Overview

Dataset statistics

Number of variables26
Number of observations795
Missing cells6444
Missing cells (%)31.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory171.7 KiB
Average record size in memory221.2 B

Variable types

Categorical6
Text6
DateTime4
Unsupported6
Numeric4

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),판매점영업면적
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-16304/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 795 (100.0%) missing valuesMissing
폐업일자 has 351 (44.2%) missing valuesMissing
휴업시작일자 has 795 (100.0%) missing valuesMissing
휴업종료일자 has 795 (100.0%) missing valuesMissing
재개업일자 has 795 (100.0%) missing valuesMissing
전화번호 has 412 (51.8%) missing valuesMissing
소재지면적 has 795 (100.0%) missing valuesMissing
소재지우편번호 has 484 (60.9%) missing valuesMissing
지번주소 has 152 (19.1%) missing valuesMissing
업태구분명 has 795 (100.0%) missing valuesMissing
좌표정보(X) has 18 (2.3%) missing valuesMissing
좌표정보(Y) has 18 (2.3%) missing valuesMissing
판매점영업면적 has 225 (28.3%) missing valuesMissing
판매점영업면적 is highly skewed (γ1 = 23.86992007)Skewed
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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
판매점영업면적 has 108 (13.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:15:44.328322
Analysis finished2024-05-11 06:15:45.444248
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
3180000
795 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 795
100.0%

Length

2024-05-11T15:15:45.576041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:45.768077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 795
100.0%

관리번호
Text

UNIQUE 

Distinct795
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T15:15:46.145768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters19875
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique795 ?
Unique (%)100.0%

Sample

1st rowPHMH320123180034087500001
2nd rowPHMH320123180034087500002
3rd rowPHMH320123180034087500003
4th rowPHMH320123180034087500004
5th rowPHMH320123180034087500005
ValueCountFrequency (%)
phmh320123180034087500001 1
 
0.1%
phmh320183180034087500013 1
 
0.1%
phmh320183180034087500015 1
 
0.1%
phmh320183180034087500016 1
 
0.1%
phmh320183180034087500017 1
 
0.1%
phmh320183180034087500018 1
 
0.1%
phmh320183180034087500019 1
 
0.1%
phmh320183180034087500020 1
 
0.1%
phmh320183180034087500021 1
 
0.1%
phmh320183180034087500022 1
 
0.1%
Other values (785) 785
98.7%
2024-05-11T15:15:46.764617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5712
28.7%
3 2677
13.5%
1 1765
 
8.9%
8 1743
 
8.8%
H 1590
 
8.0%
2 1446
 
7.3%
4 1020
 
5.1%
7 995
 
5.0%
5 993
 
5.0%
P 795
 
4.0%
Other values (3) 1139
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16695
84.0%
Uppercase Letter 3180
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5712
34.2%
3 2677
16.0%
1 1765
 
10.6%
8 1743
 
10.4%
2 1446
 
8.7%
4 1020
 
6.1%
7 995
 
6.0%
5 993
 
5.9%
6 198
 
1.2%
9 146
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
H 1590
50.0%
P 795
25.0%
M 795
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16695
84.0%
Latin 3180
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5712
34.2%
3 2677
16.0%
1 1765
 
10.6%
8 1743
 
10.4%
2 1446
 
8.7%
4 1020
 
6.1%
7 995
 
6.0%
5 993
 
5.9%
6 198
 
1.2%
9 146
 
0.9%
Latin
ValueCountFrequency (%)
H 1590
50.0%
P 795
25.0%
M 795
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5712
28.7%
3 2677
13.5%
1 1765
 
8.9%
8 1743
 
8.8%
H 1590
 
8.0%
2 1446
 
7.3%
4 1020
 
5.1%
7 995
 
5.0%
5 993
 
5.0%
P 795
 
4.0%
Other values (3) 1139
 
5.7%

인허가일자
Date

Distinct535
Distinct (%)67.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2012-11-06 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:15:46.995735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:47.271043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
3
432 
1
351 
4
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 432
54.3%
1 351
44.2%
4 12
 
1.5%

Length

2024-05-11T15:15:47.523805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:47.710286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 432
54.3%
1 351
44.2%
4 12
 
1.5%

영업상태명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
폐업
432 
영업/정상
351 
취소/말소/만료/정지/중지
 
12

Length

Max length14
Median length2
Mean length3.5056604
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 432
54.3%
영업/정상 351
44.2%
취소/말소/만료/정지/중지 12
 
1.5%

Length

2024-05-11T15:15:47.971450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:48.175416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 432
54.3%
영업/정상 351
44.2%
취소/말소/만료/정지/중지 12
 
1.5%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
3
432 
13
351 
24
 
12

Length

Max length2
Median length1
Mean length1.4566038
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row3
3rd row3
4th row3
5th row13

