Overview

Dataset statistics

Number of variables26
Number of observations30
Missing cells158
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory224.4 B

Variable types

Categorical9
Numeric4
DateTime3
Unsupported4
Text6

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),점포구분명
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-18704/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
폐업일자 is highly imbalanced (59.9%)Imbalance
인허가취소일자 has 30 (100.0%) missing valuesMissing
휴업시작일자 has 30 (100.0%) missing valuesMissing
휴업종료일자 has 30 (100.0%) missing valuesMissing
재개업일자 has 30 (100.0%) missing valuesMissing
전화번호 has 1 (3.3%) missing valuesMissing
소재지면적 has 2 (6.7%) missing valuesMissing
소재지우편번호 has 22 (73.3%) missing valuesMissing
지번주소 has 2 (6.7%) missing valuesMissing
도로명주소 has 1 (3.3%) missing valuesMissing
도로명우편번호 has 10 (33.3%) missing valuesMissing
관리번호 has unique valuesUnique
사업장명 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

Reproduction

Analysis started2024-05-11 06:09:16.976617
Analysis finished2024-05-11 06:09:17.434359
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
3020000
30 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 30
100.0%

Length

2024-05-11T15:09:17.540831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:17.705606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 30
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0079687 × 1018
Minimum1.970302 × 1018
Maximum2.022302 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:09:17.859091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.970302 × 1018
5-th percentile1.988902 × 1018
Q12.005552 × 1018
median2.008302 × 1018
Q32.013802 × 1018
95-th percentile2.022302 × 1018
Maximum2.022302 × 1018
Range5.2000008 × 1016
Interquartile range (IQR)8.2500021 × 1015

Descriptive statistics

Standard deviation1.0844779 × 1016
Coefficient of variation (CV)0.0054008707
Kurtosis4.3751317
Mean2.0079687 × 1018
Median Absolute Deviation (MAD)4.000001 × 1015
Skewness-1.5894241
Sum4.8988281 × 1018
Variance1.1760924 × 1032
MonotonicityStrictly increasing
2024-05-11T15:09:18.063090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1970302007407500005 1
 
3.3%
2008302009507500005 1
 
3.3%
2022302015007500003 1
 
3.3%
2022302015007500002 1
 
3.3%
2022302015007500001 1
 
3.3%
2021302015007500001 1
 
3.3%
2020302015007500001 1
 
3.3%
2014302009507500003 1
 
3.3%
2014302009507500002 1
 
3.3%
2014302009507500001 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1970302007407500005 1
3.3%
1985302007407500008 1
3.3%
1993302007407500001 1
3.3%
2001302007407500001 1
3.3%
2001302007407500002 1
3.3%
2004302007407500001 1
3.3%
2004302007407500002 1
3.3%
2005302007407500001 1
3.3%
2006302007407500001 1
3.3%
2006302007407500002 1
3.3%
ValueCountFrequency (%)
2022302015007500003 1
3.3%
2022302015007500002 1
3.3%
2022302015007500001 1
3.3%
2021302015007500001 1
3.3%
2020302015007500001 1
3.3%
2014302009507500003 1
3.3%
2014302009507500002 1
3.3%
2014302009507500001 1
3.3%
2012302009507500003 1
3.3%
2012302009507500002 1
3.3%

인허가일자
Date

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1960-02-17 00:00:00
Maximum2022-08-08 00:00:00
2024-05-11T15:09:18.295609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:18.570199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
25 
3
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 25
83.3%
3 5
 
16.7%

Length

2024-05-11T15:09:18.791605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:18.938632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
83.3%
3 5
 
16.7%

영업상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
영업/정상
25 
폐업
5 

Length

Max length5
Median length5
Mean length4.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 25
83.3%
폐업 5
 
16.7%

Length

2024-05-11T15:09:19.112545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:19.265229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 25
83.3%
폐업 5
 
16.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
25 
3
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 25
83.3%
3 5
 
16.7%

Length

2024-05-11T15:09:19.405393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:19.564351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
83.3%
3 5
 
16.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
정상영업
25 
폐업처리
5 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업처리
2nd row정상영업
3rd row정상영업
4th row폐업처리
5th row폐업처리

Common Values

ValueCountFrequency (%)
정상영업 25
83.3%
폐업처리 5
 
16.7%

Length

2024-05-11T15:09:19.720997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:19.887360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 25
83.3%
폐업처리 5
 
