Overview

Dataset statistics

Number of variables18
Number of observations6436
Missing cells12301
Missing cells (%)10.6%
Duplicate rows283
Duplicate rows (%)4.4%
Total size in memory949.2 KiB
Average record size in memory151.0 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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-2296/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 283 (4.4%) duplicate rowsDuplicates
운영형태 is highly overall correlated with 교부번호 and 4 other fieldsHigh correlation
업종명 is highly overall correlated with 운영형태High correlation
처분일자 is highly overall correlated with 교부번호 and 2 other fieldsHigh correlation
교부번호 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
지도점검일자 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
위반일자 is highly overall correlated with 처분일자 and 3 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 운영형태High correlation
업종명 is highly imbalanced (52.3%)Imbalance
운영형태 is highly imbalanced (96.6%)Imbalance
소재지도로명 has 3176 (49.3%) missing valuesMissing
처분기간 has 5517 (85.7%) missing valuesMissing
영업장면적(㎡) has 3567 (55.4%) missing valuesMissing
영업장면적(㎡) is highly skewed (γ1 = 33.80413529)Skewed

Reproduction

Analysis started2024-05-03 23:41:52.000919
Analysis finished2024-05-03 23:42:19.039896
Duration27.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
3160000
6436 

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 6436
100.0%

Length

2024-05-03T23:42:19.278617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:42:19.730910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 6436
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION 

Distinct1984
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124051
Minimum20011012
Maximum20240424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:20.189058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20011012
5-th percentile20020912
Q120080124
median20130225
Q320171201
95-th percentile20230131
Maximum20240424
Range229412
Interquartile range (IQR)91076.75

Descriptive statistics

Standard deviation61603.923
Coefficient of variation (CV)0.0030612088
Kurtosis-1.0301118
Mean20124051
Median Absolute Deviation (MAD)49907
Skewness-0.034198078
Sum1.2951839 × 1011
Variance3.7950433 × 109
MonotonicityNot monotonic
2024-05-03T23:42:20.795706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230201 57
 
0.9%
20141103 52
 
0.8%
20160129 50
 
0.8%
20190822 44
 
0.7%
20231123 44
 
0.7%
20111011 41
 
0.6%
20131008 34
 
0.5%
20191111 32
 
0.5%
20230607 32
 
0.5%
20140804 30
 
0.5%
Other values (1974) 6020
93.5%
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
0.2%
20240223 2
 
< 0.1%
20240215 1
 
< 0.1%
20240208 1
 
< 0.1%
20240207 1
 
< 0.1%
20240205 4
 
0.1%

교부번호
Real number (ℝ)

HIGH CORRELATION 

Distinct3186
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0039146 × 1010
Minimum1.970008 × 1010
Maximum2.0230107 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:21.395425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.970008 × 1010
5-th percentile1.988008 × 1010
Q11.998008 × 1010
median2.0040081 × 1010
Q32.011008 × 1010
95-th percentile2.0180081 × 1010
Maximum2.0230107 × 1010
Range5.3002721 × 108
Interquartile range (IQR)1.3000007 × 108

Descriptive statistics

Standard deviation90383097
Coefficient of variation (CV)0.0045103267
Kurtosis-0.21810953
Mean2.0039146 × 1010
Median Absolute Deviation (MAD)60001153
Skewness-0.34320611
Sum1.2897195 × 1014
Variance8.1691043 × 1015
MonotonicityNot monotonic
2024-05-03T23:42:22.055587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120094434 42
 
0.7%
19930080713 33
 
0.5%
20180080042 33
 
0.5%
20050080133 27
 
0.4%
19960080459 22
 
0.3%
19830080204 21
 
0.3%
19950080183 21
 
0.3%
20180080803 20
 
0.3%
20070080514 18
 
0.3%
20160080561 18
 
0.3%
Other values (3176) 6181
96.0%
ValueCountFrequency (%)
19700080001 1
 
< 0.1%
19700080003 1
 
< 0.1%
19700080004 1
 
< 0.1%
19700080012 1
 
< 0.1%
19730080005 2
< 0.1%
19750080013 1
 
< 0.1%
19770080008 2
< 0.1%
19770080019 4
0.1%
19780080017 1
 
< 0.1%
19780080020 1
 
< 0.1%
ValueCountFrequency (%)
20230107209 1
< 0.1%
20230107143 2
< 0.1%
20230107112 2
< 0.1%
20230106945 1
< 0.1%
20230106625 1
< 0.1%
20230106505 2
< 0.1%
20230106145 1
< 0.1%
20220099626 1
< 0.1%
20220099412 1
< 0.1%
20220099344 2
< 0.1%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct22
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
일반음식점
4168 
단란주점
468 
휴게음식점
 
340
식품제조가공업
 
306
즉석판매제조가공업
 
267
Other values (17)
887 

Length

Max length13
Median length5
Mean length5.5797079
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 4168
64.8%
단란주점 468
 
7.3%
휴게음식점 340
 
5.3%
식품제조가공업 306
 
4.8%
즉석판매제조가공업 267
 
4.1%
건강기능식품일반판매업 192
 
3.0%
유흥주점영업 179
 
2.8%
유통전문판매업 144
 
2.2%
식품등 수입판매업 114
 
1.8%
제과점영업 66
 
1.0%
Other values (12) 192
 
3.0%

Length

2024-05-03T23:42:22.661602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 4168
63.6%
단란주점 468
 
7.1%
휴게음식점 340
 
5.2%
식품제조가공업 306
 
4.7%
즉석판매제조가공업 267
 
4.1%
건강기능식품일반판매업 192
 
2.9%
유흥주점영업 179
 
2.7%
유통전문판매업 144
 
2.2%
식품등 114
 
1.7%
수입판매업 114
 
1.7%
Other values (13) 258
 
3.9%
Distinct64
Distinct (%)1.0%
Missing30
Missing (%)0.5%
Memory size50.4 KiB
2024-05-03T23:42:23.233289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.411177
Min length2

Characters and Unicode

Total characters28258
Distinct characters141
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

Unique5 ?
Unique (%)0.1%

Sample

1st row한식
2nd row한식
3rd row한식
4th row한식
5th row한식
ValueCountFrequency (%)
한식 1531
23.0%
호프/통닭 1423
21.4%
단란주점 468
 
7.0%
식품제조가공업 306
 
4.6%
즉석판매제조가공업 267
 
4.0%
통닭(치킨 262
 
3.9%
분식 241
 
3.6%
중국식 241
 
3.6%
기타 211
 
3.2%
유통전문판매업 144
 
2.2%
Other values (54) 1560
23.4%
2024-05-03T23:42:24.564378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2883
 
10.2%
1932
 
6.8%
1685
 
6.0%
1531
 
5.4%
/ 1505
 
5.3%
1423
 
5.0%
1423
 
5.0%
1183
 
4.2%
831
 
2.9%
830
 
2.9%
Other values (131) 13032
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25793
91.3%
Other Punctuation 1513
 
5.4%
Open Punctuation 352
 
1.2%
Close Punctuation 352
 
1.2%
Space Separator 248
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2883
 