Common Values

ValueCountFrequency (%)
3 432
54.3%
13 351
44.2%
24 12
 
1.5%

Length

2024-05-11T15:15:48.884317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:49.069038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 432
54.3%
13 351
44.2%
24 12
 
1.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
폐업
432 
영업중
351 
직권폐업
 
12

Length

Max length4
Median length2
Mean length2.4716981
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 432
54.3%
영업중 351
44.2%
직권폐업 12
 
1.5%

Length

2024-05-11T15:15:49.303345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:49.500938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 432
54.3%
영업중 351
44.2%
직권폐업 12
 
1.5%

폐업일자
Date

MISSING 

Distinct397
Distinct (%)89.4%
Missing351
Missing (%)44.2%
Memory size6.3 KiB
Minimum2012-11-19 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T15:15:49.700991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:49.972073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

전화번호
Text

MISSING 

Distinct345
Distinct (%)90.1%
Missing412
Missing (%)51.8%
Memory size6.3 KiB
2024-05-11T15:15:50.488129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.6005222
Min length3

Characters and Unicode

Total characters3677
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

Unique309 ?
Unique (%)80.7%

Sample

1st row2677-3667
2nd row2675-7839
3rd row842-5872
4th row831-5514
5th row831-2822
ValueCountFrequency (%)
815-3612 3
 
0.8%
02-833-9555 3
 
0.8%
2678-2385 2
 
0.5%
02-833-0617 2
 
0.5%
2676-0711 2
 
0.5%
2169-3801 2
 
0.5%
831-2466 2
 
0.5%
848-5070 2
 
0.5%
2636-5619 2
 
0.5%
2675-7717 2
 
0.5%
Other values (335) 361
94.3%
2024-05-11T15:15:51.306435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 509
13.8%
2 493
13.4%
6 405
11.0%
0 389
10.6%
8 361
9.8%
7 345
9.4%
3 343
9.3%
1 255
6.9%
5 202
 
5.5%
4 202
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3168
86.2%
Dash Punctuation 509
 
13.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 493
15.6%
6 405
12.8%
0 389
12.3%
8 361
11.4%
7 345
10.9%
3 343
10.8%
1 255
8.0%
5 202
6.4%
4 202
6.4%
9 173
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 509
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3677
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 509
13.8%
2 493
13.4%
6 405
11.0%
0 389
10.6%
8 361
9.8%
7 345
9.4%
3 343
9.3%
1 255
6.9%
5 202
 
5.5%
4 202
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3677
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 509
13.8%
2 493
13.4%
6 405
11.0%
0 389
10.6%
8 361
9.8%
7 345
9.4%
3 343
9.3%
1 255
6.9%
5 202
 
5.5%
4 202
 
5.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

소재지우편번호
Text

MISSING 

Distinct111
Distinct (%)35.7%
Missing484
Missing (%)60.9%
Memory size6.3 KiB
2024-05-11T15:15:51.816213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0932476
Min length5

Characters and Unicode

Total characters1895
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)16.4%

Sample

1st row150095
2nd row150045
3rd row150837
4th row150833
5th row150833
ValueCountFrequency (%)
150010 35
 
11.3%
150040 10
 
3.2%
150103 10
 
3.2%
150033 9
 
2.9%
150866 9
 
2.9%
150034 8
 
2.6%
150043 7
 
2.3%
150038 7
 
2.3%
150804 7
 
2.3%
150300 6
 
1.9%
Other values (101) 203
65.3%
2024-05-11T15:15:52.640640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 593
31.3%
1 418
22.1%
5 370
19.5%
8 127
 
6.7%
3 114
 
6.0%
4 69
 
3.6%
9 52
 
2.7%
6 51
 
2.7%
7 40
 
2.1%
- 30
 
1.6%
Other values (2) 31
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1864
98.4%
Dash Punctuation 30
 
1.6%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 593
31.8%
1 418
22.4%
5 370
19.8%
8 127
 
6.8%
3 114
 
6.1%
4 69
 
3.7%
9 52
 
2.8%
6 51
 
2.7%
7 40
 
2.1%
2 30
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1895
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 593
31.3%
1 418
22.1%
5 370
19.5%
8 127
 
6.7%
3 114
 
6.0%
4 69
 
3.6%
9 52
 
2.7%
6 51
 
2.7%
7 40
 
2.1%
- 30
 
1.6%
Other values (2) 31
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1895
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 593
31.3%
1 418
22.1%
5 370
19.5%
8 127
 
6.7%
3 114
 
6.0%
4 69
 
3.6%
9 52
 
2.7%
6 51
 
2.7%
7 40
 
2.1%
- 30
 
1.6%
Other values (2) 31
 
1.6%

지번주소
Text

MISSING 

Distinct554
Distinct (%)86.2%
Missing152
Missing (%)19.1%
Memory size6.3 KiB
2024-05-11T15:15:53.140417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length25.125972
Min length15

