Overview

Dataset statistics

Number of variables26
Number of observations31
Missing cells114
Missing cells (%)14.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory223.3 B

Variable types

Categorical10
Numeric4
DateTime4
Unsupported2
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
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-18705/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (79.4%)Imbalance
재개업일자 is highly imbalanced (79.4%)Imbalance
폐업일자 has 22 (71.0%) missing valuesMissing
휴업시작일자 has 31 (100.0%) missing valuesMissing
휴업종료일자 has 31 (100.0%) missing valuesMissing
전화번호 has 2 (6.5%) missing valuesMissing
소재지우편번호 has 14 (45.2%) missing valuesMissing
지번주소 has 1 (3.2%) missing valuesMissing
도로명주소 has 3 (9.7%) missing valuesMissing
도로명우편번호 has 10 (32.3%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
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
소재지면적 has 7 (22.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:23:13.487201
Analysis finished2024-05-11 06:23:14.250510
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
3030000
31 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3030000
2nd row3030000
3rd row3030000
4th row3030000
5th row3030000

Common Values

ValueCountFrequency (%)
3030000 31
100.0%

Length

2024-05-11T15:23:14.350268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:14.519910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3030000 31
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0038514 × 1018
Minimum1.962303 × 1018
Maximum2.023303 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T15:23:14.700577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.962303 × 1018
5-th percentile1.965803 × 1018
Q12.000803 × 1018
median2.008303 × 1018
Q32.012303 × 1018
95-th percentile2.023303 × 1018
Maximum2.023303 × 1018
Range6.1000003 × 1016
Interquartile range (IQR)1.15 × 1016

Descriptive statistics

Standard deviation1.7312498 × 1016
Coefficient of variation (CV)0.0086396117
Kurtosis0.76632361
Mean2.0038514 × 1018
Median Absolute Deviation (MAD)6 × 1015
Skewness-1.2343796
Sum6.7791611 × 1018
Variance2.9972259 × 1032
MonotonicityStrictly increasing
2024-05-11T15:23:15.010127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1962303007407500002 1
 
3.2%
1962303010307500001 1
 
3.2%
2023303010307500004 1
 
3.2%
2023303010307500003 1
 
3.2%
2023303010307500002 1
 
3.2%
2023303010307500001 1
 
3.2%
2021303010307500001 1
 
3.2%
2018303010307500001 1
 
3.2%
2014303010307500001 1
 
3.2%
2012303010307500005 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1962303007407500002 1
3.2%
1962303010307500001 1
3.2%
1969303010307500001 1
3.2%
1979303010307500006 1
3.2%
1980303010307500005 1
3.2%
1982303010307500001 1
3.2%
1998303010307500001 1
3.2%
2000303010307500001 1
3.2%
2001303010307500002 1
3.2%
2005303007407500001 1
3.2%
ValueCountFrequency (%)
2023303010307500004 1
3.2%
2023303010307500003 1
3.2%
2023303010307500002 1
3.2%
2023303010307500001 1
3.2%
2021303010307500001 1
3.2%
2018303010307500001 1
3.2%
2014303010307500001 1
3.2%
2012303010307500005 1
3.2%
2012303010307500004 1
3.2%
2012303010307500003 1
3.2%

인허가일자
Date

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1962-01-21 00:00:00
Maximum2023-09-14 00:00:00
2024-05-11T15:23:15.251715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:15.535453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
30 
20170308
 
1

Length

Max length8
Median length4
Mean length4.1290323
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
96.8%
20170308 1
 
3.2%

Length

2024-05-11T15:23:15.896538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:16.144050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
96.8%
20170308 1
 
3.2%

영업상태코드
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
20 
3
9 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 20
64.5%
3 9
29.0%
4 2
 
6.5%

Length

2024-05-11T15:23:16.402850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:16.618943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
64.5%
3 9
29.0%
4 2
 
6.5%

영업상태명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업/정상
20 
폐업
9 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length4.7096774
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 20
64.5%
폐업 9
29.0%
취소/말소/만료/정지/중지 2
 
6.5%

Length

2024-05-11T15:23:16.845389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:17.082721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 20
64.5%
폐업 9
29.0%
취소/말소/만료/정지/중지 2
 
6.5%

상세영업상태코드
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
20 
3
9 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 20
64.5%
3 9
29.0%
4 2
 
6.5%

Length

2024-05-11T15:23:17.306669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:17.499542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
64.5%
3 9
29.0%
4 2
 
6.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
정상영업
20 
폐업처리
9 
직권취소
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 20
64.5%
폐업처리 9
29.0%
직권취소 2
 