11.2%
1932
 
7.5%
1685
 
6.5%
1531
 
5.9%
1423
 
5.5%
1423
 
5.5%
1183
 
4.6%
831
 
3.2%
830
 
3.2%
647
 
2.5%
Other values (125) 11425
44.3%
Other Punctuation
ValueCountFrequency (%)
/ 1505
99.5%
, 4
 
0.3%
. 4
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 352
100.0%
Close Punctuation
ValueCountFrequency (%)
) 352
100.0%
Space Separator
ValueCountFrequency (%)
248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25793
91.3%
Common 2465
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2883
 
11.2%
1932
 
7.5%
1685
 
6.5%
1531
 
5.9%
1423
 
5.5%
1423
 
5.5%
1183
 
4.6%
831
 
3.2%
830
 
3.2%
647
 
2.5%
Other values (125) 11425
44.3%
Common
ValueCountFrequency (%)
/ 1505
61.1%
( 352
 
14.3%
) 352
 
14.3%
248
 
10.1%
, 4
 
0.2%
. 4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25793
91.3%
ASCII 2465
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2883
 
11.2%
1932
 
7.5%
1685
 
6.5%
1531
 
5.9%
1423
 
5.5%
1423
 
5.5%
1183
 
4.6%
831
 
3.2%
830
 
3.2%
647
 
2.5%
Other values (125) 11425
44.3%
ASCII
ValueCountFrequency (%)
/ 1505
61.1%
( 352
 
14.3%
) 352
 
14.3%
248
 
10.1%
, 4
 
0.2%
. 4
 
0.2%
Distinct3201
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
2024-05-03T23:42:25.388037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length27
Mean length5.4779366
Min length1

Characters and Unicode

Total characters35256
Distinct characters875
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

Unique1895 ?
Unique (%)29.4%

Sample

1st row평양면옥
2nd row황제꽃소
3rd row황제꽃소
4th row황제꽃소
5th row황제꽃소
ValueCountFrequency (%)
주식회사 67
 
0.9%
떡愛미소식품 42
 
0.6%
roasters 37
 
0.5%
어라운드 35
 
0.5%
로스터스(around 35
 
0.5%
신도림점 33
 
0.4%
치킨 28
 
0.4%
오아시스 27
 
0.4%
둘둘치킨 26
 
0.3%
여비서 25
 
0.3%
Other values (3515) 7253
95.3%
2024-05-03T23:42:26.572805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1173
 
3.3%
759
 
2.2%
756
 
2.1%
667
 
1.9%
) 561
 
1.6%
( 556
 
1.6%
537
 
1.5%
526
 
1.5%
423
 
1.2%
418
 
1.2%
Other values (865) 28880
81.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31246
88.6%
Space Separator 1173
 
3.3%
Lowercase Letter 914
 
2.6%
Close Punctuation 561
 
1.6%
Open Punctuation 556
 
1.6%
Uppercase Letter 421
 
1.2%
Decimal Number 257
 
0.7%
Other Punctuation 114
 
0.3%
Dash Punctuation 12
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
759
 
2.4%
756
 
2.4%
667
 
2.1%
537
 
1.7%
526
 
1.7%
423
 
1.4%
418
 
1.3%
416
 
1.3%
416
 
1.3%
401
 
1.3%
Other values (791) 25927
83.0%
Uppercase Letter
ValueCountFrequency (%)
B 41
 
9.7%
K 39
 
9.3%
C 37
 
8.8%
S 24
 
5.7%
M 24
 
5.7%
T 23
 
5.5%
N 22
 
5.2%
A 22
 
5.2%
L 20
 
4.8%
R 20
 
4.8%
Other values (15) 149
35.4%
Lowercase Letter
ValueCountFrequency (%)
r 134
14.7%
o 117
12.8%
a 115
12.6%
e 93
10.2%
s 84
9.2%
n 57
6.2%
u 52
 
5.7%
t 47
 
5.1%
d 41
 
4.5%
f 32
 
3.5%
Other values (12) 142
15.5%
Other Punctuation
ValueCountFrequency (%)
. 56
49.1%
& 17
 
14.9%
, 10
 
8.8%
; 8
 
7.0%
' 6
 
5.3%
! 4
 
3.5%
? 4
 
3.5%
3
 
2.6%
/ 3
 
2.6%
: 2
 
1.8%
Decimal Number
ValueCountFrequency (%)
2 55
21.4%
1 42
16.3%
0 36
14.0%
5 27
10.5%
9 23
8.9%
8 18
 
7.0%
3 16
 
6.2%
7 16
 
6.2%
6 14
 
5.4%
4 9
 
3.5%
Space Separator
ValueCountFrequency (%)
1173
100.0%
Close Punctuation
ValueCountFrequency (%)
) 561
100.0%
Open Punctuation
ValueCountFrequency (%)
( 556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31185
88.5%
Common 2675
 
7.6%
Latin 1335
 
3.8%
Han 61
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
759
 
2.4%
756
 
2.4%
667
 
2.1%
537
 
1.7%
526
 
1.7%
423
 
1.4%
418
 
1.3%
416
 
1.3%
416
 
1.3%
401
 
1.3%
Other values (775) 25866
82.9%
Latin
ValueCountFrequency (%)
r 134
 
10.0%
o 117
 
8.8%
a 115
 
8.6%
e 93
 
7.0%
s 84
 
6.3%
n 57
 
4.3%
u 52
 
3.9%
t 47
 
3.5%
B 41
 
3.1%
d 41
 
3.1%
Other values (37) 554
41.5%
Common
ValueCountFrequency (%)
1173
43.9%
) 561
21.0%
( 556
20.8%
. 56
 
2.1%
2 55
 
2.1%
1 42
 
1.6%
0 36
 
1.3%
5 27
 
1.0%
9 23
 
0.9%
8 18
 
0.7%
Other values (17) 128
 
4.8%
Han
ValueCountFrequency (%)
42
68.9%
4
 
6.6%
2
 
3.3%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Other values (6) 6
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31185
88.5%
ASCII 4006
 
11.4%
CJK 61
 
0.2%
None 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1173
29.3%
) 561
14.0%
( 556
13.9%
r 134
 
3.3%
o 117
 
2.9%
a 115
 
2.9%
e 93
 
2.3%
s 84
 
2.1%
n 57
 
1.4%
. 56
 
1.4%
Other values (62) 1060
26.5%
Hangul
ValueCountFrequency (%)
759
 
2.4%
756
 
2.4%
667
 
2.1%
537
 
1.7%
526
 
1.7%
423
 
1.4%
418
 
1.3%
416
 
1.3%
416
 
1.3%
401
 
1.3%
Other values (775) 25866
82.9%
CJK
ValueCountFrequency (%)
42
68.9%
4
 
6.6%
2
 
3.3%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Other values (6) 6
 
9.8%
None
ValueCountFrequency (%)
3
75.0%
1
 
25.0%

소재지도로명
Text

MISSING 

Distinct1629
Distinct (%)50.0%
Missing3176
Missing (%)49.3%
Memory size50.4 KiB
2024-05-03T23:42:27.498492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length56
Mean length33.987423
Min length22