Characters and Unicode

Total characters16156
Distinct characters226
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique477 ?
Unique (%)74.2%

Sample

1st row서울특별시 영등포구 문래동5가 23번지 4호
2nd row서울특별시 영등포구 당산동5가 42번지
3rd row서울특별시 영등포구 신길동 59번지 2호
4th row서울특별시 영등포구 도림동 269번지 4호
5th row서울특별시 영등포구 도림동 265번지 6호
ValueCountFrequency (%)
서울특별시 643
20.1%
영등포구 643
20.1%
신길동 110
 
3.4%
여의도동 94
 
2.9%
대림동 90
 
2.8%
1호 75
 
2.3%
2호 37
 
1.2%
3호 35
 
1.1%
1층 35
 
1.1%
당산동3가 30
 
0.9%
Other values (618) 1413
44.1%
2024-05-11T15:15:53.884755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2563
 
15.9%
영 759
 
4.7%
포 756
 
4.7%
등 754
 
4.7%
동 668
 
4.1%
시 654
 
4.0%
서 645
 
4.0%
구 644
 
4.0%
특 643
 
4.0%
별 643
 
4.0%
Other values (216) 7427
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10663
66.0%
Decimal Number 2774
 
17.2%
Space Separator 2563
 
15.9%
Dash Punctuation 120
 
0.7%
Uppercase Letter 25
 
0.2%
Other Punctuation 5
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 759
 
7.1%
포 756
 
7.1%
등 754
 
7.1%
동 668
 
6.3%
시 654
 
6.1%
서 645
 
6.0%
구 644
 
6.0%
특 643
 
6.0%
별 643
 
6.0%
울 643
 
6.0%
Other values (183) 3854
36.1%
Uppercase Letter
ValueCountFrequency (%)
S 5
20.0%
E 4
16.0%
K 2
 
8.0%
I 2
 
8.0%
V 2
 
8.0%
W 2
 
8.0%
G 1
 
4.0%
J 1
 
4.0%
B 1
 
4.0%
A 1
 
4.0%
Other values (4) 4
16.0%
Decimal Number
ValueCountFrequency (%)
1 605
21.8%
3 356
12.8%
2 335
12.1%
4 315
11.4%
5 248
8.9%
6 216
 
7.8%
7 188
 
6.8%
0 182
 
6.6%
8 171
 
6.2%
9 158
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
& 1
 
20.0%
@ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2563
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10663
66.0%
Common 5467
33.8%
Latin 26
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 759
 
7.1%
포 756
 
7.1%
등 754
 
7.1%
동 668
 
6.3%
시 654
 
6.1%
서 645
 
6.0%
구 644
 
6.0%
특 643
 
6.0%
별 643
 
6.0%
울 643
 
6.0%
Other values (183) 3854
36.1%
Common
ValueCountFrequency (%)
2563
46.9%
1 605
 
11.1%
3 356
 
6.5%
2 335
 
6.1%
4 315
 
5.8%
5 248
 
4.5%
6 216
 
4.0%
7 188
 
3.4%
0 182
 
3.3%
8 171
 
3.1%
Other values (8) 288
 
5.3%
Latin
ValueCountFrequency (%)
S 5
19.2%
E 4
15.4%
K 2
 
7.7%
I 2
 
7.7%
V 2
 
7.7%
W 2
 
7.7%
G 1
 
3.8%
e 1
 
3.8%
J 1
 
3.8%
B 1
 
3.8%
Other values (5) 5
19.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10663
66.0%
ASCII 5493
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2563
46.7%
1 605
 
11.0%
3 356
 
6.5%
2 335
 
6.1%
4 315
 
5.7%
5 248
 
4.5%
6 216
 
3.9%
7 188
 
3.4%
0 182
 
3.3%
8 171
 
3.1%
Other values (23) 314
 
5.7%
Hangul
ValueCountFrequency (%)
영 759
 
7.1%
포 756
 
7.1%
등 754
 
7.1%
동 668
 
6.3%
시 654
 
6.1%
서 645
 
6.0%
구 644
 
6.0%
특 643
 
6.0%
별 643
 
6.0%
울 643
 
6.0%
Other values (183) 3854
36.1%

도로명주소
Text

Distinct690
Distinct (%)87.6%
Missing7
Missing (%)0.9%
Memory size6.3 KiB
2024-05-11T15:15:54.433657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length52
Mean length33.611675
Min length23

Characters and Unicode

Total characters26486
Distinct characters249
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique604 ?
Unique (%)76.6%