6.5%

Length

2024-05-11T15:23:17.712491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:17.906033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 20
64.5%
폐업처리 9
29.0%
직권취소 2
 
6.5%

폐업일자
Date

MISSING 

Distinct9
Distinct (%)100.0%
Missing22
Missing (%)71.0%
Memory size380.0 B
Minimum2008-05-22 00:00:00
Maximum2023-08-18 00:00:00
2024-05-11T15:23:18.113097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:18.339951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
30 
20110705
 
1

Length

Max length8
Median length4
Mean length4.1290323
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
96.8%
20110705 1
 
3.2%

Length

2024-05-11T15:23:18.656297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:18.887578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
96.8%
20110705 1
 
3.2%

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing2
Missing (%)6.5%
Memory size380.0 B
2024-05-11T15:23:19.150445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length10.551724
Min length2

Characters and Unicode

Total characters306
Distinct characters15
Distinct categories6 ?
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 row00024644426
2nd row02 22525302
3rd row2291-6754
4th row2297-3811
5th row02-2210-4100
ValueCountFrequency (%)
02 3
 
9.4%
00024644426 1
 
3.1%
02-2200-6000 1
 
3.1%
22525302 1
 
3.1%
02-2297-5180 1
 
3.1%
02-2253-8541 1
 
3.1%
02-380-9842 1
 
3.1%
6454-6301 1
 
3.1%
2207-9991 1
 
3.1%
2282-0161 1
 
3.1%
Other values (20) 20
62.5%
2024-05-11T15:23:19.754005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 67
21.9%
0 43
14.1%
- 34
11.1%
4 30
9.8%
9 22
 
7.2%
5 22
 
7.2%
3 19
 
6.2%
1 17
 
5.6%
8 16
 
5.2%
6 15
 
4.9%
Other values (5) 21
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 263
85.9%
Dash Punctuation 34
 
11.1%
Space Separator 5
 
1.6%
Close Punctuation 2
 
0.7%
Math Symbol 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 67
25.5%
0 43
16.3%
4 30
11.4%
9 22
 
8.4%
5 22
 
8.4%
3 19
 
7.2%
1 17
 
6.5%
8 16
 
6.1%
6 15
 
5.7%
7 12
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 306
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 67
21.9%
0 43
14.1%
- 34
11.1%
4 30
9.8%
9 22
 
7.2%
5 22
 
7.2%
3 19
 
6.2%
1 17
 
5.6%
8 16
 
5.2%
6 15
 
4.9%
Other values (5) 21
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 67
21.9%
0 43
14.1%
- 34
11.1%
4 30
9.8%
9 22
 
7.2%
5 22
 
7.2%
3 19
 
6.2%
1 17
 
5.6%
8 16
 
5.2%
6 15
 
4.9%
Other values (5) 21
 
6.9%

소재지면적
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3849.3652
Minimum0
Maximum25910
Zeros7
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T15:23:20.009048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1121.275
median467.23
Q35740.655
95-th percentile15657.32
Maximum25910
Range25910
Interquartile range (IQR)5619.38

Descriptive statistics

Standard deviation6165.7224
Coefficient of variation (CV)1.6017505
Kurtosis4.7961744
Mean3849.3652
Median Absolute Deviation (MAD)467.23
Skewness2.131715
Sum119330.32
Variance38016133
MonotonicityNot monotonic
2024-05-11T15:23:20.267243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 7
22.6%
467.23 2
 
6.5%
2861.0 1
 
3.2%
99.0 1
 
3.2%
158.8 1
 
3.2%
327.3 1
 
3.2%
143.55 1
 
3.2%
13996.64 1
 
3.2%
378.11 1
 
3.2%
409.9 1
 
3.2%
Other values (14) 14
45.2%
ValueCountFrequency (%)
0.0 7
22.6%
99.0 1
 
3.2%
143.55 1
 
3.2%
158.8 1
 
3.2%
264.3 1
 
3.2%
293.34 1
 
3.2%
327.3 1
 
3.2%
378.11 1
 
3.2%
409.9 1
 
3.2%
467.23 2
 
6.5%
ValueCountFrequency (%)
25910.0 1
3.2%
17318.0 1
3.2%
13996.64 1
3.2%
11573.0 1
3.2%
8495.01 1
3.2%
7960.0 1
3.2%
7717.09 1
3.2%
5873.69 1
3.2%
5607.62 1
3.2%
4049.55 1
3.2%

소재지우편번호
Text

MISSING 

Distinct15
Distinct (%)88.2%
Missing14
Missing (%)45.2%
Memory size380.0 B
2024-05-11T15:23:20.553454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3529412
Min length6

