Overview

Dataset statistics

Number of variables26
Number of observations553
Missing cells5188
Missing cells (%)36.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory118.9 KiB
Average record size in memory220.2 B

Variable types

Categorical6
Text7
DateTime4
Unsupported6
Numeric3

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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-16300/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 553 (100.0%) missing valuesMissing
폐업일자 has 244 (44.1%) missing valuesMissing
휴업시작일자 has 553 (100.0%) missing valuesMissing
휴업종료일자 has 553 (100.0%) missing valuesMissing
재개업일자 has 553 (100.0%) missing valuesMissing
전화번호 has 457 (82.6%) missing valuesMissing
소재지면적 has 553 (100.0%) missing valuesMissing
소재지우편번호 has 448 (81.0%) missing valuesMissing
지번주소 has 211 (38.2%) missing valuesMissing
업태구분명 has 553 (100.0%) missing valuesMissing
좌표정보(X) has 15 (2.7%) missing valuesMissing
좌표정보(Y) has 15 (2.7%) missing valuesMissing
판매점영업면적 has 480 (86.8%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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 17 (3.1%) zerosZeros

Reproduction

Analysis started2024-05-10 23:15:55.151591
Analysis finished2024-05-10 23:15:56.918871
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3140000
553 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 553
100.0%

Length

2024-05-10T23:15:57.109004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:15:57.469324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 553
100.0%

관리번호
Text

UNIQUE 

Distinct553
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-10T23:15:58.045912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters13825
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

Unique553 ?
Unique (%)100.0%

Sample

1st rowPHMH320123140033087500001
2nd rowPHMH320123140033087500002
3rd rowPHMH320123140033087500003
4th rowPHMH320123140033087500004
5th rowPHMH320123140033087500005
ValueCountFrequency (%)
phmh320123140033087500001 1
 
0.2%
phmh320193140033087500004 1
 
0.2%
phmh320183140033087500024 1
 
0.2%
phmh320193140033087500009 1
 
0.2%
phmh320193140033087500008 1
 
0.2%
phmh320193140033087500007 1
 
0.2%
phmh320193140033087500006 1
 
0.2%
phmh320193140033087500005 1
 
0.2%
phmh320193140033087500011 1
 
0.2%
phmh320193140033087500010 1
 
0.2%
Other values (543) 543
98.2%
2024-05-10T23:15:59.287217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4060
29.4%
3 2414
17.5%
1 1209
 
8.7%
H 1106
 
8.0%
2 1026
 
7.4%
4 709
 
5.1%
5 681
 
4.9%
7 666
 
4.8%
8 642
 
4.6%
P 553
 
4.0%
Other values (3) 759
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11613
84.0%
Uppercase Letter 2212
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4060
35.0%
3 2414
20.8%
1 1209
 
10.4%
2 1026
 
8.8%
4 709
 
6.1%
5 681
 
5.9%
7 666
 
5.7%
8 642
 
5.5%
6 111
 
1.0%
9 95
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
H 1106
50.0%
P 553
25.0%
M 553
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11613
84.0%
Latin 2212
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4060
35.0%
3 2414
20.8%
1 1209
 
10.4%
2 1026
 
8.8%
4 709
 
6.1%
5 681
 
5.9%
7 666
 
5.7%
8 642
 
5.5%
6 111
 
1.0%
9 95
 
0.8%
Latin
ValueCountFrequency (%)
H 1106
50.0%
P 553
25.0%
M 553
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4060
29.4%
3 2414
17.5%
1 1209
 
8.7%
H 1106
 
8.0%
2 1026
 
7.4%
4 709
 
5.1%
5 681
 
4.9%
7 666
 
4.8%
8 642
 
4.6%
P 553
 
4.0%
Other values (3) 759
 
5.5%

인허가일자
Date

Distinct412
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2012-11-05 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:15:59.870826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:16:00.412390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

영업상태코드
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3
292 
1
244 
4
 
17

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 292
52.8%
1 244
44.1%
4 17
 
3.1%

Length

2024-05-10T23:16:00.861509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:16:01.223110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 292
52.8%
1 244
44.1%
4 17
 
3.1%

영업상태명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
폐업
292 
영업/정상
244 
취소/말소/만료/정지/중지
 
17

Length

Max length14
Median length2
Mean length3.6925859
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 292
52.8%
영업/정상 244
44.1%
취소/말소/만료/정지/중지 17
 
3.1%

Length

2024-05-10T23:16:01.581017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:16:02.128917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 292
52.8%
영업/정상 244
44.1%
취소/말소/만료/정지/중지 17
 