Sample

1st row서울특별시 영등포구 선유서로 15 (문래동5가)
2nd row서울특별시 영등포구 당산로 214 (당산동5가)
3rd row서울특별시 영등포구 영등포로 353 (신길동)
4th row서울특별시 영등포구 도영로 19 (도림동)
5th row서울특별시 영등포구 도영로 18 (도림동)
ValueCountFrequency (%)
서울특별시 788
 
16.1%
영등포구 788
 
16.1%
1층 269
 
5.5%
신길동 136
 
2.8%
대림동 112
 
2.3%
여의도동 106
 
2.2%
101호 51
 
1.0%
영등포로 37
 
0.8%
양평동3가 33
 
0.7%
양평동4가 32
 
0.7%
Other values (803) 2553
52.0%
2024-05-11T15:15:55.343891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4117
 
15.5%
1 1276
 
4.8%
영 1063
 
4.0%
포 1001
 
3.8%
등 998
 
3.8%
동 910
 
3.4%
시 824
 
3.1%
서 803
 
3.0%
로 795
 
3.0%
( 792
 
3.0%
Other values (239) 13907
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15751
59.5%
Decimal Number 4218
 
15.9%
Space Separator 4117
 
15.5%
Open Punctuation 792
 
3.0%
Close Punctuation 792
 
3.0%
Other Punctuation 665
 
2.5%
Dash Punctuation 97
 
0.4%
Uppercase Letter 46
 
0.2%
Math Symbol 7
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 1063
 
6.7%
포 1001
 
6.4%
등 998
 
6.3%
동 910
 
5.8%
시 824
 
5.2%
서 803
 
5.1%
로 795
 
5.0%
구 791
 
5.0%
울 788
 
5.0%
별 788
 
5.0%
Other values (206) 6990
44.4%
Uppercase Letter
ValueCountFrequency (%)
B 13
28.3%
A 8
17.4%
S 7
15.2%
K 5
 
10.9%
W 2
 
4.3%
E 2
 
4.3%
I 2
 
4.3%
V 2
 
4.3%
C 2
 
4.3%
G 1
 
2.2%
Other values (2) 2
 
4.3%
Decimal Number
ValueCountFrequency (%)
1 1276
30.3%
2 517
12.3%
3 495
 
11.7%
0 429
 
10.2%
4 371
 
8.8%
5 267
 
6.3%
6 246
 
5.8%
7 244
 
5.8%
9 194
 
4.6%
8 179
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 660
99.2%
? 2
 
0.3%
. 1
 
0.2%
@ 1
 
0.2%
& 1
 
0.2%
Space Separator
ValueCountFrequency (%)
4117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 792
100.0%
Close Punctuation
ValueCountFrequency (%)
) 792
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15751
59.5%
Common 10688
40.4%
Latin 47
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 1063
 
6.7%
포 1001
 
6.4%
등 998
 
6.3%
동 910
 
5.8%
시 824
 
5.2%
서 803
 
5.1%
로 795
 
5.0%
구 791
 
5.0%
울 788
 
5.0%
별 788
 
5.0%
Other values (206) 6990
44.4%
Common
ValueCountFrequency (%)
4117
38.5%
1 1276
 
11.9%
( 792
 
7.4%
) 792
 
7.4%
, 660
 
6.2%
2 517
 
4.8%
3 495
 
4.6%
0 429
 
4.0%
4 371
 
3.5%
5 267
 
2.5%
Other values (10) 972
 
9.1%
Latin
ValueCountFrequency (%)
B 13
27.7%
A 8
17.0%
S 7
14.9%
K 5
 
10.6%
W 2
 
4.3%
E 2
 
4.3%
I 2
 
4.3%
V 2
 
4.3%
C 2
 
4.3%
e 1
 
2.1%
Other values (3) 3
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15751
59.5%
ASCII 10735
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4117
38.4%
1 1276
 
11.9%
( 792
 
7.4%
) 792
 
7.4%
, 660
 
6.1%
2 517
 
4.8%
3 495
 
4.6%
0 429
 
4.0%
4 371
 
3.5%
5 267
 
2.5%
Other values (23) 1019
 
9.5%
Hangul
ValueCountFrequency (%)
영 1063
 
6.7%
포 1001
 
6.4%
등 998
 
6.3%
동 910
 
5.8%
시 824
 
5.2%
서 803
 
5.1%
로 795
 
5.0%
구 791
 
5.0%
울 788
 
5.0%
별 788
 
5.0%
Other values (206) 6990
44.4%

도로명우편번호
Real number (ℝ)

Distinct238
Distinct (%)30.2%
Missing7
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean22923.374
Minimum7201
Maximum150946
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-05-11T15:15:55.703377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7201
5-th percentile7209
Q17257
median7327
Q37401
95-th percentile150099.9
Maximum150946
Range143745
Interquartile range (IQR)144