Characters and Unicode

Total characters108
Distinct characters10
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

Unique13 ?
Unique (%)76.5%

Sample

1st row133805
2nd row133091
3rd row133809
4th row133120
5th row133-120
ValueCountFrequency (%)
133120 2
 
11.8%
133170 2
 
11.8%
133805 1
 
5.9%
133091 1
 
5.9%
133809 1
 
5.9%
133-120 1
 
5.9%
133050 1
 
5.9%
133040 1
 
5.9%
133-071 1
 
5.9%
133819 1
 
5.9%
Other values (5) 5
29.4%
2024-05-11T15:23:21.079648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 34
31.5%
1 30
27.8%
0 17
15.7%
8 6
 
5.6%
- 6
 
5.6%
7 4
 
3.7%
9 4
 
3.7%
2 3
 
2.8%
5 3
 
2.8%
4 1
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
94.4%
Dash Punctuation 6
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 34
33.3%
1 30
29.4%
0 17
16.7%
8 6
 
5.9%
7 4
 
3.9%
9 4
 
3.9%
2 3
 
2.9%
5 3
 
2.9%
4 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 34
31.5%
1 30
27.8%
0 17
15.7%
8 6
 
5.6%
- 6
 
5.6%
7 4
 
3.7%
9 4
 
3.7%
2 3
 
2.8%
5 3
 
2.8%
4 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 34
31.5%
1 30
27.8%
0 17
15.7%
8 6
 
5.6%
- 6
 
5.6%
7 4
 
3.7%
9 4
 
3.7%
2 3
 
2.8%
5 3
 
2.8%
4 1
 
0.9%

지번주소
Text

MISSING 

Distinct28
Distinct (%)93.3%
Missing1
Missing (%)3.2%
Memory size380.0 B
2024-05-11T15:23:21.521683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length25.6
Min length21

Characters and Unicode

Total characters768
Distinct characters79
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

Unique26 ?
Unique (%)86.7%

Sample

1st row서울특별시 성동구 성수동2가 335번지
2nd row서울특별시 성동구 금호동3가 332번지
3rd row서울특별시 성동구 금호동1가 128번지 1호
4th row서울특별시 성동구 금호동4가 548번지 1호
5th row서울특별시 성동구 용답동 234번지 한국자동차매매센터
ValueCountFrequency (%)
서울특별시 30
19.2%
성동구 30
19.2%
1호 7
 
4.5%
행당동 6
 
3.8%
성수동2가 4
 
2.6%
용답동 3
 
1.9%
5호 3
 
1.9%
옥수동 2
 
1.3%
1070 2
 
1.3%
하왕십리동 2
 
1.3%
Other values (57) 67
42.9%
2024-05-11T15:23:22.244877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
16.4%
동 63
 
8.2%
1 41
 
5.3%
성 40
 
5.2%
서 31
 
4.0%
울 31
 
4.0%
특 30
 
3.9%
별 30
 
3.9%
시 30
 
3.9%
구 30
 
3.9%
Other values (69) 316
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 499
65.0%
Decimal Number 139
 
18.1%
Space Separator 126
 
16.4%
Dash Punctuation 2
 
0.3%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 63
 
12.6%
성 40
 
8.0%
서 31
 
6.2%
울 31
 
6.2%
특 30
 
6.0%
별 30
 
6.0%
시 30
 
6.0%
구 30
 
6.0%
지 25
 
5.0%
번 25
 
5.0%
Other values (55) 164
32.9%
Decimal Number
ValueCountFrequency (%)
1 41
29.5%
3 18
12.9%
2 16
 
11.5%
6 11
 
7.9%
4 11
 
7.9%
5 11
 
7.9%
8 9
 
6.5%
0 9
 
6.5%
9 8
 
5.8%
7 5
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 499
65.0%
Common 267
34.8%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 63
 
12.6%
성 40
 
8.0%
서 31
 
6.2%
울 31
 
6.2%
특 30
 
6.0%
별 30
 
6.0%
시 30
 
6.0%
구 30
 
6.0%
지 25
 
5.0%
번 25
 
5.0%
Other values (55) 164
32.9%
Common
ValueCountFrequency (%)
126
47.2%
1 41
 
15.4%
3 18
 
6.7%
2 16
 
6.0%
6 11
 
4.1%
4 11
 
4.1%
5 11
 
4.1%
8 9
 
3.4%
0 9
 
3.4%
9 8
 
3.0%
Other values (2) 7
 
2.6%
Latin
ValueCountFrequency (%)
L 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 499
65.0%
ASCII 269
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
46.8%
1 41
 