3.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
3
292 
13
244 
24
 
17

Length

Max length2
Median length1
Mean length1.4719711
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 292
52.8%
13 244
44.1%
24 17
 
3.1%

Length

2024-05-10T23:16:02.564180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:16:02.873791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 292
52.8%
13 244
44.1%
24 17
 
3.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
폐업
292 
영업중
244 
직권폐업
 
17

Length

Max length4
Median length2
Mean length2.5027125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 292
52.8%
영업중 244
44.1%
직권폐업 17
 
3.1%

Length

2024-05-10T23:16:03.271707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:16:03.665660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 292
52.8%
영업중 244
44.1%
직권폐업 17
 
3.1%

폐업일자
Date

MISSING 

Distinct273
Distinct (%)88.3%
Missing244
Missing (%)44.1%
Memory size4.4 KiB
Minimum2013-02-08 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:16:04.100517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:16:04.720610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

전화번호
Text

MISSING 

Distinct92
Distinct (%)95.8%
Missing457
Missing (%)82.6%
Memory size4.4 KiB
2024-05-10T23:16:05.562683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9.8125
Min length8

Characters and Unicode

Total characters942
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

Unique88 ?
Unique (%)91.7%

Sample

1st row2692-1918
2nd row2607-5260
3rd row20652051
4th row2651-3065
5th row2653-6136
ValueCountFrequency (%)
1577-0711 2
 
2.1%
2608-0711 2
 
2.1%
2654-9260 2
 
2.1%
070-8873-6349 2
 
2.1%
2604-4144 1
 
1.0%
2606-8373 1
 
1.0%
02-2643-9867 1
 
1.0%
02-2695-1016 1
 
1.0%
2061-7461 1
 
1.0%
6671-1385 1
 
1.0%
Other values (82) 82
85.4%
2024-05-10T23:16:06.871924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 151
16.0%
6 149
15.8%
- 116
12.3%
0 108
11.5%
5 76
8.1%
1 73
7.7%
4 66
7.0%
3 54
 
5.7%
7 51
 
5.4%
8 50
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 826
87.7%
Dash Punctuation 116
 
12.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 151
18.3%
6 149
18.0%
0 108
13.1%
5 76
9.2%
1 73
8.8%
4 66
8.0%
3 54
 
6.5%
7 51
 
6.2%
8 50
 
6.1%
9 48
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 942
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 151
16.0%
6 149
15.8%
- 116
12.3%
0 108
11.5%
5 76
8.1%
1 73
7.7%
4 66
7.0%
3 54
 
5.7%
7 51
 
5.4%
8 50
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 942
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 151
16.0%
6 149
15.8%
- 116
12.3%
0 108
11.5%
5 76
8.1%
1 73
7.7%
4 66
7.0%
3 54
 
5.7%
7 51
 
5.4%
8 50
 
5.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

소재지우편번호
Text

MISSING 

Distinct71
Distinct (%)67.6%
Missing448
Missing (%)81.0%
Memory size4.4 KiB
2024-05-10T23:16:07.518620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9904762
Min length5

Characters and Unicode

Total characters629
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

Unique50 ?
Unique (%)47.6%

Sample

1st row158772
2nd row158865
3rd row158839
4th row158856
5th row158770
ValueCountFrequency (%)
158839 4
 
3.8%
158857 4
 
3.8%
158860 4
 
3.8%
158845 3
 
2.9%
158824 3
 
2.9%
158829 3
 
2.9%
158864 3
 
2.9%
158859 3
 
2.9%
158826 3
 
2.9%
158071 3
 
2.9%
Other values (59) 72
68.6%
2024-05-10T23:16:08.812831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 162
25.8%
5 110
17.5%
1 101
16.1%
0 59
 
9.4%
7 47
 
7.5%
9 32
 
5.1%
6 29
 
4.6%
4 27
 
4.3%
2 25
 
4.0%
3 16
 
2.5%
Other values (2) 21
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 608
96.7%
Space Separator 14
 
2.2%
Dash Punctuation 7
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 162
26.6%
5 110
18.1%
1 101
16.6%
0 59
 
9.7%
7 47
 
7.7%
9 32
 
5.3%
6 29
 
4.8%
4 27
 
4.4%
2 25
 
4.1%
3 16
 
2.6%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 629
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 162
25.8%
5 110
17.5%
1 101
16.1%
0 59
 
9.4%
7 47
 
7.5%
9 32
 
5.1%
6 29
 
4.6%
4 27
 
4.3%
2 25
 
4.0%
3 16
 
2.5%
Other values (2) 21
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 629
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 162
25.8%
5 110
17.5%
1 101
16.1%
0 59
 
