Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells105550
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory383.0 B

Variable types

Categorical19
Text7
DateTime4
Unsupported7
Numeric6
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
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-18449/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (55.5%)Imbalance
영업상태명 is highly imbalanced (55.5%)Imbalance
상세영업상태코드 is highly imbalanced (55.5%)Imbalance
상세영업상태명 is highly imbalanced (55.5%)Imbalance
남성종사자수 is highly imbalanced (75.3%)Imbalance
여성종사자수 is highly imbalanced (78.7%)Imbalance
영업장주변구분명 is highly imbalanced (86.7%)Imbalance
등급구분명 is highly imbalanced (83.6%)Imbalance
급수시설구분명 is highly imbalanced (79.7%)Imbalance
총인원 is highly imbalanced (64.9%)Imbalance
공장사무직종업원수 is highly imbalanced (50.9%)Imbalance
보증액 is highly imbalanced (72.2%)Imbalance
월세액 is highly imbalanced (72.2%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 927 (9.3%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 5889 (58.9%) missing valuesMissing
소재지면적 has 5064 (50.6%) missing valuesMissing
도로명주소 has 1819 (18.2%) missing valuesMissing
도로명우편번호 has 1857 (18.6%) missing valuesMissing
좌표정보(X) has 118 (1.2%) missing valuesMissing
좌표정보(Y) has 118 (1.2%) missing valuesMissing
공장판매직종업원수 has 7701 (77.0%) missing valuesMissing
공장생산직종업원수 has 7699 (77.0%) missing valuesMissing
다중이용업소여부 has 2172 (21.7%) missing valuesMissing
시설총규모 has 2172 (21.7%) missing valuesMissing
전통업소지정번호 has 10000 (100.0%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (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
공장판매직종업원수 has 2252 (22.5%) zerosZeros
공장생산직종업원수 has 2238 (22.4%) zerosZeros
시설총규모 has 6249 (62.5%) zerosZeros

Reproduction

Analysis started2024-05-11 09:21:12.411317
Analysis finished2024-05-11 09:21:17.597651
Duration5.19 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3220000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3220000
2nd row3220000
3rd row3220000
4th row3220000
5th row3220000

Common Values

ValueCountFrequency (%)
3220000 10000
100.0%

Length

2024-05-11T09:21:17.794932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:18.119763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3220000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:21:18.686319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3220000-107-2001-02156
2nd row3220000-107-2022-00506
3rd row3220000-107-2021-00589
4th row3220000-107-2017-00600
5th row3220000-107-2007-00155
ValueCountFrequency (%)
3220000-107-2001-02156 1
 
< 0.1%
3220000-107-2023-00521 1
 
< 0.1%
3220000-107-2017-00157 1
 
< 0.1%
3220000-107-2017-00357 1
 
< 0.1%
3220000-107-2023-00027 1
 
< 0.1%
3220000-107-2017-00785 1
 
< 0.1%
3220000-107-2010-00142 1
 
< 0.1%
3220000-107-1997-00860 1
 
< 0.1%
3220000-107-2020-00859 1
 
< 0.1%
3220000-107-2022-00186 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T09:21:19.858329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86095
39.1%
2 37791
17.2%
- 30000
 
13.6%
1 20288
 
9.2%
3 13854
 
6.3%
7 13690
 
6.2%
9 4706
 
2.1%
8 3780
 
1.7%
4 3397
 
1.5%
6 3379
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86095
45.3%
2 37791
19.9%
1 20288
 
10.7%
3 13854
 
7.3%
7 13690
 
7.2%
9 4706
 
2.5%
8 3780
 
2.0%
4 3397
 
1.8%
6 3379
 
1.8%
5 3020
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86095
39.1%
2 37791
17.2%
- 30000
 
13.6%
1 20288
 
9.2%
3 13854
 
6.3%
7 13690
 
6.2%
9 4706
 
2.1%
8 3780
 
1.7%
4 3397
 
1.5%
6 3379
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86095
39.1%
2 37791
17.2%
- 30000
 
13.6%
1 20288
 
9.2%
3 13854
 
6.3%
7 13690
 
6.2%
9 4706
 
2.1%
8 3780
 
1.7%
4 3397
 
1.5%
6 3379
 
1.5%
Distinct4007
Distinct (%)40.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1976-03-24 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T09:21:20.339572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:21:21.049716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
9073 
1
927 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 9073
90.7%
1 927
 
9.3%

Length

2024-05-11T09:21:21.475803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:21.836359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 9073
90.7%
1 927
 
9.3%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
9073 
영업/정상
927 

Length

Max length5
Median length2
Mean length2.2781
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 9073
90.7%
영업/정상 927
 
9.3%

Length

2024-05-11T09:21:22.348120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:22.721385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 9073
90.7%
영업/정상 927
 
9.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
9073 
1
927 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 9073
90.7%
1 927
 
9.3%

Length

2024-05-11T09:21:23.276608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:23.576777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 9073
90.7%
1 927
 
9.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
9073 
영업
927 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 9073
90.7%
영업 927
 
9.3%

Length

2024-05-11T09:21:23.991359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:24.442453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 9073
90.7%
영업 927
 
9.3%

폐업일자
Date

MISSING 

Distinct3657
Distinct (%)40.3%
Missing927
Missing (%)9.3%
Memory size156.2 KiB
Minimum1994-02-17 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T09:21:24.915998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:21:25.479979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct2265
Distinct (%)55.1%
Missing5889
Missing (%)58.9%
Memory size156.2 KiB
2024-05-11T09:21:26.702381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.789102
Min length1

Characters and Unicode

Total characters44354
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

Unique1845 ?
Unique (%)44.9%

Sample

1st row02 7989880
2nd row042 222 7292
3rd row34628516
4th row02 557 4636
5th row063 535 1822
ValueCountFrequency (%)
02 1865
 
21.4%
031 757
 
8.7%
070 184
 
2.1%
6949 106
 
1.2%
032 101
 
1.2%
426 93
 
1.1%
055 73
 
0.8%
062 71
 
0.8%
22816340 65
 
0.7%
792 59
 
0.7%
Other values (2426) 5358
61.4%
2024-05-11T09:21:28.148325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6692
15.1%
2 6206
14.0%
5909
13.3%
3 4040
9.1%
5 4027
9.1%
1 3891
8.8%
4 3536
8.0%
6 2962
6.7%
7 2451
 
