Overview

Dataset statistics

Number of variables44
Number of observations9264
Missing cells85357
Missing cells (%)20.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 MiB
Average record size in memory375.0 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric4
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18448/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (57.8%)Imbalance
영업상태명 is highly imbalanced (57.8%)Imbalance
상세영업상태코드 is highly imbalanced (57.8%)Imbalance
상세영업상태명 is highly imbalanced (57.8%)Imbalance
업태구분명 is highly imbalanced (99.2%)Imbalance
위생업태명 is highly imbalanced (61.9%)Imbalance
남성종사자수 is highly imbalanced (75.1%)Imbalance
여성종사자수 is highly imbalanced (75.6%)Imbalance
영업장주변구분명 is highly imbalanced (86.6%)Imbalance
등급구분명 is highly imbalanced (88.3%)Imbalance
급수시설구분명 is highly imbalanced (84.4%)Imbalance
총인원 is highly imbalanced (64.7%)Imbalance
다중이용업소여부 is highly imbalanced (92.5%)Imbalance
인허가취소일자 has 9264 (100.0%) missing valuesMissing
폐업일자 has 794 (8.6%) missing valuesMissing
휴업시작일자 has 9264 (100.0%) missing valuesMissing
휴업종료일자 has 9264 (100.0%) missing valuesMissing
재개업일자 has 9264 (100.0%) missing valuesMissing
전화번호 has 7502 (81.0%) missing valuesMissing
소재지면적 has 4204 (45.4%) missing valuesMissing
도로명주소 has 1848 (19.9%) missing valuesMissing
도로명우편번호 has 1861 (20.1%) missing valuesMissing
좌표정보(X) has 165 (1.8%) missing valuesMissing
좌표정보(Y) has 165 (1.8%) missing valuesMissing
다중이용업소여부 has 1983 (21.4%) missing valuesMissing
시설총규모 has 1983 (21.4%) missing valuesMissing
전통업소지정번호 has 9264 (100.0%) missing valuesMissing
전통업소주된음식 has 9264 (100.0%) missing valuesMissing
홈페이지 has 9264 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 6707 (72.4%) zerosZeros

Reproduction

Analysis started2024-04-06 12:05:57.703550
Analysis finished2024-04-06 12:06:01.222323
Duration3.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
3210000
9264 

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 9264
100.0%

Length

2024-04-06T21:06:01.327066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:01.468435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 9264
100.0%

관리번호
Text

UNIQUE 

Distinct9264
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
2024-04-06T21:06:01.779426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters203808
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

Unique9264 ?
Unique (%)100.0%

Sample

1st row3210000-107-1976-00013
2nd row3210000-107-1976-00030
3rd row3210000-107-1978-00166
4th row3210000-107-1979-00008
5th row3210000-107-1979-00022
ValueCountFrequency (%)
3210000-107-1976-00013 1
 
< 0.1%
3210000-107-2020-00537 1
 
< 0.1%
3210000-107-2020-00501 1
 
< 0.1%
3210000-107-2020-00492 1
 
< 0.1%
3210000-107-2020-00486 1
 
< 0.1%
3210000-107-2020-00487 1
 
< 0.1%
3210000-107-2020-00488 1
 
< 0.1%
3210000-107-2020-00489 1
 
< 0.1%
3210000-107-2020-00490 1
 
< 0.1%
3210000-107-2020-00491 1
 
< 0.1%
Other values (9254) 9254
99.9%
2024-04-06T21:06:02.307387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 80635
39.6%
- 27792
 
13.6%
1 27480
 
13.5%
2 25602
 
12.6%
3 13097
 
6.4%
7 12877
 
6.3%
9 3814
 
1.9%
8 3337
 
1.6%
6 3208
 
1.6%
4 3133
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 176016
86.4%
Dash Punctuation 27792
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 80635
45.8%
1 27480
 
15.6%
2 25602
 
14.5%
3 13097
 
7.4%
7 12877
 
7.3%
9 3814
 
2.2%
8 3337
 
1.9%
6 3208
 
1.8%
4 3133
 
1.8%
5 2833
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 27792
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203808
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 80635
39.6%
- 27792
 
13.6%
1 27480
 
13.5%
2 25602
 
12.6%
3 13097
 
6.4%
7 12877
 
6.3%
9 3814
 
1.9%
8 3337
 
1.6%
6 3208
 
1.6%
4 3133
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 80635
39.6%
- 27792
 
13.6%
1 27480
 
13.5%
2 25602
 
12.6%
3 13097
 
6.4%
7 12877
 
6.3%
9 3814
 
1.9%
8 3337
 
1.6%
6 3208
 
1.6%
4 3133
 
1.5%
Distinct3778
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
Minimum1976-07-24 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T21:06:02.611982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:06:02.867987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
3
8470 
1
 
794

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 8470
91.4%
1 794
 
8.6%

Length

2024-04-06T21:06:03.079255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:03.230721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8470
91.4%
1 794
 
8.6%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
폐업
8470 
영업/정상
 
794

Length

Max length5
Median length2
Mean length2.2571244
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 8470
91.4%
영업/정상 794
 
8.6%

Length

2024-04-06T21:06:03.410753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:03.564686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8470
91.4%
영업/정상 794
 
8.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
2
8470 
1
 
794

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 8470
91.4%
1 794
 
8.6%

Length

2024-04-06T21:06:03.743452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:03.953161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8470
91.4%
1 794
 
8.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
폐업
8470 
영업
 
794

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 8470
91.4%
영업 794
 
8.6%

Length

2024-04-06T21:06:04.126145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:04.301802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8470
91.4%
영업 794
 
8.6%

폐업일자
Date

MISSING 

Distinct3507
Distinct (%)41.4%
Missing794
Missing (%)8.6%
Memory size72.5 KiB
Minimum1995-07-04 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T21:06:04.499892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:06:04.743873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