16.7%

폐업일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
25 
20120802
 
1
20131220
 
1
20140402
 
1
20221011
 
1

Length

Max length8
Median length4
Mean length4.6666667
Min length4

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row20120802
2nd row<NA>
3rd row<NA>
4th row20131220
5th row20140402

Common Values

ValueCountFrequency (%)
<NA> 25
83.3%
20120802 1
 
3.3%
20131220 1
 
3.3%
20140402 1
 
3.3%
20221011 1
 
3.3%
20180612 1
 
3.3%

Length

2024-05-11T15:09:20.053659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:20.229498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
83.3%
20120802 1
 
3.3%
20131220 1
 
3.3%
20140402 1
 
3.3%
20221011 1
 
3.3%
20180612 1
 
3.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-05-11T15:09:20.525926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.896552
Min length7

Characters and Unicode

Total characters316
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row027980401
2nd row02 7037091
3rd row02 704 5858
4th row02)718-9555
5th row02-2012-0101
ValueCountFrequency (%)
02 5
 
13.2%
7037091 2
 
5.3%
027135602 1
 
2.6%
02)702-3411 1
 
2.6%
02)795-7501 1
 
2.6%
709-7501 1
 
2.6%
0220772800 1
 
2.6%
02-2290-5853 1
 
2.6%
02-793-9633 1
 
2.6%
027980401 1
 
2.6%
Other values (23) 23
60.5%
2024-05-11T15:09:21.051290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 64
20.3%
2 47
14.9%
7 33
10.4%
- 30
9.5%
1 29
9.2%
3 21
 
6.6%
5 16
 
5.1%
6 16
 
5.1%
9 15
 
4.7%
8 14
 
4.4%
Other values (3) 31
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 266
84.2%
Dash Punctuation 30
 
9.5%
Space Separator 13
 
4.1%
Close Punctuation 7
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 64
24.1%
2 47
17.7%
7 33
12.4%
1 29
10.9%
3 21
 
7.9%
5 16
 
6.0%
6 16
 
6.0%
9 15
 
5.6%
8 14
 
5.3%
4 11
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 316
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 64
20.3%
2 47
14.9%
7 33
10.4%
- 30
9.5%
1 29
9.2%
3 21
 
6.6%
5 16
 
5.1%
6 16
 
5.1%
9 15
 
4.7%
8 14
 
4.4%
Other values (3) 31
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 64
20.3%
2 47
14.9%
7 33
10.4%
- 30
9.5%
1 29
9.2%
3 21
 
6.6%
5 16
 
5.1%
6 16
 
5.1%
9 15
 
4.7%
8 14
 
4.4%
Other values (3) 31
9.8%

소재지면적
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)100.0%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean12367.764
Minimum106
Maximum106290.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:09:21.247751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106
5-th percentile142.7665
Q1804.55
median4851.855
Q310892.933
95-th percentile53926.614
Maximum106290.33
Range106184.33
Interquartile range (IQR)10088.383

Descriptive statistics

Standard deviation22666.563
Coefficient of variation (CV)1.8327131
Kurtosis11.500578
Mean12367.764
Median Absolute Deviation (MAD)4404.03
Skewness3.2615705
Sum346297.4
Variance5.1377309 × 108
MonotonicityNot monotonic
2024-05-11T15:09:21.432727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
3327.67 1
 
3.3%
321.65 1
 
3.3%
9879.92 1
 
3.3%
17084.22 1
 
3.3%
199.8 1
 
3.3%
8500.52 1
 
3.3%
106.0 1
 
3.3%
643.3 1
 
3.3%
121.7 1
 
3.3%
181.89 1
 
3.3%
Other values (18) 18
60.0%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
106.0 1
3.3%
121.7 1
3.3%
181.89 1
3.3%
199.8 1
3.3%
321.65 1
3.3%
574.0 1
3.3%
643.3 1
3.3%
858.3 1
3.3%
1209.2 1
3.3%
2688.42 1
3.3%
ValueCountFrequency (%)
106290.33 1
3.3%
62555.57 1
3.3%
37901.41 1
3.3%
17898.53 1
3.3%
17084.22 1
3.3%
14561.78 1
3.3%
11669.19 1
3.3%
10634.18 1
3.3%
9879.92 1
3.3%
8500.52 1
3.3%

소재지우편번호
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing22
Missing (%)73.3%
Memory size372.0 B
2024-05-11T15:09:21.605363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.125
Min length6