15.2%
3 18
 
6.7%
2 16
 
5.9%
6 11
 
4.1%
4 11
 
4.1%
5 11
 
4.1%
8 9
 
3.3%
0 9
 
3.3%
9 8
 
3.0%
Other values (4) 9
 
3.3%
Hangul
ValueCountFrequency (%)
동 63
 
12.6%
성 40
 
8.0%
서 31
 
6.2%
울 31
 
6.2%
특 30
 
6.0%
별 30
 
6.0%
시 30
 
6.0%
구 30
 
6.0%
지 25
 
5.0%
번 25
 
5.0%
Other values (55) 164
32.9%

도로명주소
Text

MISSING 

Distinct28
Distinct (%)100.0%
Missing3
Missing (%)9.7%
Memory size380.0 B
2024-05-11T15:23:22.746124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length35.5
Mean length31.071429
Min length13

Characters and Unicode

Total characters870
Distinct characters94
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)100.0%

Sample

1st row서울특별시 성동구 성수이로 32-15 (성수동2가)
2nd row서울특별시 성동구 독서당로 303-11 (금호동3가)
3rd row서울특별시 성동구 행당로 35 (금호동1가)
4th row서울특별시 성동구 독서당로 302 (금호동4가)
5th row서울특별시 성동구 자동차시장1길 70 (용답동, 장안평중고자동차시장)
ValueCountFrequency (%)
서울특별시 28
 
17.1%
성동구 27
 
16.5%
왕십리로 7
 
4.3%
행당동 7
 
4.3%
성수동1가 4
 
2.4%
행당로 4
 
2.4%
독서당로 3
 
1.8%
하왕십리동 3
 
1.8%
금호동3가 2
 
1.2%
옥수동 2
 
1.2%
Other values (65) 77
47.0%
2024-05-11T15:23:23.452971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
 
15.6%
동 61
 
7.0%
1 36
 
4.1%
성 36
 
4.1%
서 32
 
3.7%
시 30
 
3.4%
울 29
 
3.3%
( 29
 
3.3%
) 29
 
3.3%
특 28
 
3.2%
Other values (84) 424
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 527
60.6%
Space Separator 136
 
15.6%
Decimal Number 122
 
14.0%
Open Punctuation 29
 
3.3%
Close Punctuation 29
 
3.3%
Other Punctuation 19
 
2.2%
Uppercase Letter 6
 
0.7%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 61
 
11.6%
성 36
 
6.8%
서 32
 
6.1%
시 30
 
5.7%
울 29
 
5.5%
특 28
 
5.3%
별 28
 
5.3%
구 27
 
5.1%
로 26
 
4.9%
당 15
 
2.8%
Other values (67) 215
40.8%
Decimal Number
ValueCountFrequency (%)
1 36
29.5%
3 20
16.4%
0 17
13.9%
2 15
12.3%
4 9
 
7.4%
7 7
 
5.7%
5 6
 
4.9%
6 5
 
4.1%
8 4
 
3.3%
9 3
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
B 4
66.7%
L 2
33.3%
Space Separator
ValueCountFrequency (%)
136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 527
60.6%
Common 337
38.7%
Latin 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 61
 
11.6%
성 36
 
6.8%
서 32
 
6.1%
시 30
 
5.7%
울 29
 
5.5%
특 28
 
5.3%
별 28
 
5.3%
구 27
 
5.1%
로 26
 
4.9%
당 15
 
2.8%
Other values (67) 215
40.8%
Common
ValueCountFrequency (%)
136
40.4%
1 36
 
10.7%
( 29
 
8.6%
) 29
 
8.6%
3 20
 
5.9%
, 19
 
5.6%
0 17
 
5.0%
2 15
 
4.5%
4 9
 
2.7%
7 7
 
2.1%
Other values (5) 20
 
5.9%
Latin
ValueCountFrequency (%)
B 4
66.7%
L 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 527
60.6%
ASCII 343
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
39.7%
1 36
 
10.5%
( 29
 
8.5%
) 29
 
8.5%
3 20
 
5.8%
, 19
 
5.5%
0 17
 
5.0%
2 15
 
4.4%
4 9
 
2.6%
7 7
 
2.0%
Other values (7) 26
 
7.6%
Hangul
ValueCountFrequency (%)
동 61
 
11.6%
성 36
 
6.8%
서 32
 
6.1%
시 30
 
5.7%
울 29
 
5.5%
특 28
 
5.3%
별 28
 
5.3%
구 27
 
5.1%
로 26
 
4.9%
당 15
 
2.8%
Other values (67) 215
40.8%

도로명우편번호
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing10
Missing (%)32.3%
Memory size380.0 B
2024-05-11T15:23:23.806655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.7142857
Min length5

