Overview

Dataset statistics

Number of variables17
Number of observations10000
Missing cells14092
Missing cells (%)8.3%
Duplicate rows356
Duplicate rows (%)3.6%
Total size in memory1.4 MiB
Average record size in memory150.0 B

Variable types

Categorical3
Numeric5
Text9

Dataset

Description시군구코드,처분일자,교부번호,업종명,업태명,업소명,소재지도로명,소재지지번,지도점검일자,행정처분상태,처분명,법적근거,위반일자,위반내용,처분내용,처분기간,영업장면적(㎡)
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11457/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정처분상태 has constant value ""Constant
Dataset has 356 (3.6%) 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
업태명 has 118 (1.2%) missing valuesMissing
소재지도로명 has 278 (2.8%) missing valuesMissing
처분기간 has 8939 (89.4%) missing valuesMissing
영업장면적(㎡) has 4752 (47.5%) missing valuesMissing
처분일자 is highly skewed (γ1 = -60.38050684)Skewed
영업장면적(㎡) is highly skewed (γ1 = 34.14098375)Skewed

Reproduction

Analysis started2024-05-11 07:15:51.903141
Analysis finished2024-05-11 07:15:57.291584
Duration5.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3230000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 10000
100.0%

Length

2024-05-11T16:15:57.351870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:15:57.437269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 10000
100.0%

처분일자
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2644
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20136364
Minimum11111111
Maximum20240510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:15:57.533154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11111111
5-th percentile20031229
Q120090723
median20150124
Q320180529
95-th percentile20220225
Maximum20240510
Range9129399
Interquartile range (IQR)89806.25

Descriptive statistics

Standard deviation106818.17
Coefficient of variation (CV)0.0053047396
Kurtosis5097.0611
Mean20136364
Median Absolute Deviation (MAD)40095.5
Skewness-60.380507
Sum2.0136364 × 1011
Variance1.1410121 × 1010
MonotonicityNot monotonic
2024-05-11T16:15:57.665024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211224 358
 
3.6%
20170627 293
 
2.9%
20170222 286
 
2.9%
20161223 285
 
2.9%
20140218 73
 
0.7%
20161004 68
 
0.7%
20140626 61
 
0.6%
20201109 55
 
0.5%
20140724 48
 
0.5%
20170228 46
 
0.5%
Other values (2634) 8427
84.3%
ValueCountFrequency (%)
11111111 1
 
< 0.1%
20020913 1
 
< 0.1%
20020918 1
 
< 0.1%
20020919 1
 
< 0.1%
20020924 1
 
< 0.1%
20020927 3
< 0.1%
20020928 1
 
< 0.1%
20021001 1
 
< 0.1%
20021004 1
 
< 0.1%
20021007 4
< 0.1%
ValueCountFrequency (%)
20240510 4
< 0.1%
20240429 1
 
< 0.1%
20240416 1
 
< 0.1%
20240409 1
 
< 0.1%
20240405 3
< 0.1%
20240401 3
< 0.1%
20240325 1
 
< 0.1%
20240318 1
 
< 0.1%
20240312 1
 
< 0.1%
20240305 2
< 0.1%
Distinct6207
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:15:57.916107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.966
Min length2

Characters and Unicode

Total characters109660
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4540 ?
Unique (%)45.4%

Sample

1st row20040116466
2nd row20060114480
3rd row19940114953
4th row20120114037
5th row20010114808
ValueCountFrequency (%)
20140114284 34
 
0.3%
20000115215 33
 
0.3%
20000114898 23
 
0.2%
20060114414 23
 
0.2%
20080114998 22
 
0.2%
20150115336 21
 
0.2%
20150114021 20
 
0.2%
20000115778 19
 
0.2%
19990108196 18
 
0.2%
20020114096 18
 
0.2%
Other values (6197) 9769
97.7%
2024-05-11T16:15:58.327991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28694
26.2%
0 26199
23.9%
2 11949
10.9%
4 9469
 
8.6%
9 8622
 
7.9%
5 7578
 
6.9%
6 4428
 
4.0%
3 4258
 
3.9%
8 3780
 
3.4%
7 3575
 
3.3%
Other values (4) 1108
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108552
99.0%
Dash Punctuation 1105
 
1.0%
Other Letter 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28694
26.4%
0 26199
24.1%
2 11949
11.0%
4 9469
 
8.7%
9 8622
 
7.9%
5 7578
 
7.0%
6 4428
 
4.1%
3 4258
 
3.9%
8 3780
 
3.5%
7 3575
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109657
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 28694
26.2%
0 26199
23.9%
2 11949
10.9%
4 9469
 
8.6%
9 8622
 
7.9%
5 7578
 
6.9%
6 4428
 
4.0%
3 4258
 
3.9%
8 3780
 
3.4%
7 3575
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109657
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28694
26.2%
0 26199
23.9%
2 11949
10.9%
4 9469
 
8.6%
9 8622
 
7.9%
5 7578
 
6.9%
6 4428
 
4.0%
3 4258
 
3.9%
8 3780
 
3.4%
7 3575
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

업종명
Categorical

Distinct37
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반음식점
5554 
단란주점
569 
유흥주점영업
 
549
휴게음식점
 
509
식품제조가공업
 
435
Other values (32)
2384 

Length

Max length19
Median length5
Mean length5.7062
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row건강기능식품유통전문판매업
2nd row즉석판매제조가공업
3rd row단란주점
4th row건강기능식품일반판매업
5th row일반음식점

Common Values

ValueCountFrequency (%)
일반음식점 5554
55.5%
단란주점 569
 
5.7%
유흥주점영업 549
 
5.5%
휴게음식점 509
 
5.1%
식품제조가공업 435
 
4.3%
건강기능식품일반판매업 422
 
4.2%
즉석판매제조가공업 385
 
3.9%
식품등 수입판매업 234
 
2.3%
식품소분업 207
 
2.1%
유통전문판매업 179
 
1.8%
Other values (27) 957
 
9.6%

Length

2024-05-11T16:15:58.467901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 5554
54.2%
단란주점 569
 
5.6%
유흥주점영업 549
 
5.4%
휴게음식점 509
 
5.0%
식품제조가공업 435
 
4.2%
건강기능식품일반판매업 422
 
4.1%
즉석판매제조가공업 385
 
3.8%
수입판매업 234
 
2.3%
식품등 234
 
2.3%
식품소분업 207
 
2.0%
Other values (24) 1148
 
11.2%

업태명
Text

MISSING 

Distinct89
Distinct (%)0.9%
Missing118
Missing (%)1.2%
Memory size156.2 KiB
2024-05-11T16:15:58.627239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.0449302
Min length2

Characters and Unicode

Total characters39972
Distinct characters175
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

Unique13 ?
Unique (%)0.1%

Sample

1st row건강기능식품유통전문판매업
2nd row즉석판매제조가공업
3rd row단란주점
4th row분식
5th row일식
ValueCountFrequency (%)
한식 2767
26.7%
기타 775
 
7.5%
단란주점 569
 
5.5%
호프/통닭 484
 
4.7%
경양식 449
 
4.3%
식품제조가공업 435
 
4.2%
분식 423
 
4.1%
룸살롱 421
 
4.1%
즉석판매제조가공업 385
 
3.7%
식품등 234
 
2.3%
Other values (79) 3420
33.0%
2024-05-11T16:15:58.920907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5357
 
13.4%
2769
 
6.9%
2599
 
6.5%
1362
 
3.4%
1361
 
3.4%
1050
 
2.6%
972
 
2.4%
914
 
2.3%
913
 
2.3%
868
 
2.2%
Other values (165) 21807
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38347
95.9%
Other Punctuation 731
 
