Overview

Dataset statistics

Number of variables15
Number of observations252
Missing cells230
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.1 KiB
Average record size in memory126.5 B

Variable types

Categorical4
Numeric5
Text6

Dataset

Description시군구코드,지정년도,지정번호,신청일자,지정일자,업소명,소재지도로명,소재지지번,허가(신고)번호,업태명,주된음식,영업장면적(㎡),행정동명,급수시설구분,소재지전화번호
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-11064/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
지정년도 is highly overall correlated with 신청일자 and 1 other fieldsHigh correlation
신청일자 is highly overall correlated with 지정년도 and 1 other fieldsHigh correlation
지정일자 is highly overall correlated with 지정년도 and 1 other fieldsHigh correlation
업태명 is highly overall correlated with 급수시설구분High correlation
급수시설구분 is highly overall correlated with 업태명High correlation
업태명 is highly imbalanced (58.5%)Imbalance
주된음식 has 144 (57.1%) missing valuesMissing
소재지전화번호 has 86 (34.1%) missing valuesMissing
소재지지번 has unique valuesUnique
허가(신고)번호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 06:36:20.639879
Analysis finished2024-05-04 06:36:35.019643
Duration14.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3210000
252 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 252
100.0%

Length

2024-05-04T06:36:35.265750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:36:35.575245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 252
100.0%

지정년도
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.4484
Minimum2003
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-04T06:36:35.933550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2003
Q12012.75
median2018
Q32019
95-th percentile2023
Maximum2023
Range20
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation5.772006
Coefficient of variation (CV)0.0028638818
Kurtosis-0.42034971
Mean2015.4484
Median Absolute Deviation (MAD)3
Skewness-0.81707391
Sum507893
Variance33.316053
MonotonicityDecreasing
2024-05-04T06:36:36.417144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2018 61
24.2%
2023 20
 
7.9%
2020 18
 
7.1%
2019 17
 
6.7%
2016 15
 
6.0%
2003 15
 
6.0%
2009 12
 
4.8%
2022 11
 
4.4%
2017 10
 
4.0%
2015 10
 
4.0%
Other values (10) 63
25.0%
ValueCountFrequency (%)
2003 15
6.0%
2004 2
 
0.8%
2005 6
 
2.4%
2006 7
2.8%
2007 8
3.2%
2008 6
 
2.4%
2009 12
4.8%
2010 2
 
0.8%
2012 5
 
2.0%
2013 8
3.2%
ValueCountFrequency (%)
2023 20
 
7.9%
2022 11
 
4.4%
2021 9
 
3.6%
2020 18
 
7.1%
2019 17
 
6.7%
2018 61
24.2%
2017 10
 
4.0%
2016 15
 
6.0%
2015 10
 
4.0%
2014 10
 
4.0%

지정번호
Real number (ℝ)

Distinct98
Distinct (%)38.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.809524
Minimum1
Maximum1324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-04T06:36:37.043421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median21.5
Q348
95-th percentile178.6
Maximum1324
Range1323
Interquartile range (IQR)39

Descriptive statistics

Standard deviation229.08254
Coefficient of variation (CV)3.0622109
Kurtosis25.168647
Mean74.809524
Median Absolute Deviation (MAD)14.5
Skewness5.1137772
Sum18852
Variance52478.808
MonotonicityNot monotonic
2024-05-04T06:36:37.524161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 10
 
4.0%
7 9
 
3.6%
5 9
 
3.6%
14 8
 
3.2%
2 8
 
3.2%
10 8
 
3.2%
24 7
 
2.8%
6 6
 
2.4%
17 6
 
2.4%
1 6
 
2.4%
Other values (88) 175
69.4%
ValueCountFrequency (%)
1 6
2.4%
2 8
3.2%
3 6
2.4%
4 5
2.0%
5 9
3.6%
6 6
2.4%
7 9
3.6%
8 10
4.0%
9 6
2.4%
10 8
3.2%
ValueCountFrequency (%)
1324 1
0.4%
1323 1
0.4%
1322 1
0.4%
1321 1
0.4%
1318 1
0.4%
1314 1
0.4%
1309 1
0.4%
1302 1
0.4%
291 1
0.4%
284 1
0.4%

신청일자
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20153389
Minimum20030618
Maximum20230905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-04T06:36:38.059869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030618
5-th percentile20030618
Q120117869
median20181001
Q320191001
95-th percentile20230825
Maximum20230905
Range200287
Interquartile range (IQR)73132

Descriptive statistics

Standard deviation58277.531
Coefficient of variation (CV)0.0028916988
Kurtosis-0.59313317
Mean20153389
Median Absolute Deviation (MAD)30000
Skewness-0.71447625
Sum5.0786541 × 109
Variance3.3962706 × 109
MonotonicityNot monotonic
2024-05-04T06:36:38.582885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20181001 57
22.6%
20201001 18
 