5.5%
8 2378
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38445
86.7%
Space Separator 5909
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6692
17.4%
2 6206
16.1%
3 4040
10.5%
5 4027
10.5%
1 3891
10.1%
4 3536
9.2%
6 2962
7.7%
7 2451
 
6.4%
8 2378
 
6.2%
9 2262
 
5.9%
Space Separator
ValueCountFrequency (%)
5909
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44354
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6692
15.1%
2 6206
14.0%
5909
13.3%
3 4040
9.1%
5 4027
9.1%
1 3891
8.8%
4 3536
8.0%
6 2962
6.7%
7 2451
 
5.5%
8 2378
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6692
15.1%
2 6206
14.0%
5909
13.3%
3 4040
9.1%
5 4027
9.1%
1 3891
8.8%
4 3536
8.0%
6 2962
6.7%
7 2451
 
5.5%
8 2378
 
5.4%

소재지면적
Text

MISSING 

Distinct1193
Distinct (%)24.2%
Missing5064
Missing (%)50.6%
Memory size156.2 KiB
2024-05-11T09:21:29.197307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.292342
Min length3

Characters and Unicode

Total characters21187
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

Unique862 ?
Unique (%)17.5%

Sample

1st row4.95
2nd row51.12
3rd row45.77
4th row49.58
5th row25.00
ValueCountFrequency (%)
00 817
 
16.6%
3.30 400
 
8.1%
6.60 181
 
3.7%
3.00 139
 
2.8%
10.00 114
 
2.3%
6.00 106
 
2.1%
6.61 87
 
1.8%
9.90 75
 
1.5%
4.95 74
 
1.5%
5.00 72
 
1.5%
Other values (1183) 2871
58.2%
2024-05-11T09:21:30.796787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6234
29.4%
. 4936
23.3%
3 2030
 
9.6%
1 1541
 
7.3%
6 1417
 
6.7%
2 1266
 
6.0%
5 1001
 
4.7%
4 897
 
4.2%
9 867
 
4.1%
8 556
 
2.6%
Other values (2) 442
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16250
76.7%
Other Punctuation 4937
 
23.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6234
38.4%
3 2030
 
12.5%
1 1541
 
9.5%
6 1417
 
8.7%
2 1266
 
7.8%
5 1001
 
6.2%
4 897
 
5.5%
9 867
 
5.3%
8 556
 
3.4%
7 441
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 4936
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 21187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6234
29.4%
. 4936
23.3%
3 2030
 
9.6%
1 1541
 
7.3%
6 1417
 
6.7%
2 1266
 
6.0%
5 1001
 
4.7%
4 897
 
4.2%
9 867
 
4.1%
8 556
 
2.6%
Other values (2) 442
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6234
29.4%
. 4936
23.3%
3 2030
 
9.6%
1 1541
 
7.3%
6 1417
 
6.7%
2 1266
 
6.0%
5 1001
 
4.7%
4 897
 
4.2%
9 867
 
4.1%
8 556
 
2.6%
Other values (2) 442
 
2.1%
Distinct341
Distinct (%)3.4%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T09:21:31.856097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1338937
Min length6

Characters and Unicode

Total characters61296
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

Unique58 ?
Unique (%)0.6%

Sample

1st row135902
2nd row135190
3rd row135724
4th row135827
5th row135860
ValueCountFrequency (%)
135724 937
 
9.4%
135856 708
 
7.1%
135730 662
 
6.6%
135926 526
 
5.3%
135090 515
 
5.2%
135998 454
 
4.5%
135902 414
 
4.1%
135900 351
 
3.5%
135704 303
 
3.0%
135948 247
 
2.5%
Other values (331) 4876
48.8%
2024-05-11T09:21:33.550941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11972
19.5%
5 11814
19.3%
1 10875
17.7%
9 5348
8.7%
0 4724
 
7.7%
8 4046
 
6.6%
7 3199
 
5.2%
2 3042
 
5.0%
4 2903
 
4.7%
6 2035
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59958
97.8%
Dash Punctuation 1338
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11972
20.0%
5 11814
19.7%
1 10875
18.1%
9 5348
8.9%
0 4724
 
7.9%
8 4046
 
6.7%
7 3199
 
5.3%
2 3042
 
5.1%
4 2903
 
4.8%
6 2035
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 1338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11972
19.5%
5 11814
19.3%
1 10875
17.7%
9 5348
8.7%
0 4724
 
7.7%
8 4046
 
6.6%
7 3199
 
5.2%
2 3042
 
5.0%
4 2903
 
4.7%
6 2035
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11972
19.5%
5 11814
19.3%
1 10875
17.7%
9 5348
8.7%
0 4724
 
7.7%
8 4046
 
6.6%
7 3199
 
5.2%
2 3042
 
5.0%
4 2903
 
4.7%
6 2035
 
3.3%
Distinct3139
Distinct (%)31.4%
Missing7
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T09:21:34.637957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length52
Mean length25.75743
Min length16

Characters and Unicode

Total characters257394
Distinct characters404
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2601 ?
Unique (%)26.0%

Sample

1st row서울특별시 강남구 압구정동 494 갤러리아백화점지하
2nd row서울특별시 강남구 세곡동 581
3rd row서울특별시 강남구 압구정동 429 현대백화점본점
4th row서울특별시 강남구 논현동 182-31
5th row서울특별시 강남구 도곡동 950-9 지상1층
ValueCountFrequency (%)
서울특별시 9993
19.9%
강남구 9991
19.9%
압구정동 2140
 
4.3%
삼성동 1747
 
3.5%
대치동 1565
 
3.1%
159-7 1316
 
2.6%
429 1295
 
2.6%
현대백화점 1110
 
2.2%
현대백화점본점 1062
 
2.1%
역삼동 1008
 
2.0%
Other values (3026) 18977
37.8%
2024-05-11T09:21:36.675439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
47975
18.6%
12207
 