1.8%
Space Separator 480
 
1.2%
Open Punctuation 201
 
0.5%
Close Punctuation 201
 
0.5%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5357
 
14.0%
2769
 
7.2%
2599
 
6.8%
1362
 
3.6%
1361
 
3.5%
1050
 
2.7%
972
 
2.5%
914
 
2.4%
913
 
2.4%
868
 
2.3%
Other values (158) 20182
52.6%
Other Punctuation
ValueCountFrequency (%)
/ 716
97.9%
, 12
 
1.6%
. 3
 
0.4%
Space Separator
ValueCountFrequency (%)
480
100.0%
Open Punctuation
ValueCountFrequency (%)
( 201
100.0%
Close Punctuation
ValueCountFrequency (%)
) 201
100.0%
Math Symbol
ValueCountFrequency (%)
+ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38347
95.9%
Common 1625
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5357
 
14.0%
2769
 
7.2%
2599
 
6.8%
1362
 
3.6%
1361
 
3.5%
1050
 
2.7%
972
 
2.5%
914
 
2.4%
913
 
2.4%
868
 
2.3%
Other values (158) 20182
52.6%
Common
ValueCountFrequency (%)
/ 716
44.1%
480
29.5%
( 201
 
12.4%
) 201
 
12.4%
, 12
 
0.7%
+ 12
 
0.7%
. 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38347
95.9%
ASCII 1625
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5357
 
14.0%
2769
 
7.2%
2599
 
6.8%
1362
 
3.6%
1361
 
3.5%
1050
 
2.7%
972
 
2.5%
914
 
2.4%
913
 
2.4%
868
 
2.3%
Other values (158) 20182
52.6%
ASCII
ValueCountFrequency (%)
/ 716
44.1%
480
29.5%
( 201
 
12.4%
) 201
 
12.4%
, 12
 
0.7%
+ 12
 
0.7%
. 3
 
0.2%
Distinct6110
Distinct (%)61.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:15:59.207230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length5.6033
Min length1

Characters and Unicode

Total characters56033
Distinct characters999
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4382 ?
Unique (%)43.8%

Sample

1st row(주)에프앤디넷
2nd row(주)아이푸드바이오
3rd row청화대
4th row헬시트리
5th row석우동
ValueCountFrequency (%)
잠실점 41
 
0.3%
송파점 38
 
0.3%
인광로스팅커피 34
 
0.3%
카페 34
 
0.3%
주식회사 31
 
0.3%
방이점 30
 
0.2%
호프 25
 
0.2%
유한회사 24
 
0.2%
투다리 23
 
0.2%
오케이 22
 
0.2%
Other values (6747) 11815
97.5%
2024-05-11T16:15:59.632976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2121
 
3.8%
1376
 
2.5%
) 1327
 
2.4%
( 1324
 
2.4%
1262
 
2.3%
1194
 
2.1%
922
 
1.6%
837
 
1.5%
656
 
1.2%
529
 
0.9%
Other values (989) 44485
79.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48386
86.4%
Space Separator 2121
 
3.8%
Close Punctuation 1327
 
2.4%
Open Punctuation 1324
 
2.4%
Uppercase Letter 1208
 
2.2%
Lowercase Letter 919
 
1.6%
Decimal Number 563
 
1.0%
Other Punctuation 162
 
0.3%
Dash Punctuation 18
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1376
 
2.8%
1262
 
2.6%
1194
 
2.5%
922
 
1.9%
837
 
1.7%
656
 
1.4%
529
 
1.1%
516
 
1.1%
494
 
1.0%
493
 
1.0%
Other values (908) 40107
82.9%
Lowercase Letter
ValueCountFrequency (%)
e 134
14.6%
o 101
 
11.0%
a 91
 
9.9%
i 68
 
7.4%
t 52
 
5.7%
r 51
 
5.5%
c 43
 
4.7%
h 40
 
4.4%
n 39
 
4.2%
l 38
 
4.1%
Other values (16) 262
28.5%
Uppercase Letter
ValueCountFrequency (%)
S 119
 
9.9%
B 96
 
7.9%
E 89
 
7.4%
O 89
 
7.4%
A 81
 
6.7%
T 80
 
6.6%
C 64
 
5.3%
F 63
 
5.2%
L 55
 
4.6%
M 46
 
3.8%
Other values (16) 426
35.3%
Other Punctuation
ValueCountFrequency (%)
. 63
38.9%
& 42
25.9%
, 16
 
9.9%
12
 
7.4%
' 9
 
5.6%
! 5
 
3.1%
# 4
 
2.5%
? 4
 
2.5%
; 3
 
1.9%
/ 2
 
1.2%
Other values (2) 2
 
1.2%
Decimal Number
ValueCountFrequency (%)
2 125
22.2%
0 119
21.1%
1 67
11.9%
8 57
10.1%
7 52
9.2%
5 36
 
6.4%
4 34
 
6.0%
3 32
 
5.7%
9 29
 
5.2%
6 12
 
2.1%
Space Separator
ValueCountFrequency (%)
2121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1327
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48376
86.3%
Common 5520
 
9.9%
Latin 2127
 
3.8%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1376
 
2.8%
1262
 
2.6%
1194
 
2.5%
922
 
1.9%
837
 
1.7%
656
 
1.4%
529
 
1.1%
516
 
1.1%
494
 
1.0%
493
 
1.0%
Other values (902) 40097
82.9%
Latin
ValueCountFrequency (%)
e 134
 
6.3%
S 119
 
5.6%
o 101
 
4.7%
B 96
 
4.5%
a 91
 
4.3%
E 89
 
4.2%
O 89
 
4.2%
A 81
 
3.8%
T 80
 
3.8%
i 68
 
3.2%
Other values (42) 1179
55.4%
Common
ValueCountFrequency (%)
2121
38.4%
) 1327
24.0%
( 1324
24.0%
2 125
 
2.3%
0 119
 
2.2%
1 67
 
1.2%
. 63
 
1.1%
8 57
 
1.0%
7 52
 
0.9%
& 42
 
0.8%
Other values (19) 223
 
4.0%
Han
ValueCountFrequency (%)
3
30.0%
2
20.0%
2
20.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48376
86.3%
ASCII 7634
 
13.6%
None 12
 
< 0.1%
CJK 10
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2121
27.8%
) 1327
17.4%
( 1324
17.3%
e 134
 
1.8%
2 125
 
1.6%
0 119
 
1.6%
S 119
 
1.6%
o 101
 
1.3%
B 96
 
1.3%
a 91
 
1.2%
Other values (69) 2077
27.2%
Hangul
ValueCountFrequency (%)
1376
 
2.8%
1262
 
2.6%
1194
 
2.5%
922
 
1.9%
837
 
1.7%
656
 
1.4%
529
 
1.1%
516
 
1.1%
494
 
1.0%
493
 
1.0%
Other values (902) 40097
82.9%
None
ValueCountFrequency (%)
12
100.0%
CJK
ValueCountFrequency (%)
3
30.0%
2
20.0%
2
20.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%

소재지도로명
Text

MISSING 

Distinct5660
Distinct (%)58.2%
Missing278
Missing (%)2.8%
Memory size156.2 KiB
2024-05-11T16:15:59.865321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length62
Mean length32.002777
Min length22

Characters and Unicode

Total characters311131
Distinct characters424
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3867 ?
Unique (%)39.8%

Sample

1st row서울특별시 송파구 송이로 79, (가락동,진성빌딩5층)
2nd row서울특별시 송파구 올림픽로 240, (잠실동,롯데마트 지하1층식품부내)
3rd row서울특별시 송파구 오금로11길 32, (방이동)
4th row서울특별시 송파구 백제고분로32길 29-8, 402-1호 (삼전동, 시티빌)
5th row서울특별시 송파구 가락로 159, (송파동)
ValueCountFrequency (%)
서울특별시 9722
 
