Overview

Dataset statistics

Number of variables15
Number of observations326
Missing cells64
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.2 KiB
Average record size in memory126.4 B

Variable types

Categorical4
Numeric5
Text6

Dataset

Description시군구코드,지정년도,지정번호,신청일자,지정일자,업소명,소재지도로명,소재지지번,허가(신고)번호,업태명,주된음식,영업장면적(㎡),행정동명,급수시설구분,소재지전화번호
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-11449/S/1/datasetView.do

Alerts

시군구코드 has constant value ""Constant
행정동명 is highly overall correlated with 급수시설구분High correlation
급수시설구분 is highly overall correlated with 지정년도 and 6 other fieldsHigh correlation
업태명 is highly overall correlated with 급수시설구분High correlation
지정년도 is highly overall correlated with 신청일자 and 2 other fieldsHigh correlation
지정번호 is highly overall correlated with 급수시설구분High correlation
신청일자 is highly overall correlated with 지정년도 and 2 other fieldsHigh correlation
지정일자 is highly overall correlated with 지정년도 and 2 other fieldsHigh correlation
영업장면적(㎡) is highly overall correlated with 급수시설구분High correlation
업태명 is highly imbalanced (55.1%)Imbalance
주된음식 has 19 (5.8%) missing valuesMissing
소재지전화번호 has 45 (13.8%) missing valuesMissing

Reproduction

Analysis started2024-05-11 05:48:00.580949
Analysis finished2024-05-11 05:48:06.428364
Duration5.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
3230000
326 

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 326
100.0%

Length

2024-05-11T14:48:06.544988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:06.725946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 326
100.0%

지정년도
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.0368
Minimum2007
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-11T14:48:06.830794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007
Q12007
median2016
Q32019
95-th percentile2023
Maximum2023
Range16
Interquartile range (IQR)12

Descriptive statistics

Standard deviation5.7852753
Coefficient of variation (CV)0.0028724774
Kurtosis-1.5462337
Mean2014.0368
Median Absolute Deviation (MAD)6
Skewness-0.0043364793
Sum656576
Variance33.46941
MonotonicityDecreasing
2024-05-11T14:48:06.979249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2007 86
26.4%
2018 39
12.0%
2008 24
 
7.4%
2017 22
 
6.7%
2016 22
 
6.7%
2022 21
 
6.4%
2023 20
 
6.1%
2020 17
 
5.2%
2019 17
 
5.2%
2010 9
 
2.8%
Other values (7) 49
15.0%
ValueCountFrequency (%)
2007 86
26.4%
2008 24
 
7.4%
2009 9
 
2.8%
2010 9
 
2.8%
2011 4
 
1.2%
2012 8
 
2.5%
2013 4
 
1.2%
2014 8
 
2.5%
2015 7
 
2.1%
2016 22
 
6.7%
ValueCountFrequency (%)
2023 20
6.1%
2022 21
6.4%
2021 9
 
2.8%
2020 17
5.2%
2019 17
5.2%
2018 39
12.0%
2017 22
6.7%
2016 22
6.7%
2015 7
 
2.1%
2014 8
 
2.5%

지정번호
Real number (ℝ)

HIGH CORRELATION 

Distinct200
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean155.21779
Minimum1
Maximum355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-11T14:48:07.162808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q125.25
median170.5
Q3270.75
95-th percentile317.75
Maximum355
Range354
Interquartile range (IQR)245.5

Descriptive statistics

Standard deviation119.08517
Coefficient of variation (CV)0.76721343
Kurtosis-1.6511906
Mean155.21779
Median Absolute Deviation (MAD)117
Skewness0.0064263336
Sum50601
Variance14181.279
MonotonicityNot monotonic
2024-05-11T14:48:07.384238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 5
 
1.5%
15 5
 
1.5%
3 5
 
1.5%
2 5
 
1.5%
1 5
 
1.5%
6 4
 
1.2%
268 4
 
1.2%
11 4
 
1.2%
7 4
 
1.2%
5 4
 
1.2%
Other values (190) 281
86.2%
ValueCountFrequency (%)
1 5
1.5%
2 5
1.5%
3 5
1.5%
4 3
0.9%
5 4
1.2%
6 4
1.2%
7 4
1.2%
8 4
1.2%
9 3
0.9%
10 2
 
0.6%
ValueCountFrequency (%)
355 1
0.3%
352 1
0.3%
346 1
0.3%
344 1
0.3%
342 1
0.3%
337 1
0.3%
330 1
0.3%
329 1
0.3%
326 1
0.3%
323 1
0.3%

신청일자
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20141098
Minimum20070928
Maximum20230915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-11T14:48:07.584106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070928
5-th percentile20071016
Q120071019
median20161031
Q320191018
95-th percentile20230915
Maximum20230915
Range159987
Interquartile range (IQR)119999