Characters and Unicode

Total characters49
Distinct characters7
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

Unique6 ?
Unique (%)75.0%

Sample

1st row140140
2nd row140200
3rd row140013
4th row140113
5th row140026
ValueCountFrequency (%)
140026 2
25.0%
140140 1
12.5%
140200 1
12.5%
140013 1
12.5%
140113 1
12.5%
140-012 1
12.5%
140160 1
12.5%
2024-05-11T15:09:21.935345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
32.7%
1 14
28.6%
4 9
18.4%
2 4
 
8.2%
6 3
 
6.1%
3 2
 
4.1%
- 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
98.0%
Dash Punctuation 1
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
33.3%
1 14
29.2%
4 9
18.8%
2 4
 
8.3%
6 3
 
6.2%
3 2
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
32.7%
1 14
28.6%
4 9
18.4%
2 4
 
8.2%
6 3
 
6.1%
3 2
 
4.1%
- 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
32.7%
1 14
28.6%
4 9
18.4%
2 4
 
8.2%
6 3
 
6.1%
3 2
 
4.1%
- 1
 
2.0%

지번주소
Text

MISSING 

Distinct26
Distinct (%)92.9%
Missing2
Missing (%)6.7%
Memory size372.0 B
2024-05-11T15:09:22.226726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.5
Min length18

Characters and Unicode

Total characters658
Distinct characters55
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)85.7%

Sample

1st row서울특별시 용산구 이촌동 300번지 27 호
2nd row서울특별시 용산구 한강로1가 191호
3rd row서울특별시 용산구 한강로2가 413호
4th row서울특별시 용산구 한강로3가 40번지 969호
5th row서울특별시 용산구 산천동 202호
ValueCountFrequency (%)
서울특별시 28
20.6%
용산구 28
20.6%
한강로3가 9
 
6.6%
한강로2가 5
 
3.7%
40번지 3
 
2.2%
용산동6가 3
 
2.2%
나진상가 3
 
2.2%
이태원동 2
 
1.5%
30호 2
 
1.5%
1호 2
 
1.5%
Other values (42) 51
37.5%
2024-05-11T15:09:22.702978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
17.5%
산 32
 
4.9%
용 31
 
4.7%
서 29
 
4.4%
특 28
 
4.3%
별 28
 
4.3%
시 28
 
4.3%
구 28
 
4.3%
울 28
 
4.3%
1 24
 
3.6%
Other values (45) 287
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
62.2%
Decimal Number 126
 
19.1%
Space Separator 115
 
17.5%
Dash Punctuation 6
 
0.9%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 32
 
7.8%
용 31
 
7.6%
서 29
 
7.1%
특 28
 
6.8%
별 28
 
6.8%
시 28
 
6.8%
구 28
 
6.8%
울 28
 
6.8%
호 22
 
5.4%
가 22
 
5.4%
Other values (31) 133
32.5%
Decimal Number
ValueCountFrequency (%)
1 24
19.0%
3 21
16.7%
9 18
14.3%
6 16
12.7%
2 15
11.9%
0 12
9.5%
5 7
 
5.6%
4 6
 
4.8%
7 5
 
4.0%
8 2
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 409
62.2%
Common 247
37.5%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 32
 
7.8%
용 31
 
7.6%
서 29
 
7.1%
특 28
 
6.8%
별 28
 
6.8%
시 28
 
6.8%
구 28
 
6.8%
울 28
 
6.8%
호 22
 
5.4%
가 22
 
5.4%
Other values (31) 133
32.5%
Common
ValueCountFrequency (%)
115
46.6%
1 24
 
9.7%
3 21
 
8.5%
9 18
 
7.3%
6 16
 
6.5%
2 15
 
6.1%
0 12
 
4.9%
5 7
 
2.8%
4 6
 
2.4%
- 6
 
2.4%
Other values (2) 7
 
2.8%
Latin
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 409
62.2%
ASCII 249
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
46.2%
1 24
 
9.6%
3 21
 
8.4%
9 18
 
7.2%
6 16
 
6.4%
2 15
 
6.0%
0 12
 
4.8%
5 7
 
2.8%
4 6
 
2.4%
- 6
 
2.4%
Other values (4) 9
 
3.6%
Hangul
ValueCountFrequency (%)
산 32
 
7.8%
용 31
 
7.6%
서 29
 
7.1%
특 28
 
6.8%
별 28
 
6.8%
시 28
 
6.8%
구 28
 
6.8%
울 28
 
6.8%
호 22
 
5.4%
가 22
 
5.4%
Other values (31) 133
32.5%

도로명주소
Text

MISSING 

Distinct26
Distinct (%)89.7%
Missing1
Missing (%)3.3%
Memory size372.0 B
2024-05-11T15:09:23.075845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length32
Mean length27.896552
Min length16