7.1%
20191001 16
 
6.3%
20030618 15
 
6.0%
20221001 11
 
4.4%
20171001 10
 
4.0%
20211001 9
 
3.6%
20131230 9
 
3.6%
20141231 9
 
3.6%
20070531 8
 
3.2%
Other values (41) 90
35.7%
ValueCountFrequency (%)
20030618 15
6.0%
20040719 2
 
0.8%
20050728 6
 
2.4%
20060630 7
2.8%
20070531 8
3.2%
20080302 1
 
0.4%
20080530 5
 
2.0%
20090317 1
 
0.4%
20090318 1
 
0.4%
20090326 1
 
0.4%
ValueCountFrequency (%)
20230905 1
 
0.4%
20230831 5
2.0%
20230830 2
 
0.8%
20230829 4
 
1.6%
20230825 2
 
0.8%
20230823 1
 
0.4%
20230822 2
 
0.8%
20230817 3
 
1.2%
20221001 11
4.4%
20211001 9
3.6%

지정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20155390
Minimum20030718
Maximum20231114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-04T06:36:39.021744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030718
5-th percentile20030718
Q120127693
median20181218
Q320191217
95-th percentile20231114
Maximum20231114
Range200396
Interquartile range (IQR)63523.75

Descriptive statistics

Standard deviation57917.608
Coefficient of variation (CV)0.0028735543
Kurtosis-0.43537035
Mean20155390
Median Absolute Deviation (MAD)29996
Skewness-0.81082049
Sum5.0791582 × 109
Variance3.3544493 × 109
MonotonicityNot monotonic
2024-05-04T06:36:39.420780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
20181218 59
23.4%
20231114 20
 
7.9%
20201202 18
 
7.1%
20191217 16
 
6.3%
20030718 15
 
6.0%
20160718 14
 
5.6%
20090724 12
 
4.8%
20221129 11
 
4.4%
20150225 10
 
4.0%
20140121 10
 
4.0%
Other values (15) 67
26.6%
ValueCountFrequency (%)
20030718 15
6.0%
20040816 2
 
0.8%
20050728 6
 
2.4%
20060727 7
2.8%
20070726 8
3.2%
20080805 6
 
2.4%
20090724 12
4.8%
20100101 1
 
0.4%
20100630 1
 
0.4%
20120119 5
 
2.0%
ValueCountFrequency (%)
20231114 20
 
7.9%
20221129 11
 
4.4%
20211214 9
 
3.6%
20201202 18
 
7.1%
20191217 16
 
6.3%
20190228 1
 
0.4%
20181218 59
23.4%
20180627 1
 
0.4%
20180123 1
 
0.4%
20171013 10
 
4.0%

업소명
Text

Distinct249
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-04T06:36:40.120057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length17
Mean length6.4722222
Min length2

Characters and Unicode

Total characters1631
Distinct characters360
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)97.6%

Sample

1st row소곰집 양재점
2nd row낙천정
3rd row선화의 삼겹살 무한리필 방배역점
4th row금빛
5th row담채
ValueCountFrequency (%)
서초점 6
 
1.6%
교대점 4
 
1.1%
방배점 4
 
1.1%
양재점 4
 
1.1%
강남역 3
 
0.8%
강남점 3
 
0.8%
주식회사 3
 
0.8%
서초 3
 
0.8%
교대본점 2
 
0.5%
방배 2
 
0.5%
Other values (320) 332
90.7%
2024-05-04T06:36:41.329705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
 
7.1%
점 59
 
3.6%
서 36
 
2.2%
초 27
 
1.7%
) 20
 
1.2%
이 20
 
1.2%
( 20
 
1.2%
대 20
 
1.2%
남 19
 
1.2%
우 19
 
1.2%
Other values (350) 1276
78.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1403
86.0%
Space Separator 115
 
7.1%
Uppercase Letter 36
 
2.2%
Lowercase Letter 26
 
1.6%
Close Punctuation 20
 
1.2%
Open Punctuation 20
 
1.2%
Decimal Number 7
 
0.4%
Other Punctuation 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 59
 
4.2%
서 36
 
2.6%
초 27
 
1.9%
이 20
 
1.4%
대 20
 
1.4%
남 19
 
1.4%
우 19
 
1.4%
리 18
 
1.3%
배 18
 
1.3%
방 18
 
1.3%
Other values (308) 1149
81.9%
Uppercase Letter
ValueCountFrequency (%)
L 4
11.1%
A 4
11.1%
I 4
11.1%
R 3
 
8.3%
P 3
 
8.3%
O 2
 
5.6%
E 2
 
5.6%
S 2
 
5.6%
B 2
 
5.6%
D 2
 
5.6%
Other values (7) 8
22.2%
Lowercase Letter
ValueCountFrequency (%)
a 5
19.2%
t 4
15.4%
l 2
 
7.7%
e 2
 
7.7%
o 2
 
7.7%
i 2
 
7.7%
d 2
 
7.7%
h 2
 
7.7%
p 1
 
3.8%
n 1
 
3.8%
Other values (3) 3
11.5%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
9 1
14.3%
5 1
14.3%
0 1
14.3%
2 1
14.3%
4 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1403
86.0%
Common 166
 