Descriptive statistics

Standard deviation58142.475
Coefficient of variation (CV)0.002886758
Kurtosis-1.5569593
Mean20141098
Median Absolute Deviation (MAD)60098.5
Skewness-0.0021928214
Sum6.565998 × 109
Variance3.3805474 × 109
MonotonicityNot monotonic
2024-05-11T14:48:07.740058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20071016 67
20.6%
20181015 39
12.0%
20081103 23
 
7.1%
20161031 22
 
6.7%
20171010 22
 
6.7%
20230915 20
 
6.1%
20201109 17
 
5.2%
20191018 17
 
5.2%
20070928 8
 
2.5%
20071019 8
 
2.5%
Other values (23) 83
25.5%
ValueCountFrequency (%)
20070928 8
 
2.5%
20071016 67
20.6%
20071018 1
 
0.3%
20071019 8
 
2.5%
20071022 5
 
1.5%
20081103 23
 
7.1%
20081110 1
 
0.3%
20091013 5
 
1.5%
20091102 1
 
0.3%
20091109 1
 
0.3%
ValueCountFrequency (%)
20230915 20
6.1%
20221207 8
 
2.5%
20221202 2
 
0.6%
20221130 3
 
0.9%
20221129 8
 
2.5%
20211201 3
 
0.9%
20211130 1
 
0.3%
20211126 1
 
0.3%
20211118 4
 
1.2%
20201109 17
5.2%

지정일자
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20141488
Minimum20071019
Maximum20231107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-11T14:48:07.890538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20071019
5-th percentile20071019
Q120071019
median20161130
Q320191211
95-th percentile20231107
Maximum20231107
Range160088
Interquartile range (IQR)120192

Descriptive statistics

Standard deviation57913.072
Coefficient of variation (CV)0.0028753124
Kurtosis-1.546816
Mean20141488
Median Absolute Deviation (MAD)60096
Skewness-0.0052144311
Sum6.5661252 × 109
Variance3.3539239 × 109
MonotonicityDecreasing
2024-05-11T14:48:08.034183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
20071019 85
26.1%
20181112 39
12.0%
20081103 24
 
7.4%
20171214 22
 
6.7%
20161130 22
 
6.7%
20221226 21
 
6.4%
20231107 20
 
6.1%
20201222 17
 
5.2%
20191211 17
 
5.2%
20211221 9
 
2.8%
Other values (9) 50
15.3%
ValueCountFrequency (%)
20071019 85
26.1%
20071219 1
 
0.3%
20081103 24
 
7.4%
20091113 8
 
2.5%
20091228 1
 
0.3%
20100910 9
 
2.8%
20111116 4
 
1.2%
20121217 8
 
2.5%
20131223 4
 
1.2%
20141219 8
 
2.5%
ValueCountFrequency (%)
20231107 20
6.1%
20221226 21
6.4%
20211221 9
 
2.8%
20201222 17
5.2%
20191211 17
5.2%
20181112 39
12.0%
20171214 22
6.7%
20161130 22
6.7%
20151228 7
 
2.1%
20141219 8
 
2.5%

업소명
Text

Distinct308
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-11T14:48:08.292826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length7.1288344
Min length2

Characters and Unicode

Total characters2324
Distinct characters425
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)89.3%

Sample

1st row동래정 송파가락점
2nd row하늘호수보쌈족발
3rd row진대감 16가락
4th row래향
5th row황규복, 김춘자의 해주냉면
ValueCountFrequency (%)
방이점 10
 
2.0%
잠실점 6
 
1.2%
주식회사 5
 
1.0%
가든파이브점 5
 
1.0%
명륜진사갈비 4
 
0.8%
현대시티몰 3
 
0.6%
롯데월드몰 3
 
0.6%
숯불돼지 3
 
0.6%
송파 3
 
0.6%
올림픽공원점 3
 
0.6%
Other values (416) 452
90.9%
2024-05-11T14:48:08.776125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
171
 
7.4%
점 72
 
3.1%
이 45
 
1.9%
가 38
 
1.6%
주 36
 
1.5%
) 27
 
1.2%
( 27
 
1.2%
한 27
 
1.2%
리 25
 
1.1%
정 24
 
1.0%
Other values (415) 1832
78.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2017
86.8%
Space Separator 171
 
7.4%
Lowercase Letter 28
 
1.2%
Uppercase Letter 28
 
1.2%
Close Punctuation 27
 
1.2%
Open Punctuation 27
 
1.2%
Decimal Number 18
 
0.8%
Other Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 72
 
3.6%
이 45
 
2.2%
가 38
 
1.9%
주 36
 
1.8%
한 27
 
1.3%
리 25
 
1.2%
정 24
 
1.2%
식 24
 
1.2%
동 23
 
1.1%
사 23
 
1.1%
Other values (367) 1680
83.3%
Uppercase Letter
ValueCountFrequency (%)
L 5
17.9%
I 3
10.7%
H 2
 
7.1%
M 2
 
7.1%
U 2
 
7.1%
C 2
 
7.1%
B 2
 
7.1%
S 1
 
3.6%
F 1
 
3.6%
G 1
 
3.6%
Other values (7) 7
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 6
21.4%
u 3
10.7%
i 3
10.7%
r 2
 
