Overview

Dataset statistics

Number of variables44
Number of observations111
Missing cells1163
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.8 KiB
Average record size in memory376.2 B

Variable types

Categorical20
Text6
DateTime4
Unsupported7
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18316/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
총인원 is highly imbalanced (87.0%)Imbalance
보증액 is highly imbalanced (72.1%)Imbalance
월세액 is highly imbalanced (74.3%)Imbalance
인허가취소일자 has 111 (100.0%) missing valuesMissing
폐업일자 has 31 (27.9%) missing valuesMissing
휴업시작일자 has 111 (100.0%) missing valuesMissing
휴업종료일자 has 111 (100.0%) missing valuesMissing
재개업일자 has 111 (100.0%) missing valuesMissing
전화번호 has 11 (9.9%) missing valuesMissing
소재지면적 has 6 (5.4%) missing valuesMissing
도로명주소 has 47 (42.3%) missing valuesMissing
도로명우편번호 has 47 (42.3%) missing valuesMissing
좌표정보(X) has 2 (1.8%) missing valuesMissing
좌표정보(Y) has 2 (1.8%) missing valuesMissing
남성종사자수 has 88 (79.3%) missing valuesMissing
여성종사자수 has 94 (84.7%) missing valuesMissing
다중이용업소여부 has 29 (26.1%) missing valuesMissing
시설총규모 has 29 (26.1%) missing valuesMissing
전통업소지정번호 has 111 (100.0%) missing valuesMissing
전통업소주된음식 has 111 (100.0%) missing valuesMissing
홈페이지 has 111 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 6 (5.4%) zerosZeros
여성종사자수 has 10 (9.0%) zerosZeros
시설총규모 has 71 (64.0%) zerosZeros

Reproduction

Analysis started2024-05-11 05:48:33.399428
Analysis finished2024-05-11 05:48:34.533502
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
3140000
111 

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 111
100.0%

Length

2024-05-11T05:48:34.777633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:35.213257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 111
100.0%

관리번호
Text

UNIQUE 

Distinct111
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-05-11T05:48:35.538396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2442
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

Unique111 ?
Unique (%)100.0%

Sample

1st row3140000-114-1996-00406
2nd row3140000-114-1996-00407
3rd row3140000-114-1996-00408
4th row3140000-114-1996-00409
5th row3140000-114-1996-00410
ValueCountFrequency (%)
3140000-114-1996-00406 1
 
0.9%
3140000-114-2013-00003 1
 
0.9%
3140000-114-2012-00002 1
 
0.9%
3140000-114-2012-00001 1
 
0.9%
3140000-114-2011-00004 1
 
0.9%
3140000-114-2011-00003 1
 
0.9%
3140000-114-2011-00002 1
 
0.9%
3140000-114-2011-00001 1
 
0.9%
3140000-114-2010-00003 1
 
0.9%
3140000-114-2010-00002 1
 
0.9%
Other values (101) 101
91.0%
2024-05-11T05:48:36.361615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 978
40.0%
1 440
18.0%
- 333
 
13.6%
4 259
 
10.6%
3 140
 
5.7%
2 132
 
5.4%
9 67
 
2.7%
6 36
 
1.5%
8 20
 
0.8%
7 19
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2109
86.4%
Dash Punctuation 333
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 978
46.4%
1 440
20.9%
4 259
 
12.3%
3 140
 
6.6%
2 132
 
6.3%
9 67
 
3.2%
6 36
 
1.7%
8 20
 
0.9%
7 19
 
0.9%
5 18
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 333
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2442
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 978
40.0%
1 440
18.0%
- 333
 
13.6%
4 259
 
10.6%
3 140
 
5.7%
2 132
 
5.4%
9 67
 
2.7%
6 36
 
1.5%
8 20
 
0.8%
7 19
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 978
40.0%
1 440
18.0%
- 333
 
13.6%
4 259
 
10.6%
3 140
 
5.7%
2 132
 
5.4%
9 67
 
2.7%
6 36
 
1.5%
8 20
 
0.8%
7 19
 
0.8%

인허가일자
Date

Distinct99
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum1996-06-28 00:00:00
Maximum2023-01-18 00:00:00
2024-05-11T05:48:36.758098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:48:37.049765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
3
80 
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 80
72.1%
1 31
 
27.9%

Length

2024-05-11T05:48:37.283273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:37.464358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 80
72.1%
1 31
 
27.9%

영업상태명
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
폐업
80 
영업/정상
31 

Length

Max length5
Median length2
Mean length2.8378378
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 80
72.1%
영업/정상 31
 
27.9%

Length

2024-05-11T05:48:37.731221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:38.019328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 80
72.1%
영업/정상 31
 
27.9%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2
80 
1
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 80
72.1%
1 31
 
27.9%

Length

2024-05-11T05:48:38.346343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:38.662957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 80
72.1%
1 31
 
27.9%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
폐업
80 
영업
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 80
72.1%
영업 31
 
27.9%

Length

2024-05-11T05:48:38.917393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:39.143788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 80
72.1%
영업 31
 
27.9%

폐업일자
Date

MISSING 

Distinct68
Distinct (%)85.0%
Missing31
Missing (%)27.9%
Memory size1020.0 B
Minimum1997-11-04 00:00:00
Maximum2023-11-20 00:00:00
2024-05-11T05:48:39.476804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:48:39.907773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