Characters and Unicode

Total characters120
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

Unique17 ?
Unique (%)81.0%

Sample

1st row04776
2nd row133805
3rd row04808
4th row04736
5th row04713
ValueCountFrequency (%)
04768 2
 
9.5%
04701 2
 
9.5%
133-020 1
 
4.8%
04776 1
 
4.8%
133-751 1
 
4.8%
04765 1
 
4.8%
133866 1
 
4.8%
133100 1
 
4.8%
133-111 1
 
4.8%
133-091 1
 
4.8%
Other values (9) 9
42.9%
2024-05-11T15:23:24.441342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 25
20.8%
1 20
16.7%
3 20
16.7%
7 14
11.7%
4 12
10.0%
6 9
 
7.5%
8 7
 
5.8%
- 6
 
5.0%
5 4
 
3.3%
2 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 114
95.0%
Dash Punctuation 6
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 25
21.9%
1 20
17.5%
3 20
17.5%
7 14
12.3%
4 12
10.5%
6 9
 
7.9%
8 7
 
6.1%
5 4
 
3.5%
2 2
 
1.8%
9 1
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 25
20.8%
1 20
16.7%
3 20
16.7%
7 14
11.7%
4 12
10.0%
6 9
 
7.5%
8 7
 
5.8%
- 6
 
5.0%
5 4
 
3.3%
2 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 25
20.8%
1 20
16.7%
3 20
16.7%
7 14
11.7%
4 12
10.0%
6 9
 
7.5%
8 7
 
5.8%
- 6
 
5.0%
5 4
 
3.3%
2 2
 
1.7%

사업장명
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-05-11T15:23:24.845006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length10.870968
Min length4

Characters and Unicode

Total characters337
Distinct characters96
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

Unique29 ?
Unique (%)93.5%

Sample

1st row뚝도시장
2nd row금남시장
3rd row금북시장
4th row금호종합시장
5th row자동차매매센타
ValueCountFrequency (%)
gs 4
 
6.9%
the 4
 
6.9%
fresh 3
 
5.2%
홈플러스(주 3
 
5.2%
주)이마트 2
 
3.4%
익스프레스 2
 
3.4%
왕십리점 2
 
3.4%
성수점 2
 
3.4%
홈플러스(주)익스프레스 2
 
3.4%
성동센트라스점 2
 
3.4%
Other values (32) 32
55.2%
2024-05-11T15:23:25.653003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27
 
8.0%
스 22
 
6.5%
점 15
 
4.5%
E 10
 
3.0%
성 10
 
3.0%
S 9
 
2.7%
동 9
 
2.7%
) 8
 
2.4%
장 8
 
2.4%
( 8
 
2.4%
Other values (86) 211
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
72.1%
Uppercase Letter 47
 
13.9%
Space Separator 27
 
8.0%
Close Punctuation 8
 
2.4%
Open Punctuation 8
 
2.4%
Decimal Number 3
 
0.9%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 22
 
9.1%
점 15
 
6.2%
성 10
 
4.1%
동 9
 
3.7%
장 8
 
3.3%
주 8
 
3.3%
시 7
 
2.9%
프 7
 
2.9%
트 7
 
2.9%
플 6
 
2.5%
Other values (72) 144
59.3%
Uppercase Letter
ValueCountFrequency (%)
E 10
21.3%
S 9
19.1%
H 7
14.9%
G 6
12.8%
T 5
10.6%
R 5
10.6%
F 4
 
8.5%
N 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
6 1
33.3%
Space Separator
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
72.1%
Common 47
 
13.9%
Latin 47
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 22
 
9.1%
점 15
 
6.2%
성 10
 
4.1%
동 9
 
3.7%
장 8
 
3.3%
주 8
 
3.3%
시 7
 
2.9%
프 7
 
2.9%
트 7
 
2.9%
플 6
 
2.5%
Other values (72) 144
59.3%
Latin
ValueCountFrequency (%)
E 10
21.3%
S 9
19.1%
H 7
14.9%
G 6
12.8%
T 5
10.6%
R 5
10.6%
F 4
 
8.5%
N 1
 
2.1%
Common
ValueCountFrequency (%)
27
57.4%
) 8
 
17.0%
( 8
 
17.0%
2 2
 
4.3%
6 1
 
2.1%
- 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
72.1%
ASCII 94
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27
28.7%
E 10
 