전화번호
Text

MISSING 

Distinct1270
Distinct (%)72.1%
Missing7502
Missing (%)81.0%
Memory size72.5 KiB
2024-04-06T21:06:05.327685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.586266
Min length2

Characters and Unicode

Total characters18653
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

Unique1116 ?
Unique (%)63.3%

Sample

1st row02 5334459
2nd row02 5339162
3rd row02 5992059
4th row02 5324961
5th row02 5832140
ValueCountFrequency (%)
02 1134
30.9%
031 141
 
3.8%
070 50
 
1.4%
0 28
 
0.8%
585 24
 
0.7%
34725603 22
 
0.6%
032 21
 
0.6%
530 20
 
0.5%
21551234 19
 
0.5%
6820 18
 
0.5%
Other values (1437) 2195
59.8%
2024-04-06T21:06:06.312772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3039
16.3%
2 2752
14.8%
2486
13.3%
5 1971
10.6%
3 1715
9.2%
1 1256
6.7%
7 1201
 
6.4%
4 1190
 
6.4%
8 1092
 
5.9%
9 1014
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16167
86.7%
Space Separator 2486
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3039
18.8%
2 2752
17.0%
5 1971
12.2%
3 1715
10.6%
1 1256
7.8%
7 1201
 
7.4%
4 1190
 
7.4%
8 1092
 
6.8%
9 1014
 
6.3%
6 937
 
5.8%
Space Separator
ValueCountFrequency (%)
2486
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18653
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3039
16.3%
2 2752
14.8%
2486
13.3%
5 1971
10.6%
3 1715
9.2%
1 1256
6.7%
7 1201
 
6.4%
4 1190
 
6.4%
8 1092
 
5.9%
9 1014
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18653
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3039
16.3%
2 2752
14.8%
2486
13.3%
5 1971
10.6%
3 1715
9.2%
1 1256
6.7%
7 1201
 
6.4%
4 1190
 
6.4%
8 1092
 
5.9%
9 1014
 
5.4%

소재지면적
Text

MISSING 

Distinct1006
Distinct (%)19.9%
Missing4204
Missing (%)45.4%
Memory size72.5 KiB
2024-04-06T21:06:06.965738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.1428854
Min length3

Characters and Unicode

Total characters20963
Distinct characters12
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

Unique758 ?
Unique (%)15.0%

Sample

1st row13.44
2nd row13.50
3rd row39.06
4th row13.26
5th row13.65
ValueCountFrequency (%)
00 1060
20.9%
0.00 812
 
16.0%
6.00 192
 
3.8%
3.30 191
 
3.8%
6.60 152
 
3.0%
10.00 125
 
2.5%
3.00 96
 
1.9%
5.00 88
 
1.7%
33.00 76
 
1.5%
4.00 73
 
1.4%
Other values (996) 2195
43.4%
2024-04-06T21:06:07.806926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8738
41.7%
. 5060
24.1%
3 1299
 
6.2%
1 1091
 
5.2%
6 1079
 
5.1%
2 951
 
4.5%
5 767
 
3.7%
4 658
 
3.1%
9 519
 
2.5%
8 411
 
2.0%
Other values (2) 390
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15902
75.9%
Other Punctuation 5061
 
24.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8738
54.9%
3 1299
 
8.2%
1 1091
 
6.9%
6 1079
 
6.8%
2 951
 
6.0%
5 767
 
4.8%
4 658
 
4.1%
9 519
 
3.3%
8 411
 
2.6%
7 389
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 5060
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 20963
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8738
41.7%
. 5060
24.1%
3 1299
 
6.2%
1 1091
 
5.2%
6 1079
 
5.1%
2 951
 
4.5%
5 767
 
3.7%
4 658
 
3.1%
9 519
 
2.5%
8 411
 
2.0%
Other values (2) 390
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8738
41.7%
. 5060
24.1%
3 1299
 
6.2%
1 1091
 
5.2%
6 1079
 
5.1%
2 951
 
4.5%
5 767
 
3.7%
4 658
 
3.1%
9 519
 
2.5%
8 411
 
2.0%
Other values (2) 390
 
1.9%
Distinct246
Distinct (%)2.7%
Missing4
Missing (%)< 0.1%
Memory size72.5 KiB
2024-04-06T21:06:08.416955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1323974
Min length6

Characters and Unicode

Total characters56786
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

Unique49 ?
Unique (%)0.5%

Sample

1st row137829
2nd row137040
3rd row137040
4th row137030
5th row137881
ValueCountFrequency (%)
137713 1111
 
12.0%
137960 817
 
8.8%
137893 743
 
8.0%
137908 733
 
7.9%
137916 555
 
6.0%
137711 429
 
4.6%
137-960 306
 
3.3%
137907 292
 
3.2%
137140 234
 
2.5%
137924 227
 
2.5%
Other values (236) 3813
41.2%
2024-04-06T21:06:09.165644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13179
23.2%
7 12058
21.2%
3 11614
20.5%
8 5037
 
8.9%
9 4801
 
8.5%
0 4037
 
7.1%
6 2412
 
4.2%
- 1226
 
2.2%
4 1072
 
1.9%
2 812
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55560
97.8%
Dash Punctuation 1226
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13179
23.7%
7 12058
21.7%
3 11614
20.9%
8 5037
 
9.1%
9 4801
 
8.6%
0 4037
 
7.3%
6 2412
 
4.3%
4 1072
 
1.9%
2 812
 
1.5%
5 538
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56786
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13179
23.2%
7 12058
21.2%
3 11614
20.5%
8 5037
 
8.9%
9 4801
 
8.5%
0 4037
 
7.1%
6 2412
 
4.2%
- 1226
 
2.2%
4 1072
 
1.9%
2 812
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13179
23.2%
7 12058
21.2%
3 11614
20.5%
8 5037
 