전화번호
Text

MISSING 

Distinct93
Distinct (%)93.0%
Missing11
Missing (%)9.9%
Memory size1020.0 B
2024-05-11T05:48:40.454883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.75
Min length2

Characters and Unicode

Total characters975
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

Unique87 ?
Unique (%)87.0%

Sample

1st row02 6469541
2nd row02 6499466
3rd row0226452173
4th row02 6067686
5th row0226464331
ValueCountFrequency (%)
02 16
 
14.2%
0226552755 2
 
1.8%
0226499466 2
 
1.8%
0226444296 2
 
1.8%
0226027210 2
 
1.8%
0226442826 2
 
1.8%
0226956131 1
 
0.9%
0226032553 1
 
0.9%
0220629739 1
 
0.9%
0226518955 1
 
0.9%
Other values (83) 83
73.5%
2024-05-11T05:48:41.427249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 251
25.7%
0 170
17.4%
6 146
15.0%
4 89
 
9.1%
5 69
 
7.1%
9 62
 
6.4%
3 45
 
4.6%
8 44
 
4.5%
7 42
 
4.3%
1 42
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 960
98.5%
Space Separator 15
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 251
26.1%
0 170
17.7%
6 146
15.2%
4 89
 
9.3%
5 69
 
7.2%
9 62
 
6.5%
3 45
 
4.7%
8 44
 
4.6%
7 42
 
4.4%
1 42
 
4.4%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 975
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 251
25.7%
0 170
17.4%
6 146
15.0%
4 89
 
9.1%
5 69
 
7.1%
9 62
 
6.4%
3 45
 
4.6%
8 44
 
4.5%
7 42
 
4.3%
1 42
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 975
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 251
25.7%
0 170
17.4%
6 146
15.0%
4 89
 
9.1%
5 69
 
7.1%
9 62
 
6.4%
3 45
 
4.6%
8 44
 
4.5%
7 42
 
4.3%
1 42
 
4.3%

소재지면적
Text

MISSING 

Distinct78
Distinct (%)74.3%
Missing6
Missing (%)5.4%
Memory size1020.0 B
2024-05-11T05:48:41.936696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.9428571
Min length3

Characters and Unicode

Total characters624
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)63.8%

Sample

1st row.00
2nd row.00
3rd row475.68
4th row.00
5th row356.40
ValueCountFrequency (%)
00 12
 
11.4%
990.00 5
 
4.8%
726.00 3
 
2.9%
359.00 3
 
2.9%
396.00 3
 
2.9%
650.00 2
 
1.9%
627.00 2
 
1.9%
584.70 2
 
1.9%
539.00 2
 
1.9%
360.00 2
 
1.9%
Other values (68) 69
65.7%
2024-05-11T05:48:42.938014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 188
30.1%
. 105
16.8%
3 55
 
8.8%
9 41
 
6.6%
5 41
 
6.6%
6 40
 
6.4%
4 33
 
5.3%
1 33
 
5.3%
7 29
 
4.6%
8 26
 
4.2%
Other values (2) 33
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 508
81.4%
Other Punctuation 116
 
18.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 188
37.0%
3 55
 
10.8%
9 41
 
8.1%
5 41
 
8.1%
6 40
 
7.9%
4 33
 
6.5%
1 33
 
6.5%
7 29
 
5.7%
8 26
 
5.1%
2 22
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 105
90.5%
, 11
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 188
30.1%
. 105
16.8%
3 55
 
8.8%
9 41
 
6.6%
5 41
 
6.6%
6 40
 
6.4%
4 33
 
5.3%
1 33
 
5.3%
7 29
 
4.6%
8 26
 
4.2%
Other values (2) 33
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 188
30.1%
. 105
16.8%
3 55
 
8.8%
9 41
 
6.6%
5 41
 
6.6%
6 40
 
6.4%
4 33
 
5.3%
1 33
 
5.3%
7 29
 
4.6%
8 26
 
4.2%
Other values (2) 33
 
5.3%

소재지우편번호
Categorical

Distinct48
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Memory size1020.0 B
158070
11 
158849
 
6
158861
 
6
158864
 
5
158050
 
5
Other values (43)
78 

Length

Max length7
Median length6
Mean length6.1621622
Min length6

Unique

Unique22 ?
Unique (%)19.8%

Sample

1st row158861
2nd row158070
3rd row158861
4th row158824
5th row158-876

Common Values

ValueCountFrequency (%)
158070 11
 
9.9%
158849 6
 
5.4%
158861 6
 
5.4%
158864 5
 
4.5%
158050 5
 
4.5%
158834 5
 
4.5%
158856 5
 
4.5%
158791 4
 
3.6%
158829 4
 
3.6%
158815 4
 
3.6%
Other values (38) 56
50.5%

Length

2024-05-11T05:48:43.268255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
158070 11
 
9.9%
158861 6
 
5.4%
158849 6
 
5.4%
158864 5
 
4.5%
158050 5
 
4.5%
158834 5
 
4.5%
158856 5
 
4.5%
158829 4
 
3.6%
158815 4
 
3.6%
158791 4
 
3.6%
Other values (38) 56
50.5%

지번주소
Text

Distinct104
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-05-11T05:48:43.635636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length41
Mean length29.531532
Min length18