4.7%
10580
 
4.1%
10143
 
3.9%
10129
 
3.9%
10109
 
3.9%
10078
 
3.9%
10020
 
3.9%
9995
 
3.9%
9993
 
3.9%
Other values (394) 116165
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162845
63.3%
Space Separator 47975
 
18.6%
Decimal Number 39858
 
15.5%
Dash Punctuation 5721
 
2.2%
Uppercase Letter 672
 
0.3%
Lowercase Letter 95
 
< 0.1%
Close Punctuation 88
 
< 0.1%
Open Punctuation 88
 
< 0.1%
Other Punctuation 49
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12207
 
7.5%
10580
 
6.5%
10143
 
6.2%
10129
 
6.2%
10109
 
6.2%
10078
 
6.2%
10020
 
6.2%
9995
 
6.1%
9993
 
6.1%
5122
 
3.1%
Other values (341) 64469
39.6%
Uppercase Letter
ValueCountFrequency (%)
S 142
21.1%
E 135
20.1%
C 74
11.0%
B 73
10.9%
T 70
10.4%
A 50
 
7.4%
G 28
 
4.2%
L 17
 
2.5%
F 15
 
2.2%
K 10
 
1.5%
Other values (11) 58
8.6%
Lowercase Letter
ValueCountFrequency (%)
s 49
51.6%
g 26
27.4%
e 5
 
5.3%
o 3
 
3.2%
n 2
 
2.1%
a 2
 
2.1%
i 2
 
2.1%
t 1
 
1.1%
b 1
 
1.1%
r 1
 
1.1%
Other values (3) 3
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 8282
20.8%
7 5750
14.4%
9 5369
13.5%
4 5220
13.1%
5 4012
10.1%
2 3568
9.0%
6 2467
 
6.2%
3 2447
 
6.1%
0 1799
 
4.5%
8 944
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 40
81.6%
. 7
 
14.3%
/ 2
 
4.1%
Space Separator
ValueCountFrequency (%)
47975
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5721
100.0%
Close Punctuation
ValueCountFrequency (%)
) 88
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162845
63.3%
Common 93780
36.4%
Latin 769
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12207
 
7.5%
10580
 
6.5%
10143
 
6.2%
10129
 
6.2%
10109
 
6.2%
10078
 
6.2%
10020
 
6.2%
9995
 
6.1%
9993
 
6.1%
5122
 
3.1%
Other values (341) 64469
39.6%
Latin
ValueCountFrequency (%)
S 142
18.5%
E 135
17.6%
C 74
9.6%
B 73
9.5%
T 70
9.1%
A 50
 
6.5%
s 49
 
6.4%
G 28
 
3.6%
g 26
 
3.4%
L 17
 
2.2%
Other values (25) 105
13.7%
Common
ValueCountFrequency (%)
47975
51.2%
1 8282
 
8.8%
7 5750
 
6.1%
- 5721
 
6.1%
9 5369
 
5.7%
4 5220
 
5.6%
5 4012
 
4.3%
2 3568
 
3.8%
6 2467
 
2.6%
3 2447
 
2.6%
Other values (8) 2969
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162844
63.3%
ASCII 94547
36.7%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
47975
50.7%
1 8282
 
8.8%
7 5750
 
6.1%
- 5721
 
6.1%
9 5369
 
5.7%
4 5220
 
5.5%
5 4012
 
4.2%
2 3568
 
3.8%
6 2467
 
2.6%
3 2447
 
2.6%
Other values (42) 3736
 
4.0%
Hangul
ValueCountFrequency (%)
12207
 
7.5%
10580
 
6.5%
10143
 
6.2%
10129
 
6.2%
10109
 
6.2%
10078
 
6.2%
10020
 
6.2%
9995
 
6.1%
9993
 
6.1%
5122
 
3.1%
Other values (340) 64468
39.6%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3535
Distinct (%)43.2%
Missing1819
Missing (%)18.2%
Memory size156.2 KiB
2024-05-11T09:21:37.849496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length63
Mean length38.216599
Min length22

Characters and Unicode

Total characters312650
Distinct characters438
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2961 ?
Unique (%)36.2%

Sample

1st row서울특별시 강남구 헌릉로 569, 지상1층 (세곡동)
2nd row서울특별시 강남구 압구정로 165, 현대백화점본점 식품관 지하1층 (압구정동)
3rd row서울특별시 강남구 강남대로120길 28, 지상2층 (논현동)
4th row서울특별시 강남구 압구정로 343 (압구정동, 갤러리아백화점)
5th row서울특별시 강남구 봉은사로30길 69, 지하1층 B101호 (역삼동, 힐하우스)
ValueCountFrequency (%)
서울특별시 8180
 
13.8%
강남구 8179
 
13.8%
지하1층 4711
 
8.0%
압구정로 1807
 
3.1%
압구정동 1686
 
2.8%
삼성동 1439
 
2.4%
165 1307
 
2.2%
현대백화점 1260
 
2.1%
테헤란로 1176
 
2.0%
517 1145
 
1.9%
Other values (2619) 28305
47.8%
2024-05-11T09:21:39.634468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51094
 
16.3%
1 13427
 
4.3%
12058
 
3.9%
, 9784
 
3.1%
8919
 
2.9%
8842
 
2.8%
8778
 
2.8%
8552
 
2.7%
8497
 
2.7%
8278
 
2.6%
Other values (428) 174421
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195698
62.6%
Space Separator 51094
 
16.3%
Decimal Number 37144
 
11.9%
Other Punctuation 9801
 
3.1%
Open Punctuation 8253
 
2.6%
Close Punctuation 8253
 
2.6%
Uppercase Letter 1870
 
0.6%
Dash Punctuation 293
 
0.1%
Lowercase Letter 237
 
0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12058
 
6.2%
8919
 
4.6%
8842
 
4.5%
8778
 
4.5%
8552
 
4.4%
8497
 
4.3%
8278
 
4.2%
8199
 
4.2%
8183
 
4.2%
8181
 
4.2%
Other values (367) 107211
54.8%
Uppercase Letter
ValueCountFrequency (%)
S 682
36.5%
G 317
17.0%
B 184
 