8.9%
9 4801
 
8.5%
0 4037
 
7.1%
6 2412
 
4.2%
- 1226
 
2.2%
4 1072
 
1.9%
2 812
 
1.4%
Distinct3106
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
2024-04-06T21:06:09.526854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length26.715242
Min length6

Characters and Unicode

Total characters247490
Distinct characters404
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

Unique2603 ?
Unique (%)28.1%

Sample

1st row서울특별시 서초구 방배동 770-1 상가
2nd row서울특별시 서초구 반포동 885-0 한신종합상가
3rd row서울특별시 서초구 반포동 827-0 반포상가 E동 28호
4th row서울특별시 서초구 잠원동 235-0 잠원쇼핑 19동
5th row서울특별시 서초구 서초동 1671-5
ValueCountFrequency (%)
서울특별시 9259
18.7%
서초구 9258
18.7%
반포동 2940
 
5.9%
양재동 2367
 
4.8%
19-3 2259
 
4.6%
잠원동 1619
 
3.3%
서초동 1141
 
2.3%
230 1090
 
2.2%
70-2 1034
 
2.1%
1층 995
 
2.0%
Other values (2762) 17678
35.6%
2024-04-06T21:06:10.177197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47438
19.2%
20021
 
8.1%
10613
 
4.3%
10593
 
4.3%
9802
 
4.0%
9404
 
3.8%
1 9391
 
3.8%
9281
 
3.8%
9262
 
3.7%
9259
 
3.7%
Other values (394) 102426
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154703
62.5%
Space Separator 47438
 
19.2%
Decimal Number 37094
 
15.0%
Dash Punctuation 6561
 
2.7%
Uppercase Letter 785
 
0.3%
Other Punctuation 353
 
0.1%
Close Punctuation 216
 
0.1%
Open Punctuation 216
 
0.1%
Lowercase Letter 114
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20021
 
12.9%
10613
 
6.9%
10593
 
6.8%
9802
 
6.3%
9404
 
6.1%
9281
 
6.0%
9262
 
6.0%
9259
 
6.0%
3078
 
2.0%
3075
 
2.0%
Other values (337) 60315
39.0%
Uppercase Letter
ValueCountFrequency (%)
B 144
18.3%
A 128
16.3%
T 123
15.7%
G 105
13.4%
S 99
12.6%
C 26
 
3.3%
H 25
 
3.2%
E 24
 
3.1%
L 13
 
1.7%
N 12
 
1.5%
Other values (13) 86
11.0%
Lowercase Letter
ValueCountFrequency (%)
s 39
34.2%
g 38
33.3%
i 8
 
7.0%
t 8
 
7.0%
d 7
 
6.1%
o 4
 
3.5%
e 2
 
1.8%
w 2
 
1.8%
r 2
 
1.8%
c 1
 
0.9%
Other values (3) 3
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 9391
25.3%
3 5867
15.8%
2 5337
14.4%
0 3799
10.2%
9 3022
 
8.1%
7 2619
 
7.1%
5 2490
 
6.7%
4 1746
 
4.7%
8 1646
 
4.4%
6 1177
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 341
96.6%
. 5
 
1.4%
/ 4
 
1.1%
& 1
 
0.3%
? 1
 
0.3%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
47438
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 154703
62.5%
Common 91888
37.1%
Latin 899
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20021
 
12.9%
10613
 
6.9%
10593
 
6.8%
9802
 
6.3%
9404
 
6.1%
9281
 
6.0%
9262
 
6.0%
9259
 
6.0%
3078
 
2.0%
3075
 
2.0%
Other values (337) 60315
39.0%
Latin
ValueCountFrequency (%)
B 144
16.0%
A 128
14.2%
T 123
13.7%
G 105
11.7%
S 99
11.0%
s 39
 
4.3%
g 38
 
4.2%
C 26
 
2.9%
H 25
 
2.8%
E 24
 
2.7%
Other values (26) 148
16.5%
Common
ValueCountFrequency (%)
47438
51.6%
1 9391
 
10.2%
- 6561
 
7.1%
3 5867
 
6.4%
2 5337
 
5.8%
0 3799
 
4.1%
9 3022
 
3.3%
7 2619
 
2.9%
5 2490
 
2.7%
4 1746
 
1.9%
Other values (11) 3618
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154703
62.5%
ASCII 92787
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47438
51.1%
1 9391
 
10.1%
- 6561
 
7.1%
3 5867
 
6.3%
2 5337
 
5.8%
0 3799
 
4.1%
9 3022
 
3.3%
7 2619
 
2.8%
5 2490
 
2.7%
4 1746
 
1.9%
Other values (47) 4517
 
4.9%
Hangul
ValueCountFrequency (%)
20021
 
12.9%
10613
 
6.9%
10593
 
6.8%
9802
 
6.3%
9404
 
6.1%
9281
 
6.0%
9262
 
6.0%
9259
 
6.0%
3078
 
2.0%
3075
 
2.0%
Other values (337) 60315
39.0%

도로명주소
Text

MISSING 

Distinct2447
Distinct (%)33.0%
Missing1848
Missing (%)19.9%
Memory size72.5 KiB
2024-04-06T21:06:10.620486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length60
Mean length34.777778
Min length22

Characters and Unicode

Total characters257912
Distinct characters415
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1943 ?
Unique (%)26.2%

Sample

1st row서울특별시 서초구 방배로43길 5 (방배동)
2nd row서울특별시 서초구 서운로 207 (서초동,삼호종합상가 지하4호)
3rd row서울특별시 서초구 방배로13길 34 (방배동, 지하 1층)
4th row서울특별시 서초구 서초대로16길 12 (방배동)
5th row서울특별시 서초구 잠원로4길 54, 지하1층 33호 (잠원동, 매일상가)
ValueCountFrequency (%)
서울특별시 7415
 