7.1%
f 2
 
7.1%
o 2
 
7.1%
l 1
 
3.6%
y 1
 
3.6%
t 1
 
3.6%
s 1
 
3.6%
Other values (6) 6
21.4%
Decimal Number
ValueCountFrequency (%)
1 4
22.2%
4 3
16.7%
2 3
16.7%
0 2
11.1%
9 2
11.1%
5 1
 
5.6%
6 1
 
5.6%
7 1
 
5.6%
3 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 2
25.0%
& 2
25.0%
Space Separator
ValueCountFrequency (%)
171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2017
86.8%
Common 251
 
10.8%
Latin 56
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 72
 
3.6%
이 45
 
2.2%
가 38
 
1.9%
주 36
 
1.8%
한 27
 
1.3%
리 25
 
1.2%
정 24
 
1.2%
식 24
 
1.2%
동 23
 
1.1%
사 23
 
1.1%
Other values (367) 1680
83.3%
Latin
ValueCountFrequency (%)
e 6
 
10.7%
L 5
 
8.9%
u 3
 
5.4%
I 3
 
5.4%
i 3
 
5.4%
H 2
 
3.6%
M 2
 
3.6%
U 2
 
3.6%
r 2
 
3.6%
f 2
 
3.6%
Other values (23) 26
46.4%
Common
ValueCountFrequency (%)
171
68.1%
) 27
 
10.8%
( 27
 
10.8%
1 4
 
1.6%
. 4
 
1.6%
4 3
 
1.2%
2 3
 
1.2%
0 2
 
0.8%
9 2
 
0.8%
, 2
 
0.8%
Other values (5) 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2017
86.8%
ASCII 307
 
13.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
171
55.7%
) 27
 
8.8%
( 27
 
8.8%
e 6
 
2.0%
L 5
 
1.6%
1 4
 
1.3%
. 4
 
1.3%
u 3
 
1.0%
I 3
 
1.0%
4 3
 
1.0%
Other values (38) 54
 
17.6%
Hangul
ValueCountFrequency (%)
점 72
 
3.6%
이 45
 
2.2%
가 38
 
1.9%
주 36
 
1.8%
한 27
 
1.3%
리 25
 
1.2%
정 24
 
1.2%
식 24
 
1.2%
동 23
 
1.1%
사 23
 
1.1%
Other values (367) 1680
83.3%

소재지도로명
Text

Distinct301
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-11T14:48:09.165802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length49
Mean length33.779141
Min length23

Characters and Unicode

Total characters11012
Distinct characters214
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)85.3%

Sample

1st row서울특별시 송파구 양재대로62길 47, 지상1층 (가락동)
2nd row서울특별시 송파구 중대로 306, 동현빌딩 1층 (오금동)
3rd row서울특별시 송파구 중대로9길 34, (가락동,지상1층)
4th row서울특별시 송파구 중대로25길 20, 1층 (오금동)
5th row서울특별시 송파구 백제고분로7길 8-16, 남광빌딩 1층 102호 (잠실동)
ValueCountFrequency (%)
서울특별시 326
 
15.6%
송파구 326
 
15.6%
지상1층 78
 
3.7%
1층 69
 
3.3%
방이동 59
 
2.8%
문정동 42
 
2.0%
잠실동 39
 
1.9%
가락동 36
 
1.7%
올림픽로 33
 
1.6%
석촌동 29
 
1.4%
Other values (462) 1056
50.5%
2024-05-11T14:48:09.997439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1770
 
16.1%
1 531
 
4.8%
, 468
 
4.2%
파 400
 
3.6%
송 388
 
3.5%
동 375
 
3.4%
시 341
 
3.1%
) 330
 
3.0%
( 330
 
3.0%
울 329
 
3.0%
Other values (204) 5750
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6394
58.1%
Space Separator 1770
 
16.1%
Decimal Number 1624
 
14.7%
Other Punctuation 470
 
4.3%
Close Punctuation 330
 
3.0%
Open Punctuation 330
 
3.0%
Dash Punctuation 45
 
0.4%
Uppercase Letter 42
 
0.4%
Lowercase Letter 4
 
< 0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 400
 
6.3%
송 388
 
6.1%
동 375
 
5.9%
시 341
 
5.3%
울 329
 
5.1%
구 328
 
5.1%
로 327
 
5.1%
서 327
 
5.1%
별 326
 
5.1%
특 326
 
5.1%
Other values (171) 2927
45.8%
Uppercase Letter
ValueCountFrequency (%)
A 17
40.5%
B 10
23.8%
G 5
 
11.9%
T 2
 
4.8%
C 2
 
4.8%
K 1
 
2.4%
N 1
 
2.4%
S 1
 
2.4%
E 1
 
2.4%
F 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 531
32.7%
2 246
15.1%
0 161
 