Characters and Unicode

Total characters809
Distinct characters80
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)79.3%

Sample

1st row서울특별시 용산구 이촌로 224 (이촌동)
2nd row서울특별시 용산구 청파로 113-12 (한강로2가)
3rd row서울특별시 용산구 청파로20길 83 (한강로3가)
4th row서울특별시 용산구 원효로 51 (산천동)
5th row서울특별시 용산구 한강대로23길 55 (한강로3가)
ValueCountFrequency (%)
서울특별시 29
18.2%
용산구 28
17.6%
한강로3가 9
 
5.7%
청파로 9
 
5.7%
이촌로 5
 
3.1%
한강로2가 5
 
3.1%
나진상가 3
 
1.9%
352 3
 
1.9%
용산동6가 3
 
1.9%
이태원동 2
 
1.3%
Other values (56) 63
39.6%
2024-05-11T15:09:23.596433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
130
 
16.1%
로 46
 
5.7%
산 33
 
4.1%
용 32
 
4.0%
1 32
 
4.0%
서 31
 
3.8%
특 29
 
3.6%
별 29
 
3.6%
시 29
 
3.6%
울 29
 
3.6%
Other values (70) 389
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
59.8%
Space Separator 130
 
16.1%
Decimal Number 124
 
15.3%
Open Punctuation 28
 
3.5%
Close Punctuation 28
 
3.5%
Other Punctuation 9
 
1.1%
Uppercase Letter 3
 
0.4%
Dash Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 46
 
9.5%
산 33
 
6.8%
용 32
 
6.6%
서 31
 
6.4%
특 29
 
6.0%
별 29
 
6.0%
시 29
 
6.0%
울 29
 
6.0%
구 28
 
5.8%
가 24
 
5.0%
Other values (51) 174
36.0%
Decimal Number
ValueCountFrequency (%)
1 32
25.8%
2 26
21.0%
3 21
16.9%
5 10
 
8.1%
0 10
 
8.1%
7 8
 
6.5%
4 6
 
4.8%
6 5
 
4.0%
9 4
 
3.2%
8 2
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
L 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 484
59.8%
Common 322
39.8%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 46
 
9.5%
산 33
 
6.8%
용 32
 
6.6%
서 31
 
6.4%
특 29
 
6.0%
별 29
 
6.0%
시 29
 
6.0%
울 29
 
6.0%
구 28
 
5.8%
가 24
 
5.0%
Other values (51) 174
36.0%
Common
ValueCountFrequency (%)
130
40.4%
1 32
 
9.9%
( 28
 
8.7%
) 28
 
8.7%
2 26
 
8.1%
3 21
 
6.5%
5 10
 
3.1%
0 10
 
3.1%
, 9
 
2.8%
7 8
 
2.5%
Other values (6) 20
 
6.2%
Latin
ValueCountFrequency (%)
C 1
33.3%
L 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
59.8%
ASCII 325
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
130
40.0%
1 32
 
9.8%
( 28
 
8.6%
) 28
 
8.6%
2 26
 
8.0%
3 21
 
6.5%
5 10
 
3.1%
0 10
 
3.1%
, 9
 
2.8%
7 8
 
2.5%
Other values (9) 23
 
7.1%
Hangul
ValueCountFrequency (%)
로 46
 
9.5%
산 33
 
6.8%
용 32
 
6.6%
서 31
 
6.4%
특 29
 
6.0%
별 29
 
6.0%
시 29
 
6.0%
울 29
 
6.0%
구 28
 
5.8%
가 24
 
5.0%
Other values (51) 174
36.0%

도로명우편번호
Text

MISSING 

Distinct17
Distinct (%)85.0%
Missing10
Missing (%)33.3%
Memory size372.0 B
2024-05-11T15:09:23.842225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.65
Min length5

Characters and Unicode

Total characters113
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

Unique14 ?
Unique (%)70.0%

Sample

1st row140745
2nd row140780
3rd row140702
4th row04371
5th row140780
ValueCountFrequency (%)
04371 2
 
