
Distinct (%)2.6%
Missing6334
Missing (%)86.5%
Infinite0
Infinite (%)0.0%
Mean11.634343
Minimum0
Maximum61
Zeros75
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size64.5 KiB
2024-05-18T07:06:48.992296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median15
Q315
95-th percentile20
Maximum61
Range61
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.604502
Coefficient of variation (CV)0.56767294
Kurtosis11.288381
Mean11.634343
Median Absolute Deviation (MAD)5
Skewness1.5462297
Sum11518
Variance43.619446
MonotonicityNot monotonic
2024-05-18T07:06:49.582961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
15 465
 
6.3%
7 223
 
3.0%
0 75
 
1.0%
10 63
 
0.9%
20 32
 
0.4%
5 27
 
0.4%
3 13
 
0.2%
22 12
 
0.2%
17 12
 
0.2%
8 10
 
0.1%
Other values (16) 58
 
0.8%
(Missing) 6334
86.5%
ValueCountFrequency (%)
0 75
 
1.0%
1 3
 
< 0.1%
2 9
 
0.1%
3 13
 
0.2%
4 8
 
0.1%
5 27
 
0.4%
6 5
 
0.1%
7 223
3.0%
8 10
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
61 1
 
< 0.1%
60 3
 
< 0.1%
45 1
 
< 0.1%
30 5
 
0.1%
28 3
 
< 0.1%
25 4
 
0.1%
23 6
 
0.1%
22 12
 
0.2%
21 2
 
< 0.1%
20 32
0.4%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct1466
Distinct (%)39.6%
Missing3626
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean160.91386
Minimum0
Maximum29556.6
Zeros27
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size64.5 KiB
2024-05-18T07:06:50.359120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.6
Q134.07
median68.175
Q3124.005
95-th percentile482.997
Maximum29556.6
Range29556.6
Interquartile range (IQR)89.935

Descriptive statistics

Standard deviation829.82557
Coefficient of variation (CV)5.1569551
Kurtosis963.44594
Mean160.91386
Median Absolute Deviation (MAD)38.925
Skewness28.950203
Sum595059.47
Variance688610.48
MonotonicityNot monotonic
2024-05-18T07:06:51.107592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.0 41
 
0.6%
33.0 37
 
0.5%
26.4 35
 
0.5%
0.0 27
 
0.4%
66.0 24
 
0.3%
30.0 23
 
0.3%
23.1 22
 
0.3%
103.32 22
 
0.3%
66.38 22
 
0.3%
100.97 21
 
0.3%
Other values (1456) 3424
46.8%
(Missing) 3626
49.5%
ValueCountFrequency (%)
0.0 27
0.4%
1.1 2
 
< 0.1%
1.3 2
 
< 0.1%
1.6 1
 
< 0.1%
2.0 2
 
< 0.1%
3.0 4
 
0.1%
3.3 1
 
< 0.1%
4.0 3
 
< 0.1%
4.1 1
 
< 0.1%
4.3 1
 
< 0.1%
ValueCountFrequency (%)
29556.6 2
< 0.1%
21131.68 1
 
< 0.1%
6240.24 1
 
< 0.1%
5170.8 3
< 0.1%
4225.19 1
 
< 0.1%
4198.0 1
 
< 0.1%
3995.0 2
< 0.1%
3072.42 1
 
< 0.1%
2865.29 2
< 0.1%
2858.88 1
 
< 0.1%

Interactions

2024-05-18T07:06:18.343993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:12.182670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:13.663939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:15.434574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:16.811351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:18.632538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:12.479214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:14.164959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:15.730531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:17.160955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:18.917141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:12.753520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:14.494445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:15.972137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:17.459822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:19.200433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:13.024793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:14.788664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:16.249087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:17.759528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:19.475800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:13.392618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:15.108618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:16.551764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T07:06:18.049520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T07:06:51.452300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.0000.5300.6360.9910.9900.4480.098
업종명0.5301.0000.9980.5370.5320.6080.791
업태명0.6360.9981.0000.6380.6350.7230.933
지도점검일자0.9910.5370.6381.0001.0000.3580.102
위반일자0.9900.5320.6351.0001.0000.3630.102
처분기간0.4480.6080.7230.3580.3631.000NaN
영업장면적(㎡)0.0980.7910.9330.1020.102NaN1.000
2024-05-18T07:06:51.806733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명
처분일자1.0000.9990.9990.103-0.1120.212
지도점검일자0.9991.0001.0000.097-0.1150.215
위반일자0.9991.0001.0000.097-0.1150.213
처분기간0.1030.0970.0971.000-0.1600.312
영업장면적(㎡)-0.112-0.115-0.115-0.1601.0000.508
업종명0.2120.2150.2130.3120.5081.000