10.6%
S 9
 
9.6%
) 8
 
8.5%
( 8
 
8.5%
H 7
 
7.4%
G 6
 
6.4%
T 5
 
5.3%
R 5
 
5.3%
F 4
 
4.3%
Other values (4) 5
 
5.3%
Hangul
ValueCountFrequency (%)
스 22
 
9.1%
점 15
 
6.2%
성 10
 
4.1%
동 9
 
3.7%
장 8
 
3.3%
주 8
 
3.3%
시 7
 
2.9%
프 7
 
2.9%
트 7
 
2.9%
플 6
 
2.5%
Other values (72) 144
59.3%

최종수정일자
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2011-12-09 10:04:47
Maximum2024-04-26 10:27:13
2024-05-11T15:23:25.995581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:26.240925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
U
22 
I
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 22
71.0%
I 9
29.0%

Length

2024-05-11T15:23:26.524897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:26.732236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 22
71.0%
i 9
29.0%

데이터갱신일자
Date

Distinct21
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 22:08:00
2024-05-11T15:23:26.951276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:27.172289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

업태구분명
Categorical

Distinct6
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
구분없음
13 
그 밖의 대규모점포
9 
시장
5 
대형마트
2 
전문점
 
1

Length

Max length10
Median length5
Mean length5.4193548
Min length2

Unique

Unique2 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
구분없음 13
41.9%
그 밖의 대규모점포 9
29.0%
시장 5
 
16.1%
대형마트 2
 
6.5%
전문점 1
 
3.2%
복합쇼핑몰 1
 
3.2%

Length

2024-05-11T15:23:27.513349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:27.798415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구분없음 13
26.5%
그 9
18.4%
밖의 9
18.4%
대규모점포 9
18.4%
시장 5
 
10.2%
대형마트 2
 
4.1%
전문점 1
 
2.0%
복합쇼핑몰 1
 
2.0%

좌표정보(X)
Real number (ℝ)

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203235.9
Minimum201181.6
Maximum205784.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T15:23:28.062177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201181.6
5-th percentile201422.64
Q1202220.19
median203321.56
Q3204264.55
95-th percentile205045.9
Maximum205784.87
Range4603.2698
Interquartile range (IQR)2044.3637

Descriptive statistics

Standard deviation1241.854
Coefficient of variation (CV)0.0061104068
Kurtosis-0.93883146
Mean203235.9
Median Absolute Deviation (MAD)995.05929
Skewness0.16054055
Sum6300313
Variance1542201.5
MonotonicityNot monotonic
2024-05-11T15:23:28.345963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
202372.912023599 2
 
6.5%
203841.225547969 2
 
6.5%
204566.046414287 2
 
6.5%
204775.366000022 1
 
3.2%
203292.151783332 1
 
3.2%
202113.869605464 1
 
3.2%
203477.905432913 1
 
3.2%
203523.0 1
 
3.2%
201462.251313062 1
 
3.2%
204257.584861091 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
201181.598996876 1
3.2%
201383.023709556 1
3.2%
201462.251313062 1
3.2%
201772.807083568 1
3.2%
201924.287403479 1
3.2%
201939.255278432 1
3.2%
202004.452300224 1
3.2%
202113.869605464 1
3.2%
202326.503044305 1
3.2%
202372.912023599 2
6.5%
ValueCountFrequency (%)
205784.868811814 1
3.2%
205260.827743854 1
3.2%
204830.977323063 1
3.2%
204775.366000022 1
3.2%
204614.272744322 1
3.2%
204566.046414287 2
6.5%
204271.515183693 1
3.2%
204257.584861091 1
3.2%
203841.225547969 2
6.5%
203576.594691866 1
3.2%

좌표정보(Y)
Real number (ℝ)

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450256.69
Minimum448395.59
Maximum452041.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T15:23:28.938159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448395.59
5-th percentile448503.69
Q1449475.54
median450411
Q3451260.93
95-th percentile451918.89
Maximum452041.56
Range3645.9713
Interquartile range (IQR)1785.393

Descriptive statistics

Standard deviation1140.1666
Coefficient of variation (CV)0.002532259
Kurtosis-1.2103509
Mean450256.69
Median Absolute Deviation (MAD)933.55154
Skewness-0.16111522
Sum13957957
Variance1299979.8
MonotonicityNot monotonic
2024-05-11T15:23:29.178409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
451536.680876573 2
 