17.2%
송파구 9722
 
17.2%
가락동 1455
 
2.6%
방이동 1086
 
1.9%
잠실동 1054
 
1.9%
지상1층 1049
 
1.9%
지하1층 785
 
1.4%
1층 771
 
1.4%
문정동 716
 
1.3%
석촌동 670
 
1.2%
Other values (3713) 29503
52.2%
2024-05-11T16:16:00.250902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46892
 
15.1%
, 14331
 
4.6%
1 13761
 
4.4%
12087
 
3.9%
12044
 
3.9%
10672
 
3.4%
( 10288
 
3.3%
) 10288
 
3.3%
9981
 
3.2%
9753
 
3.1%
Other values (414) 161034
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178933
57.5%
Decimal Number 47481
 
15.3%
Space Separator 46892
 
15.1%
Other Punctuation 14407
 
4.6%
Open Punctuation 10290
 
3.3%
Close Punctuation 10290
 
3.3%
Dash Punctuation 1940
 
0.6%
Uppercase Letter 823
 
0.3%
Lowercase Letter 44
 
< 0.1%
Math Symbol 30
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12087
 
6.8%
12044
 
6.7%
10672
 
6.0%
9981
 
5.6%
9753
 
5.5%
9744
 
5.4%
9740
 
5.4%
9723
 
5.4%
9723
 
5.4%
9708
 
5.4%
Other values (357) 75758
42.3%
Uppercase Letter
ValueCountFrequency (%)
B 270
32.8%
A 181
22.0%
C 70
 
8.5%
G 39
 
4.7%
S 38
 
4.6%
T 30
 
3.6%
Y 28
 
3.4%
E 25
 
3.0%
L 22
 
2.7%
F 20
 
2.4%
Other values (11) 100
 
12.2%
Lowercase Letter
ValueCountFrequency (%)
b 16
36.4%
c 5
 
11.4%
t 5
 
11.4%
e 4
 
9.1%
u 3
 
6.8%
i 3
 
6.8%
l 2
 
4.5%
o 2
 
4.5%
s 2
 
4.5%
a 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 13761
29.0%
2 8043
16.9%
3 5332
 
11.2%
4 3788
 
8.0%
0 3750
 
7.9%
5 2827
 
6.0%
6 2815
 
5.9%
8 2574
 
5.4%
7 2313
 
4.9%
9 2278
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 14331
99.5%
/ 36
 
0.2%
. 25
 
0.2%
9
 
0.1%
& 2
 
< 0.1%
; 2
 
< 0.1%
* 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 10288
> 99.9%
[ 2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10288
> 99.9%
] 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
46892
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1940
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 178933
57.5%
Common 131330
42.2%
Latin 868
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12087
 
6.8%
12044
 
6.7%
10672
 
6.0%
9981
 
5.6%
9753
 
5.5%
9744
 
5.4%
9740
 
5.4%
9723
 
5.4%
9723
 
5.4%
9708
 
5.4%
Other values (357) 75758
42.3%
Latin
ValueCountFrequency (%)
B 270
31.1%
A 181
20.9%
C 70
 
8.1%
G 39
 
4.5%
S 38
 
4.4%
T 30
 
3.5%
Y 28
 
3.2%
E 25
 
2.9%
L 22
 
2.5%
F 20
 
2.3%
Other values (23) 145
16.7%
Common
ValueCountFrequency (%)
46892
35.7%
, 14331
 
10.9%
1 13761
 
10.5%
( 10288
 
7.8%
) 10288
 
7.8%
2 8043
 
6.1%
3 5332
 
4.1%
4 3788
 
2.9%
0 3750
 
2.9%
5 2827
 
2.2%
Other values (14) 12030
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 178933
57.5%
ASCII 132188
42.5%
None 9
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46892
35.5%
, 14331
 
10.8%
1 13761
 
10.4%
( 10288
 
7.8%
) 10288
 
7.8%
2 8043
 
6.1%
3 5332
 
4.0%
4 3788
 
2.9%
0 3750
 
2.8%
5 2827
 
2.1%
Other values (45) 12888
 
9.7%
Hangul
ValueCountFrequency (%)
12087
 
6.8%
12044
 
6.7%
10672
 
6.0%
9981
 
5.6%
9753
 
5.5%
9744
 
5.4%
9740
 
5.4%
9723
 
5.4%
9723
 
5.4%
9708
 
5.4%
Other values (357) 75758
42.3%
None
ValueCountFrequency (%)
9
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct5478
Distinct (%)54.8%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T16:16:00.533007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length51
Mean length28.292588
Min length20

Characters and Unicode

Total characters282841
Distinct characters407
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3631 ?
Unique (%)36.3%

Sample

1st row서울특별시 송파구 가락동 48번지 7호 진성빌딩5층
2nd row서울특별시 송파구 잠실동 40번지 1호 롯데마트 지하1층식품부내
3rd row서울특별시 송파구 방이동 58번지 6호
4th row서울특별시 송파구 삼전동 173번지 13호 시티빌-402-1
5th row서울특별시 송파구 송파동 104번지 10호
ValueCountFrequency (%)
서울특별시 9997
 
17.8%
송파구 9997
 
17.8%
가락동 2148
 
3.8%
잠실동 1605
 
2.9%
방이동 1430
 
2.5%
지상1층 978
 
1.7%
1호 957
 
1.7%
문정동 914
 
1.6%
지하1층 876
 
1.6%
석촌동 870
 
1.5%
Other values (2441) 26504
47.1%
2024-05-11T16:16:01.004006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70587
25.0%
1 13260
 
4.7%
13197
 
4.7%
11044
 
3.9%
10726
 
3.8%
10335
 
3.7%
10188
 
3.6%
10030
 
3.5%
10016
 
3.5%
10014
 
3.5%
Other values (397) 113444
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162383
57.4%
Space Separator 70587
25.0%
Decimal Number 46274
 
16.4%
Dash Punctuation 973
 
0.3%
Other Punctuation 745
 
0.3%
Close Punctuation 622
 
0.2%
Open Punctuation 621
 
0.2%
Uppercase Letter 588
 
0.2%
Lowercase Letter 26
 
< 0.1%
Math Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13197
 
8.1%
11044
 
6.8%
10726
 
6.6%
10335
 
6.4%
10188
 
6.3%
10030
 
6.2%
10016
 
6.2%
10014
 
6.2%
10005
 
6.2%
10002
 
6.2%
Other values (343) 56826
35.0%
Uppercase Letter
ValueCountFrequency (%)
B 177
30.1%
A 124
21.1%
C 46
 
7.8%
S 37
 
6.3%
T 31
 
5.3%
G 23
 
3.9%
I 19
 
3.2%
Y 18
 
3.1%
F 18
 
3.1%
L 16
 
2.7%
Other values (11) 79
13.4%
Lowercase Letter
ValueCountFrequency (%)
t 5
19.2%
e 4
15.4%
b 3
11.5%
i 3
11.5%
u 3
11.5%
m 2
 
7.7%
l 2
 
7.7%
c 1
 
3.8%
o 1
 
3.8%
a 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 13260
28.7%
2 6229
13.5%
0 4521
 
9.8%
3 3669
 
7.9%
4 3396
 
7.3%
8 3173
 
6.9%
9 3116
 
6.7%
6 3043
 
6.6%
7 2938
 
6.3%
5 2929
 
6.3%
Other Punctuation
ValueCountFrequency (%)
, 673
90.3%
/ 39
 
5.2%
. 28
 
3.8%
; 2
 
0.3%
& 2
 
0.3%
1
 
0.1%
Space Separator
ValueCountFrequency (%)
70587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 973
100.0%
Close Punctuation
ValueCountFrequency (%)
) 622
100.0%
Open Punctuation
ValueCountFrequency (%)
( 621
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162383
57.4%
Common 119843
42.4%
Latin 615
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13197
 