Missing values

2024-05-18T07:06:20.094868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T07:06:20.928371image/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.
2024-05-18T07:06:21.416793image/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(㎡)
0316000020090601002숙박업(일반)여인숙업원선서울특별시 구로구 구로동로22길 5-14, (구로동)서울특별시 구로구 구로동 733번지 35호20090305처분확정영업정지 2월(2009.6.2~8.2)공중위생관리법제11조제1항20090305성매매알선등영업정지 2월(2009.6.2~8.2)<NA>97.59
131600002003020325300410700013숙박업(일반)여인숙업충남서울특별시 구로구 구로동로26길 55-8, (구로동)서울특별시 구로구 구로동 730번지 29호20021215처분확정영업정지공중위생관리법11조1항20021215윤락행위알선영업정지<NA>47.93
2316000020140226010숙박업(일반)여인숙업나나서울특별시 구로구 경인로15길 8-6, (오류동)서울특별시 구로구 오류동 6번지 114호20120812처분확정과징금부과공중위생관리법 제11조제1항20120812청소년 이성혼숙과징금부과<NA>138.84
3316000020050325006숙박업(일반)여인숙업삼화서울특별시 구로구 구로동로35길 13, (구로동)서울특별시 구로구 구로동 414번지 30호20041001처분확정영업정지풍속영업의규제에관한법률20011001윤락행위알선제공영업정지<NA>189.42
4316000020050325<NA>숙박업(일반)여인숙업삼화서울특별시 구로구 구로동로35길 13, (구로동)서울특별시 구로구 구로동 414번지 30호20050325처분확정영업정지 1월공중위생관리법 제11조 1항20041101윤락행위알선장소제공영업정지 1월30189.42
5316000020070703005숙박업(일반)여인숙업산호서울특별시 구로구 구로동로25길 5-8, (구로동)서울특별시 구로구 구로동 728번지 12호20070526처분확정영업정지2월에 갈음하는 과징금 부과공중위생관리법제11조1항20070526청소년보호법위반(청소년이성혼숙)영업정지2월에 갈음하는 과징금 부과<NA>41.32
6316000020130122011숙박업(일반)여인숙업대교장서울특별시 구로구 구로동로17길 8-3, (구로동)서울특별시 구로구 구로동 722번지 26호20120912처분확정과징금부과공중위생관리법 제11조제1항20120912청소년 이성혼숙과징금부과<NA>167.27
7316000020040729014숙박업(일반)여인숙업수원서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20040618처분확정영업정지공중위생관리법제11조1항20040618윤락행위알선장소제공영업정지<NA>85.96
8316000020040729<NA>숙박업(일반)여인숙업수원여인숙서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20040618처분확정영업정지 2월공중위생관리법 제11조1항20040618윤락행위 알선 장소제공영업정지 2월6085.96
9316000020091124014숙박업(일반)여인숙업수원서울특별시 구로구 구로동로25길 10-15, (구로동)서울특별시 구로구 구로동 705번지 9호20090820처분확정영업정지 2월(2009.12.01~2010.01.31)공중위생관리법제11조20090820성매매 알선등 행위의 처벌에 관한 법률 위반영업정지 2월(2009.12.01~2010.01.31)<NA>85.96
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
731431600002023112320210081017건강기능식품일반판매업전자상거래(통신판매업)거위의 꿈서울특별시 구로구 디지털로34길 55, 코오롱싸이언스밸리2차 지하1층 B101-166호 (구로동)서울특별시 구로구 구로동 811번지 코오롱싸이언스밸리2차20231020처분확정과태료부과법 제47조제1항제6호202310202022년 위생교육 미이수과태료부과<NA><NA>
731531600002023020120120086921건강기능식품유통전문판매업건강기능식품유통전문판매업뉴키주식회사서울특별시 구로구 경인로 661, 신도림1차푸르지오 105동 503호 (신도림동)서울특별시 구로구 신도림동 337번지 신도림1차푸르지오20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA>
731631600002023020120120086921건강기능식품유통전문판매업건강기능식품유통전문판매업뉴키주식회사서울특별시 구로구 경인로 661, 신도림1차푸르지오 105동 503호 (신도림동)서울특별시 구로구 신도림동 337번지 신도림1차푸르지오20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA>
731731600002022011820180080399건강기능식품유통전문판매업건강기능식품유통전문판매업(주)잇라이프서울특별시 구로구 디지털로33길 12, 우림이비지센터2차 701호 (구로동)서울특별시 구로구 구로동 184번지 1호 우림이비지센터2차20211217처분확정시정명령법 제14조부터 제 17조까지20211217건강기능식품 주표시면에 제품명 “맨즈텐(73point)”을 표시하면서, 기준?규격상의 명칭(쏘팔메토열매추출물,옥타코사놀함유유지,아연,셀렌,밀크씨슬추출물,판토텐산,비타민B1, 비타민2,비타민B6)을 2분의 1미만인 8.5point 크기로 표시된 제품 유통?판매한 사실이 있음시정명령<NA>6.6