Characters and Unicode

Total characters3278
Distinct characters133
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

Unique98 ?
Unique (%)88.3%

Sample

1st row서울특별시 양천구 신정동 1023-12
2nd row서울특별시 양천구 신정동 326-0 12단지 B동 101호
3rd row서울특별시 양천구 신정동 1022-9 지하1층
4th row서울특별시 양천구 신월동 54-7
5th row서울특별시 양천구 목동 904 목동신시가지아파트4단지 관리동 105호
ValueCountFrequency (%)
서울특별시 111
17.7%
양천구 111
17.7%
신정동 53
 
8.5%
목동 32
 
5.1%
신월동 27
 
4.3%
지하1층 21
 
3.3%
1층 13
 
2.1%
지상1층 7
 
1.1%
101호 7
 
1.1%
1182-11 6
 
1.0%
Other values (166) 239
38.1%
2024-05-11T05:48:44.506229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
587
 
17.9%
1 230
 
7.0%
동 151
 
4.6%
시 123
 
3.8%
양 118
 
3.6%
천 116
 
3.5%
서 111
 
3.4%
특 111
 
3.4%
별 111
 
3.4%
구 111
 
3.4%
Other values (123) 1509
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1840
56.1%
Decimal Number 698
 
21.3%
Space Separator 587
 
17.9%
Dash Punctuation 88
 
2.7%
Uppercase Letter 21
 
0.6%
Other Punctuation 20
 
0.6%
Open Punctuation 12
 
0.4%
Close Punctuation 12
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 151
 
8.2%
시 123
 
6.7%
양 118
 
6.4%
천 116
 
6.3%
서 111
 
6.0%
특 111
 
6.0%
별 111
 
6.0%
구 111
 
6.0%
울 111
 
6.0%
신 95
 
5.2%
Other values (102) 682
37.1%
Decimal Number
ValueCountFrequency (%)
1 230
33.0%
2 101
14.5%
0 87
 
12.5%
3 58
 
8.3%
9 52
 
7.4%
7 41
 
5.9%
8 34
 
4.9%
6 34
 
4.9%
4 33
 
4.7%
5 28
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 13
61.9%
A 4
 
19.0%
G 1
 
4.8%
T 1
 
4.8%
S 1
 
4.8%
P 1
 
4.8%
Space Separator
ValueCountFrequency (%)
587
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1840
56.1%
Common 1417
43.2%
Latin 21
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 151
 
8.2%
시 123
 
6.7%
양 118
 
6.4%
천 116
 
6.3%
서 111
 
6.0%
특 111
 
6.0%
별 111
 
6.0%
구 111
 
6.0%
울 111
 
6.0%
신 95
 
5.2%
Other values (102) 682
37.1%
Common
ValueCountFrequency (%)
587
41.4%
1 230
 
16.2%
2 101
 
7.1%
- 88
 
6.2%
0 87
 
6.1%
3 58
 
4.1%
9 52
 
3.7%
7 41
 
2.9%
8 34
 
2.4%
6 34
 
2.4%
Other values (5) 105
 
7.4%
Latin
ValueCountFrequency (%)
B 13
61.9%
A 4
 
19.0%
G 1
 
4.8%
T 1
 
4.8%
S 1
 
4.8%
P 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1840
56.1%
ASCII 1438
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
587
40.8%
1 230
 
16.0%
2 101
 
7.0%
- 88
 
6.1%
0 87
 
6.1%
3 58
 
4.0%
9 52
 
3.6%
7 41
 
2.9%
8 34
 
2.4%
6 34
 
2.4%
Other values (11) 126
 
8.8%
Hangul
ValueCountFrequency (%)
동 151
 
8.2%
시 123
 
6.7%
양 118
 
6.4%
천 116
 
6.3%
서 111
 
6.0%
특 111
 
6.0%
별 111
 
6.0%
구 111
 
6.0%
울 111
 
6.0%
신 95
 
5.2%
Other values (102) 682
37.1%

도로명주소
Text

MISSING 

Distinct58
Distinct (%)90.6%
Missing47
Missing (%)42.3%
Memory size1020.0 B
2024-05-11T05:48:44.914124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length38.53125
Min length22

Characters and Unicode

Total characters2466
Distinct characters127
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

Unique53 ?
Unique (%)82.8%

Sample

1st row서울특별시 양천구 목동서로 130, 관리동 105호 (목동, 목동신시가지아파트4단지)
2nd row서울특별시 양천구 목동서로 100, 105호 (목동, 목동아파트 3단지 관리동상가)
3rd row서울특별시 양천구 목동로 212, 상가비동 102호 (목동, 목동신시가지아파트)
4th row서울특별시 양천구 목동로3길 57, 상가동 지층 비01호 (신정동, 양천아파트)
5th row서울특별시 양천구 화곡로 59, 지상1층 (신월동)
ValueCountFrequency (%)
서울특별시 64
 
13.9%
양천구 64
 
13.9%
신정동 29
 
6.3%
목동 21
 
4.6%
지하1층 17
 
3.7%
목동서로 10
 
2.2%
1층 10
 
2.2%
101호 9
 
2.0%
신월동 8
 
1.7%
목동동로 7
 
1.5%
Other values (138) 220
47.9%
2024-05-11T05:48:45.839934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
395
 