Characters and Unicode

Total characters110799
Distinct characters336
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

Unique944 ?
Unique (%)29.0%

Sample

1st row서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)
2nd row서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)
3rd row서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)
4th row서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)
5th row서울특별시 구로구 남부순환로97길 26-2, (개봉동)
ValueCountFrequency (%)
서울특별시 3260
 
16.2%
구로구 3260
 
16.2%
구로동 1373
 
6.8%
1층 586
 
2.9%
개봉동 323
 
1.6%
경인로 306
 
1.5%
고척동 301
 
1.5%
오류동 279
 
1.4%
신도림동 217
 
1.1%
2층 164
 
0.8%
Other values (1721) 10103
50.1%
2024-05-03T23:42:28.993520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16925
 
15.3%
8801
 
7.9%
8751
 
7.9%
1 5207
 
4.7%
, 4856
 
4.4%
3878
 
3.5%
3418
 
3.1%
) 3418
 
3.1%
( 3417
 
3.1%
3327
 
3.0%
Other values (326) 48801
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62740
56.6%
Decimal Number 18389
 
16.6%
Space Separator 16925
 
15.3%
Other Punctuation 4874
 
4.4%
Close Punctuation 3420
 
3.1%
Open Punctuation 3419
 
3.1%
Dash Punctuation 743
 
0.7%
Uppercase Letter 259
 
0.2%
Math Symbol 15
 
< 0.1%
Lowercase Letter 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8801
14.0%
8751
13.9%
3878
 
6.2%
3418
 
5.4%
3327
 
5.3%
3265
 
5.2%
3261
 
5.2%
3260
 
5.2%
1980
 
3.2%
1438
 
2.3%
Other values (280) 21361
34.0%
Uppercase Letter
ValueCountFrequency (%)
B 118
45.6%
A 43
 
16.6%
S 22
 
8.5%
K 18
 
6.9%
F 10
 
3.9%
C 9
 
3.5%
T 9
 
3.5%
R 6
 
2.3%
D 3
 
1.2%
I 3
 
1.2%
Other values (8) 18
 
6.9%
Decimal Number
ValueCountFrequency (%)
1 5207
28.3%
2 3133
17.0%
3 2080
 
11.3%
0 1816
 
9.9%
7 1212
 
6.6%
6 1198
 
6.5%
4 1025
 
5.6%
5 1001
 
5.4%
8 958
 
5.2%
9 759
 
4.1%
Lowercase Letter
ValueCountFrequency (%)
b 4
36.4%
k 2
18.2%
j 1
 
9.1%
n 1
 
9.1%
e 1
 
9.1%
i 1
 
9.1%
z 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 4856
99.6%
/ 9
 
0.2%
. 9
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 3418
99.9%
] 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 3417
99.9%
[ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
16925
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 743
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62738
56.6%
Common 47789
43.1%
Latin 270
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8801
14.0%
8751
13.9%
3878
 
6.2%
3418
 
5.4%
3327
 
5.3%
3265
 
5.2%
3261
 
5.2%
3260
 
5.2%
1980
 
3.2%
1438
 
2.3%
Other values (278) 21359
34.0%
Latin
ValueCountFrequency (%)
B 118
43.7%
A 43
 
15.9%
S 22
 
8.1%
K 18
 
6.7%
F 10
 
3.7%
C 9
 
3.3%
T 9
 
3.3%
R 6
 
2.2%
b 4
 
1.5%
D 3
 
1.1%
Other values (15) 28
 
10.4%
Common
ValueCountFrequency (%)
16925
35.4%
1 5207
 
10.9%
, 4856
 
10.2%
) 3418
 
7.2%
( 3417
 
7.2%
2 3133
 
6.6%
3 2080
 
4.4%
0 1816
 
3.8%
7 1212
 
2.5%
6 1198
 
2.5%
Other values (11) 4527
 
9.5%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62738
56.6%
ASCII 48055
43.4%
CJK Compat 4
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16925
35.2%
1 5207
 
10.8%
, 4856
 
10.1%
) 3418
 
7.1%
( 3417
 
7.1%
2 3133
 
6.5%
3 2080
 
4.3%
0 1816
 
3.8%
7 1212
 
2.5%
6 1198
 
2.5%
Other values (35) 4793
 
10.0%
Hangul
ValueCountFrequency (%)
8801
14.0%
8751
13.9%
3878
 
6.2%
3418
 
5.4%
3327
 
5.3%
3265
 
5.2%
3261
 
5.2%
3260
 
5.2%
1980
 
3.2%
1438
 
2.3%
Other values (278) 21359
34.0%
CJK Compat
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct2720
Distinct (%)42.3%
Missing11
Missing (%)0.2%
Memory size50.4 KiB
2024-05-03T23:42:29.756990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length60
Mean length29.708482
Min length20

Characters and Unicode

Total characters190877
Distinct characters361
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

Unique1433 ?
Unique (%)22.3%

Sample

1st row서울특별시 구로구 오류동 13번지 55호
2nd row서울특별시 구로구 개봉동 70번지 16호 우분투포레스트
3rd row서울특별시 구로구 개봉동 70번지 16호 우분투포레스트
4th row서울특별시 구로구 개봉동 70번지 16호 우분투포레스트
5th row서울특별시 구로구 개봉동 70번지 16호 우분투포레스트
ValueCountFrequency (%)
구로구 6430
 
17.7%
서울특별시 6425
 
17.7%
구로동 3173
 
8.7%
개봉동 870
 
2.4%
고척동 794
 
2.2%
오류동 548
 
1.5%
1호 487
 
1.3%
신도림동 460
 
1.3%
1층 381
 
1.0%
가리봉동 369
 
1.0%
Other values (1969) 16395
45.1%
2024-05-03T23:42:31.018128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46112
24.2%
16237
 
8.5%
9822
 
5.1%
1 9465
 
5.0%
7349
 
3.9%
6724
 
3.5%
6529
 
3.4%
6461
 
3.4%
6449
 
3.4%
6433
 
3.4%
Other values (351) 69296
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105939
55.5%
Space Separator 46112
24.2%
Decimal Number 36326
 
19.0%
Dash Punctuation 714
 
0.4%
Other Punctuation 501
 
0.3%
Uppercase Letter 445
 
0.2%
Close Punctuation 402
 
0.2%
Open Punctuation 401
 
0.2%
Math Symbol 22
 
< 0.1%
Lowercase Letter 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16237
15.3%
9822
 
9.3%
7349
 
6.9%
6724
 
6.3%
6529
 
6.2%
6461
 
6.1%
6449
 
6.1%
6433
 
6.1%
6431
 
6.1%
6428
 
6.1%
Other values (301) 27076
25.6%
Uppercase Letter
ValueCountFrequency (%)
B 165
37.1%
A 77
17.3%
K 52
 