9.9%
3 157
 
9.7%
6 110
 
6.8%
4 105
 
6.5%
5 91
 
5.6%
9 77
 
4.7%
7 75
 
4.6%
8 71
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
u 1
25.0%
i 1
25.0%
t 1
25.0%
e 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 468
99.6%
. 1
 
0.2%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1770
100.0%
Close Punctuation
ValueCountFrequency (%)
) 330
100.0%
Open Punctuation
ValueCountFrequency (%)
( 330
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6394
58.1%
Common 4572
41.5%
Latin 46
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 400
 
6.3%
송 388
 
6.1%
동 375
 
5.9%
시 341
 
5.3%
울 329
 
5.1%
구 328
 
5.1%
로 327
 
5.1%
서 327
 
5.1%
별 326
 
5.1%
특 326
 
5.1%
Other values (171) 2927
45.8%
Common
ValueCountFrequency (%)
1770
38.7%
1 531
 
11.6%
, 468
 
10.2%
) 330
 
7.2%
( 330
 
7.2%
2 246
 
5.4%
0 161
 
3.5%
3 157
 
3.4%
6 110
 
2.4%
4 105
 
2.3%
Other values (8) 364
 
8.0%
Latin
ValueCountFrequency (%)
A 17
37.0%
B 10
21.7%
G 5
 
10.9%
T 2
 
4.3%
C 2
 
4.3%
K 1
 
2.2%
N 1
 
2.2%
S 1
 
2.2%
u 1
 
2.2%
i 1
 
2.2%
Other values (5) 5
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6394
58.1%
ASCII 4618
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1770
38.3%
1 531
 
11.5%
, 468
 
10.1%
) 330
 
7.1%
( 330
 
7.1%
2 246
 
5.3%
0 161
 
3.5%
3 157
 
3.4%
6 110
 
2.4%
4 105
 
2.3%
Other values (23) 410
 
8.9%
Hangul
ValueCountFrequency (%)
파 400
 
6.3%
송 388
 
6.1%
동 375
 
5.9%
시 341
 
5.3%
울 329
 
5.1%
구 328
 
5.1%
로 327
 
5.1%
서 327
 
5.1%
별 326
 
5.1%
특 326
 
5.1%
Other values (171) 2927
45.8%

소재지지번
Text

Distinct278
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-11T14:48:10.337771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length28.064417
Min length20

Characters and Unicode

Total characters9149
Distinct characters192
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique247 ?
Unique (%)75.8%

Sample

1st row서울특별시 송파구 가락동 76번지
2nd row서울특별시 송파구 오금동 89번지 2호 동현빌딩
3rd row서울특별시 송파구 가락동 83번지 7호 지상1층
4th row서울특별시 송파구 오금동 46번지 9호 1층
5th row서울특별시 송파구 잠실동 195번지 9호 남광빌딩
ValueCountFrequency (%)
서울특별시 326
17.9%
송파구 326
17.9%
지상1층 74
 
4.1%
방이동 71
 
3.9%
문정동 43
 
2.4%
가락동 42
 
2.3%
잠실동 41
 
2.3%
1호 38
 
2.1%
석촌동 30
 
1.6%
3호 28
 
1.5%
Other values (308) 803
44.1%
2024-05-11T14:48:10.916658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2261
24.7%
지 437
 
4.8%
1 388
 
4.2%
파 361
 
3.9%
송 355
 
3.9%
동 341
 
3.7%
시 334
 
3.7%
울 327
 
3.6%
서 327
 
3.6%
구 326
 
3.6%
Other values (182) 3692
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5443
59.5%
Space Separator 2261
24.7%
Decimal Number 1373
 
15.0%
Other Punctuation 29
 
0.3%
Uppercase Letter 13
 
0.1%
Dash Punctuation 10
 
0.1%
Close Punctuation 7
 
0.1%
Open Punctuation 7
 
0.1%
Lowercase Letter 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 437
 
8.0%
파 361
 
6.6%
송 355
 
6.5%
동 341
 
6.3%
시 334
 
6.1%
울 327
 
6.0%
서 327
 
6.0%
구 326
 
6.0%
별 326
 
6.0%
번 326
 
6.0%
Other values (152) 1983
36.4%
Decimal Number
ValueCountFrequency (%)
1 388
28.3%
2 196
14.3%
4 123
 
9.0%
3 120
 
8.7%
6 109
 
7.9%
0 98
 
7.1%
5 94
 
6.8%
7 84
 
6.1%
9 81
 
5.9%
8 80
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
23.1%
A 3
23.1%
C 2
15.4%
T 1
 
7.7%
K 1
 
7.7%
F 1
 
7.7%
S 1
 
7.7%
N 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
t 1
25.0%
i 1
25.0%
u 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 27
93.1%
. 1
 
3.4%
& 1
 
3.4%
Space Separator
ValueCountFrequency (%)
2261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5443
59.5%
Common 3689
40.3%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 437
 