Descriptive statistics

Standard deviation44628.654
Coefficient of variation (CV)1.9468623
Kurtosis4.3205154
Mean22923.374
Median Absolute Deviation (MAD)70
Skewness2.5118615
Sum18063619
Variance1.9917167 × 109
MonotonicityNot monotonic
2024-05-11T15:15:55.975665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7229 13
 
1.6%
7354 12
 
1.5%
7222 12
 
1.5%
7333 12
 
1.5%
7301 11
 
1.4%
7270 10
 
1.3%
150010 10
 
1.3%
7208 10
 
1.3%
7236 10
 
1.3%
7294 10
 
1.3%
Other values (228) 678
85.3%
ValueCountFrequency (%)
7201 6
0.8%
7202 2
 
0.3%
7203 1
 
0.1%
7204 4
 
0.5%
7205 7
0.9%
7206 7
0.9%
7207 2
 
0.3%
7208 10
1.3%
7209 3
 
0.4%
7210 4
 
0.5%
ValueCountFrequency (%)
150946 1
 
0.1%
150909 2
0.3%
150895 1
 
0.1%
150867 3
0.4%
150866 3
0.4%
150855 3
0.4%
150851 1
 
0.1%
150850 1
 
0.1%
150839 1
 
0.1%
150835 2
0.3%

사업장명
Text

Distinct597
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
2024-05-11T15:15:56.562724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length11.103145
Min length3

Characters and Unicode

Total characters8827
Distinct characters281
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique462 ?
Unique (%)58.1%

Sample

1st row씨유 문래페르마타점
2nd row씨스페이스 당산역점
3rd row씨유 신길역점
4th row세븐일레븐 영등포도림동점
5th row세븐일레븐 하나텔점
ValueCountFrequency (%)
지에스25 324
 
20.5%
씨유 209
 
13.2%
세븐일레븐 75
 
4.7%
주)코리아세븐 68
 
4.3%
미니스톱 23
 
1.5%
이마트24 17
 
1.1%
대방역점 10
 
0.6%
위드미 8
 
0.5%
영등포제일점 8
 
0.5%
신길역점 8
 
0.5%
Other values (532) 834
52.7%
2024-05-11T15:15:57.371605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
789
 
8.9%
점 700
 
7.9%
스 435
 
4.9%
에 379
 
4.3%
2 374
 
4.2%
지 373
 
4.2%
5 349
 
4.0%
유 235
 
2.7%
씨 226
 
2.6%
븐 222
 
2.5%
Other values (271) 4745
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7032
79.7%
Decimal Number 790
 
8.9%
Space Separator 789
 
8.9%
Open Punctuation 92
 
1.0%
Close Punctuation 92
 
1.0%
Uppercase Letter 29
 
0.3%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 700
 
10.0%
스 435
 
6.2%
에 379
 
5.4%
지 373
 
5.3%
유 235
 
3.3%
씨 226
 
3.2%
븐 222
 
3.2%
영 182
 
2.6%
포 172
 
2.4%
등 167
 
2.4%
Other values (244) 3941
56.0%
Uppercase Letter
ValueCountFrequency (%)
S 8
27.6%
G 8
27.6%
C 3
 
10.3%
Y 1
 
3.4%
M 1
 
3.4%
I 1
 
3.4%
R 1
 
3.4%
F 1
 
3.4%
A 1
 
3.4%
K 1
 
3.4%
Other values (3) 3
 
10.3%
Decimal Number
ValueCountFrequency (%)
2 374
47.3%
5 349
44.2%
4 26
 
3.3%
3 13
 
1.6%
1 12
 
1.5%
6 8
 
1.0%
7 3
 
0.4%
8 3
 
0.4%
0 1
 
0.1%
9 1
 
0.1%
Space Separator
ValueCountFrequency (%)
789
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7035
79.7%
Common 1763
 
20.0%
Latin 29
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 700
 
10.0%
스 435
 
6.2%
에 379
 
5.4%
지 373
 
5.3%
유 235
 
3.3%
씨 226
 
3.2%
븐 222
 
3.2%
영 182
 
2.6%
포 172
 
2.4%
등 167
 
2.4%
Other values (245) 3944
56.1%
Common
ValueCountFrequency (%)
789
44.8%
2 374
21.2%
5 349
19.8%
( 92
 
5.2%
) 92
 
5.2%
4 26
 
1.5%
3 13
 
0.7%
1 12
 
0.7%
6 8
 
0.5%
7 3
 
0.2%
Other values (3) 5
 
0.3%
Latin
ValueCountFrequency (%)
S 8
27.6%
G 8
27.6%
C 3
 
10.3%
Y 1
 
3.4%
M 1
 
3.4%
I 1
 
3.4%
R 1
 
3.4%
F 1
 
3.4%
A 1
 
3.4%
K 1
 
3.4%
Other values (3) 3
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7032
79.7%
ASCII 1792
 