16.0%
동 147
 
6.0%
1 109
 
4.4%
, 108
 
4.4%
목 86
 
3.5%
시 76
 
3.1%
서 74
 
3.0%
양 73
 
3.0%
천 69
 
2.8%
( 67
 
2.7%
Other values (117) 1262
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1489
60.4%
Space Separator 395
 
16.0%
Decimal Number 332
 
13.5%
Other Punctuation 108
 
4.4%
Open Punctuation 67
 
2.7%
Close Punctuation 67
 
2.7%
Uppercase Letter 5
 
0.2%
Dash Punctuation 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 147
 
9.9%
목 86
 
5.8%
시 76
 
5.1%
서 74
 
5.0%
양 73
 
4.9%
천 69
 
4.6%
울 64
 
4.3%
로 64
 
4.3%
구 64
 
4.3%
별 64
 
4.3%
Other values (98) 708
47.5%
Decimal Number
ValueCountFrequency (%)
1 109
32.8%
0 59
17.8%
2 42
 
12.7%
3 38
 
11.4%
4 24
 
7.2%
5 18
 
5.4%
9 17
 
5.1%
7 14
 
4.2%
6 6
 
1.8%
8 5
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
S 1
 
20.0%
G 1
 
20.0%
Space Separator
ValueCountFrequency (%)
395
100.0%
Other Punctuation
ValueCountFrequency (%)
, 108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1489
60.4%
Common 972
39.4%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 147
 
9.9%
목 86
 
5.8%
시 76
 
5.1%
서 74
 
5.0%
양 73
 
4.9%
천 69
 
4.6%
울 64
 
4.3%
로 64
 
4.3%
구 64
 
4.3%
별 64
 
4.3%
Other values (98) 708
47.5%
Common
ValueCountFrequency (%)
395
40.6%
1 109
 
11.2%
, 108
 
11.1%
( 67
 
6.9%
) 67
 
6.9%
0 59
 
6.1%
2 42
 
4.3%
3 38
 
3.9%
4 24
 
2.5%
5 18
 
1.9%
Other values (6) 45
 
4.6%
Latin
ValueCountFrequency (%)
B 3
60.0%
S 1
 
20.0%
G 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1489
60.4%
ASCII 977
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
395
40.4%
1 109
 
11.2%
, 108
 
11.1%
( 67
 
6.9%
) 67
 
6.9%
0 59
 
6.0%
2 42
 
4.3%
3 38
 
3.9%
4 24
 
2.5%
5 18
 
1.8%
Other values (9) 50
 
5.1%
Hangul
ValueCountFrequency (%)
동 147
 
9.9%
목 86
 
5.8%
시 76
 
5.1%
서 74
 
5.0%
양 73
 
4.9%
천 69
 
4.6%
울 64
 
4.3%
로 64
 
4.3%
구 64
 
4.3%
별 64
 
4.3%
Other values (98) 708
47.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)65.6%
Missing47
Missing (%)42.3%
Infinite0
Infinite (%)0.0%
Mean8008.8281
Minimum7902
Maximum8104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:48:46.251699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7902
5-th percentile7921.9
Q17956
median8004
Q38066.25
95-th percentile8099.55
Maximum8104
Range202
Interquartile range (IQR)110.25

Descriptive statistics

Standard deviation61.627028
Coefficient of variation (CV)0.0076948871
Kurtosis-1.2743889
Mean8008.8281
Median Absolute Deviation (MAD)57.5
Skewness0.1270556
Sum512565
Variance3797.8906
MonotonicityNot monotonic
2024-05-11T05:48:46.819892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
7956 4
 
3.6%
8089 4
 
3.6%
7938 3
 
2.7%
7960 3
 
2.7%
8095 2
 
1.8%
7942 2
 
1.8%
7910 2
 
1.8%
8009 2
 
1.8%
8064 2
 
1.8%
8015 2
 
1.8%
Other values (32) 38
34.2%
(Missing) 47
42.3%
ValueCountFrequency (%)
7902 1
 
0.9%
7910 2
1.8%
7921 1
 
0.9%
7927 1
 
0.9%
7931 1
 
0.9%
7938 3
2.7%
7942 2
1.8%
7946 2
1.8%
7947 1
 
0.9%
7948 1
 
0.9%
ValueCountFrequency (%)
8104 2
1.8%
8101 1
 
0.9%
8100 1
 
0.9%
8097 1
 
0.9%
8096 1
 
0.9%
8095 2
1.8%
8090 1
 
0.9%
8089 4
3.6%
8086 2
1.8%
8073 1
 
0.9%

사업장명
Text

Distinct108
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2024-05-11T05:48:47.349489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.5765766
Min length3

Characters and Unicode

Total characters952
Distinct characters172
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

Unique105 ?
Unique (%)94.6%

Sample

1st row(주)무원유통
2nd row삼양유통(주)목동2호점
3rd row럭키슈퍼마트
4th row해태유통강서영업소
5th row(주)이마트에브리데이 목동점
ValueCountFrequency (%)
목동점 7
 