14.5%
서초구 7414
 
14.5%
반포동 2289
 
4.5%
지하1층 2246
 
4.4%
신반포로 2102
 
4.1%
양재동 2033
 
4.0%
176 1989
 
3.9%
1층 1618
 
3.2%
잠원동 1146
 
2.2%
청계산로 1023
 
2.0%
Other values (1936) 21722
42.6%
2024-04-06T21:06:11.367010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43616
 
16.9%
16687
 
6.5%
1 10686
 
4.1%
8991
 
3.5%
8311
 
3.2%
8265
 
3.2%
8196
 
3.2%
) 7618
 
3.0%
( 7618
 
3.0%
7557
 
2.9%
Other values (405) 130367
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163889
63.5%
Space Separator 43616
 
16.9%
Decimal Number 26768
 
10.4%
Close Punctuation 7619
 
3.0%
Open Punctuation 7619
 
3.0%
Other Punctuation 7223
 
2.8%
Uppercase Letter 738
 
0.3%
Dash Punctuation 275
 
0.1%
Lowercase Letter 160
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
16687
 
10.2%
8991
 
5.5%
8311
 
5.1%
8265
 
5.0%
8196
 
5.0%
7557
 
4.6%
7441
 
4.5%
7416
 
4.5%
7416
 
4.5%
4738
 
2.9%
Other values (348) 78871
48.1%
Uppercase Letter
ValueCountFrequency (%)
B 182
24.7%
T 113
15.3%
A 111
15.0%
G 97
13.1%
S 94
12.7%
F 18
 
2.4%
C 17
 
2.3%
E 13
 
1.8%
P 13
 
1.8%
H 12
 
1.6%
Other values (13) 68
 
9.2%
Lowercase Letter
ValueCountFrequency (%)
s 59
36.9%
g 58
36.2%
a 9
 
5.6%
t 7
 
4.4%
e 7
 
4.4%
b 4
 
2.5%
r 4
 
2.5%
n 3
 
1.9%
o 3
 
1.9%
d 2
 
1.2%
Other values (3) 4
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 10686
39.9%
6 3534
 
13.2%
7 2874
 
10.7%
2 2194
 
8.2%
0 2093
 
7.8%
5 1640
 
6.1%
3 1363
 
5.1%
4 865
 
3.2%
8 807
 
3.0%
9 712
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 7219
99.9%
. 3
 
< 0.1%
/ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 7618
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 7618
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
43616
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 275
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163889
63.5%
Common 93125
36.1%
Latin 898
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
16687
 
10.2%
8991
 
5.5%
8311
 
5.1%
8265
 
5.0%
8196
 
5.0%
7557
 
4.6%
7441
 
4.5%
7416
 
4.5%
7416
 
4.5%
4738
 
2.9%
Other values (348) 78871
48.1%
Latin
ValueCountFrequency (%)
B 182
20.3%
T 113
12.6%
A 111
12.4%
G 97
10.8%
S 94
10.5%
s 59
 
6.6%
g 58
 
6.5%
F 18
 
2.0%
C 17
 
1.9%
E 13
 
1.4%
Other values (26) 136
15.1%
Common
ValueCountFrequency (%)
43616
46.8%
1 10686
 
11.5%
) 7618
 
8.2%
( 7618
 
8.2%
, 7219
 
7.8%
6 3534
 
3.8%
7 2874
 
3.1%
2 2194
 
2.4%
0 2093
 
2.2%
5 1640
 
1.8%
Other values (11) 4033
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163889
63.5%
ASCII 94023
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43616
46.4%
1 10686
 
11.4%
) 7618
 
8.1%
( 7618
 
8.1%
, 7219
 
7.7%
6 3534
 
3.8%
7 2874
 
3.1%
2 2194
 
2.3%
0 2093
 
2.2%
5 1640
 
1.7%
Other values (47) 4931
 
5.2%
Hangul
ValueCountFrequency (%)
16687
 
10.2%
8991
 
5.5%
8311
 
5.1%
8265
 
5.0%
8196
 
5.0%
7557
 
4.6%
7441
 
4.5%
7416
 
4.5%
7416
 
4.5%
4738
 
2.9%
Other values (348) 78871
48.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct255
Distinct (%)3.4%
Missing1861
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean6641.9199
Minimum3707
Maximum14347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.6 KiB
2024-04-06T21:06:11.657832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3707
5-th percentile6511
Q16546
median6597
Q36771
95-th percentile6797
Maximum14347
Range10640
Interquartile range (IQR)225

Descriptive statistics

Standard deviation148.46589
Coefficient of variation (CV)0.022352858
Kurtosis998.95289
Mean6641.9199
Median Absolute Deviation (MAD)86
Skewness17.965887
Sum49170133
Variance22042.121
MonotonicityNot monotonic
2024-04-06T21:06:11.887680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6546 1927
20.8%
6797 967
10.4%
6511 883
9.5%
6771 489
 
5.3%
6764 261
 
2.8%
6597 160
 
1.7%
6523 158
 
1.7%
6774 143
 
1.5%
6785 135
 
1.5%
6787 125
 
1.3%
Other values (245) 2155
23.3%
(Missing) 1861
20.1%
ValueCountFrequency (%)
3707 1
 
< 0.1%
6500 3
 
< 0.1%
6501 3
 
< 0.1%
6502 16
 
0.2%
6503 42
 
0.5%
6506 9
 
0.1%
6509 8
 
0.1%
6510 3
 
< 0.1%
6511 883
9.5%
6512 3
 
< 0.1%
ValueCountFrequency (%)
14347 1
 
< 0.1%
6806 5
 
0.1%
6803 1
 
< 0.1%
6802 60
 
0.6%
6800 87
 
0.9%
6799 1
 
< 0.1%
6798 1
 
< 0.1%
6797 967
10.4%
6796 2
 
< 0.1%
6794 1
 
< 0.1%
Distinct3951
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
2024-04-06T21:06:12.370516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length6.7419041
Min length1