20.3%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
789
44.0%
2 374
20.9%
5 349
19.5%
( 92
 
5.1%
) 92
 
5.1%
4 26
 
1.5%
3 13
 
0.7%
1 12
 
0.7%
S 8
 
0.4%
G 8
 
0.4%
Other values (16) 29
 
1.6%
Hangul
ValueCountFrequency (%)
점 700
 
10.0%
스 435
 
6.2%
에 379
 
5.4%
지 373
 
5.3%
유 235
 
3.3%
씨 226
 
3.2%
븐 222
 
3.2%
영 182
 
2.6%
포 172
 
2.4%
등 167
 
2.4%
Other values (244) 3941
56.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%

최종수정일자
Date

Distinct794
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2013-09-24 16:52:14
Maximum2024-05-09 17:37:51
2024-05-11T15:15:57.709986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:58.020590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
I
410 
U
385 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 410
51.6%
U 385
48.4%

Length

2024-05-11T15:15:58.293522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:15:58.479221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 410
51.6%
u 385
48.4%

데이터갱신일자
Date

Distinct320
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Memory size6.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-11T15:15:58.694124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:15:58.972978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing795
Missing (%)100.0%
Memory size7.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct475
Distinct (%)61.1%
Missing18
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean191578.45
Minimum189549.85
Maximum194599.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-05-11T15:15:59.261056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189549.85
5-th percentile190015.63
Q1190757.98
median191425.72
Q3192256.64
95-th percentile193737.75
Maximum194599.85
Range5050.0074
Interquartile range (IQR)1498.6651

Descriptive statistics

Standard deviation1098.1443
Coefficient of variation (CV)0.005732087
Kurtosis-0.32165306
Mean191578.45
Median Absolute Deviation (MAD)700.91221
Skewness0.56067537
Sum1.4885645 × 108
Variance1205921
MonotonicityNot monotonic
2024-05-11T15:15:59.562455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192747.419300064 8
 
1.0%
190544.956362087 7
 
0.9%
192327.822443146 5
 
0.6%
193281.875201994 5
 
0.6%
193999.840415079 5
 
0.6%
191656.718494378 5
 
0.6%
190996.357288859 5
 
0.6%
190484.482550269 5
 
0.6%
193781.852246267 4
 
0.5%
190587.567878858 4
 
0.5%
Other values (465) 724
91.1%
(Missing) 18
 
2.3%
ValueCountFrequency (%)
189549.847307536 1
 
0.1%
189607.598899153 1
 
0.1%
189641.475801911 1
 
0.1%
189653.829218246 2
0.3%
189661.13220677 1
 
0.1%
189664.262881986 2
0.3%
189672.655047131 1
 
0.1%
189700.355755718 3
0.4%
189734.544016734 1
 
0.1%
189770.729021019 2
0.3%
ValueCountFrequency (%)
194599.854707059 2
 
0.3%
194504.656267957 3
0.4%
194370.32715363 1
 
0.1%
194324.398950764 1
 
0.1%
194294.277022719 1
 
0.1%
194124.497455922 4
0.5%
194015.180457719 1
 
0.1%
193999.840415079 5
0.6%
193989.272586157 1
 
0.1%
193964.752865597 3
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct475
Distinct (%)61.1%
Missing18
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean446099.58
Minimum442621.79
Maximum449021.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-05-11T15:15:59.814337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442621.79
5-th percentile443428.96
Q1445159.81
median446351
Q3447142.74
95-th percentile448275.2
Maximum449021.44
Range6399.6526
Interquartile range (IQR)1982.9352

Descriptive statistics

Standard deviation1470.3737
Coefficient of variation (CV)0.0032960661
Kurtosis-0.54535287
Mean446099.58
Median Absolute Deviation (MAD)874.56906
Skewness-0.42529663
Sum3.4661937 × 108
Variance2161998.9
MonotonicityNot monotonic
2024-05-11T15:16:00.174869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447054.988337321 8
 
1.0%
445806.741877798 7
 
0.9%
446217.607733472 5
 
0.6%
445570.814215436 5
 
0.6%
446201.591130575 5
 
0.6%
447216.454149009 5
 
0.6%
445841.377603245 5
 
0.6%
446650.413562534 5
 
0.6%
446488.190917868 4
 
0.5%
448642.112414847 4
 
0.5%
Other values (465) 724
91.1%
(Missing) 18
 
2.3%
ValueCountFrequency (%)
442621.787911877 2
0.3%
442710.662421803 3
0.4%
442715.677609564 1
 