4.9%
gs수퍼 3
 
2.1%
주)이마트에브리데이 3
 
2.1%
준할인마트 2
 
1.4%
신세계아울렛마트 2
 
1.4%
주)신월홈마트 2
 
1.4%
주)이마트 2
 
1.4%
홈플러스(주 2
 
1.4%
빅마트 2
 
1.4%
팝마트 2
 
1.4%
Other values (115) 115
81.0%
2024-05-11T05:48:48.258031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 71
 
7.5%
트 71
 
7.5%
( 46
 
4.8%
) 45
 
4.7%
주 43
 
4.5%
점 34
 
3.6%
31
 
3.3%
동 28
 
2.9%
목 26
 
2.7%
스 23
 
2.4%
Other values (162) 534
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 796
83.6%
Open Punctuation 46
 
4.8%
Close Punctuation 45
 
4.7%
Space Separator 31
 
3.3%
Uppercase Letter 17
 
1.8%
Decimal Number 11
 
1.2%
Lowercase Letter 5
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 71
 
8.9%
트 71
 
8.9%
주 43
 
5.4%
점 34
 
4.3%
동 28
 
3.5%
목 26
 
3.3%
스 23
 
2.9%
신 19
 
2.4%
리 18
 
2.3%
인 15
 
1.9%
Other values (143) 448
56.3%
Decimal Number
ValueCountFrequency (%)
2 3
27.3%
1 3
27.3%
3 2
18.2%
5 1
 
9.1%
7 1
 
9.1%
0 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
S 8
47.1%
G 5
29.4%
C 2
 
11.8%
J 1
 
5.9%
K 1
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
f 1
20.0%
r 1
20.0%
m 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 796
83.6%
Common 134
 
14.1%
Latin 22
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 71
 
8.9%
트 71
 
8.9%
주 43
 
5.4%
점 34
 
4.3%
동 28
 
3.5%
목 26
 
3.3%
스 23
 
2.9%
신 19
 
2.4%
리 18
 
2.3%
인 15
 
1.9%
Other values (143) 448
56.3%
Common
ValueCountFrequency (%)
( 46
34.3%
) 45
33.6%
31
23.1%
2 3
 
2.2%
1 3
 
2.2%
3 2
 
1.5%
5 1
 
0.7%
7 1
 
0.7%
0 1
 
0.7%
- 1
 
0.7%
Latin
ValueCountFrequency (%)
S 8
36.4%
G 5
22.7%
e 2
 
9.1%
C 2
 
9.1%
J 1
 
4.5%
K 1
 
4.5%
f 1
 
4.5%
r 1
 
4.5%
m 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 796
83.6%
ASCII 156
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 71
 
8.9%
트 71
 
8.9%
주 43
 
5.4%
점 34
 
4.3%
동 28
 
3.5%
목 26
 
3.3%
스 23
 
2.9%
신 19
 
2.4%
리 18
 
2.3%
인 15
 
1.9%
Other values (143) 448
56.3%
ASCII
ValueCountFrequency (%)
( 46
29.5%
) 45
28.8%
31
19.9%
S 8
 
5.1%
G 5
 
3.2%
2 3
 
1.9%
1 3
 
1.9%
e 2
 
1.3%
C 2
 
1.3%
3 2
 
1.3%
Other values (9) 9
 
5.8%

최종수정일자
Date

Distinct105
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum1999-04-06 00:00:00
Maximum2024-04-30 16:29:23
2024-05-11T05:48:48.520965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:48:49.073697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
I
65 
U
46 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 65
58.6%
U 46
41.4%

Length

2024-05-11T05:48:49.589892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:49.908705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 65
58.6%
u 46
41.4%

데이터갱신일자
Date

Distinct37
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T05:48:50.297093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:48:50.643255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
기타식품판매업
111 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 111
100.0%

Length

2024-05-11T05:48:51.066327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:51.381086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 111
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)56.0%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean187440.56
Minimum184710.01
Maximum189519.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:48:51.703516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184710.01
5-th percentile184952.83
Q1186885.13
median187670.42
Q3188185.68
95-th percentile189027.82
Maximum189519.86
Range4809.849
Interquartile range (IQR)1300.5528

Descriptive statistics

Standard deviation1256.7543
Coefficient of variation (CV)0.006704815
Kurtosis-0.42943505
Mean187440.56
Median Absolute Deviation (MAD)680.34601
Skewness-0.61289149
Sum20431021
Variance1579431.3
MonotonicityNot monotonic
2024-05-11T05:48:52.171561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186990.07041522 6
 
5.4%
187520.306766633 4
 
3.6%
188175.450195493 4
 
3.6%
187864.50227698 4
 
3.6%
187766.276177683 4
 
3.6%
188793.497546726 4
 
3.6%
187531.38903074 4
 
3.6%
184710.013493293 3
 
2.7%
185962.809546697 3
 
2.7%
185940.486089755 3
 
2.7%
Other values (51) 70
63.1%
ValueCountFrequency (%)
184710.013493293 3
2.7%
184781.091128181 1
 