9.4%
7 47
 
7.5%
9 32
 
5.1%
6 29
 
4.6%
4 27
 
4.3%
2 25
 
4.0%
3 16
 
2.5%
Other values (2) 21
 
3.3%

지번주소
Text

MISSING 

Distinct285
Distinct (%)83.3%
Missing211
Missing (%)38.2%
Memory size4.4 KiB
2024-05-10T23:16:09.543876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length22.894737
Min length12

Characters and Unicode

Total characters7830
Distinct characters148
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)71.9%

Sample

1st row서울특별시 양천구 신정동 326번지 112호
2nd row서울특별시 양천구 신정동 1289번지 대림프라자 101호
3rd row서울특별시 양천구 신월동 523번지 6호
4th row서울특별시 양천구 신정동 890번지 27호 105호
5th row서울특별시 양천구 311번지
ValueCountFrequency (%)
서울특별시 341
20.7%
양천구 341
20.7%
신정동 129
 
7.8%
신월동 114
 
6.9%
목동 95
 
5.8%
1호 32
 
1.9%
5호 16
 
1.0%
7호 12
 
0.7%
4호 9
 
0.5%
15호 8
 
0.5%
Other values (368) 553
33.5%
2024-05-10T23:16:10.958851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1316
 
16.8%
동 376
 
4.8%
시 361
 
4.6%
1 344
 
4.4%
서 343
 
4.4%
특 341
 
4.4%
별 341
 
4.4%
양 341
 
4.4%
천 341
 
4.4%
구 341
 
4.4%
Other values (138) 3385
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4895
62.5%
Decimal Number 1517
 
19.4%
Space Separator 1316
 
16.8%
Dash Punctuation 81
 
1.0%
Uppercase Letter 15
 
0.2%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 376
 
7.7%
시 361
 
7.4%
서 343
 
7.0%
특 341
 
7.0%
별 341
 
7.0%
양 341
 
7.0%
천 341
 
7.0%
구 341
 
7.0%
울 341
 
7.0%
신 275
 
5.6%
Other values (116) 1494
30.5%
Decimal Number
ValueCountFrequency (%)
1 344
22.7%
2 176
11.6%
3 157
10.3%
0 156
10.3%
9 148
9.8%
5 137
 
9.0%
4 133
 
8.8%
7 106
 
7.0%
6 83
 
5.5%
8 77
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
O 3
20.0%
K 3
20.0%
M 2
13.3%
S 2
13.3%
A 2
13.3%
L 1
 
6.7%
T 1
 
6.7%
B 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Space Separator
ValueCountFrequency (%)
1316
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4895
62.5%
Common 2920
37.3%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 376
 
7.7%
시 361
 
7.4%
서 343
 
7.0%
특 341
 
7.0%
별 341
 
7.0%
양 341
 
7.0%
천 341
 
7.0%
구 341
 
7.0%
울 341
 
7.0%
신 275
 
5.6%
Other values (116) 1494
30.5%
Common
ValueCountFrequency (%)
1316
45.1%
1 344
 
11.8%
2 176
 
6.0%
3 157
 
5.4%
0 156
 
5.3%
9 148
 
5.1%
5 137
 
4.7%
4 133
 
4.6%
7 106
 
3.6%
6 83
 
2.8%
Other values (4) 164
 
5.6%
Latin
ValueCountFrequency (%)
O 3
20.0%
K 3
20.0%
M 2
13.3%
S 2
13.3%
A 2
13.3%
L 1
 
6.7%
T 1
 
6.7%
B 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4895
62.5%
ASCII 2935
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1316
44.8%
1 344
 
11.7%
2 176
 
6.0%
3 157
 
5.3%
0 156
 
5.3%
9 148
 
5.0%
5 137
 
4.7%
4 133
 
4.5%
7 106
 
3.6%
6 83
 
2.8%
Other values (12) 179
 
6.1%
Hangul
ValueCountFrequency (%)
동 376
 
7.7%
시 361
 
7.4%
서 343
 
7.0%
특 341
 
7.0%
별 341
 
7.0%
양 341
 
7.0%
천 341
 
7.0%
구 341
 
7.0%
울 341
 
7.0%
신 275
 
5.6%
Other values (116) 1494
30.5%

도로명주소
Text

Distinct475
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-10T23:16:11.614115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length56
Mean length31.703436
Min length21

Characters and Unicode

Total characters17532
Distinct characters216
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

Unique408 ?
Unique (%)73.8%

Sample

1st row서울특별시 양천구 목동동로 50 (신정동)
2nd row서울특별시 양천구 남부순환로70길 20, 1층 (신월동)
3rd row서울특별시 양천구 오목로 146 (신정동)
4th row서울특별시 양천구 신정로13길 22 (신정동, 대림프라자 101호)
5th row서울특별시 양천구 목동서로2길 20 (목동)
ValueCountFrequency (%)
서울특별시 553
 