11.7%
S 44
 
9.9%
D 25
 
5.6%
C 21
 
4.7%
F 18
 
4.0%
T 11
 
2.5%
E 8
 
1.8%
I 5
 
1.1%
Other values (8) 19
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 9465
26.1%
2 5194
14.3%
3 4200
11.6%
0 3418
 
9.4%
4 3067
 
8.4%
5 2656
 
7.3%
7 2621
 
7.2%
8 2069
 
5.7%
6 2042
 
5.6%
9 1594
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
k 4
30.8%
b 2
15.4%
s 2
15.4%
j 1
 
7.7%
n 1
 
7.7%
e 1
 
7.7%
i 1
 
7.7%
z 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 461
92.0%
. 28
 
5.6%
/ 10
 
2.0%
? 1
 
0.2%
1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 400
99.5%
] 2
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 399
99.5%
[ 2
 
0.5%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
46112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 714
100.0%
Math Symbol
ValueCountFrequency (%)
~ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105937
55.5%
Common 84478
44.3%
Latin 460
 
0.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16237
15.3%
9822
 
9.3%
7349
 
6.9%
6724
 
6.3%
6529
 
6.2%
6461
 
6.1%
6449
 
6.1%
6433
 
6.1%
6431
 
6.1%
6428
 
6.1%
Other values (299) 27074
25.6%
Latin
ValueCountFrequency (%)
B 165
35.9%
A 77
16.7%
K 52
 
11.3%
S 44
 
9.6%
D 25
 
5.4%
C 21
 
4.6%
F 18
 
3.9%
T 11
 
2.4%
E 8
 
1.7%
I 5
 
1.1%
Other values (18) 34
 
7.4%
Common
ValueCountFrequency (%)
46112
54.6%
1 9465
 
11.2%
2 5194
 
6.1%
3 4200
 
5.0%
0 3418
 
4.0%
4 3067
 
3.6%
5 2656
 
3.1%
7 2621
 
3.1%
8 2069
 
2.4%
6 2042
 
2.4%
Other values (12) 3634
 
4.3%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105937
55.5%
ASCII 84935
44.5%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46112
54.3%
1 9465
 
11.1%
2 5194
 
6.1%
3 4200
 
4.9%
0 3418
 
4.0%
4 3067
 
3.6%
5 2656
 
3.1%
7 2621
 
3.1%
8 2069
 
2.4%
6 2042
 
2.4%
Other values (37) 4091
 
4.8%
Hangul
ValueCountFrequency (%)
16237
15.3%
9822
 
9.3%
7349
 
6.9%
6724
 
6.3%
6529
 
6.2%
6461
 
6.1%
6449
 
6.1%
6433
 
6.1%
6431
 
6.1%
6428
 
6.1%
Other values (299) 27074
25.6%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct2594
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121733
Minimum20001218
Maximum20240228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:31.541577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001218
5-th percentile20020710
Q120071121
median20121024
Q320170928
95-th percentile20220548
Maximum20240228
Range239010
Interquartile range (IQR)99807

Descriptive statistics

Standard deviation61631.154
Coefficient of variation (CV)0.0030629148
Kurtosis-1.0049835
Mean20121733
Median Absolute Deviation (MAD)49904.5
Skewness-0.03494572
Sum1.2950347 × 1011
Variance3.7983992 × 109
MonotonicityNot monotonic
2024-05-03T23:42:32.211686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20221124 61
 
0.9%
20230417 55
 
0.9%
20190730 51
 
0.8%
20231020 45
 
0.7%
20140101 37
 
0.6%
20210526 34
 
0.5%
20191002 33
 
0.5%
20140701 31
 
0.5%
20130101 28
 
0.4%
20150706 28
 
0.4%
Other values (2584) 6033
93.7%
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 2
 
< 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 size50.4 KiB
처분확정
6436 

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 6436
100.0%

Length

2024-05-03T23:42:32.831093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:42:33.196197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 6436
100.0%
Distinct716
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
2024-05-03T23:42:33.775711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length66
Mean length7.947949
Min length2

Characters and Unicode

Total characters51153
Distinct characters214
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

Unique414 ?
Unique (%)6.4%

Sample

1st row과징금부과
2nd row과태료부과
3rd row과태료부과
4th row과태료부과
5th row과태료부과
ValueCountFrequency (%)
시정명령 1471
16.0%
영업정지 1466
15.9%
과태료부과 1207
13.1%
영업소폐쇄 589
 
6.4%
부과 301
 
3.3%
과태료 264
 
2.9%
263
 
2.9%
과징금 230
 
2.5%
시설개수명령 207
 
2.3%
과징금부과 207
 
2.3%
Other values (714) 2987
32.5%
2024-05-03T23:42:35.196855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4633
 
9.1%
3616
 
7.1%
2757
 
5.4%
2537
 
5.0%
2521
 
4.9%
0 2402
 
4.7%
2309
 
4.5%
2023
 
4.0%
2 1910
 
3.7%
1908
 
3.7%
Other values (204) 24537
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37632
73.6%
Decimal Number 7685
 
15.0%
Space Separator 2757
 
5.4%
Other Punctuation 1161
 
2.3%
Open Punctuation 833
 
1.6%
Close Punctuation 830
 
1.6%
Math Symbol 184
 
0.4%
Dash Punctuation 71
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (178) 12516
33.3%
Decimal Number
ValueCountFrequency (%)
0 2402
31.3%
2 1910
24.9%
1 1182
15.4%
5 524
 
6.8%
3 452
 
5.9%
4 433
 
5.6%
6 290
 
3.8%
7 198
 
2.6%
8 153
 
2.0%
9 141
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 968
83.4%
, 136
 
11.7%
: 20
 
1.7%
% 17
 
1.5%
17
 
1.5%
/ 3
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 152
82.6%
> 27
 
14.7%
4
 
2.2%
= 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 832
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 829
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37632
73.6%
Common 13521
 
26.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (178) 12516
33.3%
Common
ValueCountFrequency (%)
2757
20.4%
0 2402
17.8%
2 1910
14.1%
1 1182
8.7%
. 968
 
7.2%
( 832
 
6.2%
) 829
 
6.1%
5 524
 
3.9%
3 452
 
3.3%
4 433
 
3.2%
Other values (16) 1232
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37606
73.5%
ASCII 13500
 
26.4%
Compat Jamo 26
 
0.1%
Punctuation 17
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (177) 12490
33.2%
ASCII
ValueCountFrequency (%)
2757
20.4%
0 2402
17.8%
2 1910
14.1%
1 1182
8.8%
. 968
 
7.2%
( 832
 
6.2%
) 829
 
6.1%
5 524
 
3.9%
3 452
 
3.3%
4 433
 
3.2%
Other values (14) 1211
9.0%
Compat Jamo
ValueCountFrequency (%)
26
100.0%
Punctuation
ValueCountFrequency (%)
17
100.0%
Arrows
ValueCountFrequency (%)
4
100.0%
Distinct402
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
2024-05-03T23:42:36.116009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length53
Mean length14.16532
Min length3

Characters and Unicode

Total characters91168
Distinct characters123
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