9.8%
E 183
 
9.8%
T 121
 
6.5%
C 98
 
5.2%
A 74
 
4.0%
W 60
 
3.2%
F 33
 
1.8%
D 26
 
1.4%
Other values (13) 92
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
s 114
48.1%
g 59
24.9%
l 15
 
6.3%
a 9
 
3.8%
e 9
 
3.8%
t 7
 
3.0%
b 5
 
2.1%
w 4
 
1.7%
o 3
 
1.3%
n 2
 
0.8%
Other values (7) 10
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 13427
36.1%
5 4438
 
11.9%
3 3566
 
9.6%
0 3539
 
9.5%
2 3344
 
9.0%
4 2668
 
7.2%
6 2454
 
6.6%
7 2271
 
6.1%
8 819
 
2.2%
9 618
 
1.7%
Other Punctuation
ValueCountFrequency (%)
, 9784
99.8%
. 12
 
0.1%
/ 2
 
< 0.1%
? 2
 
< 0.1%
; 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
51094
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8253
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8253
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 293
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 195698
62.6%
Common 114843
36.7%
Latin 2109
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12058
 
6.2%
8919
 
4.6%
8842
 
4.5%
8778
 
4.5%
8552
 
4.4%
8497
 
4.3%
8278
 
4.2%
8199
 
4.2%
8183
 
4.2%
8181
 
4.2%
Other values (367) 107211
54.8%
Latin
ValueCountFrequency (%)
S 682
32.3%
G 317
15.0%
B 184
 
8.7%
E 183
 
8.7%
T 121
 
5.7%
s 114
 
5.4%
C 98
 
4.6%
A 74
 
3.5%
W 60
 
2.8%
g 59
 
2.8%
Other values (31) 217
 
10.3%
Common
ValueCountFrequency (%)
51094
44.5%
1 13427
 
11.7%
, 9784
 
8.5%
( 8253
 
7.2%
) 8253
 
7.2%
5 4438
 
3.9%
3 3566
 
3.1%
0 3539
 
3.1%
2 3344
 
2.9%
4 2668
 
2.3%
Other values (10) 6477
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 195697
62.6%
ASCII 116950
37.4%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51094
43.7%
1 13427
 
11.5%
, 9784
 
8.4%
( 8253
 
7.1%
) 8253
 
7.1%
5 4438
 
3.8%
3 3566
 
3.0%
0 3539
 
3.0%
2 3344
 
2.9%
4 2668
 
2.3%
Other values (50) 8584
 
7.3%
Hangul
ValueCountFrequency (%)
12058
 
6.2%
8919
 
4.6%
8842
 
4.5%
8778
 
4.5%
8552
 
4.4%
8497
 
4.3%
8278
 
4.2%
8199
 
4.2%
8183
 
4.2%
8181
 
4.2%
Other values (366) 107210
54.8%
Number Forms
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct315
Distinct (%)3.9%
Missing1857
Missing (%)18.6%
Infinite0
Infinite (%)0.0%
Mean6161.638
Minimum4530
Maximum6378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:21:40.197037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4530
5-th percentile6001
Q16029
median6164
Q36279
95-th percentile6365
Maximum6378
Range1848
Interquartile range (IQR)250

Descriptive statistics

Standard deviation121.42605
Coefficient of variation (CV)0.019706781
Kurtosis3.049819
Mean6161.638
Median Absolute Deviation (MAD)119
Skewness-0.30383162
Sum50174218
Variance14744.286
MonotonicityNot monotonic
2024-05-11T09:21:40.742756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6001 1308
13.1%
6164 1302
13.0%
6206 645
 
6.5%
6293 538
 
5.4%
6217 487
 
4.9%
6008 434
 
4.3%
6367 272
 
2.7%
6062 267
 
2.7%
6292 117
 
1.2%
6336 108
 
1.1%
Other values (305) 2665
26.7%
(Missing) 1857
18.6%
ValueCountFrequency (%)
4530 1
 
< 0.1%
5260 1
 
< 0.1%
6000 9
 
0.1%
6001 1308
13.1%
6002 9
 
0.1%
6004 29
 
0.3%
6005 4
 
< 0.1%
6006 2
 
< 0.1%
6008 434
 
4.3%
6009 7
 
0.1%
ValueCountFrequency (%)
6378 3
 
< 0.1%
6376 76
 
0.8%
6373 32
 
0.3%
6369 18
 
0.2%
6368 1
 
< 0.1%
6367 272
2.7%
6366 1
 
< 0.1%
6365 19
 
0.2%
6363 1
 
< 0.1%
6362 1
 
< 0.1%
Distinct4872
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:21:41.476667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32
Mean length8.1659
Min length1

Characters and Unicode

Total characters81659
Distinct characters889
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3797 ?
Unique (%)38.0%

Sample

1st row(주)딤섬
2nd row더원씨푸드 주식회사(한시적)
3rd row오브네계란빵(한시적)
4th row삼부자
5th row세림반찬
ValueCountFrequency (%)
주식회사 651
 
5.4%
주)햇살드림 142
 
1.2%
주)인네이처 112
 
0.9%
감동푸드(한시적 98
 
0.8%
주)해가원 98
 
0.8%
월드푸드(한시적 94
 
0.8%
엠엔에이치 78
 
0.6%
토담 67
 
0.6%
슬로패밀리(한시적 65
 
0.5%
주식회사(한시적 59
 
0.5%
Other values (5224) 10560
87.8%
2024-05-11T09:21:42.931462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 6173
 
7.6%
( 6080
 
7.4%
3690
 
4.5%
3611
 
4.4%
3550
 
4.3%
3219
 
3.9%
2027
 
2.5%
1798
 
2.2%
1456
 
1.8%
1421
 
1.7%
Other values (879) 48634
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64630
79.1%
Close Punctuation 6174
 