6.5%
449475.540141228 2
 
6.5%
451260.933119786 2
 
6.5%
448395.587760252 1
 
3.2%
451267.730992123 1
 
3.2%
451897.581865192 1
 
3.2%
450542.454417279 1
 
3.2%
450411.0 1
 
3.2%
448744.038108098 1
 
3.2%
449412.544118545 1
 
3.2%
Other values (18) 18
58.1%
ValueCountFrequency (%)
448395.587760252 1
3.2%
448399.948660115 1
3.2%
448607.441251647 1
3.2%
448609.588125745 1
3.2%
448744.038108098 1
3.2%
448744.245842924 1
3.2%
449412.544118545 1
3.2%
449475.540141228 2
6.5%
449477.448459906 1
3.2%
449505.43323776 1
3.2%
ValueCountFrequency (%)
452041.559037331 1
3.2%
451940.205444395 1
3.2%
451897.581865192 1
3.2%
451536.680876573 2
6.5%
451346.281102634 1
3.2%
451267.730992123 1
3.2%
451260.933119786 2
6.5%
451160.356013436 1
3.2%
451001.868687869 1
3.2%
450883.524006222 1
3.2%

점포구분명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
17 
대규모점포
12 
준대규모점포
2 

Length

Max length6
Median length4
Mean length4.516129
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
54.8%
대규모점포 12
38.7%
준대규모점포 2
 
6.5%

Length

2024-05-11T15:23:29.446054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:29.689828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
54.8%
대규모점포 12
38.7%
준대규모점포 2
 