8.0%
파 361
 
6.6%
송 355
 
6.5%
동 341
 
6.3%
시 334
 
6.1%
울 327
 
6.0%
서 327
 
6.0%
구 326
 
6.0%
별 326
 
6.0%
번 326
 
6.0%
Other values (152) 1983
36.4%
Common
ValueCountFrequency (%)
2261
61.3%
1 388
 
10.5%
2 196
 
5.3%
4 123
 
3.3%
3 120
 
3.3%
6 109
 
3.0%
0 98
 
2.7%
5 94
 
2.5%
7 84
 
2.3%
9 81
 
2.2%
Other values (8) 135
 
3.7%
Latin
ValueCountFrequency (%)
B 3
17.6%
A 3
17.6%
C 2
11.8%
T 1
 
5.9%
K 1
 
5.9%
F 1
 
5.9%
e 1
 
5.9%
t 1
 
5.9%
i 1
 
5.9%
u 1
 
5.9%
Other values (2) 2
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5443
59.5%
ASCII 3706
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2261
61.0%
1 388
 
10.5%
2 196
 
5.3%
4 123
 
3.3%
3 120
 
3.2%
6 109
 
2.9%
0 98
 
2.6%
5 94
 
2.5%
7 84
 
2.3%
9 81
 
2.2%
Other values (20) 152
 
4.1%
Hangul
ValueCountFrequency (%)
지 437
 
8.0%
파 361
 
6.6%
송 355
 
6.5%
동 341
 
6.3%
시 334
 
6.1%
울 327
 
6.0%
서 327
 
6.0%
구 326
 
6.0%
별 326
 
6.0%
번 326
 
6.0%
Other values (152) 1983
36.4%

허가(신고)번호
Text

Distinct308
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2024-05-11T14:48:11.276233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7172
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

Unique291 ?
Unique (%)89.3%

Sample

1st row3230000-101-1995-07899
2nd row3230000-101-2018-00889
3rd row3230000-101-2007-00385
4th row3230000-101-2015-00515
5th row3230000-101-2019-00019
ValueCountFrequency (%)
3230000-101-1987-14236 3
 
0.9%
3230000-101-1986-08020 2
 
0.6%
3230000-101-2006-00541 2
 
0.6%
3230000-101-2004-00008 2
 
0.6%
3230000-101-2005-00117 2
 
0.6%
3230000-101-1999-00776 2
 
0.6%
3230000-101-1996-11075 2
 
0.6%
3230000-101-2003-00247 2
 
0.6%
3230000-101-1987-08039 2
 
0.6%
3230000-101-1988-07957 2
 
0.6%
Other values (298) 305
93.6%
2024-05-11T14:48:11.818554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2605
36.3%
1 1047
14.6%
- 978
 
13.6%
3 818
 
11.4%
2 708
 
9.9%
9 256
 
3.6%
7 177
 
2.5%
8 163
 
2.3%
5 150
 
2.1%
4 140
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6194
86.4%
Dash Punctuation 978
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2605
42.1%
1 1047
16.9%
3 818
 
13.2%
2 708
 
11.4%
9 256
 
4.1%
7 177
 
2.9%
8 163
 
2.6%
5 150
 
2.4%
4 140
 
2.3%
6 130
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 978
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2605
36.3%
1 1047
14.6%
- 978
 
13.6%
3 818
 
11.4%
2 708
 
9.9%
9 256
 
3.6%
7 177
 
2.5%
8 163
 
2.3%
5 150
 
2.1%
4 140
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2605
36.3%
1 1047
14.6%
- 978
 
13.6%
3 818
 
11.4%
2 708
 
9.9%
9 256
 
3.6%
7 177
 
2.5%
8 163
 
2.3%
5 150
 
2.1%
4 140
 
2.0%

업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
한식
227 
일식
27 
기타
23 
경양식
 
16
중국식
 
13
Other values (10)
 
20

Length

Max length15
Median length2
Mean length2.2116564
Min length2

Unique

Unique6 ?
Unique (%)1.8%

Sample

1st row한식
2nd row기타
3rd row일식
4th row중국식
5th row한식

Common Values

ValueCountFrequency (%)
한식 227
69.6%
일식 27
 
8.3%
기타 23
 
7.1%
경양식 16
 
4.9%
중국식 13
 
4.0%
분식 7
 
2.1%
뷔페식 3
 
0.9%
호프/통닭 2
 
0.6%
공공기관 2
 
0.6%
통닭(치킨) 1
 
0.3%
Other values (5) 5
 
1.5%

Length

2024-05-11T14:48:12.144198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 227
69.6%
일식 27
 
8.3%
기타 23
 
7.1%
경양식 16
 
4.9%
중국식 13
 
4.0%
분식 7
 
2.1%
뷔페식 3
 
0.9%
호프/통닭 2
 
0.6%
공공기관 2
 
0.6%
통닭(치킨 1
 
0.3%
Other values (5) 5
 
1.5%

주된음식
Text

MISSING 

Distinct205
Distinct (%)66.8%
Missing19
Missing (%)5.8%
Memory size2.7 KiB
2024-05-11T14:48:12.596344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length4.4136808
Min length1