7.6%
Open Punctuation 6081
 
7.4%
Space Separator 2027
 
2.5%
Lowercase Letter 1110
 
1.4%
Uppercase Letter 1005
 
1.2%
Other Punctuation 246
 
0.3%
Dash Punctuation 192
 
0.2%
Decimal Number 188
 
0.2%
Connector Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3690
 
5.7%
3611
 
5.6%
3550
 
5.5%
3219
 
5.0%
1798
 
2.8%
1456
 
2.3%
1421
 
2.2%
1223
 
1.9%
1205
 
1.9%
963
 
1.5%
Other values (801) 42494
65.7%
Uppercase Letter
ValueCountFrequency (%)
E 90
 
9.0%
M 81
 
8.1%
A 76
 
7.6%
H 72
 
7.2%
O 64
 
6.4%
S 59
 
5.9%
B 57
 
5.7%
T 55
 
5.5%
L 46
 
4.6%
C 44
 
4.4%
Other values (16) 361
35.9%
Lowercase Letter
ValueCountFrequency (%)
e 176
15.9%
o 89
 
8.0%
a 89
 
8.0%
h 68
 
6.1%
i 64
 
5.8%
m 63
 
5.7%
l 63
 
5.7%
t 61
 
5.5%
n 60
 
5.4%
r 60
 
5.4%
Other values (15) 317
28.6%
Decimal Number
ValueCountFrequency (%)
1 50
26.6%
2 27
14.4%
9 26
13.8%
3 21
11.2%
8 18
 
9.6%
0 16
 
8.5%
5 11
 
5.9%
4 9
 
4.8%
7 6
 
3.2%
6 4
 
2.1%
Other Punctuation
ValueCountFrequency (%)
& 135
54.9%
, 47
 
19.1%
. 32
 
13.0%
? 19
 
7.7%
' 8
 
3.3%
2
 
0.8%
/ 1
 
0.4%
; 1
 
0.4%
: 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 6173
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 6080
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2027
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64626
79.1%
Common 14913
 
18.3%
Latin 2115
 
2.6%
Han 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3690
 
5.7%
3611
 
5.6%
3550
 
5.5%
3219
 
5.0%
1798
 
2.8%
1456
 
2.3%
1421
 
2.2%
1223
 
1.9%
1205
 
1.9%
963
 
1.5%
Other values (799) 42490
65.7%
Latin
ValueCountFrequency (%)
e 176
 
8.3%
E 90
 
4.3%
o 89
 
4.2%
a 89
 
4.2%
M 81
 
3.8%
A 76
 
3.6%
H 72
 
3.4%
h 68
 
3.2%
O 64
 
3.0%
i 64
 
3.0%
Other values (41) 1246
58.9%
Common
ValueCountFrequency (%)
) 6173
41.4%
( 6080
40.8%
2027
 
13.6%
- 192
 
1.3%
& 135
 
0.9%
1 50
 
0.3%
, 47
 
0.3%
. 32
 
0.2%
2 27
 
0.2%
9 26
 
0.2%
Other values (16) 124
 
0.8%
Han
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64624
79.1%
ASCII 17026
 
20.9%
CJK 5
 
< 0.1%
None 3
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 6173
36.3%
( 6080
35.7%
2027
 
11.9%
- 192
 
1.1%
e 176
 
1.0%
& 135
 
0.8%
E 90
 
0.5%
o 89
 
0.5%
a 89
 
0.5%
M 81
 
0.5%
Other values (66) 1894
 
11.1%
Hangul
ValueCountFrequency (%)
3690
 
5.7%
3611
 
5.6%
3550
 
5.5%
3219
 
5.0%
1798
 
2.8%
1456
 
2.3%
1421
 
2.2%
1223
 
1.9%
1205
 
1.9%
963
 
1.5%
Other values (797) 42488
65.7%
CJK
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
None
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct5565
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2000-07-06 00:00:00
Maximum2024-05-09 11:08:30
2024-05-11T09:21:43.477885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:21:43.929295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
U
5389 
I
4610 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
U 5389
53.9%
I 4610
46.1%
D 1
 
< 0.1%

Length

2024-05-11T09:21:44.483159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:44.862041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 5389
53.9%
i 4610
46.1%
d 1
 
< 0.1%
Distinct1699
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T09:21:45.195296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:21:45.778337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

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

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

Length

2024-05-11T09:21:46.367625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:46.728740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 10000
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1538
Distinct (%)15.6%
Missing118
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean204403.99
Minimum198263.91
Maximum211820.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:21:47.141647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198263.91
5-th percentile202358.51
Q1203342.7
median204538.14
Q3205210.36
95-th percentile207748.49
Maximum211820.88
Range13556.97
Interquartile range (IQR)1867.6569

Descriptive statistics

Standard deviation1641.6431
Coefficient of variation (CV)0.0080313652
Kurtosis1.1079957
Mean204403.99
Median Absolute Deviation (MAD)748.55676
Skewness0.88873377
Sum2.0199202 × 109
Variance2694992
MonotonicityNot monotonic
2024-05-11T09:21:47.800373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
202358.505687227 1430
 
14.3%
205210.358779172 1317
 
13.2%
204669.543366778 851
 
8.5%
204749.304517964 619
 
6.2%
203470.848439305 617
 
6.2%
204213.643236507 566
 
5.7%
209052.072465426 303
 
3.0%
203789.588128352 260
 
2.6%
205130.591678902 160
 
1.6%
204538.144891563 141
 
1.4%
Other values (1528) 3618
36.2%
ValueCountFrequency (%)
198263.90839194 1
 
< 0.1%
201620.446225572 2
 
< 0.1%
201646.385389914 3
 
< 0.1%
201650.787158848 1
 
< 0.1%
201653.207482566 1
 
< 0.1%
201664.929814711 1
 
< 0.1%
201667.786866215 16
0.2%
201670.69965165 1
 
< 0.1%
201677.130384848 1
 
< 0.1%
201677.925882649 1
 
< 0.1%
ValueCountFrequency (%)
211820.878022259 1
 
< 0.1%
210442.413455881 1
 
< 0.1%
209628.773156947 2
< 0.1%
209428.428164038 1
 
< 0.1%
209423.649311203 3
< 0.1%
209409.371497729 1
 
< 0.1%
209384.708472884 1
 
< 0.1%
209376.158650195 1
 
< 0.1%
209371.036034514 2
< 0.1%
209349.691167499 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1536
Distinct (%)15.5%
Missing118
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean444973.44
Minimum439796.04
Maximum450960.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:21:48.398342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439796.04
5-th percentile442693.09
Q1443682.97
median445154.42
Q3446796.13
95-th percentile447369.58
Maximum450960.76
Range11164.718
Interquartile range (IQR)3113.1542