16.1%
양천구 553
 
16.1%
1층 205
 
6.0%
신정동 190
 
5.5%
신월동 181
 
5.3%
목동 179
 
5.2%
목동동로 40
 
1.2%
목동서로 39
 
1.1%
오목로 37
 
1.1%
101호 28
 
0.8%
Other values (572) 1431
41.6%
2024-05-10T23:16:12.932720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2884
 
16.4%
1 919
 
5.2%
동 905
 
5.2%
서 608
 
3.5%
시 592
 
3.4%
양 576
 
3.3%
로 569
 
3.2%
천 559
 
3.2%
울 554
 
3.2%
구 554
 
3.2%
Other values (206) 8812
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10194
58.1%
Space Separator 2884
 
16.4%
Decimal Number 2723
 
15.5%
Close Punctuation 553
 
3.2%
Open Punctuation 553
 
3.2%
Other Punctuation 543
 
3.1%
Uppercase Letter 39
 
0.2%
Dash Punctuation 34
 
0.2%
Math Symbol 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 905
 
8.9%
서 608
 
6.0%
시 592
 
5.8%
양 576
 
5.7%
로 569
 
5.6%
천 559
 
5.5%
울 554
 
5.4%
구 554
 
5.4%
특 553
 
5.4%
별 553
 
5.4%
Other values (180) 4171
40.9%
Decimal Number
ValueCountFrequency (%)
1 919
33.7%
0 370
13.6%
2 297
 
10.9%
3 274
 
10.1%
4 184
 
6.8%
5 183
 
6.7%
7 147
 
5.4%
6 143
 
5.3%
9 108
 
4.0%
8 98
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
A 13
33.3%
B 8
20.5%
C 4
 
10.3%
S 3
 
7.7%
K 3
 
7.7%
O 3
 
7.7%
M 3
 
7.7%
T 1
 
2.6%
L 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 541
99.6%
. 2
 
0.4%
Space Separator
ValueCountFrequency (%)
2884
100.0%
Close Punctuation
ValueCountFrequency (%)
) 553
100.0%
Open Punctuation
ValueCountFrequency (%)
( 553
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10194
58.1%
Common 7299
41.6%
Latin 39
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 905
 
8.9%
서 608
 
6.0%
시 592
 
5.8%
양 576
 
5.7%
로 569
 
5.6%
천 559
 
5.5%
울 554
 
5.4%
구 554
 
5.4%
특 553
 
5.4%
별 553
 
5.4%
Other values (180) 4171
40.9%
Common
ValueCountFrequency (%)
2884
39.5%
1 919
 
12.6%
) 553
 
7.6%
( 553
 
7.6%
, 541
 
7.4%
0 370
 
5.1%
2 297
 
4.1%
3 274
 
3.8%
4 184
 
2.5%
5 183
 
2.5%
Other values (7) 541
 
7.4%
Latin
ValueCountFrequency (%)
A 13
33.3%
B 8
20.5%
C 4
 
10.3%
S 3
 
7.7%
K 3
 
7.7%
O 3
 
7.7%
M 3
 
7.7%
T 1
 
2.6%
L 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10194
58.1%
ASCII 7338
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2884
39.3%
1 919
 
12.5%
) 553
 
7.5%
( 553
 
7.5%
, 541
 
7.4%
0 370
 
5.0%
2 297
 
4.0%
3 274
 
3.7%
4 184
 
2.5%
5 183
 
2.5%
Other values (16) 580
 
7.9%
Hangul
ValueCountFrequency (%)
동 905
 
8.9%
서 608
 
6.0%
시 592
 
5.8%
양 576
 
5.7%
로 569
 
5.6%
천 559
 
5.5%
울 554
 
5.4%
구 554
 
5.4%
특 553
 
5.4%
별 553
 
5.4%
Other values (180) 4171
40.9%

도로명우편번호
Text

Distinct176
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-10T23:16:13.843607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0632911
Min length5

Characters and Unicode

Total characters2800
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

Unique52 ?
Unique (%)9.4%

Sample

1st row158772
2nd row158846
3rd row08019
4th row08080
5th row07978
ValueCountFrequency (%)
07946 10
 
1.8%
08032 9
 
1.6%
08096 9
 
1.6%
07964 8
 
1.4%
08023 8
 
1.4%
07903 8
 
1.4%
07960 7
 
1.3%
08007 7
 
1.3%
08087 7
 
1.3%
07983 7
 
1.3%
Other values (166) 473
85.5%
2024-05-10T23:16:15.467923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 876
31.3%
7 401
14.3%
8 400
14.3%
9 372
13.3%
1 148
 