0.9%
184796.999053109 1
 
0.9%
184806.911534822 1
 
0.9%
185171.699050872 1
 
0.9%
185177.64285441 1
 
0.9%
185221.95790954 1
 
0.9%
185222.73244302 2
1.8%
185458.613850038 1
 
0.9%
185478.063988449 1
 
0.9%
ValueCountFrequency (%)
189519.862506193 1
 
0.9%
189508.199599752 2
1.8%
189423.528553032 1
 
0.9%
189077.657991611 1
 
0.9%
189031.829869484 1
 
0.9%
189021.797866206 1
 
0.9%
188986.143679742 2
1.8%
188977.171050288 3
2.7%
188884.075622342 1
 
0.9%
188793.497546726 4
3.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct61
Distinct (%)56.0%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean447052.34
Minimum445124.13
Maximum449649.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:48:52.619287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445124.13
5-th percentile445634.17
Q1446265.89
median446903.32
Q3447750.85
95-th percentile449104.01
Maximum449649.02
Range4524.8846
Interquartile range (IQR)1484.9544

Descriptive statistics

Standard deviation1081.7613
Coefficient of variation (CV)0.0024197644
Kurtosis-0.36590654
Mean447052.34
Median Absolute Deviation (MAD)726.50627
Skewness0.61268422
Sum48728705
Variance1170207.6
MonotonicityNot monotonic
2024-05-11T05:48:53.076577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446176.810389121 6
 
5.4%
446450.347274241 4
 
3.6%
448339.835468341 4
 
3.6%
448953.063207171 4
 
3.6%
446265.890841351 4
 
3.6%
446277.050684118 4
 
3.6%
447310.609246804 4
 
3.6%
448160.092461161 3
 
2.7%
446176.170952681 3
 
2.7%
446959.982843463 3
 
2.7%
Other values (51) 70
63.1%
ValueCountFrequency (%)
445124.131588947 2
1.8%
445309.994400633 1
 
0.9%
445428.447103333 2
1.8%
445620.250253049 1
 
0.9%
445655.04439912 3
2.7%
445782.650926649 2
1.8%
446003.941216623 2
1.8%
446140.068718483 1
 
0.9%
446149.197185122 2
1.8%
446176.170952681 3
2.7%
ValueCountFrequency (%)
449649.016215774 1
 
0.9%
449586.974248859 1
 
0.9%
449409.143621821 1
 
0.9%
449377.63880433 1
 
0.9%
449364.309292872 1
 
0.9%
449204.635182585 1
 
0.9%
448953.063207171 4
3.6%
448625.389554748 1
 
0.9%
448552.989897945 2
1.8%
448551.489178583 1
 
0.9%

위생업태명
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
기타식품판매업
82 
<NA>
29 

Length

Max length7
Median length7
Mean length6.2162162
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타식품판매업 82
73.9%
<NA> 29
 
26.1%

Length

2024-05-11T05:48:53.466436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:53.762742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타식품판매업 82
73.9%
na 29
 
26.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)26.1%
Missing88
Missing (%)79.3%
Infinite0
Infinite (%)0.0%
Mean2.4782609
Minimum0
Maximum20
Zeros6
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:48:54.063533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median1
Q33
95-th percentile7.7
Maximum20
Range20
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation4.3156119
Coefficient of variation (CV)1.7413873
Kurtosis12.997418
Mean2.4782609
Median Absolute Deviation (MAD)1
Skewness3.3797193
Sum57
Variance18.624506
MonotonicityNot monotonic
2024-05-11T05:48:54.336264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 10
 
9.0%
0 6
 
5.4%
3 3
 
2.7%
5 2
 
1.8%
8 1
 
0.9%
20 1
 
0.9%
(Missing) 88
79.3%
ValueCountFrequency (%)
0 6
5.4%
1 10
9.0%
3 3
 
2.7%
5 2
 
1.8%
8 1
 
0.9%
20 1
 
0.9%
ValueCountFrequency (%)
20 1
 
0.9%
8 1
 
0.9%
5 2
 
1.8%
3 3
 
2.7%
1 10
9.0%
0 6
5.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)35.3%
Missing94
Missing (%)84.7%
Infinite0
Infinite (%)0.0%
Mean7.3529412
Minimum0
Maximum99
Zeros10
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:48:54.573328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile28.6
Maximum99
Range99
Interquartile range (IQR)3

Descriptive statistics

Standard deviation23.787973
Coefficient of variation (CV)3.2351643
Kurtosis16.416318
Mean7.3529412
Median Absolute Deviation (MAD)0
Skewness4.0274002
Sum125
Variance565.86765
MonotonicityNot monotonic
2024-05-11T05:48:54.932890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 10
 
9.0%
2 2
 
1.8%
3 2
 
1.8%
5 1
 
0.9%
11 1
 
0.9%
99 1
 
0.9%
(Missing) 94
84.7%
ValueCountFrequency (%)
0 10
9.0%
2 2
 
1.8%
3 2
 
1.8%
5 1
 
0.9%
11 1
 
0.9%
99 1
 
0.9%
ValueCountFrequency (%)
99 1
 
0.9%
11 1
 
0.9%
5 1
 
0.9%
3 2
 
1.8%
2 2
 
1.8%
0 10
9.0%

영업장주변구분명
Categorical

Distinct4
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
85 
주택가주변
15 
아파트지역
 
6
기타
 
5

Length

Max length5
Median length4
Mean length4.0990991
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
76.6%
주택가주변 15
 
13.5%
아파트지역 6
 
5.4%
기타 5
 
4.5%

Length

2024-05-11T05:48:55.453385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:55.752355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
76.6%
주택가주변 15
 