731831600002022011820180080399건강기능식품유통전문판매업건강기능식품유통전문판매업(주)잇라이프서울특별시 구로구 디지털로33길 12, 우림이비지센터2차 701호 (구로동)서울특별시 구로구 구로동 184번지 1호 우림이비지센터2차20211217처분확정시정명령법 제14조부터 제 17조까지20211217건강기능식품 주표시면에 제품명 “맨즈텐(73point)”을 표시하면서, 기준?규격상의 명칭(쏘팔메토열매추출물,옥타코사놀함유유지,아연,셀렌,밀크씨슬추출물,판토텐산,비타민B1, 비타민2,비타민B6)을 2분의 1미만인 8.5point 크기로 표시된 제품 유통?판매한 사실이 있음시정명령<NA><NA>
731931600002023112320190081079건강기능식품유통전문판매업건강기능식품유통전문판매업주식회사 에이지엣랩스서울특별시 구로구 디지털로32길 55, 5층 (구로동)서울특별시 구로구 구로동 817번지20231020처분확정과태료부과법 제47조제1항제6호202310202022년도 위생교육 미이수과태료부과<NA><NA>
732031600002023112320190081079건강기능식품유통전문판매업건강기능식품유통전문판매업주식회사 에이지엣랩스서울특별시 구로구 디지털로32길 55, 5층 (구로동)서울특별시 구로구 구로동 817번지20231020처분확정과태료부과법 제47조제1항제6호202310202022년도 위생교육 미이수과태료부과<NA><NA>
732131600002023020120190081354건강기능식품유통전문판매업건강기능식품유통전문판매업(주)비올서울특별시 구로구 디지털로26길 5, 에이스하이엔드타워1차 1117호 (구로동)서울특별시 구로구 구로동 235번지 2호 에이스하이엔드타워1차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA>
732231600002023020120210080110건강기능식품유통전문판매업건강기능식품유통전문판매업(주)알에이치마케팅서울특별시 구로구 디지털로33길 50, 벽산디지털밸리7차 9층 905호 (구로동)서울특별시 구로구 구로동 170번지 13호 벽산디지털밸리7차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA>7.5
732331600002023020120210080110건강기능식품유통전문판매업건강기능식품유통전문판매업(주)알에이치마케팅서울특별시 구로구 디지털로33길 50, 벽산디지털밸리7차 9층 905호 (구로동)서울특별시 구로구 구로동 170번지 13호 벽산디지털밸리7차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
26331600002016012920030080686식품등 수입판매업식품등 수입판매업(주)제이비엔서울특별시 구로구 가마산로 279, 908호 (구로동, 동남오피스텔)서울특별시 구로구 구로동 104번지 10호 동남오피스텔-90820150126처분확정영업소폐쇄법 제71조, 법 제74조,법 제75조 및 법 제76조20150126무단폐업(영업시설의 전부를 철거)영업소폐쇄<NA><NA>8
3531600002006112319910080356일반음식점한식오류동집<NA>서울특별시 구로구 오류동 56번지 39호20061020처분확정영업정지 7일갈음 과징금 840,000원 부과식품위생법 제22조5항20061020영업장 무단확장 영업영업정지 7일갈음 과징금 840,000원 부과738.876
8031600002009080319980080014단란주점단란주점골든벨노래클럽<NA>서울특별시 구로구 신도림동 292번지 123호20090618처분확정시정명령 및 시설개수명령식품위생법 제21조20090618개실에 불투명 유리 설치(1차)시정명령 및 시설개수명령<NA>60.486
931600002003032420000080645식품제조가공업식품제조가공업서울식품서울특별시 구로구 부일로9길 133, (온수동,온수상가 105호)서울특별시 구로구 온수동 141번지 0호 온수상가 105호20030319처분확정시정명령식품위생법 제55조20030319표시기준 위반(포장지 재질 미표시)시정명령<NA><NA>4
3431600002006112319910080356일반음식점한식오류동집<NA>서울특별시 구로구 오류동 56번지 39호20061020처분확정영업정지 7일갈음 과징금 840,000원 부과식품위생법 제22조 5항20061020영업장 무단확장 영업영업정지 7일갈음 과징금 840,000원 부과738.874
13831600002011090719950080576단란주점단란주점뉴월드<NA>서울특별시 구로구 개봉동 353번지 30호20110513처분확정시설개수명령식품위생법 36조 37조20110513시설개수명령(1차)시설개수명령<NA>146.964
142316000020111201358이용업일반이용업만남서울특별시 구로구 구로동로 159, (구로동)서울특별시 구로구 구로동 413번지 80호20110601처분확정면허정지2월공중위생관리법 제11조제1항20110601성매매알선 등면허정지2월<NA><NA>4
143316000020111201358이용업일반이용업만남서울특별시 구로구 구로동로 159, (구로동)서울특별시 구로구 구로동 413번지 80호20110601처분확정영업정지2월공중위생관리법 제11조제1항20110601성매매알선 등영업정지2월<NA><NA>4
15031600002012020120000080651일반음식점분식풀코스호프<NA>서울특별시 구로구 고척동 76번지 181호20111210처분확정영업정지15일 및 과징금 150만원식품위생법제44조20111210청소년주류제공(1차)영업정지15일 및 과징금 150만원15<NA>4
160316000020120904284이용업일반이용업휴게이용원서울특별시 구로구 경인로 216, (오류동,(3층))서울특별시 구로구 오류동 55번지 50호 (3층)20111104처분확정면허정지공중위생관리법 제11조제1항20111104성매매알선면허정지0136.04