Characters and Unicode

Total characters1355
Distinct characters188
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

Unique162 ?
Unique (%)52.8%

Sample

1st row삼겹살
2nd row보쌈,족발
3rd row차돌삼합
4th row짜장면, 짬뽕
5th row냉면
ValueCountFrequency (%)
삼겹살 14
 
4.0%
돼지갈비 13
 
3.7%
회 9
 
2.5%
설렁탕 8
 
2.3%
냉면 7
 
2.0%
갈비 6
 
1.7%
추어탕 6
 
1.7%
쌀국수 5
 
1.4%
고기구이 5
 
1.4%
부대찌개 5
 
1.4%
Other values (195) 275
77.9%
2024-05-11T14:48:13.259982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 83
 
6.1%
탕 49
 
3.6%
46
 
3.4%
비 40
 
3.0%
갈 36
 
2.7%
이 35
 
2.6%
구 33
 
2.4%
지 31
 
2.3%
스 29
 
2.1%
국 28
 
2.1%
Other values (178) 945
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1220
90.0%
Other Punctuation 85
 
6.3%
Space Separator 46
 
3.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 49
 
4.0%
비 40
 
3.3%
갈 36
 
3.0%
이 35
 
2.9%
구 33
 
2.7%
지 31
 
2.5%
스 29
 
2.4%
국 28
 
2.3%
기 27
 
2.2%
삼 26
 
2.1%
Other values (173) 886
72.6%
Other Punctuation
ValueCountFrequency (%)
, 83
97.6%
. 2
 
2.4%
Space Separator
ValueCountFrequency (%)
46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1220
90.0%
Common 135
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 49
 
4.0%
비 40
 
3.3%
갈 36
 
3.0%
이 35
 
2.9%
구 33
 
2.7%
지 31
 
2.5%
스 29
 
2.4%
국 28
 
2.3%
기 27
 
2.2%
삼 26
 
2.1%
Other values (173) 886
72.6%
Common
ValueCountFrequency (%)
, 83
61.5%
46
34.1%
. 2
 
1.5%
( 2
 
1.5%
) 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1220
90.0%
ASCII 135
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 83
61.5%
46
34.1%
. 2
 
1.5%
( 2
 
1.5%
) 2
 
1.5%
Hangul
ValueCountFrequency (%)
탕 49
 
4.0%
비 40
 
3.3%
갈 36
 
3.0%
이 35
 
2.9%
구 33
 
2.7%
지 31
 
2.5%
스 29
 
2.4%
국 28
 
2.3%
기 27
 
2.2%
삼 26
 
2.1%
Other values (173) 886
72.6%

영업장면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct282
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean202.29202
Minimum0
Maximum3261.23
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2024-05-11T14:48:13.486491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile50.04
Q196.4
median132
Q3212.6625
95-th percentile523.23
Maximum3261.23
Range3261.23
Interquartile range (IQR)116.2625

Descriptive statistics

Standard deviation282.66615
Coefficient of variation (CV)1.3973173
Kurtosis65.450821
Mean202.29202
Median Absolute Deviation (MAD)47.975
Skewness7.1139548
Sum65947.2
Variance79900.154
MonotonicityNot monotonic
2024-05-11T14:48:13.724365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.0 7
 
2.1%
132.0 3
 
0.9%
279.55 3
 
0.9%
120.0 3
 
0.9%
110.0 3
 
0.9%
82.5 3
 
0.9%
129.91 2
 
0.6%
163.8 2
 
0.6%
56.1 2
 
0.6%
33.54 2
 
0.6%
Other values (272) 296
90.8%
ValueCountFrequency (%)
0.0 1
0.3%
23.0 1
0.3%
30.0 1
0.3%
32.0 1
0.3%
32.01 1
0.3%
32.39 1
0.3%
33.0 1
0.3%
33.54 2
0.6%
39.8 1
0.3%
40.87 1
0.3%
ValueCountFrequency (%)
3261.23 1
0.3%
2815.37 1
0.3%
1334.06 2
0.6%
1193.39 1
0.3%
902.52 1
0.3%
853.62 1
0.3%
843.25 1
0.3%
806.59 2
0.6%
610.0 2
0.6%
561.36 1
0.3%

행정동명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
방이1동
37 
문정1동
35 
잠실본동
33 
방이2동
33 
가락본동
32 
Other values (19)
156 

Length

Max length4
Median length4
Mean length3.7944785
Min length3

Unique

Unique3 ?
Unique (%)0.9%

Sample

1st row가락본동
2nd row오금동
3rd row가락본동
4th row오금동
5th row잠실본동

Common Values

ValueCountFrequency (%)
방이1동 37
11.3%
문정1동 35
10.7%
잠실본동 33
10.1%
방이2동 33
10.1%
가락본동 32
9.8%
석촌동 30
9.2%
오금동 21
 