10.2%
Latin 62
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 59
 
4.2%
서 36
 
2.6%
초 27
 
1.9%
이 20
 
1.4%
대 20
 
1.4%
남 19
 
1.4%
우 19
 
1.4%
리 18
 
1.3%
배 18
 
1.3%
방 18
 
1.3%
Other values (308) 1149
81.9%
Latin
ValueCountFrequency (%)
a 5
 
8.1%
L 4
 
6.5%
t 4
 
6.5%
A 4
 
6.5%
I 4
 
6.5%
R 3
 
4.8%
P 3
 
4.8%
O 2
 
3.2%
E 2
 
3.2%
S 2
 
3.2%
Other values (20) 29
46.8%
Common
ValueCountFrequency (%)
115
69.3%
) 20
 
12.0%
( 20
 
12.0%
. 2
 
1.2%
1 2
 
1.2%
& 1
 
0.6%
9 1
 
0.6%
5 1
 
0.6%
0 1
 
0.6%
2 1
 
0.6%
Other values (2) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1403
86.0%
ASCII 228
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
50.4%
) 20
 
8.8%
( 20
 
8.8%
a 5
 
2.2%
L 4
 
1.8%
t 4
 
1.8%
A 4
 
1.8%
I 4
 
1.8%
R 3
 
1.3%
P 3
 
1.3%
Other values (32) 46
 
20.2%
Hangul
ValueCountFrequency (%)
점 59
 
4.2%
서 36
 
2.6%
초 27
 
1.9%
이 20
 
1.4%
대 20
 
1.4%
남 19
 
1.4%
우 19
 
1.4%
리 18
 
1.3%
배 18
 
1.3%
방 18
 
1.3%
Other values (308) 1149
81.9%

소재지도로명
Text

Distinct251
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-04T06:36:42.041995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length54
Mean length32.968254
Min length23

Characters and Unicode

Total characters8308
Distinct characters212
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)99.2%

Sample

1st row서울특별시 서초구 남부순환로350길 38, 1층 (양재동)
2nd row서울특별시 서초구 효령로49길 19, (서초동,2층,3층)
3rd row서울특별시 서초구 효령로31길 7, 1층 (방배동)
4th row서울특별시 서초구 방배중앙로29길 3, 2층 (방배동)
5th row서울특별시 서초구 서초중앙로20길 34-5, (서초동, 1층)
ValueCountFrequency (%)
서울특별시 252
 
15.9%
서초구 252
 
15.9%
1층 109
 
6.9%
서초동 99
 
6.2%
방배동 54
 
3.4%
2층 24
 
1.5%
양재동 23
 
1.5%
지하1층 22
 
1.4%
반포동 17
 
1.1%
서초대로 13
 
0.8%
Other values (417) 719
45.4%
2024-05-04T06:36:43.197846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1332
 
16.0%
서 698
 
8.4%
1 438
 
5.3%
초 433
 
5.2%
, 390
 
4.7%
동 276
 
3.3%
) 260
 
3.1%
( 260
 
3.1%
시 255
 
3.1%
울 254
 
3.1%
Other values (202) 3712
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4641
55.9%
Decimal Number 1349
 
16.2%
Space Separator 1332
 
16.0%
Other Punctuation 390
 
4.7%
Close Punctuation 260
 
3.1%
Open Punctuation 260
 
3.1%
Dash Punctuation 41
 
0.5%
Uppercase Letter 31
 
0.4%
Math Symbol 3
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 698
15.0%
초 433
 
9.3%
동 276
 
5.9%
시 255
 
5.5%
울 254
 
5.5%
구 252
 
5.4%
별 252
 
5.4%
특 252
 
5.4%
로 242
 
5.2%
층 234
 
5.0%
Other values (167) 1493
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 8
25.8%
B 4
12.9%
N 2
 
6.5%
C 2
 
6.5%
T 2
 
6.5%
E 1
 
3.2%
D 1
 
3.2%
S 1
 
3.2%
K 1
 
3.2%
V 1
 
3.2%
Other values (8) 8
25.8%
Decimal Number
ValueCountFrequency (%)
1 438
32.5%
2 229
17.0%
3 134
 
9.9%
0 111
 
8.2%
4 90
 
6.7%
5 86
 
6.4%
7 73
 
5.4%
6 68
 
5.0%
8 61
 
4.5%
9 59
 
4.4%
Space Separator
ValueCountFrequency (%)
1332
100.0%
Other Punctuation
ValueCountFrequency (%)
, 390
100.0%
Close Punctuation
ValueCountFrequency (%)
) 260
100.0%
Open Punctuation
ValueCountFrequency (%)
( 260
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4641
55.9%
Common 3635
43.8%
Latin 32
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 698
15.0%
초 433
 