8.1%
11044
 
6.8%
10726
 
6.6%
10335
 
6.4%
10188
 
6.3%
10030
 
6.2%
10016
 
6.2%
10014
 
6.2%
10005
 
6.2%
10002
 
6.2%
Other values (343) 56826
35.0%
Latin
ValueCountFrequency (%)
B 177
28.8%
A 124
20.2%
C 46
 
7.5%
S 37
 
6.0%
T 31
 
5.0%
G 23
 
3.7%
I 19
 
3.1%
Y 18
 
2.9%
F 18
 
2.9%
L 16
 
2.6%
Other values (23) 106
17.2%
Common
ValueCountFrequency (%)
70587
58.9%
1 13260
 
11.1%
2 6229
 
5.2%
0 4521
 
3.8%
3 3669
 
3.1%
4 3396
 
2.8%
8 3173
 
2.6%
9 3116
 
2.6%
6 3043
 
2.5%
7 2938
 
2.5%
Other values (11) 5911
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162383
57.4%
ASCII 120456
42.6%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70587
58.6%
1 13260
 
11.0%
2 6229
 
5.2%
0 4521
 
3.8%
3 3669
 
3.0%
4 3396
 
2.8%
8 3173
 
2.6%
9 3116
 
2.6%
6 3043
 
2.5%
7 2938
 
2.4%
Other values (42) 6524
 
5.4%
Hangul
ValueCountFrequency (%)
13197
 
8.1%
11044
 
6.8%
10726
 
6.6%
10335
 
6.4%
10188
 
6.3%
10030
 
6.2%
10016
 
6.2%
10014
 
6.2%
10005
 
6.2%
10002
 
6.2%
Other values (343) 56826
35.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%

지도점검일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3110
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20135690
Minimum20000524
Maximum20240315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:16:01.153258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000524
5-th percentile20031106
Q120090522
median20141210
Q320180402
95-th percentile20211227
Maximum20240315
Range239791
Interquartile range (IQR)89880.5

Descriptive statistics

Standard deviation57090.074
Coefficient of variation (CV)0.0028352679
Kurtosis-0.90148517
Mean20135690
Median Absolute Deviation (MAD)40051.5
Skewness-0.33131725
Sum2.013569 × 1011
Variance3.2592766 × 109
MonotonicityNot monotonic
2024-05-11T16:16:01.283242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211129 357
 
3.6%
20170410 332
 
3.3%
20161109 329
 
3.3%
20140501 109
 
1.1%
20161212 101
 
1.0%
20161213 100
 
1.0%
20161214 89
 
0.9%
20200101 75
 
0.8%
20170110 71
 
0.7%
20140609 46
 
0.5%
Other values (3100) 8391
83.9%
ValueCountFrequency (%)
20000524 1
 
< 0.1%
20020720 1
 
< 0.1%
20020723 1
 
< 0.1%
20020725 3
< 0.1%
20020726 1
 
< 0.1%
20020801 2
< 0.1%
20020803 1
 
< 0.1%
20020806 1
 
< 0.1%
20020810 1
 
< 0.1%
20020816 2
< 0.1%
ValueCountFrequency (%)
20240315 2
 
< 0.1%
20240308 1
 
< 0.1%
20240307 3
< 0.1%
20240226 1
 
< 0.1%
20240223 3
< 0.1%
20240207 2
 
< 0.1%
20240205 5
0.1%
20240131 2
 
< 0.1%
20240130 2
 
< 0.1%
20240126 1
 
< 0.1%

행정처분상태
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
처분확정 10000
100.0%

Length

2024-05-11T16:16:01.662655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:16:01.739628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
처분확정 10000
100.0%
Distinct1287
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:16:01.986921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length132
Median length116
Mean length9.2481
Min length2

Characters and Unicode

Total characters92481
Distinct characters246
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique851 ?
Unique (%)8.5%

Sample

1st row영업정지1월(2010.07.09~2010.08.08)
2nd row영업소폐쇄(직권말소)
3rd row영업정지
4th row영업정지
5th row과태료부과
ValueCountFrequency (%)
영업소폐쇄 1535
 
10.1%
시정명령 1442
 
9.5%
영업정지 1435
 
9.4%
과태료부과 1206
 
7.9%
시설개수명령 759
 
5.0%
직권말소 691
 
4.5%
영업소폐쇄(직권말소 679
 
4.4%
과태료 464
 
3.0%
10만원 367
 
2.4%
288
 
1.9%
Other values (1575) 6393
41.9%
2024-05-11T16:16:02.461174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5267
 
5.7%
5264
 
5.7%
4680
 
5.1%
4595
 
5.0%
4000
 
4.3%
3790
 
4.1%
0 3648
 
3.9%
1 3127
 
3.4%
2810
 
3.0%
2533
 
2.7%
Other values (236) 52767
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66644
72.1%
Decimal Number 13542
 
14.6%
Space Separator 5267
 
5.7%
Other Punctuation 2657
 
2.9%
Open Punctuation 2022
 
2.2%
Close Punctuation 2007
 
2.2%
Math Symbol 280
 
0.3%
Dash Punctuation 56
 
0.1%
Uppercase Letter 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (206) 31473
47.2%
Decimal Number
ValueCountFrequency (%)
0 3648
26.9%
1 3127
23.1%
2 2376
17.5%
5 760
 
5.6%
3 711
 
5.3%
4 682
 
5.0%
8 639
 
4.7%
6 618
 
4.6%
9 513
 
3.8%
7 468
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 2192
82.5%
, 392
 
14.8%
/ 43
 
1.6%
: 17
 
0.6%
% 8
 
0.3%
* 3
 
0.1%
2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 249
88.9%
+ 28
 
10.0%
2
 
0.7%
= 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
P 1
20.0%
H 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
5267
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2022
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2007
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66644
72.1%
Common 25832
 
27.9%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (206) 31473
47.2%
Common
ValueCountFrequency (%)
5267
20.4%
0 3648
14.1%
1 3127
12.1%
2 2376
9.2%
. 2192
8.5%
( 2022
 
7.8%
) 2007
 
7.8%
5 760
 
2.9%
3 711
 
2.8%
4 682
 
2.6%
Other values (16) 3040
11.8%
Latin
ValueCountFrequency (%)
C 2
40.0%
P 1
20.0%
H 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66619
72.0%
ASCII 25833
 
27.9%
Compat Jamo 25
 
< 0.1%
None 2
 
< 0.1%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5267
20.4%
0 3648
14.1%
1 3127
12.1%
2 2376
9.2%
. 2192
8.5%
( 2022
 
7.8%
) 2007
 
7.8%
5 760
 
2.9%
3 711
 
2.8%
4 682
 
2.6%
Other values (18) 3041
11.8%
Hangul
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (205) 31448
47.2%
Compat Jamo
ValueCountFrequency (%)
25
100.0%
None
ValueCountFrequency (%)
2
100.0%
Arrows
ValueCountFrequency (%)
2
100.0%
Distinct945
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:16:02.746381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length11.8576
Min length1

Characters and Unicode

Total characters118576
Distinct characters170
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique498 ?
Unique (%)5.0%

Sample

1st row건강기능식품에 관한 법률 제32조
2nd row법 제37조 7항
3rd row식품위생법제31조
4th row법 제32조 및 제33조
5th row식품위생법제26조
ValueCountFrequency (%)
6194
23.6%
식품위생법 2722
 
10.4%
제75조 2006
 
7.6%
1412
 
5.4%
제37조 1405
 
5.4%
제71조 1241
 
4.7%
7항 1114
 
4.2%
제74조 561
 
2.1%
제101조제4항1호 394
 
1.5%
제36조 363
 
1.4%
Other values (694) 8832
33.7%
2024-05-11T16:16:03.153169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16414
13.8%
15085
12.7%
13056
11.0%
11162
 