5.3%
5 129
 
4.6%
4 126
 
4.5%
2 120
 
4.3%
3 114
 
4.1%
6 113
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2799
> 99.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 876
31.3%
7 401
14.3%
8 400
14.3%
9 372
13.3%
1 148
 
5.3%
5 129
 
4.6%
4 126
 
4.5%
2 120
 
4.3%
3 114
 
4.1%
6 113
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2800
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 876
31.3%
7 401
14.3%
8 400
14.3%
9 372
13.3%
1 148
 
5.3%
5 129
 
4.6%
4 126
 
4.5%
2 120
 
4.3%
3 114
 
4.1%
6 113
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 876
31.3%
7 401
14.3%
8 400
14.3%
9 372
13.3%
1 148
 
5.3%
5 129
 
4.6%
4 126
 
4.5%
2 120
 
4.3%
3 114
 
4.1%
6 113
 
4.0%

사업장명
Text

Distinct474
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
2024-05-10T23:16:16.472032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.735986
Min length4

Characters and Unicode

Total characters5937
Distinct characters258
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique412 ?
Unique (%)74.5%

Sample

1st row(주)바이더웨이 신정타운점
2nd row씨유 신월남부점
3rd row씨유 신정역점
4th row(주)바이더웨이 신정백암점
5th row씨유목동1호점
ValueCountFrequency (%)
씨유 143
 
14.0%
gs25 91
 
8.9%
지에스25 59
 
5.8%
주)코리아세븐 37
 
3.6%
세븐일레븐 36
 
3.5%
미니스톱 17
 
1.7%
지에스(gs)25 15
 
1.5%
이마트24 14
 
1.4%
목동13단지점 8
 
0.8%
주)비지에프리테일 8
 
0.8%
Other values (414) 594
58.1%
2024-05-10T23:16:18.111254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 505
 
8.5%
471
 
7.9%
신 276
 
4.6%
목 239
 
4.0%
동 234
 
3.9%
2 229
 
3.9%
5 209
 
3.5%
유 178
 
3.0%
씨 167
 
2.8%
월 159
 
2.7%
Other values (248) 3270
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4405
74.2%
Decimal Number 537
 
9.0%
Space Separator 471
 
7.9%
Uppercase Letter 311
 
5.2%
Close Punctuation 97
 
1.6%
Open Punctuation 97
 
1.6%
Other Symbol 13
 
0.2%
Lowercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 505
 
11.5%
신 276
 
6.3%
목 239
 
5.4%
동 234
 
5.3%
유 178
 
4.0%
씨 167
 
3.8%
월 159
 
3.6%
스 153
 
3.5%
지 150
 
3.4%
븐 145
 
3.3%
Other values (214) 2199
49.9%
Uppercase Letter
ValueCountFrequency (%)
S 137
44.1%
G 132
42.4%
U 8
 
2.6%
C 7
 
2.3%
K 7
 
2.3%
A 4
 
1.3%
R 3
 
1.0%
L 2
 
0.6%
O 2
 
0.6%
P 2
 
0.6%
Other values (4) 7
 
2.3%
Decimal Number
ValueCountFrequency (%)
2 229
42.6%
5 209
38.9%
1 33
 
6.1%
4 27
 
5.0%
3 20
 
3.7%
6 7
 
1.3%
0 6
 
1.1%
7 4
 
0.7%
9 1
 
0.2%
8 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
m 1
16.7%
a 1
16.7%
r 1
16.7%
s 1
16.7%
g 1
16.7%
t 1
16.7%
Space Separator
ValueCountFrequency (%)
471
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4418
74.4%
Common 1202
 
20.2%
Latin 317
 
5.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 505
 
11.4%
신 276
 
6.2%
목 239
 
5.4%
동 234
 
5.3%
유 178
 
4.0%
씨 167
 
3.8%
월 159
 
3.6%
스 153
 
3.5%
지 150
 
3.4%
븐 145
 
3.3%
Other values (215) 2212
50.1%
Latin
ValueCountFrequency (%)
S 137
43.2%
G 132
41.6%
U 8
 
2.5%
C 7
 
2.2%
K 7
 
2.2%
A 4
 
1.3%
R 3
 
0.9%
L 2
 
0.6%
O 2
 
0.6%
P 2
 
0.6%
Other values (10) 13
 
4.1%
Common
ValueCountFrequency (%)
471
39.2%
2 229
19.1%
5 209
17.4%
) 97
 
8.1%
( 97
 
8.1%
1 33
 
2.7%
4 27
 
2.2%
3 20
 
1.7%
6 7
 
0.6%
0 6
 
0.5%
Other values (3) 6
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4405
74.2%
ASCII 1519
 