6.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03030000196230300740750000219620125<NA>1영업/정상1정상영업<NA><NA><NA><NA>000246444262861.0<NA>서울특별시 성동구 성수동2가 335번지서울특별시 성동구 성수이로 32-15 (성수동2가)04776뚝도시장2022-04-15 19:12:47U2021-12-03 23:07:00.0시장204775.366448395.58776<NA>
13030000196230301030750000119620121<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 225253021156.0133805서울특별시 성동구 금호동3가 332번지서울특별시 성동구 독서당로 303-11 (금호동3가)133805금남시장2021-01-04 13:45:52U2021-01-06 02:40:00.0시장201939.255278449589.213832대규모점포
23030000196930301030750000119690109<NA>3폐업3폐업처리20151130<NA><NA><NA>2291-67540.0133091서울특별시 성동구 금호동1가 128번지 1호서울특별시 성동구 행당로 35 (금호동1가)<NA>금북시장2015-12-03 11:03:00I2018-08-31 23:59:59.0그 밖의 대규모점포202004.4523450411.463617대규모점포
33030000197930301030750000619790810<NA>3폐업3폐업처리20080522<NA><NA><NA>2297-38110.0133809서울특별시 성동구 금호동4가 548번지 1호서울특별시 성동구 독서당로 302 (금호동4가)<NA>금호종합시장2012-05-10 10:10:00I2018-08-31 23:59:59.0그 밖의 대규모점포201924.287403449505.433238대규모점포
43030000198030301030750000519800905<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2210-41000.0<NA>서울특별시 성동구 용답동 234번지 한국자동차매매센터서울특별시 성동구 자동차시장1길 70 (용답동, 장안평중고자동차시장)04808자동차매매센타2019-04-30 17:44:20U2019-05-02 02:40:00.0전문점205784.868812450883.524006대규모점포
5303000019823030103075000011982-10-16<NA>1영업/정상1정상영업<NA><NA><NA><NA>2297-24840.0<NA>서울특별시 성동구 옥수동 220번지 1호 한남하이츠아파트서울특별시 성동구 독서당로 160, 한남하이츠아파트 (옥수동)04736한남하이츠상가2023-12-07 15:08:50U2022-11-02 00:09:00.0구분없음201181.598997448609.588126<NA>
63030000199830301030750000119980803<NA>1영업/정상1정상영업<NA><NA><NA><NA>02)2297-62054049.55<NA>서울특별시 성동구 행당동 347번지 행당동 대림아파트서울특별시 성동구 행당로 87, 행당동 대림아파트 (행당동)04713대림리빙프라자2018-10-02 16:57:38U2018-10-04 02:37:24.0그 밖의 대규모점포202326.503044450625.584227대규모점포
7303000020003030103075000012000-03-31<NA>1영업/정상1정상영업<NA><NA><NA><NA>02)2281-70035873.69<NA>서울특별시 성동구 행당동 346번지 행당 한진타운 종합상가서울특별시 성동구 행당로 84, 행당 한진타운 종합상가 (행당동)04717한진종합상가2024-01-22 16:10:33U2023-11-30 22:04:00.0그 밖의 대규모점포202511.142931450401.303716<NA>
83030000200130301030750000220010913201703084취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>463-7547~88495.01133120서울특별시 성동구 성수동2가 231번지 1호<NA><NA>성동마트2017-03-08 15:17:20I2018-08-31 23:59:59.0그 밖의 대규모점포205260.827744448399.94866대규모점포
9303000020053030074075000012005-03-31<NA>3폐업3폐업처리2023-05-19<NA><NA><NA>02-3408-123417318.0133-120서울특별시 성동구 성수동2가 333번지 16호서울특별시 뚝섬로 379133-120(주)이마트 성수점2023-05-19 12:53:54U2022-12-04 22:01:00.0대형마트204614.272744448607.441252<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
21303000020123030103075000032012-03-21<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2292-8545293.34133-091서울특별시 성동구 금호동1가 481번지 5호서울특별시 성동구 행당로 6 (금호동1가)133-091홈플러스(주) 익스프레스 금호점2024-03-29 13:33:32U2023-12-02 21:01:00.0구분없음201772.807084450250.366445<NA>
22303000020123030103075000042012-03-22<NA>3폐업3폐업처리2023-03-27<NA><NA><NA>02-499-8545409.9133-111서울특별시 성동구 성수1가1동 14번지 17호서울특별시 성동구 아차산로 41 (성수동1가)133-111홈플러스(주)익스프레스 뚝섬점2023-03-28 17:26:48U2022-12-02 21:00:00.0구분없음204257.584861449412.544119<NA>
233030000201230301030750000520120402<NA>3폐업3폐업처리20220405<NA><NA><NA>2282-0161378.11133100서울특별시 성동구 옥수동 191번지 3호서울특별시 성동구 한림말길 56 (옥수동)133100GS수퍼 성동옥수점2022-04-06 08:30:04U2021-12-04 00:08:00.0구분없음201462.251313448744.038108<NA>
243030000201430301030750000120141209<NA>1영업/정상1정상영업<NA><NA><NA><NA>2207-9991, 6454-630113996.64<NA><NA>서울특별시 성동구 왕십리로 241 (행당동)133866파크에비뉴 엔터식스 한양대점2019-09-20 17:52:31U2019-09-22 02:40:00.0복합쇼핑몰203523.0450411.0대규모점포
253030000201830301030750000120180228<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-98420.0<NA>서울특별시 성동구 행당동 155번지 1호 서울숲 더샵서울특별시 성동구 왕십리로 241 (행당동, 서울숲 더샵)04765노브랜드 엔터식스한양대점2018-10-02 17:36:14I2018-10-04 02:37:24.0구분없음203477.905433450542.454417준대규모점포
26303000020213030103075000012013-02-19<NA>3폐업3폐업처리2023-08-18<NA><NA><NA>02-2253-8541143.55<NA>서울특별시 성동구 성수동1가 656-1208 성수만세주유소서울특별시 성동구 왕십리로 109, 성수만세주유소 (성수동1가)04768홈플러스익스프레스 뚝섬2점2023-08-18 16:32:14U2022-12-07 22:00:00.0구분없음203841.225548449475.540141<NA>
27303000020233030103075000012023-06-16<NA>4취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA><NA>467.23<NA>서울특별시 성동구 하왕십리동 1070 센트라스상가 L동 B102호서울특별시 성동구 왕십리로 410, L동 지하1층 B102, B103호 (하왕십리동, 센트라스)04701GS THE FRESH 성동센트라스점2023-06-20 09:18:09U2022-12-05 22:02:00.0구분없음202372.912024451536.680877<NA>
28303000020233030103075000022023-06-16<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA>467.23<NA>서울특별시 성동구 하왕십리동 1070 센트라스서울특별시 성동구 왕십리로 410, 상가(L)동 지하1층 B102,B103호 (하왕십리동, 센트라스)04701GS THE FRESH 성동센트라스점2023-11-03 09:43:47U2022-11-01 00:05:00.0구분없음202372.912024451536.680877<NA>
29303000020233030103075000032023-07-21<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2297-5180327.3<NA>서울특별시 성동구 상왕십리동 811 텐즈힐서울특별시 성동구 마장로 137, 221동 1층 1230호,1231호,1232(일부)호 (상왕십리동, 텐즈힐)04700GS THE FRESH 성동텐즈힐점2023-10-13 15:02:37U2022-10-30 23:05:00.0구분없음202113.869605451897.581865<NA>
30303000020233030103075000042023-09-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-499-4519158.8<NA>서울특별시 성동구 성수동1가 656-1208 성수만세주유소서울특별시 성동구 왕십리로 109, 성수만세주유소 1층 (성수동1가)04768GS THE FRESG 서울숲점2023-10-13 10:11:13I2022-10-30 23:05:00.0구분없음203841.225548449475.540141<NA>