9.3%
동 276
 
5.9%
시 255
 
5.5%
울 254
 
5.5%
구 252
 
5.4%
별 252
 
5.4%
특 252
 
5.4%
로 242
 
5.2%
층 234
 
5.0%
Other values (167) 1493
32.2%
Latin
ValueCountFrequency (%)
A 8
25.0%
B 4
12.5%
N 2
 
6.2%
C 2
 
6.2%
T 2
 
6.2%
E 1
 
3.1%
D 1
 
3.1%
S 1
 
3.1%
K 1
 
3.1%
V 1
 
3.1%
Other values (9) 9
28.1%
Common
ValueCountFrequency (%)
1332
36.6%
1 438
 
12.0%
, 390
 
10.7%
) 260
 
7.2%
( 260
 
7.2%
2 229
 
6.3%
3 134
 
3.7%
0 111
 
3.1%
4 90
 
2.5%
5 86
 
2.4%
Other values (6) 305
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4641
55.9%
ASCII 3666
44.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1332
36.3%
1 438
 
11.9%
, 390
 
10.6%
) 260
 
7.1%
( 260
 
7.1%
2 229
 
6.2%
3 134
 
3.7%
0 111
 
3.0%
4 90
 
2.5%
5 86
 
2.3%
Other values (24) 336
 
9.2%
Hangul
ValueCountFrequency (%)
서 698
15.0%
초 433
 
9.3%
동 276
 
5.9%
시 255
 
5.5%
울 254
 
5.5%
구 252
 
5.4%
별 252
 
5.4%
특 252
 
5.4%
로 242
 
5.2%
층 234
 
5.0%
Other values (167) 1493
32.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

소재지지번
Text

UNIQUE 

Distinct252
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-04T06:36:44.224492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length47
Mean length31.34127
Min length23

Characters and Unicode

Total characters7898
Distinct characters187
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)100.0%

Sample

1st row서울특별시 서초구 양재동 13번지 10호 1층
2nd row서울특별시 서초구 서초동 1531번지 3호 2층,3층
3rd row서울특별시 서초구 방배동 912번지 9호 1층
4th row서울특별시 서초구 방배동 761번지 2호 2층-202
5th row서울특별시 서초구 서초동 1665번지 1호 1층
ValueCountFrequency (%)
서울특별시 252
 
15.9%
서초구 252
 
15.9%
1층 115
 
7.3%
서초동 114
 
7.2%
방배동 64
 
4.0%
양재동 29
 
1.8%
1호 25
 
1.6%
2층 24
 
1.5%
반포동 21
 
1.3%
2호 20
 
1.3%
Other values (365) 669
42.2%
2024-05-04T06:36:45.729887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1864
23.6%
서 625
 
7.9%
1 552
 
7.0%
초 370
 
4.7%
지 305
 
3.9%
호 288
 
3.6%
동 265
 
3.4%
시 254
 
3.2%
울 254
 
3.2%
특 252
 
3.2%
Other values (177) 2869
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4235
53.6%
Space Separator 1864
23.6%
Decimal Number 1638
 
20.7%
Other Punctuation 70
 
0.9%
Uppercase Letter 26
 
0.3%
Dash Punctuation 24
 
0.3%
Open Punctuation 18
 
0.2%
Close Punctuation 18
 
0.2%
Math Symbol 4
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 625
14.8%
초 370
 
8.7%
지 305
 
7.2%
호 288
 
6.8%
동 265
 
6.3%
시 254
 
6.0%
울 254
 
6.0%
특 252
 
6.0%
별 252
 
6.0%
구 252
 
6.0%
Other values (145) 1118
26.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
26.9%
B 5
19.2%
C 2
 
7.7%
T 2
 
7.7%
D 1
 
3.8%
I 1
 
3.8%
Y 1
 
3.8%
F 1
 
3.8%
P 1
 
3.8%
L 1
 
3.8%
Other values (4) 4
15.4%
Decimal Number
ValueCountFrequency (%)
1 552
33.7%
2 203
 
12.4%
3 153
 
9.3%
0 147
 
9.0%
5 121
 
7.4%
7 114
 
7.0%
4 109
 
6.7%
6 95
 
5.8%
8 72
 
4.4%
9 72
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 61
87.1%
? 9
 
12.9%
Space Separator
ValueCountFrequency (%)
1864
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4235
53.6%
Common 3636
46.0%
Latin 27
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 625
14.8%
초 370
 
8.7%
지 305
 
7.2%
호 288
 
6.8%
동 265
 
6.3%
시 254
 
6.0%
울 254
 
6.0%
특 252
 
6.0%
별 252
 
6.0%
구 252
 
6.0%
Other values (145) 1118
26.4%
Common
ValueCountFrequency (%)
1864
51.3%
1 552
 
15.2%
2 203
 
5.6%
3 153
 
4.2%
0 147
 
4.0%
5 121
 
3.3%
7 114
 
3.1%
4 109
 
3.0%
6 95
 
2.6%
8 72
 
2.0%
Other values (7) 206
 
5.7%
Latin
ValueCountFrequency (%)
A 7
25.9%
B 5
18.5%
C 2
 
7.4%
T 2
 
7.4%
D 1
 
3.7%
I 1
 
3.7%
Y 1
 
3.7%
F 1
 
3.7%
P 1
 
3.7%
Ⅰ 1
 
3.7%
Other values (5) 5
18.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4235
53.6%
ASCII 3662
46.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1864
50.9%
1 552
 