9.4%
7 7998
 
6.7%
1 7540
 
6.4%
4448
 
3.8%
4336
 
3.7%
4192
 
3.5%
3 4139
 
3.5%
Other values (160) 30206
25.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67974
57.3%
Decimal Number 31655
26.7%
Space Separator 16414
 
13.8%
Other Punctuation 1969
 
1.7%
Open Punctuation 274
 
0.2%
Close Punctuation 274
 
0.2%
Dash Punctuation 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15085
22.2%
13056
19.2%
11162
16.4%
4448
 
6.5%
4336
 
6.4%
4192
 
6.2%
4064
 
6.0%
3654
 
5.4%
1443
 
2.1%
1197
 
1.8%
Other values (141) 5337
 
7.9%
Decimal Number
ValueCountFrequency (%)
7 7998
25.3%
1 7540
23.8%
3 4139
13.1%
5 2799
 
8.8%
2 2659
 
8.4%
4 2557
 
8.1%
6 1648
 
5.2%
0 1491
 
4.7%
8 589
 
1.9%
9 235
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 1907
96.9%
. 50
 
2.5%
: 12
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 272
99.3%
[ 2
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 272
99.3%
] 2
 
0.7%
Space Separator
ValueCountFrequency (%)
16414
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67974
57.3%
Common 50602
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15085
22.2%
13056
19.2%
11162
16.4%
4448
 
6.5%
4336
 
6.4%
4192
 
6.2%
4064
 
6.0%
3654
 
5.4%
1443
 
2.1%
1197
 
1.8%
Other values (141) 5337
 
7.9%
Common
ValueCountFrequency (%)
16414
32.4%
7 7998
15.8%
1 7540
14.9%
3 4139
 
8.2%
5 2799
 
5.5%
2 2659
 
5.3%
4 2557
 
5.1%
, 1907
 
3.8%
6 1648
 
3.3%
0 1491
 
2.9%
Other values (9) 1450
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67928
57.3%
ASCII 50602
42.7%
Compat Jamo 46
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16414
32.4%
7 7998
15.8%
1 7540
14.9%
3 4139
 
8.2%
5 2799
 
5.5%
2 2659
 
5.3%
4 2557
 
5.1%
, 1907
 
3.8%
6 1648
 
3.3%
0 1491
 
2.9%
Other values (9) 1450
 
2.9%
Hangul
ValueCountFrequency (%)
15085
22.2%
13056
19.2%
11162
16.4%
4448
 
6.5%
4336
 
6.4%
4192
 
6.2%
4064
 
6.0%
3654
 
5.4%
1443
 
2.1%
1197
 
1.8%
Other values (139) 5291
 
7.8%
Compat Jamo
ValueCountFrequency (%)
45
97.8%
1
 
2.2%

위반일자
Real number (ℝ)

HIGH CORRELATION 

Distinct3219
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20134860
Minimum19940501
Maximum20240308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:16:03.306682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19940501
5-th percentile20031107
Q120090512
median20141108
Q320180307
95-th percentile20211129
Maximum20240308
Range299807
Interquartile range (IQR)89795

Descriptive statistics

Standard deviation56721.479
Coefficient of variation (CV)0.0028170784
Kurtosis-0.9017691
Mean20134860
Median Absolute Deviation (MAD)40100.5
Skewness-0.34637305
Sum2.013486 × 1011
Variance3.2173262 × 109
MonotonicityNot monotonic
2024-05-11T16:16:03.433442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20211129 357
 
3.6%
20170410 332
 
3.3%
20161109 327
 
3.3%
20161212 101
 
1.0%
20161213 100
 
1.0%
20161214 87
 
0.9%
20170110 73
 
0.7%
20200101 72
 
0.7%
20140515 62
 
0.6%
20140501 52
 
0.5%
Other values (3209) 8437
84.4%
ValueCountFrequency (%)
19940501 1
 
< 0.1%
19960930 1
 
< 0.1%
20020220 3
< 0.1%
20020720 1
 
< 0.1%
20020723 1
 
< 0.1%
20020725 3
< 0.1%
20020726 1
 
< 0.1%
20020731 1
 
< 0.1%
20020801 2
< 0.1%
20020803 1
 
< 0.1%
ValueCountFrequency (%)
20240308 1
 
< 0.1%
20240227 3
< 0.1%
20240226 1
 
< 0.1%
20240223 2
 
< 0.1%
20240207 2
 
< 0.1%
20240205 4
< 0.1%
20240131 1
 
< 0.1%
20240130 3
< 0.1%
20240124 5
0.1%
20240123 1
 
< 0.1%
Distinct4264
Distinct (%)42.6%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T16:16:03.700427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length202
Median length144
Mean length20.596419
Min length1

Characters and Unicode

Total characters205923
Distinct characters787
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3078 ?
Unique (%)30.8%

Sample

1st row맘스엽산600 및 락피도엘 등 건강기능식품에 대하여 자사홈페이지에 질병을 예방한다는 허위과대광고
2nd row폐업신고없이 사업자등록 폐업(시설물멸실) (사업자등록 폐업일자 2008.03.31)
3rd row유흥접객원 고용 영업
4th row-질병의 예방 및 치료에 효능.효과가 있거나 의약품으로 오인.혼동할 우려가 있는 내용의 표시.광고를 한 경우 -사실과 다르거나 과장된 표시.광고를 한 경우 -소비자를 기만하거나 오인.혼동시킬 우려가 있는 표시.광고를 한 경우
5th row종업원건강진단미필(2/4)
ValueCountFrequency (%)
사업자등록 1473
 
3.8%
1093
 
2.8%
폐업 841
 
2.2%
영업장 655
 
1.7%
적발 582
 
1.5%
폐업신고없이 566
 
1.5%
미이수 507
 
1.3%
427
 
1.1%
폐업일자 414
 
1.1%
건강진단 404
 
1.0%
Other values (6448) 31686
82.0%
2024-05-11T16:16:04.140452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30285
 
14.7%
8935
 
4.3%
. 5758
 
2.8%
0 5380
 
2.6%
2 5260
 
2.6%
1 4802
 
2.3%
) 4193
 
2.0%
( 4184
 
2.0%
3473
 
1.7%
3243
 
1.6%
Other values (777) 130410
63.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135860
66.0%
Space Separator 30285
 
14.7%
Decimal Number 21308
 
10.3%
Other Punctuation 8119
 
3.9%
Close Punctuation 4228
 
2.1%
Open Punctuation 4220
 
2.0%
Dash Punctuation 777
 
0.4%
Uppercase Letter 397
 
0.2%
Lowercase Letter 329
 
0.2%
Control 190
 
0.1%
Other values (3) 210
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8935
 
6.6%
3473
 
2.6%
3243
 
2.4%
3198
 
2.4%
3116
 
2.3%
2931
 
2.2%
2853
 
2.1%
2660
 
2.0%
2645
 
1.9%
2432
 
1.8%
Other values (688) 100374
73.9%
Uppercase Letter
ValueCountFrequency (%)
E 36
 
9.1%
S 36
 
9.1%
A 33
 
8.3%
U 27
 
6.8%
R 24
 
6.0%
O 23
 
5.8%
C 23
 
5.8%
H 21
 
5.3%
D 20
 
5.0%
F 20
 
5.0%
Other values (15) 134
33.8%
Lowercase Letter
ValueCountFrequency (%)
g 99
30.1%
m 45
13.7%
k 44
13.4%
c 27
 