0.1%
442717.639571997 2
0.3%
442751.471769958 2
0.3%
442871.749486384 1
 
0.1%
442877.350755944 3
0.4%
442960.820547845 2
0.3%
442970.374521635 1
 
0.1%
443092.554741355 2
0.3%
ValueCountFrequency (%)
449021.440559054 2
0.3%
448990.816559516 2
0.3%
448971.217992424 1
 
0.1%
448896.727242794 2
0.3%
448779.57454276 1
 
0.1%
448699.972523898 1
 
0.1%
448656.726986041 3
0.4%
448642.112414847 4
0.5%
448618.587308851 1
 
0.1%
448582.888957042 1
 
0.1%

판매점영업면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct161
Distinct (%)28.2%
Missing225
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean190.85725
Minimum0
Maximum82064
Zeros108
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size7.1 KiB
2024-05-11T15:16:00.471030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.4
median47.925
Q366
95-th percentile99.17
Maximum82064
Range82064
Interquartile range (IQR)39.6

Descriptive statistics

Standard deviation3435.5429
Coefficient of variation (CV)18.000589
Kurtosis569.84829
Mean190.85725
Median Absolute Deviation (MAD)18.075
Skewness23.86992
Sum108788.63
Variance11802955
MonotonicityNot monotonic
2024-05-11T15:16:00.762290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 108
13.6%
33.0 45
 
5.7%
49.5 38
 
4.8%
66.0 37
 
4.7%
42.9 15
 
1.9%
39.6 14
 
1.8%
59.4 13
 
1.6%
56.1 12
 
1.5%
99.0 12
 
1.5%
46.2 11
 
1.4%
Other values (151) 265
33.3%
(Missing) 225
28.3%
ValueCountFrequency (%)
0.0 108
13.6%
3.0 1
 