Characters and Unicode

Total characters62457
Distinct characters848
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3101 ?
Unique (%)33.5%

Sample

1st row믿음기름집
2nd row한신기름집
3rd row새마을
4th row한신기름집
5th row서초기름집
ValueCountFrequency (%)
주식회사 740
 
6.5%
월드푸드 173
 
1.5%
다정 133
 
1.2%
주)행복생활건강 128
 
1.1%
푸드뱅크코리아 111
 
1.0%
마켓인 110
 
1.0%
엠엔에이치(m&h 88
 
0.8%
주)메르시푸드 86
 
0.7%
주)인네이처 82
 
0.7%
주)푸드뱅크코리아 71
 
0.6%
Other values (4365) 9748
85.0%
2024-04-06T21:06:13.172026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3226
 
5.2%
) 2685
 
4.3%
( 2628
 
4.2%
2209
 
3.5%
1784
 
2.9%
1447
 
2.3%
1424
 
2.3%
1362
 
2.2%
1313
 
2.1%
1032
 
1.7%
Other values (838) 43347
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52346
83.8%
Close Punctuation 2685
 
4.3%
Open Punctuation 2628
 
4.2%
Space Separator 2209
 
3.5%
Lowercase Letter 1074
 
1.7%
Uppercase Letter 1018
 
1.6%
Other Punctuation 301
 
0.5%
Decimal Number 171
 
0.3%
Dash Punctuation 24
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3226
 
6.2%
1784
 
3.4%
1447
 
2.8%
1424
 
2.7%
1362
 
2.6%
1313
 
2.5%
1032
 
2.0%
953
 
1.8%
939
 
1.8%
783
 
1.5%
Other values (764) 38083
72.8%
Lowercase Letter
ValueCountFrequency (%)
e 170
15.8%
o 102
 
9.5%
a 82
 
7.6%
h 80
 
7.4%
m 69
 
6.4%
n 57
 
5.3%
i 57
 
5.3%
t 56
 
5.2%
r 53
 
4.9%
f 50
 
4.7%
Other values (16) 298
27.7%
Uppercase Letter
ValueCountFrequency (%)
H 128
 
12.6%
M 126
 
12.4%
C 70
 
6.9%
O 69
 
6.8%
E 64
 
6.3%
A 54
 
5.3%
F 51
 
5.0%
S 47
 
4.6%
B 43
 
4.2%
L 42
 
4.1%
Other values (15) 324
31.8%
Decimal Number
ValueCountFrequency (%)
2 42
24.6%
1 24
14.0%
3 23
13.5%
8 22
12.9%
6 14
 
8.2%
0 14
 
8.2%
4 9
 
5.3%
5 9
 
5.3%
7 8
 
4.7%
9 6
 
3.5%
Other Punctuation
ValueCountFrequency (%)
& 201
66.8%
, 51
 
16.9%
. 29
 
9.6%
' 10
 
3.3%
: 4
 
1.3%
? 4
 
1.3%
/ 1
 
0.3%
! 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 2685
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2628
100.0%
Space Separator
ValueCountFrequency (%)
2209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52341
83.8%
Common 8019
 
12.8%
Latin 2092
 
3.3%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3226
 
6.2%
1784
 
3.4%
1447
 
2.8%
1424
 
2.7%
1362
 
2.6%
1313
 
2.5%
1032
 
2.0%
953
 
1.8%
939
 
1.8%
783
 
1.5%
Other values (759) 38078
72.7%
Latin
ValueCountFrequency (%)
e 170
 
8.1%
H 128
 
6.1%
M 126
 
6.0%
o 102
 
4.9%
a 82
 
3.9%
h 80
 
3.8%
C 70
 
3.3%
O 69
 
3.3%
m 69
 
3.3%
E 64
 
3.1%
Other values (41) 1132
54.1%
Common
ValueCountFrequency (%)
) 2685
33.5%
( 2628
32.8%
2209
27.5%
& 201
 
2.5%
, 51
 
0.6%
2 42
 
0.5%
. 29
 
0.4%
1 24
 
0.3%
- 24
 
0.3%
3 23
 
0.3%
Other values (13) 103
 
1.3%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
滿 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52334
83.8%
ASCII 10111
 
16.2%
Compat Jamo 7
 
< 0.1%
CJK 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3226
 
6.2%
1784
 
3.4%
1447
 
2.8%
1424
 
2.7%
1362
 
2.6%
1313
 
2.5%
1032
 
2.0%
953
 
1.8%
939
 
1.8%
783
 
1.5%
Other values (753) 38071
72.7%
ASCII
ValueCountFrequency (%)
) 2685
26.6%
( 2628
26.0%
2209
21.8%
& 201
 
2.0%
e 170
 
1.7%
H 128
 
1.3%
M 126
 
1.2%
o 102
 
1.0%
a 82
 
0.8%
h 80
 
0.8%
Other values (64) 1700
16.8%
Compat Jamo
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
滿 1
25.0%
Distinct4926
Distinct (%)53.2%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
Minimum1999-02-09 00:00:00
Maximum2024-04-04 15:32:07
2024-04-06T21:06:13.862449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:06:14.217030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
U
4860 
I
4403 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowU
2nd rowI
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
U 4860
52.5%
I 4403
47.5%
D 1
 
< 0.1%

Length

2024-04-06T21:06:14.541692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:14.699332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 4860
52.5%
i 4403
47.5%
d 1
 