25.6%
None 13
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 505
 
11.5%
신 276
 
6.3%
목 239
 
5.4%
동 234
 
5.3%
유 178
 
4.0%
씨 167
 
3.8%
월 159
 
3.6%
스 153
 
3.5%
지 150
 
3.4%
븐 145
 
3.3%
Other values (214) 2199
49.9%
ASCII
ValueCountFrequency (%)
471
31.0%
2 229
15.1%
5 209
13.8%
S 137
 
9.0%
G 132
 
8.7%
) 97
 
6.4%
( 97
 
6.4%
1 33
 
2.2%
4 27
 
1.8%
3 20
 
1.3%
Other values (23) 67
 
4.4%
None
ValueCountFrequency (%)
㈜ 13
100.0%

최종수정일자
Date

UNIQUE 

Distinct553
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2013-08-20 16:44:06
Maximum2024-05-09 16:16:12
2024-05-10T23:16:18.911106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:16:19.488870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
I
332 
U
221 

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 332
60.0%
U 221
40.0%

Length

2024-05-10T23:16:20.037520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:16:20.416550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 332
60.0%
u 221
40.0%

데이터갱신일자
Date

Distinct275
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Memory size4.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-10T23:16:20.862933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:16:21.411021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing553
Missing (%)100.0%
Memory size5.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct335
Distinct (%)62.3%
Missing15
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean187178.52
Minimum184449.39
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-10T23:16:21.917670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184449.39
5-th percentile184830.12
Q1185760.11
median187553.46
Q3188373.33
95-th percentile189158.15
Maximum189878.41
Range5429.0206
Interquartile range (IQR)2613.2212

Descriptive statistics

Standard deviation1466.2722
Coefficient of variation (CV)0.0078335494
Kurtosis-1.2506871
Mean187178.52
Median Absolute Deviation (MAD)1185.8561
Skewness-0.23884155
Sum1.0070204 × 108
Variance2149954.2
MonotonicityNot monotonic
2024-05-10T23:16:22.757435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187995.261631804 9
 
1.6%
185940.44604599 6
 
1.1%
187437.037841856 5
 
0.9%
188431.286329151 5
 
0.9%
186737.931737226 4
 
0.7%
185165.228441912 4
 
0.7%
188827.890646121 4
 
0.7%
187892.354708086 4
 
0.7%
188215.9325217 4
 
0.7%
185785.396465404 4
 
0.7%
Other values (325) 489
88.4%
(Missing) 15
 
2.7%
ValueCountFrequency (%)
184449.386660638 1
 
0.2%
184463.737895899 1
 
0.2%
184549.26 2
0.4%
184633.623963945 2
0.4%
184638.966406494 1
 
0.2%
184644.415616888 1
 
0.2%
184663.278216529 1
 
0.2%
184672.622849866 1
 
0.2%
184678.753937033 3
0.5%
184679.867647534 1
 
0.2%
ValueCountFrequency (%)
189878.40729119 2
0.4%
189755.541308355 2
0.4%
189749.776358917 2
0.4%
189709.803505321 1
 
0.2%
189645.577035228 1
 
0.2%
189519.862506193 2
0.4%
189508.199599752 3
0.5%
189498.233991849 3
0.5%
189473.530827695 1
 
0.2%
189471.306217651 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct335
Distinct (%)62.3%
Missing15
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean447322.27
Minimum444916.93
Maximum449843.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-10T23:16:23.863305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444916.93
5-th percentile445674.62
Q1446517.54
median447045.99
Q3448247.53
95-th percentile449315.69
Maximum449843.2
Range4926.2718
Interquartile range (IQR)1729.9919

Descriptive statistics

Standard deviation1113.7781
Coefficient of variation (CV)0.0024898784
Kurtosis-0.79786208
Mean447322.27
Median Absolute Deviation (MAD)831.14649
Skewness0.29112084
Sum2.4065938 × 108
Variance1240501.6
MonotonicityNot monotonic
2024-05-10T23:16:24.441459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445782.650926649 9
 