10.0%
140780 2
 
10.0%
04370 2
 
10.0%
140-012 1
 
5.0%
04402 1
 
5.0%
04387 1
 
5.0%
04372 1
 
5.0%
140752 1
 
5.0%
140-111 1
 
5.0%
140745 1
 
5.0%
Other values (7) 7
35.0%
2024-05-11T15:09:24.618759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 30
26.5%
4 25
22.1%
1 17
15.0%
7 13
11.5%
2 8
 
7.1%
3 7
 
6.2%
8 7
 
6.2%
5 2
 
1.8%
- 2
 
1.8%
6 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 111
98.2%
Dash Punctuation 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 30
27.0%
4 25
22.5%
1 17
15.3%
7 13
11.7%
2 8
 
7.2%
3 7
 
6.3%
8 7
 
6.3%
5 2
 
1.8%
6 1
 
0.9%
9 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 113
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 30
26.5%
4 25
22.1%
1 17
15.0%
7 13
11.5%
2 8
 
7.1%
3 7
 
6.2%
8 7
 
6.2%
5 2
 
1.8%
- 2
 
1.8%
6 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 30
26.5%
4 25
22.1%
1 17
15.0%
7 13
11.5%
2 8
 
7.1%
3 7
 
6.2%
8 7
 
6.2%
5 2
 
1.8%
- 2
 
1.8%
6 1
 
0.9%

사업장명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-05-11T15:09:24.963200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length9.9333333
Min length4

Characters and Unicode

Total characters298
Distinct characters112
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row한강상가
2nd row국제센터아케이드
3rd row(주)전자타운
4th row터미널전자상가
5th row삼성테마트
ValueCountFrequency (%)
주식회사 2
 
4.2%
fresh 2
 
4.2%
the 2
 
4.2%
gs 2
 
4.2%
롯데프레시 1
 
2.1%
쇼핑센터 1
 
2.1%
신동아쇼핑센터 1
 
2.1%
주)농협유통하나로클럽용산점 1
 
2.1%
롯데쇼핑(주)롯데슈퍼 1
 
2.1%
신동아점 1
 
2.1%
Other values (34) 34
70.8%
2024-05-11T15:09:25.546690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
6.0%
점 10
 
3.4%
이 9
 
3.0%
( 9
 
3.0%
) 9
 
3.0%
주 8
 
2.7%
데 7
 
2.3%
가 7
 
2.3%
롯 7
 
2.3%
자 6
 
2.0%
Other values (102) 208
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 217
72.8%
Uppercase Letter 37
 
12.4%
Space Separator 18
 
6.0%
Open Punctuation 9
 
3.0%
Close Punctuation 9
 
3.0%
Lowercase Letter 5
 
1.7%
Decimal Number 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 10
 
4.6%
이 9
 
4.1%
주 8
 
3.7%
데 7
 
3.2%
가 7
 
3.2%
롯 7
 
3.2%
자 6
 
2.8%
아 6
 
2.8%
산 6
 
2.8%
핑 5
 
2.3%
Other values (81) 146
67.3%
Uppercase Letter
ValueCountFrequency (%)
S 5
13.5%
A 4
10.8%
E 4
10.8%
H 4
10.8%
R 4
10.8%
L 3
8.1%
K 2
 
5.4%
F 2
 
5.4%
T 2
 
5.4%
I 2
 
5.4%
Other values (3) 5
13.5%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
v 1
20.0%
n 1
20.0%
u 1
20.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Decimal Number
ValueCountFrequency (%)
9 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 217
72.8%
Latin 42
 
14.1%
Common 39
 
13.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 10
 
4.6%
이 9
 
4.1%
주 8
 
3.7%
데 7
 
3.2%
가 7
 
3.2%
롯 7
 
3.2%
자 6
 
2.8%
아 6
 
2.8%
산 6
 
2.8%
핑 5
 
2.3%
Other values (81) 146
67.3%
Latin
ValueCountFrequency (%)
S 5
11.9%
A 4
 
9.5%
E 4
 
9.5%
H 4
 
9.5%
R 4
 
9.5%
L 3
 
7.1%
e 2
 
4.8%
K 2
 
4.8%
F 2
 
4.8%
T 2
 
4.8%
Other values (7) 10
23.8%
Common
ValueCountFrequency (%)
18
46.2%
( 9
23.1%
) 9
23.1%
9 3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 217
72.8%
ASCII 81
 
27.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
22.2%
( 9
11.1%
) 9
11.1%
S 5
 