8.2%
p 18
 
5.5%
o 17
 
5.2%
t 12
 
3.6%
e 11
 
3.3%
l 10
 
3.0%
v 9
 
2.7%
Other values (13) 37
 
11.2%
Other Punctuation
ValueCountFrequency (%)
. 5758
70.9%
: 1180
 
14.5%
, 685
 
8.4%
/ 328
 
4.0%
* 66
 
0.8%
? 62
 
0.8%
% 24
 
0.3%
' 5
 
0.1%
; 3
 
< 0.1%
2
 
< 0.1%
Other values (3) 6
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 5380
25.2%
2 5260
24.7%
1 4802
22.5%
3 1418
 
6.7%
9 876
 
4.1%
6 846
 
4.0%
4 755
 
3.5%
5 723
 
3.4%
8 639
 
3.0%
7 609
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 4193
99.2%
] 32
 
0.8%
} 2
 
< 0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4184
99.1%
[ 33
 
0.8%
{ 2
 
< 0.1%
1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
164
95.3%
7
 
4.1%
1
 
0.6%
Math Symbol
ValueCountFrequency (%)
~ 30
85.7%
= 4
 
11.4%
+ 1
 
2.9%
Space Separator
ValueCountFrequency (%)
30285
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 777
100.0%
Control
ValueCountFrequency (%)
190
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135860
66.0%
Common 69334
33.7%
Latin 729
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8935
 
6.6%
3473
 
2.6%
3243
 
2.4%
3198
 
2.4%
3116
 
2.3%
2931
 
2.2%
2853
 
2.1%
2660
 
2.0%
2645
 
1.9%
2432
 
1.8%
Other values (688) 100374
73.9%
Latin
ValueCountFrequency (%)
g 99
 
13.6%
m 45
 
6.2%
k 44
 
6.0%
E 36
 
4.9%
S 36
 
4.9%
A 33
 
4.5%
c 27
 
3.7%
U 27
 
3.7%
R 24
 
3.3%
O 23
 
3.2%
Other values (39) 335
46.0%
Common
ValueCountFrequency (%)
30285
43.7%
. 5758
 
8.3%
0 5380
 
7.8%
2 5260
 
7.6%
1 4802
 
6.9%
) 4193
 
6.0%
( 4184
 
6.0%
3 1418
 
2.0%
: 1180
 
1.7%
9 876
 
1.3%
Other values (30) 5998
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135806
65.9%
ASCII 69878
33.9%
CJK Compat 165
 
0.1%
Compat Jamo 54
 
< 0.1%
None 8
 
< 0.1%
Geometric Shapes 7
 
< 0.1%
Number Forms 3
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30285
43.3%
. 5758
 
8.2%
0 5380
 
7.7%
2 5260
 
7.5%
1 4802
 
6.9%
) 4193
 
6.0%
( 4184
 
6.0%
3 1418
 
2.0%
: 1180
 
1.7%
9 876
 
1.3%
Other values (69) 6542
 
9.4%
Hangul
ValueCountFrequency (%)
8935
 
6.6%
3473
 
2.6%
3243
 
2.4%
3198
 
2.4%
3116
 
2.3%
2931
 
2.2%
2853
 
2.1%
2660
 
2.0%
2645
 
1.9%
2432
 
1.8%
Other values (687) 100320
73.9%
CJK Compat
ValueCountFrequency (%)
164
99.4%
1
 
0.6%
Compat Jamo
ValueCountFrequency (%)
54
100.0%
Geometric Shapes
ValueCountFrequency (%)
7
100.0%
Number Forms
ValueCountFrequency (%)
3
100.0%
None
ValueCountFrequency (%)
2
25.0%
2
25.0%
2
25.0%
1
12.5%
1
12.5%
Punctuation
ValueCountFrequency (%)
2
100.0%
Distinct1287
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T16:16:04.399701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length132
Median length116
Mean length9.2481
Min length2

Characters and Unicode

Total characters92481
Distinct characters246
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique851 ?
Unique (%)8.5%

Sample

1st row영업정지1월(2010.07.09~2010.08.08)
2nd row영업소폐쇄(직권말소)
3rd row영업정지
4th row영업정지
5th row과태료부과
ValueCountFrequency (%)
영업소폐쇄 1535
 
10.1%
시정명령 1442
 
9.5%
영업정지 1435
 
9.4%
과태료부과 1206
 
7.9%
시설개수명령 759
 
5.0%
직권말소 691
 
4.5%
영업소폐쇄(직권말소 679
 
4.4%
과태료 464
 
3.0%
10만원 367
 
2.4%
288
 
1.9%
Other values (1575) 6393
41.9%
2024-05-11T16:16:04.865965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5267
 
5.7%
5264
 
5.7%
4680
 
5.1%
4595
 
5.0%
4000
 
4.3%
3790
 
4.1%
0 3648
 
3.9%
1 3127
 
3.4%
2810
 
3.0%
2533
 
2.7%
Other values (236) 52767
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66644
72.1%
Decimal Number 13542
 
14.6%
Space Separator 5267
 
5.7%
Other Punctuation 2657
 
2.9%
Open Punctuation 2022
 
2.2%
Close Punctuation 2007
 
2.2%
Math Symbol 280
 
0.3%
Dash Punctuation 56
 
0.1%
Uppercase Letter 5
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (206) 31473
47.2%
Decimal Number
ValueCountFrequency (%)
0 3648
26.9%
1 3127
23.1%
2 2376
17.5%
5 760
 
5.6%
3 711
 
5.3%
4 682
 
5.0%
8 639
 
4.7%
6 618
 
4.6%
9 513
 
3.8%
7 468
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 2192
82.5%
, 392
 
14.8%
/ 43
 
1.6%
: 17
 
0.6%
% 8
 
0.3%
* 3
 
0.1%
2
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 249
88.9%
+ 28
 
10.0%
2
 
0.7%
= 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
P 1
20.0%
H 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
5267
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2022
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2007
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66644
72.1%
Common 25832
 
27.9%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (206) 31473
47.2%
Common
ValueCountFrequency (%)
5267
20.4%
0 3648
14.1%
1 3127
12.1%
2 2376
9.2%
. 2192
8.5%
( 2022
 
7.8%
) 2007
 
7.8%
5 760
 
2.9%
3 711
 
2.8%
4 682
 
2.6%
Other values (16) 3040
11.8%
Latin
ValueCountFrequency (%)
C 2
40.0%
P 1
20.0%
H 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66619
72.0%
ASCII 25833
 
27.9%
Compat Jamo 25
 
< 0.1%
None 2
 
< 0.1%
Arrows 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5267
20.4%
0 3648
14.1%
1 3127
12.1%
2 2376
9.2%
. 2192
8.5%
( 2022
 
7.8%
) 2007
 
7.8%
5 760
 
2.9%
3 711
 
2.8%
4 682
 
2.6%
Other values (18) 3041
11.8%
Hangul
ValueCountFrequency (%)
5264
 
7.9%
4680
 
7.0%
4595
 
6.9%
4000
 
6.0%
3790
 
5.7%
2810
 
4.2%
2533
 
3.8%
2533
 
3.8%
2528
 
3.8%
2438
 
3.7%
Other values (205) 31448
47.2%
Compat Jamo
ValueCountFrequency (%)
25
100.0%
None
ValueCountFrequency (%)
2
100.0%
Arrows
ValueCountFrequency (%)
2
100.0%

처분기간
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)2.5%
Missing8939
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean12.344015
Minimum0
Maximum30
Zeros19
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:16:04.978482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q17
median15
Q315
95-th percentile19
Maximum30
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.2932348
Coefficient of variation (CV)0.42880981
Kurtosis0.75700008
Mean12.344015
Median Absolute Deviation (MAD)0
Skewness0.09636523
Sum13097
Variance28.018334
MonotonicityNot monotonic
2024-05-11T16:16:05.098518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
15 568
 