15.1%
2 203
 
5.5%
3 153
 
4.2%
0 147
 
4.0%
5 121
 
3.3%
7 114
 
3.1%
4 109
 
3.0%
6 95
 
2.6%
8 72
 
2.0%
Other values (21) 232
 
6.3%
Hangul
ValueCountFrequency (%)
서 625
14.8%
초 370
 
8.7%
지 305
 
7.2%
호 288
 
6.8%
동 265
 
6.3%
시 254
 
6.0%
울 254
 
6.0%
특 252
 
6.0%
별 252
 
6.0%
구 252
 
6.0%
Other values (145) 1118
26.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

허가(신고)번호
Text

UNIQUE 

Distinct252
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-04T06:36:46.296215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters5544
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)100.0%

Sample

1st row3210000-101-2003-00419
2nd row3210000-101-2007-00441
3rd row3210000-101-1984-03480
4th row3210000-101-2014-00504
5th row3210000-101-2003-00026
ValueCountFrequency (%)
3210000-101-2003-00419 1
 
0.4%
3210000-101-2009-00293 1
 
0.4%
3210000-101-1989-04044 1
 
0.4%
3210000-101-2010-00205 1
 
0.4%
3210000-101-1994-03576 1
 
0.4%
3210000-101-2007-00517 1
 
0.4%
3210000-101-2014-00230 1
 
0.4%
3210000-101-2013-00047 1
 
0.4%
3210000-101-2005-00188 1
 
0.4%
3210000-101-2013-00519 1
 
0.4%
Other values (242) 242
96.0%
2024-05-04T06:36:47.339065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2052
37.0%
1 1065
19.2%
- 756
 
13.6%
2 569
 
10.3%
3 382
 
6.9%
9 192
 
3.5%
5 130
 
2.3%
4 125
 
2.3%
6 96
 
1.7%
7 89
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4788
86.4%
Dash Punctuation 756
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2052
42.9%
1 1065
22.2%
2 569
 
11.9%
3 382
 
8.0%
9 192
 
4.0%
5 130
 
2.7%
4 125
 
2.6%
6 96
 
2.0%
7 89
 
1.9%
8 88
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5544
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2052
37.0%
1 1065
19.2%
- 756
 
13.6%
2 569
 
10.3%
3 382
 
6.9%
9 192
 
3.5%
5 130
 
2.3%
4 125
 
2.3%
6 96
 
1.7%
7 89
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5544
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2052
37.0%
1 1065
19.2%
- 756
 
13.6%
2 569
 
10.3%
3 382
 
6.9%
9 192
 
3.5%
5 130
 
2.3%
4 125
 
2.3%
6 96
 
1.7%
7 89
 
1.6%

업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct13
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
한식
187 
중국식
19 
경양식
 
16
일식
 
13
분식
 
4
Other values (8)
 
13

Length

Max length8
Median length2
Mean length2.2103175
Min length2

Unique

Unique5 ?
Unique (%)2.0%

Sample

1st row한식
2nd row한식
3rd row한식
4th row경양식
5th row한식

Common Values

ValueCountFrequency (%)
한식 187
74.2%
중국식 19
 
7.5%
경양식 16
 
6.3%
일식 13
 
5.2%
분식 4
 
1.6%
기타 3
 
1.2%
복어취급 3
 
1.2%
뷔페식 2
 
0.8%
식육(숯불구이) 1
 
0.4%
회집 1
 
0.4%
Other values (3) 3
 
1.2%

Length

2024-05-04T06:36:47.926155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 187
74.2%
중국식 19
 
7.5%
경양식 16
 
6.3%
일식 13
 
5.2%
분식 4
 
1.6%
기타 3
 
1.2%
복어취급 3
 
1.2%
뷔페식 2
 
0.8%
식육(숯불구이 1
 
0.4%
회집 1
 
0.4%
Other values (3) 3
 
1.2%

주된음식
Text

MISSING 

Distinct74
Distinct (%)68.5%
Missing144
Missing (%)57.1%
Memory size2.1 KiB
2024-05-04T06:36:48.679757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10.5
Mean length3.537037
Min length2

Characters and Unicode

Total characters382
Distinct characters117
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

Unique61 ?
Unique (%)56.5%

Sample

1st row삼겹살
2nd row한정식
3rd row삼겹살
4th row장어구이
5th row한정식
ValueCountFrequency (%)
한정식 10
 
8.5%
등심 7
 
5.9%
설렁탕 5
 
4.2%
감자탕 4
 
3.4%
삼겹살 4
 
3.4%
곰탕 3
 
2.5%
중국요리 3
 
2.5%
갈비탕 3
 
2.5%
짬뽕 2
 
1.7%
생선구이 2
 
1.7%
Other values (69) 75
63.6%
2024-05-04T06:36:50.024714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 23
 