0.1%
3.3 2
 
0.3%
5.0 3
 
0.4%
6.6 2
 
0.3%
9.9 1
 
0.1%
14.5 1
 
0.1%
16.0 1
 
0.1%
16.5 2
 
0.3%
17.0 1
 
0.1%
ValueCountFrequency (%)
82064.0 1
 
0.1%
463.0 1
 
0.1%
333.0 1
 
0.1%
270.6 1
 
0.1%
231.0 1
 
0.1%
143.87 1
 
0.1%
135.54 1
 
0.1%
132.23 1
 
0.1%
132.0 5
0.6%
129.0 1
 
0.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
03180000PHMH32012318003408750000120121106<NA>1영업/정상13영업중<NA><NA><NA><NA>2677-3667<NA>150095서울특별시 영등포구 문래동5가 23번지 4호서울특별시 영등포구 선유서로 15 (문래동5가)7284씨유 문래페르마타점2013-09-24 16:52:14I2018-08-31 23:59:59.0<NA>189661.132207446112.83600842.9
13180000PHMH32012318003408750000220121106<NA>3폐업3폐업20140605<NA><NA><NA>2675-7839<NA>150045서울특별시 영등포구 당산동5가 42번지서울특별시 영등포구 당산로 214 (당산동5가)150045씨스페이스 당산역점2014-06-05 17:16:09I2018-08-31 23:59:59.0<NA>191362.376781447750.19265459.4
23180000PHMH32012318003408750000320121106<NA>3폐업3폐업20190516<NA><NA><NA>842-5872<NA>150837서울특별시 영등포구 신길동 59번지 2호서울특별시 영등포구 영등포로 353 (신길동)7318씨유 신길역점2019-05-16 15:49:45U2019-05-18 02:40:00.0<NA>192689.195811445874.84326825.0
33180000PHMH32012318003408750000420121106<NA>3폐업3폐업20181031<NA><NA><NA>831-5514<NA>150833서울특별시 영등포구 도림동 269번지 4호서울특별시 영등포구 도영로 19 (도림동)7372세븐일레븐 영등포도림동점2018-10-31 11:07:28U2018-11-02 02:35:45.0<NA>190690.263824445152.31687233.0
43180000PHMH32012318003408750000520121106<NA>1영업/정상13영업중<NA><NA><NA><NA>831-2822<NA>150833서울특별시 영등포구 도림동 265번지 6호서울특별시 영등포구 도영로 18 (도림동)7375세븐일레븐 하나텔점2013-09-24 16:53:46I2018-08-31 23:59:59.0<NA>190693.098773445103.70546566.0
53180000PHMH32012318003408750000620121107<NA>1영업/정상13영업중<NA><NA><NA><NA>2676-8807<NA>150103서울특별시 영등포구 양평동3가 23번지 4호서울특별시 영등포구 선유서로 117 (양평동3가)7269지에스25 양평역점2022-09-02 10:17:12U2021-12-09 00:04:00.0<NA>189862.67094447108.692357<NA>
63180000PHMH32012318003408750000720121107<NA>3폐업3폐업20151125<NA><NA><NA>831-9491<NA>150822서울특별시 영등포구 대림동 962번지 4호서울특별시 영등포구 시흥대로 6591 (대림동)150822지에스25 대림성모점2015-11-25 16:25:58I2018-08-31 23:59:59.0<NA>191757.371972443206.12337627.0
73180000PHMH32012318003408750000820121107<NA>1영업/정상13영업중<NA><NA><NA><NA>2068-8455<NA>150040서울특별시 영등포구 당산동 121번지 131호서울특별시 영등포구 버드나루로 95 (당산동)7229씨유 당산행운점2013-09-24 16:55:13I2018-08-31 23:59:59.0<NA>191835.40591447161.71733546.2
83180000PHMH32012318003408750000920121107<NA>3폐업3폐업20160707<NA><NA><NA>3667-0617<NA>150096서울특별시 영등포구 문래동6가 8번지서울특별시 영등포구 선유로 71 (문래동6가)7280지에스25 문래임광2016-07-08 11:30:38I2018-08-31 23:59:59.0<NA>190107.271464446454.59461282.5
93180000PHMH32012318003408750001020121107<NA>3폐업3폐업20130701<NA><NA><NA>2628-9111<NA>150093서울특별시 영등포구 문래동3가 55번지 16호서울특별시 영등포구 문래로 164 (문래동3가)150093세븐일레븐2013-09-24 16:58:39I2018-08-31 23:59:59.0<NA>191087.758954446157.43728923.1
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
7853180000PHMH3202431800340875000072024-02-29<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동6가 127-8서울특별시 영등포구 영등포로33길 15, 1층 (영등포동6가)7251세븐일레븐 영신로점2024-02-29 15:52:41I2023-12-03 00:02:00.0<NA>191324.0145446624.390643<NA>
7863180000PHMH3202431800340875000082024-03-11<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 525 브라이튼 여의도서울특별시 영등포구 국제금융로 39 (여의도동, 브라이튼 여의도)7339지에스25 브라이튼 여의도 2호점2024-03-13 09:42:21I2023-12-02 23:05:00.0<NA><NA><NA><NA>
7873180000PHMH3202431800340875000092024-03-13<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 1101-7 G밸리소홈서울특별시 영등포구 도림천로19길 11, 204호 (대림동, G밸리소홈)7448지에스25 대림밸리소홈점2024-03-13 11:17:00I2023-12-02 23:05:00.0<NA>191102.761901442717.639572<NA>
7883180000PHMH3202431800340875000102024-04-03<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 영등포동 575-12 1층서울특별시 영등포구 영등포로62길 27, 1층 (영등포동)7310GS25 신길타운점2024-04-04 09:35:26I2023-12-04 00:06:00.0<NA>192409.848232445982.704078<NA>
7893180000PHMH3202431800340875000112024-04-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동3가 82-20 문래비즈타워서울특별시 영등포구 문래로 89, 문래비즈타워 107호 (문래동3가)7294씨유 문래아카데미점2024-04-22 16:26:42I2023-12-03 22:04:00.0<NA>190378.925728446388.933977<NA>
7903180000PHMH3202431800340875000122024-04-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 대림동 700-1 기영빌딩서울특별시 영등포구 대림로 154, 기영빌딩 1층 104,105호 (대림동)7422씨유 영등포금화점2024-04-22 16:09:54I2023-12-03 22:04:00.0<NA>191124.182012443626.294389<NA>
7913180000PHMH3202431800340875000132024-04-22<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동3가 295-2 1층서울특별시 영등포구 당산로 114, 1층 (당산동3가)7259씨유 영등포제일점2024-04-24 14:30:19I2023-12-03 22:06:00.0<NA>190790.924654446955.085784<NA>
7923180000PHMH3202431800340875000142024-04-24<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 문래동6가 54 문래동미원아파트서울특별시 영등포구 문래로 38, 문래동미원아파트 102,103호 (문래동6가)7282GS25문래미원점2024-04-24 17:51:17I2023-12-03 22:06:00.0<NA>189887.928482446412.131186<NA>
7933180000PHMH3202431800340875000152024-04-26<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 당산동 121-41 강변 한솔 그라치아 103호서울특별시 영등포구 버드나루로22길 5, 103호 (당산동, 강변 한솔 그라치아)7224지에스25 당산리버파크점2024-04-29 09:19:09I2023-12-05 00:01:00.0<NA>191763.779422447633.778132<NA>
7943180000PHMH3202431800340875000162024-05-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 158-41 푸른학원서울특별시 영등포구 도신로48길 9-2, 1층 (신길동)7348GS25우신초교점2024-05-09 17:37:51I2023-12-04 23:01:00.0<NA>192260.03785445337.259103<NA>