5.7%
7 212
 
2.1%
10 52
 
0.5%
5 49
 
0.5%
17 23
 
0.2%
0 19
 
0.2%
22 18
 
0.2%
3 16
 
0.2%
2 13
 
0.1%
6 13
 
0.1%
Other values (17) 78
 
0.8%
(Missing) 8939
89.4%
ValueCountFrequency (%)
0 19
 
0.2%
1 3
 
< 0.1%
2 13
 
0.1%
3 16
 
0.2%
4 4
 
< 0.1%
5 49
 
0.5%
6 13
 
0.1%
7 212
2.1%
8 11
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
30 9
 
0.1%
29 9
 
0.1%
25 3
 
< 0.1%
24 5
 
0.1%
23 2
 
< 0.1%
22 18
0.2%
20 7
 
0.1%
19 2
 
< 0.1%
18 6
 
0.1%
17 23
0.2%

영업장면적(㎡)
Real number (ℝ)

MISSING  SKEWED 

Distinct2329
Distinct (%)44.4%
Missing4752
Missing (%)47.5%
Infinite0
Infinite (%)0.0%
Mean158.95337
Minimum0
Maximum29316
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T16:16:05.231446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17.77
Q136.9075
median80.89
Q3135.2625
95-th percentile488.11
Maximum29316
Range29316
Interquartile range (IQR)98.355

Descriptive statistics

Standard deviation662.59745
Coefficient of variation (CV)4.1685021
Kurtosis1446.3623
Mean158.95337
Median Absolute Deviation (MAD)47.69
Skewness34.140984
Sum834187.28
Variance439035.39
MonotonicityNot monotonic
2024-05-11T16:16:05.375374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 95
 
0.9%
66.0 57
 
0.6%
26.4 52
 
0.5%
30.0 43
 
0.4%
82.5 38
 
0.4%
29.7 37
 
0.4%
60.0 35
 
0.4%
23.1 33
 
0.3%
99.0 29
 
0.3%
20.0 29
 
0.3%
Other values (2319) 4800
48.0%
(Missing) 4752
47.5%
ValueCountFrequency (%)
0.0 5
 
0.1%
1.33 1
 
< 0.1%
3.0 3
 
< 0.1%
3.3 19
0.2%
3.42 3
 
< 0.1%
4.0 3
 
< 0.1%
4.5 1
 
< 0.1%
4.95 2
 
< 0.1%
5.0 2
 
< 0.1%
5.09 8
0.1%
ValueCountFrequency (%)
29316.0 2
< 0.1%
10985.1 1
 
< 0.1%
5932.92 2
< 0.1%
5244.88 1
 
< 0.1%
4690.8 1
 
< 0.1%
4234.09 2
< 0.1%
3488.38 3
< 0.1%
3169.0 1
 
< 0.1%
2975.0 1
 
< 0.1%
2622.64 3
< 0.1%

Interactions

2024-05-11T16:15:56.311313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.268938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.684325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.381928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.837934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.402626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.346401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.779084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.469519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.927532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.495575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.427423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.102640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.560395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.019520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.590342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.507413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.193352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.651127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.117030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.683043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:54.593773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.289282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:55.751874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:15:56.214156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T16:16:05.465123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자업종명업태명지도점검일자위반일자처분기간영업장면적(㎡)
처분일자1.000NaNNaNNaNNaNNaNNaN
업종명NaN1.0000.9980.5900.5210.5180.319
업태명NaN0.9981.0000.6440.5830.6100.636
지도점검일자NaN0.5900.6441.0000.9180.3210.092
위반일자NaN0.5210.5830.9181.0000.2200.021
처분기간NaN0.5180.6100.3210.2201.0000.294
영업장면적(㎡)NaN0.3190.6360.0920.0210.2941.000
2024-05-11T16:16:05.574221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
처분일자지도점검일자위반일자처분기간영업장면적(㎡)업종명
처분일자1.0000.9990.987-0.118-0.1500.000
지도점검일자0.9991.0000.988-0.119-0.1510.249
위반일자0.9870.9881.000-0.119-0.1470.220
처분기간-0.118-0.119-0.1191.0000.1390.227
영업장면적(㎡)-0.150-0.151-0.1470.1391.0000.157
업종명0.0000.2490.2200.2270.1571.000