1.6%
446506.307051421 6
 
1.1%
446140.068718483 5
 
0.9%
446909.365903882 5
 
0.9%
446648.984649193 4
 
0.7%
448490.772592345 4
 
0.7%
446169.555330517 4
 
0.7%
447311.563663095 4
 
0.7%
448470.289357226 4
 
0.7%
446152.066202692 4
 
0.7%
Other values (325) 489
88.4%
(Missing) 15
 
2.7%
ValueCountFrequency (%)
444916.93118 1
 
0.2%
445018.996790344 1
 
0.2%
445081.396522145 1
 
0.2%
445094.16222004 1
 
0.2%
445113.109971419 1
 
0.2%
445197.198550791 3
0.5%
445226.553879059 1
 
0.2%
445256.468917074 2
0.4%
445479.209299057 3
0.5%
445524.71062635 1
 
0.2%
ValueCountFrequency (%)
449843.203005652 2
0.4%
449753.158413664 1
0.2%
449727.47955699 1
0.2%
449698.560303556 2
0.4%
449677.36412672 1
0.2%
449668.428997479 2
0.4%
449603.052220201 1
0.2%
449565.722768071 1
0.2%
449497.62570732 1
0.2%
449464.01919905 1
0.2%

판매점영업면적
Real number (ℝ)

MISSING  ZEROS 

Distinct49
Distinct (%)67.1%
Missing480
Missing (%)86.8%
Infinite0
Infinite (%)0.0%
Mean50.989726
Minimum0
Maximum230
Zeros17
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2024-05-10T23:16:24.895173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123.56
median50.59
Q366
95-th percentile121.176
Maximum230
Range230
Interquartile range (IQR)42.44

Descriptive statistics

Standard deviation43.244758
Coefficient of variation (CV)0.84810728
Kurtosis3.3141642
Mean50.989726
Median Absolute Deviation (MAD)20.89
Skewness1.2922588
Sum3722.25
Variance1870.1091
MonotonicityNot monotonic
2024-05-10T23:16:25.496457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.0 17
 