6.2%
A 4
 
4.9%
E 4
 
4.9%
H 4
 
4.9%
R 4
 
4.9%
L 3
 
3.7%
9 3
 
3.7%
Other values (11) 18
22.2%
Hangul
ValueCountFrequency (%)
점 10
 
4.6%
이 9
 
4.1%
주 8
 
3.7%
데 7
 
3.2%
가 7
 
3.2%
롯 7
 
3.2%
자 6
 
2.8%
아 6
 
2.8%
산 6
 
2.8%
핑 5
 
2.3%
Other values (81) 146
67.3%

최종수정일자
Date

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2007-07-21 10:15:07
Maximum2024-02-05 09:28:30
2024-05-11T15:09:25.719186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:25.913229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
I
17 
U
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 17
56.7%
U 13
43.3%

Length

2024-05-11T15:09:26.095373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:26.245439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 17
56.7%
u 13
43.3%

데이터갱신일자
Date

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-02 00:07:00
2024-05-11T15:09:26.365056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:09:26.540330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
전문점
9 
구분없음
7 
시장
4 
그 밖의 대규모점포
4 
쇼핑센터
3 
Other values (3)
3 

Length

Max length10
Median length5
Mean length4.2333333
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row시장
2nd row그 밖의 대규모점포
3rd row그 밖의 대규모점포
4th row전문점
5th row그 밖의 대규모점포

Common Values

ValueCountFrequency (%)
전문점 9
30.0%
구분없음 7
23.3%
시장 4
13.3%
그 밖의 대규모점포 4
13.3%
쇼핑센터 3
 
10.0%
백화점 1
 
3.3%
복합쇼핑몰 1
 
3.3%
대형마트 1
 
3.3%

Length

2024-05-11T15:09:26.716493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:26.898319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문점 9
23.7%
구분없음 7
18.4%
시장 4
10.5%
그 4
10.5%
밖의 4
10.5%
대규모점포 4
10.5%
쇼핑센터 3
 
7.9%
백화점 1
 
2.6%
복합쇼핑몰 1
 
2.6%
대형마트 1
 
2.6%

좌표정보(X)
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197408.28
Minimum195547.14
Maximum200431.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:09:27.076006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum195547.14
5-th percentile196377.26
Q1196719.01
median196942.75
Q3197613.42
95-th percentile199689.1
Maximum200431.15
Range4884.0053
Interquartile range (IQR)894.41361

Descriptive statistics

Standard deviation1147.0321
Coefficient of variation (CV)0.0058104558
Kurtosis0.85299657
Mean197408.28
Median Absolute Deviation (MAD)334.6579
Skewness1.1961819
Sum5922248.3
Variance1315682.6
MonotonicityNot monotonic
2024-05-11T15:09:27.235807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
198622.89264988 3
 
10.0%
196697.031086973 2
 
6.7%
196775.639878418 2
 
6.7%
196762.077394917 2
 
6.7%
196385.232032928 1
 
3.3%
197221.439324261 1
 
3.3%
196727.535753619 1
 
3.3%
197071.403205622 1
 
3.3%
196605.511573689 1
 
3.3%
197514.145785647 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
195547.140326252 1
3.3%
196370.746398773 1
3.3%
196385.232032928 1
3.3%
196605.511573689 1
3.3%
196610.663839509 1
3.3%
196697.031086973 2
6.7%
196716.165873094 1
3.3%
196727.535753619 1
3.3%
196762.077394917 2
6.7%
196775.639878418 2
6.7%
ValueCountFrequency (%)
200431.145594386 1
 
3.3%
199955.429742269 1
 
3.3%
199363.595799729 1
 
3.3%
199051.158829761 1
 
3.3%
198622.89264988 3
10.0%
197646.514005514 1
 
3.3%
197514.145785647 1
 
3.3%
197450.277644237 1
 
3.3%
197443.881826007 1
 
3.3%
197221.439324261 1
 
3.3%

좌표정보(Y)
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447661.24
Minimum446114.16
Maximum449892.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-05-11T15:09:27.418311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446114.16
5-th percentile446114.16
Q1447366.42
median447865.68
Q3447970.98
95-th percentile448688.13
Maximum449892.56
Range3778.4025
Interquartile range (IQR)604.56085