Descriptive statistics

Standard deviation1718.5663
Coefficient of variation (CV)0.0038621773
Kurtosis-0.93351794
Mean444973.44
Median Absolute Deviation (MAD)1622.8572
Skewness-0.049621352
Sum4.3972276 × 109
Variance2953470.2
MonotonicityNot monotonic
2024-05-11T09:21:48.972114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447232.955697694 1430
 
14.3%
445154.42225208 1317
 
13.2%
443873.621189048 851
 
8.5%
443058.194678364 619
 
6.2%
447369.579851952 617
 
6.2%
444113.028210915 566
 
5.7%
442797.138150563 303
 
3.0%
446796.128299612 260
 
2.6%
445590.096837802 160
 
1.6%
442942.853505354 141
 
1.4%
Other values (1526) 3618
36.2%
ValueCountFrequency (%)
439796.044686133 1
 
< 0.1%
440112.987487173 2
 
< 0.1%
440114.723537769 6
0.1%
440137.950597011 1
 
< 0.1%
440151.497594716 1
 
< 0.1%
440158.402062979 1
 
< 0.1%
440182.898235134 2
 
< 0.1%
440183.87349816 2
 
< 0.1%
440208.558412381 3
< 0.1%
440222.022016185 1
 
< 0.1%
ValueCountFrequency (%)
450960.762964932 1
 
< 0.1%
449831.785568227 1
 
< 0.1%
447864.763737276 10
0.1%
447782.51322707 5
0.1%
447748.161018109 8
0.1%
447680.961855446 1
 
< 0.1%
447663.86257666 4
 
< 0.1%
447649.978394541 3
 
< 0.1%
447521.520319158 12
0.1%
447491.028995399 10
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
즉석판매제조가공업
7828 
<NA>
2172 

Length

Max length9
Median length9
Mean length7.914
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 7828
78.3%
<NA> 2172
 
21.7%

Length

2024-05-11T09:21:49.524729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:50.375638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 7828
78.3%
na 2172
 
21.7%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8991 
0
980 
1
 
19
2
 
10

Length

Max length4
Median length4
Mean length3.6973
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8991
89.9%
0 980
 
9.8%
1 19
 
0.2%
2 10
 
0.1%

Length

2024-05-11T09:21:50.804470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:51.110824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8991
89.9%
0 980
 
9.8%
1 19
 
0.2%
2 10
 
0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8992 
0
979 
1
 
22
2
 
5
4
 
2

Length

Max length4
Median length4
Mean length3.6976
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8992
89.9%
0 979
 
9.8%
1 22
 
0.2%
2 5
 
0.1%
4 2
 
< 0.1%

Length

2024-05-11T09:21:51.612897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:52.002810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8992
89.9%
0 979
 
9.8%
1 22
 
0.2%
2 5
 
< 0.1%
4 2
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9530 
기타
 
403
아파트지역
 
36
주택가주변
 
30
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9264
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9530
95.3%
기타 403
 
4.0%
아파트지역 36
 
0.4%
주택가주변 30
 
0.3%
유흥업소밀집지역 1
 
< 0.1%

Length

2024-05-11T09:21:52.496678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:52.942215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9530
95.3%
기타 403
 
4.0%
아파트지역 36
 
0.4%
주택가주변 30
 
0.3%
유흥업소밀집지역 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9530 
기타
 
234
자율
 
220
 
16

Length

Max length4
Median length4
Mean length3.9044
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9530
95.3%
기타 234
 
2.3%
자율 220
 
2.2%
16
 
0.2%

Length

2024-05-11T09:21:53.449162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:53.881265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9530
95.3%
기타 234
 
2.3%
자율 220
 
2.2%
16
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9200 
상수도전용
 
797
상수도(음용)지하수(주방용)겸용
 
2
지하수전용
 
1

Length

Max length17
Median length4
Mean length4.0824
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9200
92.0%
상수도전용 797
 
8.0%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T09:21:54.328572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:54.788397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9200
92.0%
상수도전용 797
 
8.0%
상수도(음용)지하수(주방용)겸용 2
 
< 0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9339 
0
 
661

Length

Max length4
Median length4
Mean length3.8017
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9339
93.4%
0 661
 
6.6%

Length

2024-05-11T09:21:55.143878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:55.527259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9339
93.4%
0 661
 
6.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7702 
0
2298 

Length

Max length4
Median length4
Mean length3.3106
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7702
77.0%
0 2298
 
23.0%

Length

2024-05-11T09:21:56.085896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:56.683333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7702
77.0%
0 2298
 
23.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7702 
0
2297 
2
 
1

Length

Max length4
Median length4
Mean length3.3106
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7702
77.0%
0 2297
 
23.0%
2 1
 
< 0.1%

Length

2024-05-11T09:21:57.220311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:21:57.720501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7702
77.0%
0 2297
 
23.0%
2 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.3%
Missing7701
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean0.04784689
Minimum0
Maximum10
Zeros2252
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:21:58.157124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.40057446
Coefficient of variation (CV)8.3720062
Kurtosis225.89082
Mean0.04784689
Median Absolute Deviation (MAD)0
Skewness12.78523
Sum110
Variance0.1604599
MonotonicityNot monotonic
2024-05-11T09:21:58.618711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2252
 
22.5%
2 25
 
0.2%
1 11
 
0.1%
3 5
 
0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
10 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 7701
77.0%
ValueCountFrequency (%)
0 2252
22.5%
1 11
 