3.1%
66.0 4
 
0.7%
49.5 3
 
0.5%
59.4 2
 
0.4%
60.0 2
 
0.4%
64.0 2
 
0.4%
33.0 1
 
0.2%
59.0 1
 
0.2%
147.84 1
 
0.2%
53.89 1
 
0.2%
Other values (39) 39
 
7.1%
(Missing) 480
86.8%
ValueCountFrequency (%)
0.0 17
3.1%
20.0 1
 
0.2%
23.56 1
 
0.2%
24.0 1
 
0.2%
26.4 1
 
0.2%
29.0 1
 
0.2%
29.7 1
 
0.2%
29.75 1
 
0.2%
33.0 1
 
0.2%
37.38 1
 
0.2%
ValueCountFrequency (%)
230.0 1
0.2%
165.0 1
0.2%
147.84 1
0.2%
125.46 1
0.2%
118.32 1
0.2%
106.0 1
0.2%
101.98 1
0.2%
100.0 1
0.2%
99.0 1
0.2%
96.6 1
0.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
03140000PHMH32012314003308750000120121119<NA>3폐업3폐업20130819<NA><NA><NA><NA><NA>158772서울특별시 양천구 신정동 326번지 112호서울특별시 양천구 목동동로 50 (신정동)158772(주)바이더웨이 신정타운점2013-08-20 16:44:06I2018-08-31 23:59:59.0<NA>187652.903985445655.044399<NA>
13140000PHMH32012314003308750000220121114<NA>3폐업3폐업20130926<NA><NA><NA>2692-1918<NA><NA><NA>서울특별시 양천구 남부순환로70길 20, 1층 (신월동)158846씨유 신월남부점2013-09-26 17:39:10I2018-08-31 23:59:59.0<NA>185313.848748446617.17723<NA>
23140000PHMH32012314003308750000320121115<NA>3폐업3폐업20130926<NA><NA><NA>2607-5260<NA><NA><NA>서울특별시 양천구 오목로 146 (신정동)08019씨유 신정역점2016-02-24 11:38:17I2018-08-31 23:59:59.0<NA>186992.734329446925.412722<NA>
33140000PHMH32012314003308750000420121116<NA>3폐업3폐업20131010<NA><NA><NA><NA><NA>158865서울특별시 양천구 신정동 1289번지 대림프라자 101호서울특별시 양천구 신정로13길 22 (신정동, 대림프라자 101호)08080(주)바이더웨이 신정백암점2016-02-24 10:37:52I2018-08-31 23:59:59.0<NA>186064.682339445479.209299<NA>
43140000PHMH32012314003308750000520121121<NA>3폐업3폐업20131017<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동서로2길 20 (목동)07978씨유목동1호점2016-02-24 11:42:53I2018-08-31 23:59:59.0<NA>189498.233992448633.408281<NA>
53140000PHMH32012314003308750000620121113<NA>3폐업3폐업20131021<NA><NA><NA><NA><NA>158839서울특별시 양천구 신월동 523번지 6호서울특별시 양천구 신월로9길 38 (신월동, 모던그린힐 101, 102호)08032씨유 신월일등점2016-02-24 11:32:04I2018-08-31 23:59:59.0<NA>185685.538176446514.871872<NA>
63140000PHMH32012314003308750000720121109<NA>3폐업3폐업20131113<NA><NA><NA><NA><NA>158856서울특별시 양천구 신정동 890번지 27호 105호서울특별시 양천구 목동로23길 10 (신정동)07938씨유 신정4동점2016-02-24 11:29:39I2018-08-31 23:59:59.0<NA>187780.221358447256.377194<NA>
73140000PHMH32012314003308750000820121109<NA>3폐업3폐업20131122<NA><NA><NA><NA><NA>158770서울특별시 양천구 311번지서울특별시 양천구 목동서로 400 (신정동, 목동10단지 A상가 101호)158770GS25 목동10단지2013-11-22 13:05:10I2018-08-31 23:59:59.0<NA>187437.037842446140.068718<NA>
83140000PHMH32012314003308750000920121123<NA>3폐업3폐업20131128<NA><NA><NA><NA><NA>158864서울특별시 양천구 신정동 1182번지 2호 102,103호서울특별시 양천구 중앙로 251 (신정동, 102,103호)158864GS25 신정코아점2013-11-28 14:21:22I2018-08-31 23:59:59.0<NA>186953.199758446282.381841<NA>
93140000PHMH32012314003308750001020121123<NA>3폐업3폐업20131206<NA><NA><NA>20652051<NA>158859서울특별시 양천구 신정동 971번지 15호서울특별시 양천구 중앙로 290 (신정동)158859GS25 신정네거리점2013-12-06 17:48:41I2018-08-31 23:59:59.0<NA>186865.729139446669.777229<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)판매점영업면적
5433140000PHMH3202431400330875000102024-03-19<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1282 푸른마을 1단지아파트서울특별시 양천구 신정로7길 70, B105,106,107호 (신정동, 푸른마을 1단지아파트)08048지에스(GS)25 신정푸른마을점2024-03-20 08:56:40I2023-12-02 22:02:00.0<NA>185451.540644445616.763199<NA>
5443140000PHMH3202431400330875000112024-03-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 남부순환로 338 (신월동)07909지에스25 신월기쁨점2024-03-21 16:01:16I2023-12-02 22:03:00.0<NA>184672.62285448273.098689<NA>
5453140000PHMH3202431400330875000122024-03-21<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 295-4서울특별시 양천구 신목로 25, 1층 (신정동)08017지에스25 신정사랑점2024-03-21 16:01:28I2023-12-02 22:03:00.0<NA>188827.890646446169.555331<NA>
5463140000PHMH3202431400330875000132024-05-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 564-1서울특별시 양천구 남부순환로85길 12, 1층 (신월동)08080지에스25 신정뉴타운점2024-05-02 09:05:16I2023-12-05 00:04:00.0<NA>185974.484909445834.345525<NA>
5473140000PHMH3202431400330875000142024-05-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 751-2 해피하우스서울특별시 양천구 목동중앙본로 26, 해피하우스 1층 (목동)07976지에스25 목동고목점2024-05-02 09:05:41I2023-12-05 00:04:00.0<NA>188466.125047448535.743636<NA>
5483140000PHMH3202431400330875000152024-05-01<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 133-13서울특별시 양천구 곰달래로5길 21, 1층 (신월동)07921지에스25 신월1동점2024-05-02 09:06:02I2023-12-05 00:04:00.0<NA>185219.569419447715.338113<NA>
5493140000PHMH3202431400330875000162024-05-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 911 목동신시가지아파트6단지서울특별시 양천구 목동동로 430, 상가동 107,108호 (목동, 목동신시가지아파트6단지)07986씨유 목동6단지점2024-05-07 17:21:05I2023-12-05 00:09:00.0<NA>189749.776359448050.161097<NA>
5503140000PHMH3202431400330875000172024-05-07<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 공항대로 558 (목동)07946지에스25 공항로2024-05-07 17:20:24I2023-12-05 00:09:00.0<NA>188212.125473449668.428997<NA>
5513140000PHMH3202431400330875000182024-05-08<NA>1영업/정상13영업중<NA><NA><NA><NA>02-2699-9919<NA><NA><NA>서울특별시 양천구 중앙로46길 29, 1층 (신정동)08025지에스25 신정동성당점2024-05-08 17:46:19I2023-12-04 23:00:00.0<NA>187141.916926446705.027444<NA>
5523140000PHMH3202431400330875000192024-05-09<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 남부순환로59길 5, 1층 (신월동)07920씨유 양천카인드점2024-05-09 16:16:12I2023-12-04 23:01:00.0<NA>185078.559215447791.952952<NA>