Unique182 ?
Unique (%)2.8%

Sample

1st row식품위생법7조
2nd row법 제101조제3항제1호
3rd row법 제101조제3항제1호
4th row법 제101조제3항제1호
5th row법 제101조제3항제1호
ValueCountFrequency (%)
3997
20.2%
식품위생법 2959
14.9%
1864
 
9.4%
제75조 1717
 
8.7%
제71조 1317
 
6.6%
제31조 584
 
2.9%
제74조 457
 
2.3%
제101조제2항제1호 419
 
2.1%
제72조 359
 
1.8%
제22조 352
 
1.8%
Other values (314) 5806
29.3%
2024-05-03T23:42:38.096096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13429
14.7%
12206
13.4%
9682
10.6%
8488
9.3%
1 5977
 
6.6%
7 5099
 
5.6%
4159
 
4.6%
4157
 
4.6%
4156
 
4.6%
4105
 
4.5%
Other values (113) 19710
21.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53348
58.5%
Decimal Number 23022
25.3%
Space Separator 13429
 
14.7%
Other Punctuation 1299
 
1.4%
Open Punctuation 34
 
< 0.1%
Close Punctuation 34
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12206
22.9%
9682
18.1%
8488
15.9%
4159
 
7.8%
4157
 
7.8%
4156
 
7.8%
4105
 
7.7%
1900
 
3.6%
1873
 
3.5%
935
 
1.8%
Other values (93) 1687
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 5977
26.0%
7 5099
22.1%
2 2940
12.8%
5 2554
11.1%
4 2247
 
9.8%
3 1508
 
6.6%
0 1153
 
5.0%
6 933
 
4.1%
8 569
 
2.5%
9 42
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1271
97.8%
. 19
 
1.5%
? 8
 
0.6%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 31
91.2%
[ 3
 
8.8%
Close Punctuation
ValueCountFrequency (%)
) 31
91.2%
] 3
 
8.8%
Space Separator
ValueCountFrequency (%)
13429
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53347
58.5%
Common 37818
41.5%
Latin 2
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12206
22.9%
9682
18.1%
8488
15.9%
4159
 
7.8%
4157
 
7.8%
4156
 
7.8%
4105
 
7.7%
1900
 
3.6%
1873
 
3.5%
935
 
1.8%
Other values (92) 1686
 
3.2%
Common
ValueCountFrequency (%)
13429
35.5%
1 5977
15.8%
7 5099
 
13.5%
2 2940
 
7.8%
5 2554
 
6.8%
4 2247
 
5.9%
3 1508
 
4.0%
, 1271
 
3.4%
0 1153
 
3.0%
6 933
 
2.5%
Other values (9) 707
 
1.9%
Latin
ValueCountFrequency (%)
2
100.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53345
58.5%
ASCII 37817
41.5%
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 (%)
13429
35.5%
1 5977
15.8%
7 5099
 
13.5%
2 2940
 
7.8%
5 2554
 
6.8%
4 2247
 
5.9%
3 1508
 
4.0%
, 1271
 
3.4%
0 1153
 
3.0%
6 933
 
2.5%
Other values (8) 706
 
1.9%
Hangul
ValueCountFrequency (%)
12206
22.9%
9682
18.1%
8488
15.9%
4159
 
7.8%
4157
 
7.8%
4156
 
7.8%
4105
 
7.7%
1900
 
3.6%
1873
 
3.5%
935
 
1.8%
Other values (91) 1684
 
3.2%
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 

Distinct2608
Distinct (%)40.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20121612
Minimum20001218
Maximum20240222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:38.756775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001218
5-th percentile20020709
Q120071121
median20121026
Q320170925
95-th percentile20220294
Maximum20240222
Range239004
Interquartile range (IQR)99804

Descriptive statistics

Standard deviation61531.552
Coefficient of variation (CV)0.0030579833
Kurtosis-1.0012721
Mean20121612
Median Absolute Deviation (MAD)49904.5
Skewness-0.036220785
Sum1.2950269 × 1011
Variance3.7861319 × 109
MonotonicityNot monotonic
2024-05-03T23:42:39.323842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20221124 61
 
0.9%
20230417 55
 
0.9%
20190730 51
 
0.8%
20231020 45
 
0.7%
20050715 38
 
0.6%
20140101 37
 
0.6%
20191002 33
 
0.5%
20140701 31
 
0.5%
20210526 30
 
0.5%
20191231 28
 
0.4%
Other values (2598) 6027
93.6%
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 2
 
< 0.1%
20240202 6
0.1%
20240201 4
0.1%
20240116 1
 
< 0.1%
20240103 1
 
< 0.1%
20231230 1
 
< 0.1%
Distinct1980
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
2024-05-03T23:42:40.237942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length218
Median length109
Mean length16.784338
Min length4

Characters and Unicode

Total characters108024
Distinct characters567
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

Unique1196 ?
Unique (%)18.6%

Sample

1st row대장균기준위반(1차)
2nd row건강진단을 받지 않은 자를 영업에 종사시킨 영업자(1차)
3rd row건강진단을 받지 않은 자를 영업에 종사시킨 영업자(1차)
4th row종업원 건강진단 미필(3명중 1명)(1차)
5th row종업원 건강진단 미필(3명중 1명)(1차)
ValueCountFrequency (%)
1차 482
 
2.3%
위생교육 457
 
2.2%
미이수 392
 
1.9%
건강진단 390
 
1.9%
전부 283
 
1.4%
영업장외 278
 
1.3%
영업시설물 264
 
1.3%
256
 
1.2%
미필 234
 
1.1%
영업 226
 
1.1%
Other values (2496) 17681
84.4%
2024-05-03T23:42:42.376885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15419
 
14.3%
3967
 
3.7%
1 3488
 
3.2%
) 3205
 
3.0%
( 3180
 
2.9%
3026
 
2.8%
2665
 
2.5%
2318
 
2.1%
1622
 
1.5%
1555
 
1.4%
Other values (557) 67579
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77352
71.6%
Space Separator 15419
 
14.3%
Decimal Number 6928
 
6.4%
Close Punctuation 3209
 
3.0%
Open Punctuation 3184
 
2.9%
Other Punctuation 1489
 
1.4%
Dash Punctuation 229
 
0.2%
Uppercase Letter 122
 
0.1%
Lowercase Letter 54
 
< 0.1%
Initial Punctuation 8
 
< 0.1%
Other values (5) 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3967
 
5.1%
3026
 
3.9%
2665
 
3.4%
2318
 
3.0%
1622
 
2.1%
1555
 
2.0%
1440
 
1.9%
1406
 
1.8%
1317
 
1.7%
1293
 
1.7%
Other values (492) 56743
73.4%
Uppercase Letter
ValueCountFrequency (%)
A 18
14.8%
O 11
9.0%
U 11
9.0%
N 10
8.2%
E 10
8.2%
Y 9
 
7.4%
G 8
 
6.6%
P 8
 
6.6%
B 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%
i 4
 
7.4%
n 4
 
7.4%
p 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 3488
50.3%
2 1473
21.3%
0 881
 