< 0.1%
Distinct1600
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T21:06:14.873732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:06:15.122051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
즉석판매제조가공업
9254 
기타
 
9
한식
 
1

Length

Max length9
Median length9
Mean length8.9924439
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 9254
99.9%
기타 9
 
0.1%
한식 1
 
< 0.1%

Length

2024-04-06T21:06:15.367547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:15.540246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 9254
99.9%
기타 9
 
0.1%
한식 1
 
< 0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1151
Distinct (%)12.6%
Missing165
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean201392.96
Minimum189878.79
Maximum207766.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.6 KiB
2024-04-06T21:06:15.739822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189878.79
5-th percentile198984.36
Q1200250.45
median200576.61
Q3203204.76
95-th percentile203811.37
Maximum207766.38
Range17887.592
Interquartile range (IQR)2954.3078

Descriptive statistics

Standard deviation1607.7727
Coefficient of variation (CV)0.0079832615
Kurtosis-0.57028694
Mean201392.96
Median Absolute Deviation (MAD)774.05039
Skewness0.39313037
Sum1.8324745 × 109
Variance2584932.9
MonotonicityNot monotonic
2024-04-06T21:06:16.022502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200250.447804795 2259
24.4%
200576.608647619 1030
 
11.1%
203811.366422118 898
 
9.7%
203204.755637424 582
 
6.3%
202151.207983366 248
 
2.7%
201104.26895551 230
 
2.5%
203811.14583381 204
 
2.2%
200996.974700931 161
 
1.7%
203392.793460583 145
 
1.6%
203630.238293919 119
 
1.3%
Other values (1141) 3223
34.8%
(Missing) 165
 
1.8%
ValueCountFrequency (%)
189878.788781586 1
 
< 0.1%
193502.720357107 1
 
< 0.1%
198351.955 1
 
< 0.1%
198359.032400861 2
< 0.1%
198359.105676344 1
 
< 0.1%
198389.022273532 1
 
< 0.1%
198391.007333333 4
< 0.1%
198392.031081002 1
 
< 0.1%
198394.421455426 1
 
< 0.1%
198397.797879556 1
 
< 0.1%
ValueCountFrequency (%)
207766.380638846 1
 
< 0.1%
207147.911759758 1
 
< 0.1%
207136.404532812 1
 
< 0.1%
205578.791967297 1
 
< 0.1%
205525.422778498 3
 
< 0.1%
205329.561120927 1
 
< 0.1%
205235.018649725 3
 
< 0.1%
205231.176713429 1
 
< 0.1%
205229.0 1
 
< 0.1%
205219.282487819 9
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1151
Distinct (%)12.6%
Missing165
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean443077.64
Minimum435405.63
Maximum451561.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.6 KiB
2024-04-06T21:06:16.300643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum435405.63
5-th percentile440070.73
Q1440676.38
median443999.07
Q3444683.22
95-th percentile445266.68
Maximum451561.44
Range16155.808
Interquartile range (IQR)4006.8406

Descriptive statistics

Standard deviation2081.5334
Coefficient of variation (CV)0.0046978976
Kurtosis-1.2883345
Mean443077.64
Median Absolute Deviation (MAD)1242.8313
Skewness-0.50684178
Sum4.0315634 × 109
Variance4332781.1
MonotonicityNot monotonic
2024-04-06T21:06:16.559812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444683.220506107 2259
24.4%
445241.8984183 1030
 
11.1%
440070.727589935 898
 
9.7%
440136.781183797 582
 
6.3%
440152.039102831 248
 
2.7%
445266.678558749 230
 
2.5%
440070.874222824 204
 
2.2%
444526.688404154 161
 
1.7%
440676.379919661 145
 
1.6%
440753.038269237 119
 
1.3%
Other values (1141) 3223
34.8%
(Missing) 165
 
1.8%
ValueCountFrequency (%)
435405.631407888 1
< 0.1%
437864.710924867 2
< 0.1%
437890.507732031 1
< 0.1%
437918.245734193 1
< 0.1%
437922.839052347 1
< 0.1%
438034.049256635 1
< 0.1%
438046.941961006 1
< 0.1%
438079.517474227 1
< 0.1%
438092.114640553 1
< 0.1%
438193.564894704 1
< 0.1%
ValueCountFrequency (%)
451561.439755385 1
 
< 0.1%
446565.028672992 1
 
< 0.1%
446331.380046658 1
 
< 0.1%
446247.719636035 2
 
< 0.1%
446180.260965954 1
 
< 0.1%
446179.309516814 11
0.1%
446166.39371284 1
 
< 0.1%
446143.95956442 1
 
< 0.1%
446143.546154841 1
 
< 0.1%
446102.588876 14
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
즉석판매제조가공업
7271 
<NA>
1983 
기타
 
9
한식
 
1

Length

Max length9
Median length9
Mean length7.9221718
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 7271
78.5%
<NA> 1983
 
21.4%
기타 9
 
0.1%
한식 1
 
< 0.1%

Length

2024-04-06T21:06:16.805379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:16.978220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 7271
78.5%
na 1983
 
21.4%
기타 9
 
0.1%
한식 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8393 
0
 
782
1
 
83
2
 
6

Length

Max length4
Median length4
Mean length3.7179404
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 8393
90.6%
0 782
 
8.4%
1 83
 
0.9%
2 6
 
0.1%

Length

2024-04-06T21:06:17.149638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:17.346694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8393
90.6%
0 782
 
8.4%
1 83
 
0.9%
2 6
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8403 
0
 
783
1
 
75
2
 
3

Length

Max length4
Median length4
Mean length3.7211788
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 8403
90.7%
0 783
 
8.5%
1 75
 
0.8%
2 3
 
< 0.1%

Length

2024-04-06T21:06:17.540082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:17.813690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8403
90.7%
0 783
 