6.0%
식 18
 
4.7%
국 16
 
4.2%
한 14
 
3.7%
정 14
 
3.7%
리 10
 
2.6%
, 10
 
2.6%
10
 
2.6%
등 8
 
2.1%
구 8
 
2.1%
Other values (107) 251
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 362
94.8%
Other Punctuation 10
 
2.6%
Space Separator 10
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 23
 
6.4%
식 18
 
5.0%
국 16
 
4.4%
한 14
 
3.9%
정 14
 
3.9%
리 10
 
2.8%
등 8
 
2.2%
구 8
 
2.2%
밥 7
 
1.9%
수 7
 
1.9%
Other values (105) 237
65.5%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 362
94.8%
Common 20
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 23
 
6.4%
식 18
 
5.0%
국 16
 
4.4%
한 14
 
3.9%
정 14
 
3.9%
리 10
 
2.8%
등 8
 
2.2%
구 8
 
2.2%
밥 7
 
1.9%
수 7
 
1.9%
Other values (105) 237
65.5%
Common
ValueCountFrequency (%)
, 10
50.0%
10
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 362
94.8%
ASCII 20
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 23
 
6.4%
식 18
 
5.0%
국 16
 
4.4%
한 14
 
3.9%
정 14
 
3.9%
리 10
 
2.8%
등 8
 
2.2%
구 8
 
2.2%
밥 7
 
1.9%
수 7
 
1.9%
Other values (105) 237
65.5%
ASCII
ValueCountFrequency (%)
, 10
50.0%
10
50.0%

영업장면적(㎡)
Real number (ℝ)

Distinct238
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean228.55028
Minimum0
Maximum1839.21
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-04T06:36:50.641969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile63.244
Q1103.875
median152.75
Q3251.7825
95-th percentile649.5475
Maximum1839.21
Range1839.21
Interquartile range (IQR)147.9075

Descriptive statistics

Standard deviation235.91757
Coefficient of variation (CV)1.0322349
Kurtosis16.408346
Mean228.55028
Median Absolute Deviation (MAD)60.35
Skewness3.5525943
Sum57594.67
Variance55657.101
MonotonicityNot monotonic
2024-05-04T06:36:51.233255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
148.5 4
 
1.6%
165.0 3
 
1.2%
92.4 2
 
0.8%
187.21 2
 
0.8%
115.5 2
 
0.8%
86.4 2
 
0.8%
152.75 2
 
0.8%
155.0 2
 
0.8%
139.0 2
 
0.8%
82.5 2
 
0.8%
Other values (228) 229
90.9%
ValueCountFrequency (%)
0.0 1
0.4%
27.36 1
0.4%
38.88 1
0.4%
39.66 1
0.4%
42.34 1
0.4%
45.0 1
0.4%
47.95 1
0.4%
53.2 1
0.4%
53.69 1
0.4%
55.0 1
0.4%
ValueCountFrequency (%)
1839.21 1
0.4%
1639.55 1
0.4%
1350.62 1
0.4%
1159.74 1
0.4%
1100.1 1
0.4%
948.82 1
0.4%
907.1 1
0.4%
839.07 1
0.4%
788.08 1
0.4%
764.69 1
0.4%

행정동명
Categorical

Distinct16
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
서초제3동
49 
서초제2동
27 
서초제1동
24 
서초제4동
19 
양재제2동
19 
Other values (11)
114 

Length

Max length5
Median length5
Mean length4.781746
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양재제1동
2nd row서초제3동
3rd row방배제4동
4th row방배본동
5th row서초제1동

Common Values

ValueCountFrequency (%)
서초제3동 49
19.4%
서초제2동 27
10.7%
서초제1동 24
9.5%
서초제4동 19
 
7.5%
양재제2동 19
 
7.5%
양재제1동 17
 
6.7%
방배제4동 16
 
6.3%
방배본동 15
 
6.0%
반포제4동 12
 
4.8%
잠원동 12
 
4.8%
Other values (6) 42
16.7%

Length

2024-05-04T06:36:51.845674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서초제3동 49
19.4%
서초제2동 27
10.7%
서초제1동 24
9.5%
서초제4동 19
 
7.5%
양재제2동 19
 
7.5%
양재제1동 17
 
6.7%
방배제4동 16
 
6.3%
방배본동 15
 
6.0%
반포제4동 12
 
4.8%
잠원동 12
 
4.8%
Other values (6) 42
16.7%

급수시설구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
<NA>
132 
상수도전용
119 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.5238095
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 132
52.4%
상수도전용 119
47.2%
상수도(음용)지하수(주방용)겸용 1
 
0.4%

Length

2024-05-04T06:36:52.366798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T06:36:52.833131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 132
52.4%
상수도전용 119
47.2%
상수도(음용)지하수(주방용)겸용 1
 