12.7%
3 303
 
4.4%
4 193
 
2.8%
5 152
 
2.2%
7 123
 
1.8%
6 119
 
1.7%
8 117
 
1.7%
9 79
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 993
66.7%
. 163
 
10.9%
/ 149
 
10.0%
: 134
 
9.0%
% 29
 
1.9%
? 17
 
1.1%
' 4
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3205
99.9%
] 3
 
0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3180
99.9%
[ 3
 
0.1%
1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 7
87.5%
~ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
15419
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 229
100.0%
Initial Punctuation
ValueCountFrequency (%)
8
100.0%
Final Punctuation
ValueCountFrequency (%)
8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77352
71.6%
Common 30496
 
28.2%
Latin 176
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3967
 
5.1%
3026
 
3.9%
2665
 
3.4%
2318
 
3.0%
1622
 
2.1%
1555
 
2.0%
1440
 
1.9%
1406
 
1.8%
1317
 
1.7%
1293
 
1.7%
Other values (492) 56743
73.4%
Latin
ValueCountFrequency (%)
A 18
 
10.2%
o 11
 
6.2%
O 11
 
6.2%
U 11
 
6.2%
N 10
 
5.7%
E 10
 
5.7%
Y 9
 
5.1%
G 8
 
4.5%
P 8
 
4.5%
B 8
 
4.5%
Other values (23) 72
40.9%
Common
ValueCountFrequency (%)
15419
50.6%
1 3488
 
11.4%
) 3205
 
10.5%
( 3180
 
10.4%
2 1473
 
4.8%
, 993
 
3.3%
0 881
 
2.9%
3 303
 
1.0%
- 229
 
0.8%
4 193
 
0.6%
Other values (22) 1132
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77338
71.6%
ASCII 30652
 
28.4%
Punctuation 16
 
< 0.1%
Compat Jamo 14
 
< 0.1%
Geometric Shapes 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15419
50.3%
1 3488
 
11.4%
) 3205
 
10.5%
( 3180
 
10.4%
2 1473
 
4.8%
, 993
 
3.2%
0 881
 
2.9%
3 303
 
1.0%
- 229
 
0.7%
4 193
 
0.6%
Other values (50) 1288
 
4.2%
Hangul
ValueCountFrequency (%)
3967
 
5.1%
3026
 
3.9%
2665
 
3.4%
2318
 
3.0%
1622
 
2.1%
1555
 
2.0%
1440
 
1.9%
1406
 
1.8%
1317
 
1.7%
1293
 
1.7%
Other values (491) 56729
73.4%
Compat Jamo
ValueCountFrequency (%)
14
100.0%
Punctuation
ValueCountFrequency (%)
8
50.0%
8
50.0%
Geometric Shapes
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct716
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
2024-05-03T23:42:43.643429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length66
Mean length7.947949
Min length2

Characters and Unicode

Total characters51153
Distinct characters214
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

Unique414 ?
Unique (%)6.4%

Sample

1st row과징금부과
2nd row과태료부과
3rd row과태료부과
4th row과태료부과
5th row과태료부과
ValueCountFrequency (%)
시정명령 1471
16.0%
영업정지 1466
15.9%
과태료부과 1207
13.1%
영업소폐쇄 589
 
6.4%
부과 301
 
3.3%
과태료 264
 
2.9%
263
 
2.9%
과징금 230
 
2.5%
시설개수명령 207
 
2.3%
과징금부과 207
 
2.3%
Other values (714) 2987
32.5%
2024-05-03T23:42:45.188065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4633
 
9.1%
3616
 
7.1%
2757
 
5.4%
2537
 
5.0%
2521
 
4.9%
0 2402
 
4.7%
2309
 
4.5%
2023
 
4.0%
2 1910
 
3.7%
1908
 
3.7%
Other values (204) 24537
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37632
73.6%
Decimal Number 7685
 
15.0%
Space Separator 2757
 
5.4%
Other Punctuation 1161
 
2.3%
Open Punctuation 833
 
1.6%
Close Punctuation 830
 
1.6%
Math Symbol 184
 
0.4%
Dash Punctuation 71
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (178) 12516
33.3%
Decimal Number
ValueCountFrequency (%)
0 2402
31.3%
2 1910
24.9%
1 1182
15.4%
5 524
 
6.8%
3 452
 
5.9%
4 433
 
5.6%
6 290
 
3.8%
7 198
 
2.6%
8 153
 
2.0%
9 141
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 968
83.4%
, 136
 
11.7%
: 20
 
1.7%
% 17
 
1.5%
17
 
1.5%
/ 3
 
0.3%
Math Symbol
ValueCountFrequency (%)
~ 152
82.6%
> 27
 
14.7%
4
 
2.2%
= 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 832
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 829
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2757
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37632
73.6%
Common 13521
 
26.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (178) 12516
33.3%
Common
ValueCountFrequency (%)
2757
20.4%
0 2402
17.8%
2 1910
14.1%
1 1182
8.7%
. 968
 
7.2%
( 832
 
6.2%
) 829
 
6.1%
5 524
 
3.9%
3 452
 
3.3%
4 433
 
3.2%
Other values (16) 1232
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37606
73.5%
ASCII 13500
 
26.4%
Compat Jamo 26
 
0.1%
Punctuation 17
 
< 0.1%
Arrows 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4633
 
12.3%
3616
 
9.6%
2537
 
6.7%
2521
 
6.7%
2309
 
6.1%
2023
 
5.4%
1908
 
5.1%
1863
 
5.0%
1856
 
4.9%
1850
 
4.9%
Other values (177) 12490
33.2%
ASCII
ValueCountFrequency (%)
2757
20.4%
0 2402
17.8%
2 1910
14.1%
1 1182
8.8%
. 968
 
7.2%
( 832
 
6.2%
) 829
 
6.1%
5 524
 
3.9%
3 452
 
3.3%
4 433
 
3.2%
Other values (14) 1211
9.0%
Compat Jamo
ValueCountFrequency (%)
26
100.0%
Punctuation
ValueCountFrequency (%)
17
100.0%
Arrows
ValueCountFrequency (%)
4
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)2.4%
Missing5517
Missing (%)85.7%
Infinite0
Infinite (%)0.0%
Mean11.677911
Minimum0
Maximum30
Zeros42
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:45.935432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median15
Q315
95-th percentile20
Maximum30
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.3507336
Coefficient of variation (CV)0.45819271
Kurtosis-0.024294869
Mean11.677911
Median Absolute Deviation (MAD)2
Skewness-0.19841877
Sum10732
Variance28.63035
MonotonicityNot monotonic
2024-05-03T23:42:46.342748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
15 452
 