13.5%
아파트지역 6
 
5.4%
기타 5
 
4.5%

등급구분명
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
85 
기타
25 
자율
 
1

Length

Max length4
Median length4
Mean length3.5315315
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 85
76.6%
기타 25
 
22.5%
자율 1
 
0.9%

Length

2024-05-11T05:48:56.009726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:56.254404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 85
76.6%
기타 25
 
22.5%
자율 1
 
0.9%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
76 
상수도전용
35 

Length

Max length5
Median length4
Mean length4.3153153
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 76
68.5%
상수도전용 35
31.5%

Length

2024-05-11T05:48:56.616871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:57.025434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
68.5%
상수도전용 35
31.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
109 
0
 
2

Length

Max length4
Median length4
Mean length3.9459459
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 109
98.2%
0 2
 
1.8%

Length

2024-05-11T05:48:57.398121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:57.733392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 109
98.2%
0 2
 
1.8%

본사종업원수
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
71 
0
40 

Length

Max length4
Median length4
Mean length2.9189189
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
64.0%
0 40
36.0%

Length

2024-05-11T05:48:58.099583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:58.378966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
64.0%
0 40
36.0%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
71 
0
38 
1
 
2

Length

Max length4
Median length4
Mean length2.9189189
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
64.0%
0 38
34.2%
1 2
 
1.8%

Length

2024-05-11T05:48:58.680506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:59.016554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
64.0%
0 38
34.2%
1 2
 
1.8%

공장판매직종업원수
Categorical

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
71 
0
35 
5
 
2
4
 
2
10
 
1

Length

Max length4
Median length4
Mean length2.9279279
Min length1

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
64.0%
0 35
31.5%
5 2
 
1.8%
4 2
 
1.8%
10 1
 
0.9%

Length

2024-05-11T05:48:59.414217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:48:59.770961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
64.0%
0 35
31.5%
5 2
 
1.8%
4 2
 
1.8%
10 1
 
0.9%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
71 
0
40 

Length

Max length4
Median length4
Mean length2.9189189
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 71
64.0%
0 40
36.0%

Length

2024-05-11T05:49:00.378431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:00.806773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 71
64.0%
0 40
36.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
65 
임대
29 
자가
17 

Length

Max length4
Median length4
Mean length3.1711712
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 65
58.6%
임대 29
26.1%
자가 17
 
15.3%

Length

2024-05-11T05:49:01.282073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:01.670778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 65
58.6%
임대 29
26.1%
자가 17
 
15.3%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
99 
0
 
8
100000000
 
2
400000000
 
1
20000000
 
1

Length

Max length9
Median length4
Mean length3.954955
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
89.2%
0 8
 
7.2%
100000000 2
 
1.8%
400000000 1
 
0.9%
20000000 1
 
0.9%

Length

2024-05-11T05:49:02.093474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:02.487574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
89.2%
0 8
 
7.2%
100000000 2
 
1.8%
400000000 1
 
0.9%
20000000 1
 
0.9%

월세액
Categorical

IMBALANCE 

Distinct6
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1020.0 B
<NA>
99 
0
 
8
3500000
 
1
22000000
 
1
5000000
 
1

Length

Max length8
Median length4
Mean length3.9099099
Min length1

Unique

Unique4 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
89.2%
0 8
 
7.2%
3500000 1
 
0.9%
22000000 1
 
0.9%
5000000 1
 
0.9%
10000000 1
 
0.9%

Length

2024-05-11T05:49:02.877381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:49:03.264438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
89.2%
0 8
 
7.2%
3500000 1
 
0.9%
22000000 1
 
0.9%
5000000 1
 
0.9%
10000000 1
 
0.9%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)1.2%
Missing29
Missing (%)26.1%
Memory size354.0 B
False
82 
(Missing)
29 
ValueCountFrequency (%)
False 82
73.9%
(Missing) 29
 
26.1%
2024-05-11T05:49:03.559878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)14.6%
Missing29
Missing (%)26.1%
Infinite0
Infinite (%)0.0%
Mean88.364146
Minimum0
Maximum1158.03
Zeros71
Zeros (%)64.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-11T05:49:03.829855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile689.197
Maximum1158.03
Range1158.03
Interquartile range (IQR)0

Descriptive statistics

Standard deviation248.64423
Coefficient of variation (CV)2.8138588
Kurtosis8.0642502
Mean88.364146
Median Absolute Deviation (MAD)0
Skewness2.9461011
Sum7245.86
Variance61823.952
MonotonicityNot monotonic
2024-05-11T05:49:04.214542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 71
64.0%
313.5 1
 