0.1%
2 25
 
0.2%
3 5
 
0.1%
4 2
 
< 0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
6 1
 
< 0.1%
5 2
 
< 0.1%
4 2
 
< 0.1%
3 5
 
0.1%
2 25
 
0.2%
1 11
 
0.1%
0 2252
22.5%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.3%
Missing7699
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean0.056931769
Minimum0
Maximum10
Zeros2238
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:21:59.081050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4157455
Coefficient of variation (CV)7.3025221
Kurtosis208.22556
Mean0.056931769
Median Absolute Deviation (MAD)0
Skewness12.042909
Sum131
Variance0.17284432
MonotonicityNot monotonic
2024-05-11T09:21:59.529399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2238
 
22.4%
2 35
 
0.4%
1 19
 
0.2%
3 5
 
0.1%
4 1
 
< 0.1%
10 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 7699
77.0%
ValueCountFrequency (%)
0 2238
22.4%
1 19
 
0.2%
2 35
 
0.4%
3 5
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
3 5
 
0.1%
2 35
 
0.4%
1 19
 
0.2%
0 2238
22.4%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6457 
자가
2664 
임대
879 

Length

Max length4
Median length4
Mean length3.2914
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6457
64.6%
자가 2664
26.6%
임대 879
 
8.8%

Length

2024-05-11T09:21:59.985702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:22:00.339219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6457
64.6%
자가 2664
26.6%
임대 879
 
8.8%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8370 
0
1627 
5000000
 
1
40000000
 
1
15000000
 
1

Length

Max length8
Median length4
Mean length3.513
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8370
83.7%
0 1627
 
16.3%
5000000 1
 
< 0.1%
40000000 1
 
< 0.1%
15000000 1
 
< 0.1%

Length

2024-05-11T09:22:00.683361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:22:01.012920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8370
83.7%
0 1627
 
16.3%
5000000 1
 
< 0.1%
40000000 1
 
< 0.1%
15000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8370 
0
1627 
400000
 
1
300000
 
1
500000
 
1

Length

Max length6
Median length4
Mean length3.5125
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8370
83.7%
0 1627
 
16.3%
400000 1
 
< 0.1%
300000 1
 
< 0.1%
500000 1
 
< 0.1%

Length

2024-05-11T09:22:01.432738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:22:01.857497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8370
83.7%
0 1627
 
16.3%
400000 1
 
< 0.1%
300000 1
 
< 0.1%
500000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing2172
Missing (%)21.7%
Memory size97.7 KiB
False
7828 
(Missing)
2172 
ValueCountFrequency (%)
False 7828
78.3%
(Missing) 2172
 
21.7%
2024-05-11T09:22:02.328446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct520
Distinct (%)6.6%
Missing2172
Missing (%)21.7%
Infinite0
Infinite (%)0.0%
Mean4.2846717
Minimum0
Maximum366.5
Zeros6249
Zeros (%)62.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:22:02.816104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile26.337
Maximum366.5
Range366.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.478674
Coefficient of variation (CV)3.8459595
Kurtosis110.23519
Mean4.2846717
Median Absolute Deviation (MAD)0
Skewness8.4996338
Sum33540.41
Variance271.54669
MonotonicityNot monotonic
2024-05-11T09:22:03.398728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 6249
62.5%
3.3 249
 