7.0%
7 221
 
3.4%
10 59
 
0.9%
0 42
 
0.7%
20 31
 
0.5%
5 23
 
0.4%
3 13
 
0.2%
17 12
 
0.2%
8 10
 
0.2%
2 9
 
0.1%
Other values (12) 47
 
0.7%
(Missing) 5517
85.7%
ValueCountFrequency (%)
0 42
 
0.7%
1 3
 
< 0.1%
2 9
 
0.1%
3 13
 
0.2%
4 8
 
0.1%
5 23
 
0.4%
6 5
 
0.1%
7 221
3.4%
8 10
 
0.2%
9 1
 
< 0.1%
ValueCountFrequency (%)
30 3
 
< 0.1%
28 3
 
< 0.1%
25 4
 
0.1%
23 6
 
0.1%
22 6
 
0.1%
21 2
 
< 0.1%
20 31
 
0.5%
17 12
 
0.2%
15 452
7.0%
14 1
 
< 0.1%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION  MISSING  SKEWED 

Distinct1201
Distinct (%)41.9%
Missing3567
Missing (%)55.4%
Infinite0
Infinite (%)0.0%
Mean127.88154
Minimum0
Maximum29556.6
Zeros8
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size56.7 KiB
2024-05-03T23:42:46.743023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.6
Q136
median67.71
Q3116.3
95-th percentile271.1
Maximum29556.6
Range29556.6
Interquartile range (IQR)80.3

Descriptive statistics

Standard deviation809.81296
Coefficient of variation (CV)6.3325245
Kurtosis1217.464
Mean127.88154
Median Absolute Deviation (MAD)36.01
Skewness33.804135
Sum366892.13
Variance655797.03
MonotonicityNot monotonic
2024-05-03T23:42:47.253673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 29
 
0.5%
66.38 22
 
0.3%
100.97 21
 
0.3%
103.32 21
 
0.3%
330.88 21
 
0.3%
52.0 16
 
0.2%
23.1 16
 
0.2%
30.0 15
 
0.2%
66.0 15
 
0.2%
26.4 15
 
0.2%
Other values (1191) 2678
41.6%
(Missing) 3567
55.4%
ValueCountFrequency (%)
0.0 8
0.1%
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%
5170.8 3
< 0.1%
2865.29 2
< 0.1%
2450.0 1
 
< 0.1%
2254.29 2
< 0.1%
1603.82 1
 
< 0.1%
1447.41 1
 
< 0.1%
1324.29 2
< 0.1%
1121.0 2
< 0.1%
1117.38 1
 
< 0.1%

운영형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size50.4 KiB
<NA>
6400 
직영
 
29
(조합)위탁
 
7

Length

Max length6
Median length4
Mean length3.9931635
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> 6400
99.4%
직영 29
 
0.5%
(조합)위탁 7
 
0.1%

Length

2024-05-03T23:42:47.747382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T23:42:48.057368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6400
99.4%
직영 29
 
0.5%
조합)위탁 7
 
0.1%

Interactions

2024-05-03T23:42:14.999917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:02.676667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:04.730050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:07.435920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:10.210188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:12.724082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:15.334095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:03.072431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:05.084150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:07.839156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:10.603933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:13.028071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:15.666568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:03.427481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:05.491853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:08.321877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:11.003036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:13.321468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:16.046647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:03.829610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:05.944433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:08.694737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:11.498252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:13.699379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:16.376370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:04.120929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:06.432839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:09.290524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:11.811819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:14.044076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:16.689567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:04.434813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:06.938995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:09.709419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:12.407458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T23:42:14.606727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T23:42:48.286070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)운영형태
처분일자1.0000.7150.4620.6150.9900.9900.6620.0400.530
교부번호0.7151.0000.5330.6930.7200.7180.4230.0900.495
업종명0.4620.5331.0001.0000.4880.4840.6150.225NaN
업태명0.6150.6931.0001.0000.6270.6250.7020.5720.623
지도점검일자0.9900.7200.4880.6271.0001.0000.6280.0000.768
위반일자0.9900.7180.4840.6251.0001.0000.6280.0000.768
처분기간0.6620.4230.6150.7020.6280.6281.000NaNNaN
영업장면적(㎡)0.0400.0900.2250.5720.0000.000NaN1.000NaN
운영형태0.5300.495NaN0.6230.7680.768NaNNaN1.000
2024-05-03T23:42:48.683731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영형태업종명
운영형태1.0001.000
업종명1.0001.000
2024-05-03T23:42:48.928735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자교부번호지도점검일자위반일자처분기간영업장면적(㎡)업종명운영형태
처분일자1.0000.6100.9990.9990.078-0.0360.1900.356
교부번호0.6101.0000.6120.611-0.001-0.0060.2290.572
지도점검일자0.9990.6121.0001.0000.070-0.0390.2030.699
위반일자0.9990.6111.0001.0000.070-0.0390.2010.699
처분기간0.078-0.0010.0700.0701.000-0.1190.2840.000
영업장면적(㎡)-0.036-0.006-0.039-0.039-0.1191.0000.1051.000
업종명0.1900.2290.2030.2010.2840.1051.0001.000
운영형태0.3560.5720.6990.6990.0001.0001.0001.000