6.4%
송파1동 17
 
5.2%
삼전동 14
 
4.3%
잠실4동 12
 
3.7%
Other values (14) 62
19.0%

Length

2024-05-11T14:48:13.962781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
방이1동 37
11.3%
문정1동 35
10.7%
잠실본동 33
10.1%
방이2동 33
10.1%
가락본동 32
9.8%
석촌동 30
9.2%
오금동 21
 
6.4%
송파1동 17
 
5.2%
삼전동 14
 
4.3%
잠실4동 12
 
3.7%
Other values (14) 62
19.0%

급수시설구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
<NA>
228 
상수도전용
98 

Length

Max length5
Median length4
Mean length4.3006135
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 228
69.9%
상수도전용 98
30.1%

Length

2024-05-11T14:48:14.651901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:48:14.802372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
69.9%
상수도전용 98
30.1%

소재지전화번호
Text

MISSING 

Distinct262
Distinct (%)93.2%
Missing45
Missing (%)13.8%
Memory size2.7 KiB
2024-05-11T14:48:15.183845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.185053
Min length2

Characters and Unicode

Total characters2862
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

Unique244 ?
Unique (%)86.8%

Sample

1st row02 4049825
2nd row02 4247192
3rd row02 478 5194
4th row02 4095551
5th row02
ValueCountFrequency (%)
02 220
42.5%
417 4
 
0.8%
4180003 3
 
0.6%
0234310607 2
 
0.4%
4043227 2
 
0.4%
423 2
 
0.4%
4143611 2
 
0.4%
425 2
 
0.4%
4209704 2
 
0.4%
4124218 2
 
0.4%
Other values (264) 277
53.5%
2024-05-11T14:48:15.804333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 588
20.5%
0 518
18.1%
4 344
12.0%
268
9.4%
1 260
9.1%
3 222
 
7.8%
8 152
 
5.3%
7 144
 
5.0%
6 131
 
4.6%
5 128
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2594
90.6%
Space Separator 268
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 588
22.7%
0 518
20.0%
4 344
13.3%
1 260
10.0%
3 222
 
8.6%
8 152
 
5.9%
7 144
 
5.6%
6 131
 
5.1%
5 128
 
4.9%
9 107
 
4.1%
Space Separator
ValueCountFrequency (%)
268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2862
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 588
20.5%
0 518
18.1%
4 344
12.0%
268
9.4%
1 260
9.1%
3 222
 
7.8%
8 152
 
5.3%
7 144
 
5.0%
6 131
 
4.6%
5 128
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2862
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 588
20.5%
0 518
18.1%
4 344
12.0%
268
9.4%
1 260
9.1%
3 222
 