8.5%
1 75
 
0.8%
2 3
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8848 
기타
 
312
주택가주변
 
70
아파트지역
 
33
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9441926
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row기타
2nd row아파트지역
3rd row주택가주변
4th row기타
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 8848
95.5%
기타 312
 
3.4%
주택가주변 70
 
0.8%
아파트지역 33
 
0.4%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-04-06T21:06:18.001940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:18.181059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8848
95.5%
기타 312
 
3.4%
주택가주변 70
 
0.8%
아파트지역 33
 
0.4%
유흥업소밀집지역 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8848 
기타
 
409
자율
 
3
 
3
우수
 
1

Length

Max length4
Median length4
Mean length3.9098661
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8848
95.5%
기타 409
 
4.4%
자율 3
 
< 0.1%
3
 
< 0.1%
우수 1
 
< 0.1%

Length

2024-04-06T21:06:18.362212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:18.525083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8848
95.5%
기타 409
 
4.4%
자율 3
 
< 0.1%
3
 
< 0.1%
우수 1
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8884 
상수도전용
 
379
지하수전용
 
1

Length

Max length5
Median length4
Mean length4.041019
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8884
95.9%
상수도전용 379
 
4.1%
지하수전용 1
 
< 0.1%

Length

2024-04-06T21:06:18.718293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:18.990810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8884
95.9%
상수도전용 379
 
4.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8647 
0
 
617

Length

Max length4
Median length4
Mean length3.8001943
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8647
93.3%
0 617
 
6.7%

Length

2024-04-06T21:06:19.256708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:19.440495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8647
93.3%
0 617
 
6.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
7444 
0
1820 

Length

Max length4
Median length4
Mean length3.4106218
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7444
80.4%
0 1820
 
19.6%

Length

2024-04-06T21:06:19.655857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:19.984169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7444
80.4%
0 1820
 
19.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
7444 
0
1820 

Length

Max length4
Median length4
Mean length3.4106218
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7444
80.4%
0 1820
 
19.6%

Length

2024-04-06T21:06:20.160670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:20.343348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7444
80.4%
0 1820
 
19.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
7444 
0
1820 

Length

Max length4
Median length4
Mean length3.4106218
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7444
80.4%
0 1820
 
19.6%

Length

2024-04-06T21:06:20.547225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:20.734544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7444
80.4%
0 1820
 
19.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
7444 
0
1820 

Length

Max length4
Median length4
Mean length3.4106218
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 7444
80.4%
0 1820
 
19.6%

Length

2024-04-06T21:06:20.954286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:21.165318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7444
80.4%
0 1820
 
19.6%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
6408 
자가
1449 
임대
1407 

Length

Max length4
Median length4
Mean length3.3834197
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6408
69.2%
자가 1449
 
15.6%
임대 1407
 
15.2%

Length

2024-04-06T21:06:21.365890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:21.569121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6408
69.2%
자가 1449
 
15.6%
임대 1407
 
15.2%

보증액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8004 
0
1260 

Length

Max length4
Median length4
Mean length3.5919689
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8004
86.4%
0 1260
 
13.6%

Length

2024-04-06T21:06:21.754246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:21.950674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8004
86.4%
0 1260
 
13.6%

월세액
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.5 KiB
<NA>
8004 
0
1260 

Length

Max length4
Median length4
Mean length3.5919689
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8004
86.4%
0 1260
 
13.6%

Length

2024-04-06T21:06:22.162767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:06:22.379914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8004
86.4%
0 1260
 
13.6%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1983
Missing (%)21.4%
Memory size18.2 KiB
False
7214 
True
 
67
(Missing)
1983 
ValueCountFrequency (%)
False 7214
77.9%
True 67
 
0.7%
(Missing) 1983
 
21.4%
2024-04-06T21:06:22.535908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct278
Distinct (%)3.8%
Missing1983
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean2.2075155
Minimum0
Maximum647.86
Zeros6707
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size81.6 KiB
2024-04-06T21:06:22.760495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum647.86
Range647.86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.287257
Coefficient of variation (CV)6.4720982
Kurtosis647.15738
Mean2.2075155
Median Absolute Deviation (MAD)0
Skewness18.960493
Sum16072.92
Variance204.12571
MonotonicityNot monotonic
2024-04-06T21:06:23.062307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6707
72.4%
3.3 38
 