Descriptive statistics

Standard deviation813.47193
Coefficient of variation (CV)0.0018171596
Kurtosis1.4004817
Mean447661.24
Median Absolute Deviation (MAD)154.28883
Skewness-0.055037511
Sum13429837
Variance661736.58
MonotonicityNot monotonic
2024-05-11T15:09:27.664106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
446114.155238838 3
 
10.0%
447931.108267379 2
 
6.7%
447984.6345458 2
 
6.7%
447480.039577359 2
 
6.7%
447938.19246116 1
 
3.3%
446524.508385914 1
 
3.3%
447868.128308607 1
 
3.3%
447073.62284187 1
 
3.3%
447841.270074498 1
 
3.3%
448264.322314594 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
446114.155238838 3
10.0%
446437.197878548 1
 
3.3%
446524.508385914 1
 
3.3%
447073.62284187 1
 
3.3%
447219.161582186 1
 
3.3%
447328.548832245 1
 
3.3%
447480.039577359 2
6.7%
447742.348636253 1
 
3.3%
447763.414163072 1
 
3.3%
447841.270074498 1
 
3.3%
ValueCountFrequency (%)
449892.557718372 1
3.3%
448884.957554763 1
3.3%
448447.558967085 1
3.3%
448264.322314594 1
3.3%
448050.926289223 1
3.3%
447984.6345458 2
6.7%
447976.775939762 1
3.3%
447953.601666521 1
3.3%
447938.19246116 1
3.3%
447931.108267379 2
6.7%

점포구분명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
17 
대규모점포
11 
준대규모점포
2 

Length

Max length6
Median length4
Mean length4.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
56.7%
대규모점포 11
36.7%
준대규모점포 2
 
6.7%

Length

2024-05-11T15:09:27.924881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:09:28.109875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
56.7%
대규모점포 11
36.7%
준대규모점포 2
 