7.8%
8 152
 
5.3%
7 144
 
5.0%
6 131
 
4.6%
5 128
 
4.5%

Interactions

2024-05-11T14:48:04.919343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:01.649597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.352195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:03.433954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.152142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:05.083510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:01.793083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.496703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:03.569014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.295050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:05.254296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:01.910632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.680160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:03.707265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.449816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:05.388066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.035503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.884140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:03.860024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.612391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:05.536472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:02.198097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:03.309143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.024689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:48:04.777813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:48:16.006871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자업태명영업장면적(㎡)행정동명
지정년도1.0000.9150.9981.0000.1650.1610.575
지정번호0.9151.0000.8410.9030.0000.0000.637
신청일자0.9980.8411.0001.0000.0000.0000.546
지정일자1.0000.9031.0001.0000.1010.1520.565
업태명0.1650.0000.0000.1011.0000.5690.000
영업장면적(㎡)0.1610.0000.0000.1520.5691.0000.576
행정동명0.5750.6370.5460.5650.0000.5761.000
2024-05-11T14:48:16.194128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명급수시설구분업태명
행정동명1.0001.0000.000
급수시설구분1.0001.0001.000
업태명0.0001.0001.000
2024-05-11T14:48:16.344808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정년도지정번호신청일자지정일자영업장면적(㎡)업태명행정동명급수시설구분
지정년도1.000-0.2870.9941.000-0.1330.0320.2401.000
지정번호-0.2871.000-0.258-0.2840.1710.0000.2861.000
신청일자0.994-0.2581.0000.994-0.1410.0000.2311.000
지정일자1.000-0.2840.9941.000-0.1330.0000.2371.000
영업장면적(㎡)-0.1330.171-0.141-0.1331.0000.2960.2821.000
업태명0.0320.0000.0000.0000.2961.0000.0001.000
행정동명0.2400.2860.2310.2370.2820.0001.0001.000
급수시설구분1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-11T14:48:05.741804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:48:06.101727image/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.
2024-05-11T14:48:06.318304image/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
03230000202352023091520231107동래정 송파가락점서울특별시 송파구 양재대로62길 47, 지상1층 (가락동)서울특별시 송파구 가락동 76번지3230000-101-1995-07899한식삼겹살99.18가락본동상수도전용02 4049825
132300002023112023091520231107하늘호수보쌈족발서울특별시 송파구 중대로 306, 동현빌딩 1층 (오금동)서울특별시 송파구 오금동 89번지 2호 동현빌딩3230000-101-2018-00889기타보쌈,족발121.18오금동<NA><NA>
23230000202342023091520231107진대감 16가락서울특별시 송파구 중대로9길 34, (가락동,지상1층)서울특별시 송파구 가락동 83번지 7호 지상1층3230000-101-2007-00385일식차돌삼합146.6가락본동<NA><NA>
33230000202382023091520231107래향서울특별시 송파구 중대로25길 20, 1층 (오금동)서울특별시 송파구 오금동 46번지 9호 1층3230000-101-2015-00515중국식짜장면, 짬뽕157.28오금동<NA><NA>
432300002023142023091520231107황규복, 김춘자의 해주냉면서울특별시 송파구 백제고분로7길 8-16, 남광빌딩 1층 102호 (잠실동)서울특별시 송파구 잠실동 195번지 9호 남광빌딩3230000-101-2019-00019한식냉면105.6잠실본동<NA>02 4247192
532300002023182023091520231107청진동해장국서울특별시 송파구 풍성로 77, C동 지상1층 (풍납동)서울특별시 송파구 풍납동 497번지 C 지상1층3230000-101-2010-00283한식해장국96.0풍납1동<NA>02 478 5194
63230000202322023091520231107완도산회 특급포차 가락본점서울특별시 송파구 중대로9길 42, 지상1층 (가락동)서울특별시 송파구 가락동 83번지 10호 지상1층3230000-101-2013-00406한식회92.56가락본동<NA><NA>
732300002023102023091520231107나고야서울특별시 송파구 중대로25길 10, (오금동)서울특별시 송파구 오금동 48번지 11호3230000-101-2001-16908일식회115.0오금동<NA>02 4095551
83230000202312023091520231107완도산회포장마차서울특별시 송파구 백제고분로41길 10, (송파동)서울특별시 송파구 송파동 22번지 2호3230000-101-2002-17444한식회99.0송파1동<NA>02
93230000202362023091520231107소풍서울특별시 송파구 마천로 250, 1층 3호 (거여동)서울특별시 송파구 거여동 1번지 1호3230000-101-2019-00220한식한정식232.01거여1동<NA><NA>
시군구코드지정년도지정번호신청일자지정일자업소명소재지도로명소재지지번허가(신고)번호업태명주된음식영업장면적(㎡)행정동명급수시설구분소재지전화번호
316323000020072682007101620071019동경서울특별시 송파구 양재대로 1164, 지상2층 (오금동)서울특별시 송파구 오금동 1번지 지상2층3230000-101-2003-00160한식샤브샤브149.17오금동<NA>02 4040036
3173230000200712007092820071019발리서울특별시 송파구 동남로 133, (가락동)서울특별시 송파구 가락동 108번지 8호3230000-101-1995-08572경양식파스타273.6가락본동상수도전용0234010770
318323000020071852007101620071019영동족발 방이점서울특별시 송파구 오금로13길 3-20, 지상1층 (방이동)서울특별시 송파구 방이동 64번지 3호 지상1층3230000-101-1985-07955한식낙지해물99.12방이2동상수도전용02 4170355
319323000020072562007101620071019필녀의한정식&백번가코다리서울특별시 송파구 동남로 308, 지상2,3층 (오금동)서울특별시 송파구 오금동 129번지 24호 지상2,3층3230000-101-2002-17438한식한정식400.0오금동<NA>02 4005560
320323000020071232007101620071019샛집남원추어탕서울특별시 송파구 오금로11길 7-12, (방이동)서울특별시 송파구 방이동 24번지 1호3230000-101-1991-12953한식추어탕93.67방이2동상수도전용02 4218163
32132300002007782007101620071019가야촌오리주물럭서울특별시 송파구 오금로 533, (거여동)서울특별시 송파구 거여동 35번지 5호3230000-101-1996-11066한식오리주물럭148.36거여2동상수도전용02 4135292
322323000020073212007101920071019마싯소서울특별시 송파구 오금로11길 49, 지상1층 101호 (방이동, 보보스타워)서울특별시 송파구 방이동 47번지 13호 보보스타워 1층-1013230000-101-2006-00394한식소고기211.18방이2동<NA>02 4254200
323323000020072892007101620071019깐부치킨서울특별시 송파구 백제고분로7길 19, (잠실동)서울특별시 송파구 잠실동 179번지 3호3230000-101-1987-08039한식해물탕114.62잠실본동상수도전용02 4188181
324323000020072382007101620071019더컨벤션 교통회관서울특별시 송파구 올림픽로 319, (신천동)서울특별시 송파구 신천동 11번지 7호3230000-101-1986-07779뷔페식부페1334.06잠실6동상수도전용02 4143611
325323000020071982007101620071019돈족골서울특별시 송파구 삼학사로 66, (석촌동)서울특별시 송파구 석촌동 14번지 6호3230000-101-1999-00573한식삼겹살163.8석촌동상수도전용02 4165252