Missing values

2024-05-03T23:42:17.277864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T23:42:18.295621image/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.
2024-05-03T23:42:18.774314image/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
031600002012080219790080033일반음식점한식평양면옥<NA>서울특별시 구로구 오류동 13번지 55호20120605처분확정과징금부과식품위생법7조20120704대장균기준위반(1차)과징금부과1535.5<NA>
131600002023030719790080017일반음식점한식황제꽃소서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)서울특별시 구로구 개봉동 70번지 16호 우분투포레스트20230131처분확정과태료부과법 제101조제3항제1호20230131건강진단을 받지 않은 자를 영업에 종사시킨 영업자(1차)과태료부과<NA>101.9<NA>
231600002023030719790080017일반음식점한식황제꽃소서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)서울특별시 구로구 개봉동 70번지 16호 우분투포레스트20230131처분확정과태료부과법 제101조제3항제1호20230131건강진단을 받지 않은 자를 영업에 종사시킨 영업자(1차)과태료부과<NA>62.8<NA>
331600002023030719790080017일반음식점한식황제꽃소서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)서울특별시 구로구 개봉동 70번지 16호 우분투포레스트20230131처분확정과태료부과법 제101조제3항제1호20230131종업원 건강진단 미필(3명중 1명)(1차)과태료부과<NA>101.9<NA>
431600002023030719790080017일반음식점한식황제꽃소서울특별시 구로구 경인로 237, 1층 102호 (개봉동, 우분투포레스트)서울특별시 구로구 개봉동 70번지 16호 우분투포레스트20230131처분확정과태료부과법 제101조제3항제1호20230131종업원 건강진단 미필(3명중 1명)(1차)과태료부과<NA>62.8<NA>
531600002002090919790080013일반음식점호프/통닭약속<NA>서울특별시 구로구 개봉동 289번지 2호20020904처분확정시정명령(2002.9.25까지)식품위생법제55조20020904해당업종 미표시시정명령(2002.9.25까지)<NA>14.76<NA>
631600002011120719800080058일반음식점중국식영춘각<NA>서울특별시 구로구 개봉동 139번지 107호20110920처분확정과태료부과식품위생법제3조20110920위생모 미착용과태료부과<NA>33.62<NA>
731600002009042919810080031일반음식점중국식중국관<NA>서울특별시 구로구 가리봉동 127번지 4호20090225처분확정시정명령식품위생법 제3조20090225조리장 위생상태 불량시정명령<NA>53.19<NA>
831600002020122119810080097일반음식점호프/통닭리치서울특별시 구로구 남부순환로97길 26-2, (개봉동)서울특별시 구로구 개봉동 202번지 12호20200625처분확정영업정지법 제71조 및 법 제75조20200625손님이 노래를 부르도록 허용하는 행위 (1차, 1회+2회)영업정지1564.02<NA>
931600002020122119810080097일반음식점호프/통닭리치서울특별시 구로구 남부순환로97길 26-2, (개봉동)서울특별시 구로구 개봉동 202번지 12호20200625처분확정영업정지법 제71조 및 법 제75조20200625손님이 노래를 부르도록 허용하는 행위 (1차, 1회+2회)영업정지1568.06<NA>
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태
642631600002023112320210081017건강기능식품일반판매업전자상거래(통신판매업)거위의 꿈서울특별시 구로구 디지털로34길 55, 코오롱싸이언스밸리2차 지하1층 B101-166호 (구로동)서울특별시 구로구 구로동 811번지 코오롱싸이언스밸리2차20231020처분확정과태료부과법 제47조제1항제6호202310202022년 위생교육 미이수과태료부과<NA><NA><NA>
642731600002023020120120086921건강기능식품유통전문판매업건강기능식품유통전문판매업뉴키주식회사서울특별시 구로구 경인로 661, 신도림1차푸르지오 105동 503호 (신도림동)서울특별시 구로구 신도림동 337번지 신도림1차푸르지오20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA><NA>
642831600002023020120120086921건강기능식품유통전문판매업건강기능식품유통전문판매업뉴키주식회사서울특별시 구로구 경인로 661, 신도림1차푸르지오 105동 503호 (신도림동)서울특별시 구로구 신도림동 337번지 신도림1차푸르지오20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA><NA>
642931600002022011820180080399건강기능식품유통전문판매업건강기능식품유통전문판매업(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<NA>
643031600002022011820180080399건강기능식품유통전문판매업건강기능식품유통전문판매업(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><NA>
643131600002023112320190081079건강기능식품유통전문판매업건강기능식품유통전문판매업주식회사 에이지엣랩스서울특별시 구로구 디지털로32길 55, 5층 (구로동)서울특별시 구로구 구로동 817번지20231020처분확정과태료부과법 제47조제1항제6호202310202022년도 위생교육 미이수과태료부과<NA><NA><NA>
643231600002023112320190081079건강기능식품유통전문판매업건강기능식품유통전문판매업주식회사 에이지엣랩스서울특별시 구로구 디지털로32길 55, 5층 (구로동)서울특별시 구로구 구로동 817번지20231020처분확정과태료부과법 제47조제1항제6호202310202022년도 위생교육 미이수과태료부과<NA><NA><NA>
643331600002023020120190081354건강기능식품유통전문판매업건강기능식품유통전문판매업(주)비올서울특별시 구로구 디지털로26길 5, 에이스하이엔드타워1차 1117호 (구로동)서울특별시 구로구 구로동 235번지 2호 에이스하이엔드타워1차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA><NA>
643431600002023020120210080110건강기능식품유통전문판매업건강기능식품유통전문판매업(주)알에이치마케팅서울특별시 구로구 디지털로33길 50, 벽산디지털밸리7차 9층 905호 (구로동)서울특별시 구로구 구로동 170번지 13호 벽산디지털밸리7차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA>7.5<NA>
643531600002023020120210080110건강기능식품유통전문판매업건강기능식품유통전문판매업(주)알에이치마케팅서울특별시 구로구 디지털로33길 50, 벽산디지털밸리7차 9층 905호 (구로동)서울특별시 구로구 구로동 170번지 13호 벽산디지털밸리7차20221124처분확정과태료부과법 제47조제1항제6호202211242021 위생교육 미이수과태료부과<NA><NA><NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)운영형태# duplicates
19831600002016012920030080686식품등 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><NA>8
2631600002006112319910080356일반음식점한식오류동집<NA>서울특별시 구로구 오류동 56번지 39호20061020처분확정영업정지 7일갈음 과징금 840,000원 부과식품위생법 제22조5항20061020영업장 무단확장 영업영업정지 7일갈음 과징금 840,000원 부과738.87<NA>6
5531600002009080319980080014단란주점단란주점골든벨노래클럽<NA>서울특별시 구로구 신도림동 292번지 123호20090618처분확정시정명령 및 시설개수명령식품위생법 제21조20090618개실에 불투명 유리 설치(1차)시정명령 및 시설개수명령<NA>60.48<NA>6
831600002003032420000080645식품제조가공업식품제조가공업서울식품서울특별시 구로구 부일로9길 133, (온수동,온수상가 105호)서울특별시 구로구 온수동 141번지 0호 온수상가 105호20030319처분확정시정명령식품위생법 제55조20030319표시기준 위반(포장지 재질 미표시)시정명령<NA><NA><NA>4
2531600002006112319910080356일반음식점한식오류동집<NA>서울특별시 구로구 오류동 56번지 39호20061020처분확정영업정지 7일갈음 과징금 840,000원 부과식품위생법 제22조 5항20061020영업장 무단확장 영업영업정지 7일갈음 과징금 840,000원 부과738.87<NA>4
9831600002011090719950080576단란주점단란주점뉴월드<NA>서울특별시 구로구 개봉동 353번지 30호20110513처분확정시설개수명령식품위생법 36조 37조20110513시설개수명령(1차)시설개수명령<NA>146.96<NA>4
10631600002012020120000080651일반음식점분식풀코스호프<NA>서울특별시 구로구 고척동 76번지 181호20111210처분확정영업정지15일 및 과징금 150만원식품위생법제44조20111210청소년주류제공(1차)영업정지15일 및 과징금 150만원15<NA><NA>4
11731600002013011420050080095일반음식점한식나노갈매기<NA>서울특별시 구로구 구로동 31번지 5호20120625처분확정시정명령식품위생법제37조20120704영업장외 영업(1차)시정명령<NA><NA><NA>4
15231600002013080820100080006식품등 수입판매업식품등 수입판매업차가인차가버섯서울특별시 구로구 공원로 3, (구로동,선경오피스텔 501-A/B호)서울특별시 구로구 구로동 106번지 4호 선경오피스텔 501-A/B호20130604처분확정영업정지식품위생법 제71조, 제72조, 제75조, 제76조20130604식품위생법 제13조(허위표시 등의 금지)위반영업정지7<NA><NA>4
19231600002015122220020081000식품등 수입판매업식품등 수입판매업(주)한국자원통상서울특별시 구로구 구로중앙로28다길 13, (구로동,2층)서울특별시 구로구 구로동 111번지 12호 2층20150706처분확정영업소폐쇄법 제71조, 법 제74조,법 제75조 및 법 제76조20150706무단폐업(영업시설의 전부를 철거)영업소폐쇄<NA><NA><NA>4