Missing values

2024-05-11T16:15:56.816575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T16:15:57.037812image/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.
2024-05-11T16:15:57.206411image/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(㎡)
1066532300002010062820040116466건강기능식품유통전문판매업건강기능식품유통전문판매업(주)에프앤디넷서울특별시 송파구 송이로 79, (가락동,진성빌딩5층)서울특별시 송파구 가락동 48번지 7호 진성빌딩5층20100621처분확정영업정지1월(2010.07.09~2010.08.08)건강기능식품에 관한 법률 제32조20100621맘스엽산600 및 락피도엘 등 건강기능식품에 대하여 자사홈페이지에 질병을 예방한다는 허위과대광고영업정지1월(2010.07.09~2010.08.08)<NA><NA>
599632300002017011220060114480즉석판매제조가공업즉석판매제조가공업(주)아이푸드바이오서울특별시 송파구 올림픽로 240, (잠실동,롯데마트 지하1층식품부내)서울특별시 송파구 잠실동 40번지 1호 롯데마트 지하1층식품부내20161109처분확정영업소폐쇄(직권말소)법 제37조 7항20161109폐업신고없이 사업자등록 폐업(시설물멸실) (사업자등록 폐업일자 2008.03.31)영업소폐쇄(직권말소)<NA><NA>
1482832300002003012819940114953단란주점단란주점청화대서울특별시 송파구 오금로11길 32, (방이동)서울특별시 송파구 방이동 58번지 6호20021128처분확정영업정지식품위생법제31조20021128유흥접객원 고용 영업영업정지<NA>78.1
738332300002015043020120114037건강기능식품일반판매업<NA>헬시트리서울특별시 송파구 백제고분로32길 29-8, 402-1호 (삼전동, 시티빌)서울특별시 송파구 삼전동 173번지 13호 시티빌-402-120150330처분확정영업정지법 제32조 및 제33조20180307-질병의 예방 및 치료에 효능.효과가 있거나 의약품으로 오인.혼동할 우려가 있는 내용의 표시.광고를 한 경우 -사실과 다르거나 과장된 표시.광고를 한 경우 -소비자를 기만하거나 오인.혼동시킬 우려가 있는 표시.광고를 한 경우영업정지<NA>3.3
1462732300002003052920010114808일반음식점분식석우동서울특별시 송파구 가락로 159, (송파동)서울특별시 송파구 송파동 104번지 10호20030418처분확정과태료부과식품위생법제26조20030418종업원건강진단미필(2/4)과태료부과<NA><NA>
127132300002021122420180115730일반음식점일식부타야 돈이찌서울특별시 송파구 올림픽로32길 41, 1층 (방이동)서울특별시 송파구 방이동 99번지 21호20211129처분확정과태료부과 10만원법 제101조제4항1호202111292020년 식품위생교육 미이수과태료부과 10만원<NA><NA>
1045432300002011011320000115620일반음식점한식장터식당서울특별시 송파구 백제고분로48길 14, (방이동)서울특별시 송파구 방이동 113번지 0호20101216처분확정영업소폐쇄식품위생법 제36조 및 제37조20101216영업시설의 전부철거영업소폐쇄<NA>24.84
1362932300002005030520040116390일반음식점정종/대포집/소주방산골포차오천냥서울특별시 송파구 백제고분로7길 52-24, (잠실동)서울특별시 송파구 잠실동 207번지 7호20041218처분확정영업정지제31조20041218청소년주류제공영업정지<NA><NA>
72132300002022072820220139620일반음식점기타마이 위스키 테이블(MY WHISKY TABLE)서울특별시 송파구 법원로 114, 엠스테이트 제C동 1층 제C-105호 (문정동)서울특별시 송파구 문정동 643번지 1호 엠스테이트20220622처분확정시정명령법 제71조, 법 제74조 및 법 제75조20220622영업장 외 영업행위시정명령<NA><NA>
909132300002013032619960115246단란주점단란주점코리아서울특별시 송파구 백제고분로 426, (송파동,,18)서울특별시 송파구 송파동 135번지 0호 ,1820121119처분확정영업정지1월15일을 영업정지23일 및 과징금264만원으로 변경처분함식품위생법 제75조20121119유흥접객행위를 함 (12.11.19/12.11.23 2회 적발)영업정지1월15일을 영업정지23일 및 과징금264만원으로 변경처분함22132.84
시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)
571632300002017022220100115581일반음식점중국식김한성 짬뽕서울특별시 송파구 오금로 194, (송파동,지상1층)서울특별시 송파구 송파동 142번지 2호 지상1층20161212처분확정직권말소법 제37조 7항20161212사업자등록폐업(2013.10.10.)직권말소<NA><NA>
1406232300002004052819940114793일반음식점분식엄마손김밥서울특별시 송파구 백제고분로7길 18, (잠실동)서울특별시 송파구 잠실동 192번지 0호20040422처분확정과태료부과식품위생법제26조 및 제22조200404221. 영업장(조리장) 무단확장 2. 영업주건강진단미필 및 종업원건강진단미필과태료부과<NA><NA>
471932300002017062720090114246건강기능식품일반판매업<NA>미슬림서울특별시 송파구 오금로46길 27, (가락동,301호)서울특별시 송파구 가락동 181번지 15호 301호20170410처분확정영업소폐쇄(직권말소)법 제6조 4항20170410폐업신고없이 사업자등록 폐업 (사업자등록 폐업일자:2010.04.23)영업소폐쇄(직권말소)<NA><NA>
29032300002023081120150115480식품소분업식품소분업(주)정도티앤에프서울특별시 송파구 거마로 61, 지하1층 (마천동)서울특별시 송파구 마천동 35번지 1호 지하1층20230728처분확정직권말소법 제37조 7항20230728사업자등록 폐업에 따른 영업신고사항 직권말소직권말소<NA><NA>
850232300002014021820010116116일반음식점분식마녀공장서울특별시 송파구 백제고분로7길 52-5, 1층 (잠실동)서울특별시 송파구 잠실동 185번지 8호 1층20131211처분확정시정명령식품위생법 제75조20131211영업장외 영업시정명령<NA><NA>
790832300002014091720130115373일반음식점기타소노서울특별시 송파구 오금로44길 20, 지상1층 (가락동)서울특별시 송파구 가락동 173번지 19호 지상1층20140713처분확정영업정지식품위생법 제44조20140713청소년 주류제공영업정지<NA>33.0
1470632300002003041619980115595식품소분업식품소분업금양상사(주)서울특별시 송파구 동남로3길 17, (가락동,(지층))서울특별시 송파구 가락동 104번지 12호 (지층)20030314처분확정영업소폐쇄식품위생법 제21조20030314시설물 무단멸실영업소폐쇄<NA><NA>
331132300002018103020100115699휴게음식점일반조리판매샌드리치서울특별시 송파구 동남로 274, (오금동, 지상1층)서울특별시 송파구 오금동 151번지 4호 외3필지(151-5,6,12) 지상1층20181011처분확정직권말소법 제37조 7항20181011사업자등록 폐업직권말소<NA>23.1
1385432300002004090620020114541일반음식점한식캔버라서울특별시 송파구 송파대로 286, (가락동)서울특별시 송파구 가락동 96번지 12호20040818처분확정과태료부과법26조20040818영업주건강진단미필과태료부과<NA><NA>
1023532300002011063020010115528단란주점단란주점영클럽 스탠드바서울특별시 송파구 송파대로 274, (가락동,(지하1층))서울특별시 송파구 가락동 98번지 3호 (지하1층)20110720처분확정영업정지7일식품위생법 제36조 및 같은법 제37조, 식품위생법 제75조20110210영업장을 무단확장하고 변경신고를 하지 않은 사실영업정지7일7<NA>

Duplicate rows

Most frequently occurring

시군구코드처분일자교부번호업종명업태명업소명소재지도로명소재지지번지도점검일자행정처분상태처분명법적근거위반일자위반내용처분내용처분기간영업장면적(㎡)# duplicates
10432300002011011320000115620일반음식점한식장터식당서울특별시 송파구 백제고분로48길 14, (방이동)서울특별시 송파구 방이동 113번지 0호20101216처분확정영업소폐쇄식품위생법 제36조 및 제37조20101216영업시설의 전부철거영업소폐쇄<NA>24.848
3632300002005092119940114246일반음식점한식우리한식서울특별시 송파구 올림픽로35길 94, (신천동,장미씨상가 210호)서울특별시 송파구 신천동 11번지 0호 장미씨상가 210호20050907처분확정시설개수명령(10.4한)법제57조20050907주방바닥시설 및 후드청소 불량시설개수명령(10.4한)<NA><NA>5
11732300002011112320040114407식품등 수입판매업식품등 수입판매업대림농수산서울특별시 송파구 송파대로32길 15, (가락동,가락금호상가 B3호)서울특별시 송파구 가락동 95번지 1호 가락금호상가 B3호20110930처분확정영업정지 15일 및 해당제품 폐기,시정명령식품위생법 제7조제4항 및 제13조 제1항20110930-식중독균 황색포도상구균 검출 -제조회사명을 수입신고한 사항과 다르게표시영업정지 15일 및 해당제품 폐기,시정명령15<NA>5
26332300002017071120000114798일반음식점일식영산포서울특별시 송파구 양재대로 932, 1층 가락몰5관 편의시설003-1호 (가락동, 농수산물도매시장내)서울특별시 송파구 가락동 600번지20170424처분확정시설개수명령법 제71조, 법 제74조 및 법 제75조20170424영업장 내 조리시설 없음시설개수명령<NA>6.55
1923230000201408042003-02-136목욕장업공동탕업가락한양사우나서울특별시 송파구 가락로 183, (송파동,B층)서울특별시 송파구 송파동 121번지 B층20140619처분확정과태료부과법 제4조제2항20140619욕수의 수질기준에 적합하게 욕수를 유지한지 않음과태료부과<NA><NA>4
21832300002015091620150114609단란주점단란주점디바서울특별시 송파구 송파대로28길 35, (가락동, 302호)서울특별시 송파구 가락동 77번지 7호 302호20150722처분확정영업정지1월식품위생법 제75조20150714유흥접객영업영업정지1월<NA><NA>4
632300002003032619930115784일반음식점경양식연경서울특별시 송파구 송파대로28길 28, (가락동)서울특별시 송파구 가락동 79번지 6호20030220처분확정과태료부과식품위생법제26조20020220종업원건강진단미필(2/3)과태료부과<NA><NA>3
2132300002004101119900114110일반음식점한식토왈서울특별시 송파구 백제고분로7길 43, (잠실동,,12,14)서울특별시 송파구 잠실동 183번지 2호 ,12,1420040716처분확정영업정지식품위생법제31조20040716청소년주류제공영업정지<NA><NA>3
2632300002005041519850114117일반음식점일식성전서울특별시 송파구 양재대로 932, (가락동,(수산시장3층))서울특별시 송파구 가락동 600번지 0호 (수산시장3층)20050408처분확정과태료부과26조20050308건강진단미필(4/13명)과태료부과<NA><NA>3
3132300002005071419940115142일반음식점한식풀촌갈비서울특별시 송파구 중대로9길 42, (가락동)서울특별시 송파구 가락동 83번지 10호20050707처분확정영업소폐쇄21조200507076월이상 장기휴업영업소폐쇄<NA><NA>3