6.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03020000197030200740750000519701130<NA>3폐업3폐업처리20120802<NA><NA><NA>0279804014858.45<NA>서울특별시 용산구 이촌동 300번지 27 호서울특별시 용산구 이촌로 224 (이촌동)<NA>한강상가2012-08-02 14:23:00I2018-08-31 23:59:59.0시장197450.277644446437.197879대규모점포
13020000198530200740750000819850701<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로1가 191호<NA><NA>국제센터아케이드2007-07-21 10:15:07I2018-08-31 23:59:59.0그 밖의 대규모점포197646.514006447909.07065<NA>
23020000199330200740750000119930413<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 7037091<NA><NA>서울특별시 용산구 한강로2가 413호서울특별시 용산구 청파로 113-12 (한강로2가)<NA>(주)전자타운2007-07-21 10:15:07I2018-08-31 23:59:59.0그 밖의 대규모점포196775.639878447984.634546<NA>
33020000200130200740750000120010524<NA>3폐업3폐업처리20131220<NA><NA><NA>02 704 585814561.78<NA>서울특별시 용산구 한강로3가 40번지 969호서울특별시 용산구 청파로20길 83 (한강로3가)140745터미널전자상가2013-12-20 16:12:19I2018-08-31 23:59:59.0전문점196610.66384447742.348636대규모점포
43020000200130200740750000220010804<NA>3폐업3폐업처리20140402<NA><NA><NA>02)718-95553386.0<NA>서울특별시 용산구 산천동 202호서울특별시 용산구 원효로 51 (산천동)<NA>삼성테마트2014-04-03 09:51:54I2018-08-31 23:59:59.0그 밖의 대규모점포195547.140326447976.77594대규모점포
53020000200430200740750000120040921<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2012-0101106290.33<NA>서울특별시 용산구 한강로3가 40번지 999호서울특별시 용산구 한강대로23길 55 (한강로3가)140780아이파크몰(I PARK MALL)2022-08-11 09:29:42U2021-12-07 23:03:00.0쇼핑센터196762.077395447480.039577<NA>
63020000200430200740750000220041222<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 799 71146876.34<NA>서울특별시 용산구 한강로2가 191호서울특별시 용산구 한강대로 92 (한강로2가)140702LS Avenue2012-10-15 09:45:52I2018-08-31 23:59:59.0그 밖의 대규모점포197099.381482447328.548832대규모점포
73020000200530200740750000119930413<NA>1영업/정상1정상영업<NA><NA><NA><NA>703709110634.18<NA>서울특별시 용산구 한강로2가 413호서울특별시 용산구 청파로 113-12 (한강로2가)<NA>전자타운2014-10-24 10:37:15I2018-08-31 23:59:59.0전문점196775.639878447984.634546대규모점포
83020000200630200740750000119600217<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 794 5682574.0<NA>서울특별시 용산구 이태원동 56번지 9호서울특별시 용산구 이태원로14길 6 (이태원동)<NA>이태원시장2012-03-30 14:02:23I2018-08-31 23:59:59.0시장199051.15883447953.601667대규모점포
93020000200630200740750000219871126<NA>1영업/정상1정상영업<NA><NA><NA><NA>02)718-711337901.41<NA>서울특별시 용산구 한강로2가 15번지 14호서울특별시 용산구 새창로 181 (한강로2가, 선인상가)04371선인상가2022-10-07 14:43:20U2021-10-31 00:09:00.0전문점196839.641743447863.232025<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
203020000201230200950750000220120320<NA>3폐업3폐업처리20221011<NA><NA><NA>02-2290-5853858.3140026서울특별시 용산구 용산동6가 69번지 167호서울특별시 용산구 이촌로 352 (용산동6가)140026롯데쇼핑(주)롯데슈퍼 신동아점2022-10-17 14:06:31U2021-10-30 23:09:00.0구분없음198622.89265446114.155239<NA>
213020000201230200950750000320120323<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-793-9633181.89<NA>서울특별시 용산구 한남동 631번지 5호 허준빌딩서울특별시 용산구 대사관로34길 26, 허준빌딩 1층 (한남동)04402롯데슈퍼 한남점(가맹점)2019-03-19 14:40:19U2019-03-21 02:40:00.0구분없음200431.145594447763.414163준대규모점포
223020000201430200950750000120140731<NA>1영업/정상1정상영업<NA><NA><NA><NA>027135602121.7140160서울특별시 용산구 남영동 93번지 30호서울특별시 한강대로77길 12140807롯데프레시 갈월점2022-09-21 09:08:42U2021-12-08 22:03:00.0구분없음197443.881826448884.957555<NA>
23302000020143020095075000022014-07-31<NA>1영업/정상1정상영업<NA><NA><NA><NA>027115602643.3<NA><NA>서울특별시 용산구 백범로 341 (원효로1가)140-111롯데쇼핑(주)롯데슈퍼원효로점2023-05-04 15:08:19U2022-12-05 00:07:00.0구분없음197045.849468448447.558967<NA>
243020000201430200950750000320140805<NA>3폐업3폐업처리20180612<NA><NA><NA>02-796-8331106.0<NA><NA>서울특별시 용산구 한강대로 205 (한강로1가)140752롯데마켓999 용산파크자이가맹점2018-06-12 11:32:44I2018-08-31 23:59:59.0구분없음197514.145786448264.322315준대규모점포
253020000202030201500750000120200813<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2689-00358500.52<NA>서울특별시 용산구 한강로3가 2-8서울특별시 용산구 청파로 100, 12동 2층 (한강로3가)04372(주)서부티엔디2020-08-13 09:12:59I2020-08-15 00:23:13.0전문점196605.511574447841.270074대규모점포
263020000202130201500750000120210415<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2676199.8<NA>서울특별시 용산구 한강로3가 63-70서울특별시 용산구 서빙고로 17, 용산해링턴스퀘어 C동 1층 111~115호 (한강로3가)04387GS THE FRESH 용산해링턴점2022-04-29 14:07:52U2021-12-05 00:03:00.0구분없음197071.403206447073.622842<NA>
273020000202230201500750000120220502<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-716-387217084.22<NA>서울특별시 용산구 한강로3가 3-23 나진상가서울특별시 용산구 청파로 112, 나진상가 (한강로3가)04371용산라이프시티피에프브이 주식회사2022-05-03 13:40:25I2021-12-05 00:07:00.0전문점196727.535754447868.128309<NA>
283020000202230201500750000220220629<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3670-08019879.92<NA>서울특별시 용산구 한강로3가 1-1 나진상가서울특별시 용산구 청파로 109, 나진상가 14동 (한강로3가)04370나진전자월드상가2022-06-29 10:52:49I2021-12-07 00:01:00.0전문점196697.031087447931.108267<NA>
293020000202230201500750000320220808<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2364321.65<NA>서울특별시 용산구 이촌동 302-52 LG프라자서울특별시 용산구 이촌로 200, LG프라자 지하1층 (이촌동)04427GS THE FRESH 용산이촌점2022-09-27 16:49:41U2021-12-08 22:09:00.0구분없음197221.439324446524.508386<NA>