0.4%

소재지전화번호
Text

MISSING 

Distinct166
Distinct (%)100.0%
Missing86
Missing (%)34.1%
Memory size2.1 KiB
2024-05-04T06:36:53.715418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.048193
Min length7

Characters and Unicode

Total characters1834
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)100.0%

Sample

1st row02 34738232
2nd row02 5859388
3rd row02 5348800
4th row02 583 5349
5th row02 34738261
ValueCountFrequency (%)
02 145
38.1%
537 4
 
1.0%
532 4
 
1.0%
521 4
 
1.0%
596 3
 
0.8%
581 3
 
0.8%
597 3
 
0.8%
535 3
 
0.8%
534 2
 
0.5%
585 2
 
0.5%
Other values (196) 208
54.6%
2024-05-04T06:36:55.216511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
16.8%
2 282
15.4%
0 266
14.5%
5 220
12.0%
3 154
8.4%
8 135
7.4%
9 110
 
6.0%
7 110
 
6.0%
4 106
 
5.8%
1 77
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1526
83.2%
Space Separator 308
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 282
18.5%
0 266
17.4%
5 220
14.4%
3 154
10.1%
8 135
8.8%
9 110
 
7.2%
7 110
 
7.2%
4 106
 
6.9%
1 77
 
5.0%
6 66
 
4.3%
Space Separator
ValueCountFrequency (%)
308
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1834
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
308
16.8%
2 282
15.4%
0 266
14.5%
5 220
12.0%
3 154
8.4%
8 135
7.4%
9 110
 
6.0%
7 110
 
6.0%
4 106
 
5.8%
1 77
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
16.8%
2 282
15.4%
0 266
14.5%
5 220
12.0%
3 154
8.4%
8 135
7.4%
9 110
 
6.0%
7 110
 
6.0%
4 106
 
5.8%
1 77
 
4.2%

Interactions

2024-05-04T06:36:31.748531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:23.377942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:25.515444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:27.795401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:29.567311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:32.050936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:23.730133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:25.906248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:28.193501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:29.938220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:32.385617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:24.192991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:26.253568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:28.552718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:30.400084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:32.741992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:24.651120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:26.805385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:28.835740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:31.059155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:33.092190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:25.097625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:27.273884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:29.198405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T06:36:31.411618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T06:36:55.997579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자업태명주된음식영업장면적(㎡)행정동명급수시설구분
지정년도1.0000.9220.9910.9980.0000.8920.1780.166NaN
지정번호0.9221.0000.8970.9220.0000.8430.0000.4820.497
신청일자0.9910.8971.0000.9980.3410.9200.0000.142NaN
지정일자0.9980.9220.9981.0000.0000.8920.1850.171NaN
업태명0.0000.0000.3410.0001.0001.0000.6030.3010.701
주된음식0.8920.8430.9200.8921.0001.0000.9200.9281.000
영업장면적(㎡)0.1780.0000.0000.1850.6030.9201.0000.3750.000
행정동명0.1660.4820.1420.1710.3010.9280.3751.0000.141
급수시설구분NaN0.497NaNNaN0.7011.0000.0000.1411.000
2024-05-04T06:36:56.573036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명행정동명급수시설구분
업태명1.0000.1100.521
행정동명0.1101.0000.098
급수시설구분0.5210.0981.000
2024-05-04T06:36:56.959522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자영업장면적(㎡)업태명행정동명급수시설구분
지정년도1.000-0.3550.9880.999-0.1810.0000.1120.000
지정번호-0.3551.000-0.352-0.351-0.0380.0000.2370.334
신청일자0.988-0.3521.0000.992-0.1840.0740.1110.000
지정일자0.999-0.3510.9921.000-0.1830.0000.1110.000
영업장면적(㎡)-0.181-0.038-0.184-0.1831.0000.2990.1540.000
업태명0.0000.0000.0740.0000.2991.0000.1100.521
행정동명0.1120.2370.1110.1110.1540.1101.0000.098
급수시설구분0.0000.3340.0000.0000.0000.5210.0981.000

Missing values

2024-05-04T06:36:33.632599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T06:36:34.376361image/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.
2024-05-04T06:36:34.795426image/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