0.4%
10.0 30
 
0.3%
6.6 25
 
0.3%
6.0 21
 
0.2%
20.0 17
 
0.2%
33.0 15
 
0.2%
30.0 14
 
0.2%
5.0 13
 
0.1%
9.9 12
 
0.1%
Other values (268) 389
 
4.2%
(Missing) 1983
 
21.4%
ValueCountFrequency (%)
0.0 6707
72.4%
1.0 2
 
< 0.1%
1.3 1
 
< 0.1%
1.8 1
 
< 0.1%
1.9 1
 
< 0.1%
2.0 6
 
0.1%
2.2 2
 
< 0.1%
2.25 1
 
< 0.1%
2.27 1
 
< 0.1%
2.3 1
 
< 0.1%
ValueCountFrequency (%)
647.86 1
< 0.1%
303.0 1
< 0.1%
230.3 1
< 0.1%
211.22 1
< 0.1%
184.45 1
< 0.1%
170.0 1
< 0.1%
161.7 1
< 0.1%
158.81 1
< 0.1%
150.5 1
< 0.1%
149.44 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9264
Missing (%)100.0%
Memory size81.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-107-1976-0001319760724<NA>1영업/정상1영업<NA><NA><NA><NA>02 533445913.44137829서울특별시 서초구 방배동 770-1 상가서울특별시 서초구 방배로43길 5 (방배동)6556믿음기름집2018-12-14 10:12:32U2018-12-16 02:40:00.0즉석판매제조가공업198791.828234443667.105204즉석판매제조가공업<NA><NA>기타기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
132100003210000-107-1976-0003019760724<NA>3폐업2폐업20061009<NA><NA><NA>02 533916213.50137040서울특별시 서초구 반포동 885-0 한신종합상가<NA><NA>한신기름집2002-07-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업198845.040146444439.89559즉석판매제조가공업11아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232100003210000-107-1978-0016619780728<NA>3폐업2폐업20000414<NA><NA><NA>02 599205939.06137040서울특별시 서초구 반포동 827-0 반포상가 E동 28호<NA><NA>새마을2002-07-05 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업198657.120895444437.950786즉석판매제조가공업11주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332100003210000-107-1979-0000819790523<NA>3폐업2폐업19970328<NA><NA><NA>02 532496113.26137030서울특별시 서초구 잠원동 235-0 잠원쇼핑 19동<NA><NA>한신기름집2002-07-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432100003210000-107-1979-0002219790823<NA>3폐업2폐업20001103<NA><NA><NA>02 583214013.65137881서울특별시 서초구 서초동 1671-5<NA><NA>서초기름집2002-07-04 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업201295.700038443474.524865즉석판매제조가공업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532100003210000-107-1979-0013419790502<NA>3폐업2폐업20090714<NA><NA><NA>02 533806260.84137030서울특별시 서초구 잠원동 235-0 잠원쇼핑 지하동 23호<NA><NA>반포2003-01-29 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632100003210000-107-1980-0001019800820<NA>3폐업2폐업20200616<NA><NA><NA>02 573176312.81137070서울특별시 서초구 서초동 1310 ,1311번지 삼호종합상가 지하 4호서울특별시 서초구 서운로 207 (서초동,삼호종합상가 지하4호)6608삼호식품2020-06-17 09:06:02U2020-06-19 02:40:00.0즉석판매제조가공업201945.128259444423.971934즉석판매제조가공업11아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732100003210000-107-1980-0002820000302<NA>3폐업2폐업20161017<NA><NA><NA>02 583815213.20137843서울특별시 서초구 방배동 922-24 지하1층서울특별시 서초구 방배로13길 34 (방배동, 지하 1층)6683비엘푸드2015-12-11 16:00:29I2018-08-31 23:59:59.0즉석판매제조가공업199457.931749442272.33953즉석판매제조가공업11주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832100003210000-107-1980-0002919800711<NA>3폐업2폐업19990927<NA><NA><NA>02 532474328.35137806서울특별시 서초구 반포동 93-6<NA><NA>우일기름집2003-03-27 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업199798.009413444137.233603즉석판매제조가공업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932100003210000-107-1980-0004819800707<NA>3폐업2폐업20160921<NA><NA><NA>02 5849737.00137844서울특별시 서초구 방배동 941-21서울특별시 서초구 서초대로16길 12 (방배동)6673들녘2002-12-05 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업199093.687122442653.655542즉석판매제조가공업11기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
925432100003210000-107-2024-002082024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA>0319663852<NA>137-908서울특별시 서초구 잠원동 70-2 뉴코아백화점 킴스클럽 강남점 지하1층서울특별시 서초구 잠원로 51, 뉴코아백화점 (잠원동)6511(주)또바기2024-04-01 10:18:28I2023-12-04 00:03:00.0즉석판매제조가공업200576.608648445241.898418<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
925532100003210000-107-2024-002092024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-916서울특별시 서초구 양재동 230 농협하나로클럽 식자재 행사장 내 일부서울특별시 서초구 청계산로 10, 농협하나로클럽 (양재동)6797만나유통2024-04-01 17:11:31I2023-12-04 00:03:00.0즉석판매제조가공업203811.145834440070.874223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
925632100003210000-107-2024-002102024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-870서울특별시 서초구 서초동 1498-5 마제스타시티, 힐스테이트 서리풀 지하1층 롯데마트서울특별시 서초구 서초대로38길 12 (서초동, 마제스타시티, 힐스테이트 서리풀)6655주식회사 메르시푸드2024-04-01 17:17:36I2023-12-04 00:03:00.0즉석판매제조가공업200440.010812443124.671418<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
925732100003210000-107-2024-002112024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-916서울특별시 서초구 양재동 230 농협하나로클럽서울특별시 서초구 청계산로 10, 농협하나로클럽 양재점 (양재동)6797디앤에이치(D&H)2024-04-02 16:28:06I2023-12-04 00:04:00.0즉석판매제조가공업203811.145834440070.874223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
925832100003210000-107-2024-002122024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-855서울특별시 서초구 서초동 1306-6 파고다타워서울특별시 서초구 강남대로 419, MUJI 강남점 1층 (서초동)6614비앤컴퍼니2024-04-03 09:38:12I2023-12-04 00:05:00.0즉석판매제조가공업202244.583321444183.247964<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
925932100003210000-107-2024-002132024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-960서울특별시 서초구 반포동 19-3 센트럴시티서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 (반포동)6546플디(도산점)2024-04-03 13:52:41I2023-12-04 00:05:00.0즉석판매제조가공업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
926032100003210000-107-2024-002142024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-916서울특별시 서초구 양재동 230 농협하나로클럽서울특별시 서초구 청계산로 10, 하나로마트 양재점 (양재동)6797(주)대산유통시스템 농협유통창동점2024-04-03 15:09:18I2023-12-04 00:05:00.0즉석판매제조가공업203811.145834440070.874223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
926132100003210000-107-2024-002152024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-916서울특별시 서초구 양재동 230 농협하나로클럽서울특별시 서초구 청계산로 10, 농협하나로클럽 양재점 1층 (양재동)6797주식회사우창갤러리아백화점센터시티점2024-04-04 10:09:11I2023-12-04 00:06:00.0즉석판매제조가공업203811.145834440070.874223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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