2.5%
6.6 89
 
0.9%
10.0 60
 
0.6%
3.0 48
 
0.5%
6.0 45
 
0.4%
9.9 44
 
0.4%
5.0 36
 
0.4%
33.0 35
 
0.4%
20.0 34
 
0.3%
Other values (510) 939
 
9.4%
(Missing) 2172
 
21.7%
ValueCountFrequency (%)
0.0 6249
62.5%
0.39 1
 
< 0.1%
0.5 1
 
< 0.1%
0.66 1
 
< 0.1%
1.0 4
 
< 0.1%
1.02 1
 
< 0.1%
1.2 1
 
< 0.1%
1.47 1
 
< 0.1%
1.5 6
 
0.1%
1.6 1
 
< 0.1%
ValueCountFrequency (%)
366.5 1
< 0.1%
350.0 1
< 0.1%
285.94 1
< 0.1%
234.12 1
< 0.1%
222.29 1
< 0.1%
219.84 1
< 0.1%
218.46 1
< 0.1%
198.0 1
< 0.1%
197.32 1
< 0.1%
194.58 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
78632200003220000-107-2001-0215620010613<NA>3폐업2폐업20100802<NA><NA><NA>02 79898804.95135902서울특별시 강남구 압구정동 494 갤러리아백화점지하<NA><NA>(주)딤섬2001-09-18 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업203470.848439447369.579852즉석판매제조가공업<NA><NA>기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
966132200003220000-107-2022-0050620220629<NA>3폐업2폐업20220706<NA><NA><NA><NA><NA>135190서울특별시 강남구 세곡동 581서울특별시 강남구 헌릉로 569, 지상1층 (세곡동)6376더원씨푸드 주식회사(한시적)2022-07-07 04:15:09U2021-12-06 23:02:00.0즉석판매제조가공업208882.24587440405.743741<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
866932200003220000-107-2021-0058920210713<NA>3폐업2폐업20210722<NA><NA><NA><NA><NA>135724서울특별시 강남구 압구정동 429 현대백화점본점서울특별시 강남구 압구정로 165, 현대백화점본점 식품관 지하1층 (압구정동)6001오브네계란빵(한시적)2021-07-23 04:15:09U2021-07-25 02:40:00.0즉석판매제조가공업202358.505687447232.955698즉석판매제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
445832200003220000-107-2017-0060020170901<NA>3폐업2폐업20170907<NA><NA><NA>042 222 7292<NA>135827서울특별시 강남구 논현동 182-31서울특별시 강남구 강남대로120길 28, 지상2층 (논현동)6119삼부자2017-09-08 04:15:25I2018-08-31 23:59:59.0즉석판매제조가공업202212.978176445019.536621즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
197332200003220000-107-2007-0015520070823<NA>3폐업2폐업20080424<NA><NA><NA>3462851651.12135860서울특별시 강남구 도곡동 950-9 지상1층<NA><NA>세림반찬2007-08-23 16:47:43I2018-08-31 23:59:59.0즉석판매제조가공업203093.235319442697.728869즉석판매제조가공업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
370732200003220000-107-2016-0038320161031<NA>3폐업2폐업20161130<NA><NA><NA><NA><NA>135906서울특별시 강남구 압구정동 494서울특별시 강남구 압구정로 343 (압구정동, 갤러리아백화점)6008(주)한설식품2016-12-01 04:15:26I2018-08-31 23:59:59.0즉석판매제조가공업203470.848439447369.579852즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
945532200003220000-107-2022-002992022-04-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>45.77135-915서울특별시 강남구 역삼동 669-7 힐하우스서울특별시 강남구 봉은사로30길 69, 지하1층 B101호 (역삼동, 힐하우스)6140여수에프앤비2024-03-13 11:15:24U2023-12-02 23:06:00.0즉석판매제조가공업203520.045844444972.043726<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
305232200003220000-107-2013-0002120130312<NA>3폐업2폐업20141015<NA><NA><NA>02 557 4636<NA>135843서울특별시 강남구 대치동 920서울특별시 강남구 선릉로72길 12, 지상1층 (대치동)6199더 야채가게2013-03-12 10:14:24I2018-08-31 23:59:59.0즉석판매제조가공업204553.499652444219.018401즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
642232200003220000-107-2019-0073120190902<NA>3폐업2폐업20190930<NA><NA><NA><NA><NA>135730서울특별시 강남구 삼성동 159-7 현대백화점서울특별시 강남구 테헤란로 517, 현대백화점 지하1층 (삼성동)6164(주)햇살드림 한시적2019-10-01 04:15:10U2019-10-03 02:40:00.0즉석판매제조가공업205210.358779445154.422252즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
354932200003220000-107-2016-0022520160803<NA>3폐업2폐업20160831<NA><NA><NA><NA><NA>135856서울특별시 강남구 도곡동 467-17서울특별시 강남구 언주로30길 57, 지하1층 (도곡동, 타워팰리스 스타수퍼)6293송원지이2016-09-01 04:15:25I2018-08-31 23:59:59.0즉석판매제조가공업204749.304518443058.194678즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
757432200003220000-107-2020-007472020-07-21<NA>3폐업2폐업2024-03-20<NA><NA><NA><NA>39.74135-994서울특별시 강남구 개포동 186-4 세종빌딩서울특별시 강남구 개포로82길 13-9, 세종빌딩 지상1층 113호 (개포동)6329슈퍼키친 개포점2024-03-20 13:42:54U2023-12-02 22:02:00.0즉석판매제조가공업205924.357258442939.847403<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
347232200003220000-107-2016-0014820160621<NA>3폐업2폐업20170512<NA><NA><NA><NA>178.30135822서울특별시 강남구 논현동 122-8서울특별시 강남구 학동로4길 15, 지하1층 B02-01호 (논현동, 동화상가)6110(주)커틀러리2017-05-12 13:37:57I2018-08-31 23:59:59.0즉석판매제조가공업202010.01034445368.131755즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>자가<NA><NA>N0.0<NA><NA><NA>
841532200003220000-107-2021-0033520210421<NA>3폐업2폐업20210508<NA><NA><NA><NA><NA>135948서울특별시 강남구 청담동 4-1 피엔폴루스서울특별시 강남구 도산대로 442, 피엔폴루스 지하1층 (청담동)6062감동푸드(한시적)2021-05-09 04:15:10U2021-05-11 02:40:00.0즉석판매제조가공업203789.588128446796.1283즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
814932200003220000-107-2021-000672021-01-25<NA>3폐업2폐업2023-11-27<NA><NA><NA><NA>13.40135-957서울특별시 강남구 청담동 128-6 rio128서울특별시 강남구 도산대로101길 22, rio128 지하1층 (청담동)6013엘세뇨르둘세2023-11-27 12:31:28U2022-10-31 22:09:00.0즉석판매제조가공업204613.569346447119.83574<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1101232200003220000-107-2023-008712023-12-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.11135-930서울특별시 강남구 역삼동 792-13서울특별시 강남구 논현로71길 43, 지상2층 (역삼동)6249바이무이2023-12-26 11:54:42I2022-11-01 22:08:00.0즉석판매제조가공업203122.295663443536.460562<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
227232200003220000-107-2009-0003420090227<NA>3폐업2폐업20100714<NA><NA><NA>02 531 284133.30135998서울특별시 강남구 대치동 937-0 롯데백화점지하1층<NA><NA>신풍유통(주)2009-02-27 13:28:25I2018-08-31 23:59:59.0즉석판매제조가공업204669.543367443873.621189즉석판매제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
118432200003220000-107-2003-0013920031001<NA>3폐업2폐업20100802<NA><NA><NA>344940406.61135902서울특별시 강남구 압구정동 494-0 갤러리아백화점지하1층<NA><NA>(주)비앤지유통2003-10-01 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업203470.848439447369.579852즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
940232200003220000-107-2022-002462022-04-05<NA>3폐업2폐업2023-05-12<NA><NA><NA><NA>15.00135-812서울특별시 강남구 논현동 10-7서울특별시 강남구 논현로149길 31, 1동 지상1층 101-1호 (논현동)6040주식회사 히어로파운더2023-05-12 14:48:59U2022-12-04 23:04:00.0즉석판매제조가공업202224.687391446167.054385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
926032200003220000-107-2022-0010420220216<NA>3폐업2폐업20220301<NA><NA><NA>02 313 3129<NA>135724서울특별시 강남구 압구정동 429 현대백화점본점서울특별시 강남구 압구정로 165, 현대백화점본점 지하1층 (압구정동)6001대신에프앤(한시적)2022-03-02 04:15:10U2022-03-04 02:40:00.0즉석판매제조가공업202358.505687447232.955698즉석판매제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
862232200003220000-107-2021-0054220210628<NA>3폐업2폐업20210711<NA><NA><NA>031 543 6513<NA>135730서울특별시 강남구 삼성동 159-7 현대백화점서울특별시 강남구 테헤란로 517, 현대백화점 무역센터점 지하1층 식품관일부호 (삼성동)6164(주)명진푸드시스템(한시적)2021-07-12 04:15:08U2021-07-14 02:40:00.0즉석판매제조가공업205210.358779445154.422252즉석판매제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>