시군구코드지정년도지정번호신청일자지정일자업소명소재지도로명소재지지번허가(신고)번호업태명주된음식영업장면적(㎡)행정동명급수시설구분소재지전화번호
03210000202362023083020231114소곰집 양재점서울특별시 서초구 남부순환로350길 38, 1층 (양재동)서울특별시 서초구 양재동 13번지 10호 1층3210000-101-2003-00419한식삼겹살141.9양재제1동상수도전용<NA>
13210000202372023090520231114낙천정서울특별시 서초구 효령로49길 19, (서초동,2층,3층)서울특별시 서초구 서초동 1531번지 3호 2층,3층3210000-101-2007-00441한식한정식299.96서초제3동상수도전용02 34738232
23210000202312023083120231114선화의 삼겹살 무한리필 방배역점서울특별시 서초구 효령로31길 7, 1층 (방배동)서울특별시 서초구 방배동 912번지 9호 1층3210000-101-1984-03480한식삼겹살130.93방배제4동상수도전용02 5859388
332100002023142023083120231114금빛서울특별시 서초구 방배중앙로29길 3, 2층 (방배동)서울특별시 서초구 방배동 761번지 2호 2층-2023210000-101-2014-00504경양식장어구이136.0방배본동<NA>02 5348800
43210000202342023083120231114담채서울특별시 서초구 서초중앙로20길 34-5, (서초동, 1층)서울특별시 서초구 서초동 1665번지 1호 1층3210000-101-2003-00026한식한정식175.77서초제1동상수도전용02 583 5349
532100002023112023082220231114장모사랑서울특별시 서초구 남부순환로350길 36, 프렌닥터 지하1층 101호 (양재동)서울특별시 서초구 양재동 13번지 9호 프렌닥터 지하1층 101호3210000-101-2013-00172한식한정식122.04양재제1동<NA>02 34738261
632100002023202023082920231114성덕서울특별시 서초구 서초중앙로 38, 지하1층 (서초동)서울특별시 서초구 서초동 1603번지 20호 지하1층3210000-101-2023-00176중국식딤섬116.96서초제1동<NA><NA>
732100002023152023083020231114포본PhoBon(양재점)서울특별시 서초구 강남대로27길 7-21, 102호 (양재동)서울특별시 서초구 양재동 67번지 7호 -1023210000-101-2014-00507기타쌀국수113.99양재제1동<NA><NA>
83210000202332023082220231114땅끝마을서울특별시 서초구 법원로2길 7-4, 동용빌딩 지하1층 101호,105호 (서초동)서울특별시 서초구 서초동 1712번지 2호 동용빌딩-1013210000-101-1996-13746한식한정식160.0서초제1동상수도전용02 537 0073
932100002023192023082520231114나주댁 부엌서울특별시 서초구 마방로10길 34-11, 1층 (양재동)서울특별시 서초구 양재동 269번지 4호3210000-101-2022-00226한식제철음식, 수제비45.0양재제1동<NA><NA>
시군구코드지정년도지정번호신청일자지정일자업소명소재지도로명소재지지번허가(신고)번호업태명주된음식영업장면적(㎡)행정동명급수시설구분소재지전화번호
242321000020031392003061820030718오발탄서울특별시 서초구 반포대로 154, 1,2,3층 (서초동)서울특별시 서초구 서초동 1720번지 1호 1,2,3층3210000-101-1999-14236한식양대창구이683.77서초제3동상수도전용02 5916657
243321000020032242003061820030718조가네 갑오징어 방배카페거리점서울특별시 서초구 방배중앙로 173, 1층 (방배동)서울특별시 서초구 방배동 768번지 13호 1층3210000-101-1992-04966한식국밥134.3방배본동상수도전용02 5364842
244321000020032912003061820030718한촌설렁탕서울특별시 서초구 동산로 87, (양재동)서울특별시 서초구 양재동 289번지 9호3210000-101-1998-13104한식설렁탕102.35양재제2동상수도전용02 5746767
245321000020031732003061820030718내고향본가서울특별시 서초구 나루터로 69, 샤르망 101호 (잠원동)서울특별시 서초구 잠원동 15번지 4호 샤르망3210000-101-1995-02625한식남도요리124.42잠원동상수도전용02 5406331
24632100002003752003061820030718서초버드나무집서울특별시 서초구 효령로 434, (서초동)서울특별시 서초구 서초동 1340번지 5호3210000-101-1985-05161한식갈비탕839.07서초제2동상수도전용02 34738354
247321000020031002003061820030718서초정육식당서울특별시 서초구 서초대로38길 51, (서초동)서울특별시 서초구 서초동 1503번지 19호3210000-101-1988-04336한식등심85.0서초제3동상수도전용02 5880290
24832100002003992003061820030718영변서울특별시 서초구 반포대로23길 22, 2층 (서초동, 영변빌딩)서울특별시 서초구 서초동 1503번지 13호 2층3210000-101-1993-09167일식회정식161.58서초제1동상수도전용02 5831123
24932100002003722003061820030718삼호복집서울특별시 서초구 강남대로51길 5, (서초동)서울특별시 서초구 서초동 1338번지 10호3210000-101-1987-05074복어취급복지리239.8서초제2동상수도전용02 542 7296
250321000020032842003061820030718(주)배나무골서울특별시 서초구 마방로2길 12, (양재동)서울특별시 서초구 양재동 241번지 3호3210000-101-1999-03985한식오리231.76양재제2동상수도전용02 5715252
251321000020031752003061820030718삼호복집서울특별시 서초구 강남대로99길 19, 용량빌딩 1층 (잠원동)서울특별시 서초구 잠원동 22번지 17호 용량빌딩 1층3210000-101-1987-04715복어취급복매운탕151.45잠원동상수도(음용)지하수(주방용)겸용02 5427296