0.9%
1158.03 1
 
0.9%
777.0 1
 
0.9%
303.0 1
 
0.9%
499.74 1
 
0.9%
914.53 1
 
0.9%
650.0 1
 
0.9%
691.26 1
 
0.9%
1064.0 1
 
0.9%
Other values (2) 2
 
1.8%
(Missing) 29
26.1%
ValueCountFrequency (%)
0.0 71
64.0%
303.0 1
 
0.9%
313.5 1
 
0.9%
360.0 1
 
0.9%
499.74 1
 
0.9%
514.8 1
 
0.9%
650.0 1
 
0.9%
691.26 1
 
0.9%
777.0 1
 
0.9%
914.53 1
 
0.9%
ValueCountFrequency (%)
1158.03 1
0.9%
1064.0 1
0.9%
914.53 1
0.9%
777.0 1
0.9%
691.26 1
0.9%
650.0 1
0.9%
514.8 1
0.9%
499.74 1
0.9%
360.0 1
0.9%
313.5 1
0.9%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing111
Missing (%)100.0%
Memory size1.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-114-1996-0040619960628<NA>3폐업2폐업20010423<NA><NA><NA>02 6469541.00158861서울특별시 양천구 신정동 1023-12<NA><NA>(주)무원유통2001-09-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업187520.306767446450.347274기타식품판매업1<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131400003140000-114-1996-0040719960701<NA>3폐업2폐업19971104<NA><NA><NA>02 6499466.00158070서울특별시 양천구 신정동 326-0 12단지 B동 101호<NA><NA>삼양유통(주)목동2호점2001-09-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업187652.903985445655.044399기타식품판매업1<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231400003140000-114-1996-0040819960703<NA>3폐업2폐업20060601<NA><NA><NA>0226452173475.68158861서울특별시 양천구 신정동 1022-9 지하1층<NA><NA>럭키슈퍼마트2006-04-07 00:00:00I2018-08-31 23:59:59.0기타식품판매업187523.574256446408.633352기타식품판매업82주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331400003140000-114-1996-0040919960703<NA>3폐업2폐업20000113<NA><NA><NA>02 6067686.00158824서울특별시 양천구 신월동 54-7<NA><NA>해태유통강서영업소2000-01-13 00:00:00I2018-08-31 23:59:59.0기타식품판매업184806.911535448551.489179기타식품판매업10주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
431400003140000-114-1996-004101996-07-03<NA>1영업/정상1영업<NA><NA><NA><NA>0226464331356.40158-876서울특별시 양천구 목동 904 목동신시가지아파트4단지 관리동 105호서울특별시 양천구 목동서로 130, 관리동 105호 (목동, 목동신시가지아파트4단지)7989(주)이마트에브리데이 목동점2024-04-30 16:29:23U2023-12-05 00:02:00.0기타식품판매업188580.483662447750.845211<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531400003140000-114-1996-0041119960703<NA>3폐업2폐업20020130<NA><NA><NA>02 4400783.00158880서울특별시 양천구 목동 912-0 5단단지 A동 201호<NA><NA>(주)해태유통2001-09-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업189508.1996447992.012379기타식품판매업1<NA>아파트지역기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631400003140000-114-1996-004121996-07-03<NA>1영업/정상1영업<NA><NA><NA><NA>0226470824396.00158-875서울특별시 양천구 목동 903 (목동아파트 3단지 관리동상가) 105호서울특별시 양천구 목동서로 100, 105호 (목동, 목동아파트 3단지 관리동상가)7982씨에스유통(주)롯데슈퍼 목동점2023-05-24 11:11:52U2022-12-04 22:06:00.0기타식품판매업188700.85117448020.090999<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731400003140000-114-1996-0041319960703<NA>1영업/정상1영업<NA><NA><NA><NA>0226488026313.50158050서울특별시 양천구 목동 925 목동신시가지아파트 상가비동 102호서울특별시 양천구 목동로 212, 상가비동 102호 (목동, 목동신시가지아파트)7993(주)지에스리테일목동7점2016-02-11 17:21:12I2018-08-31 23:59:59.0기타식품판매업188248.454327447406.301288기타식품판매업1<NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N313.5<NA><NA><NA>
831400003140000-114-1996-0041419960716<NA>3폐업2폐업20021204<NA><NA><NA>02 6012858.00158834서울특별시 양천구 신월동 447-5<NA><NA>한라쇼핑(주)본점2001-09-28 00:00:00I2018-08-31 23:59:59.0기타식품판매업185940.48609446959.982843기타식품판매업1<NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931400003140000-114-1996-0041519960716<NA>3폐업2폐업20080310<NA><NA><NA>0226041012379.80158845서울특별시 양천구 신월동 952-1<NA><NA>한라할인마트2004-02-09 00:00:00I2018-08-31 23:59:59.0기타식품판매업185177.642854446600.090923기타식품판매업10주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
10131400003140000-114-2020-0000120200207<NA>3폐업2폐업20220624<NA><NA><NA>0226524227395.60158811서울특별시 양천구 목동 610-22 1층서울특별시 양천구 목동중앙북로 21, 1층 (목동)7946장터식자재마트2022-06-24 13:12:53U2021-12-05 22:06:00.0기타식품판매업188103.234482449586.974249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10231400003140000-114-2020-0000220200616<NA>3폐업2폐업20200804<NA><NA><NA><NA>584.70158070서울특별시 양천구 신정동 312 목동신시가지아파트9단지 상가비동 지하101호서울특별시 양천구 목동서로 340, 상가비동 지하층 101호 (신정동, 목동신시가지아파트9단지)8089(주)올마트2020-08-04 13:31:31U2020-08-06 02:40:00.0기타식품판매업187766.276178446265.890841기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
10331400003140000-114-2020-0000320200825<NA>3폐업2폐업20201208<NA><NA><NA>0226552755558.30158070서울특별시 양천구 신정동 312 목동신시가지아파트9단지서울특별시 양천구 목동서로 340, 상가비동 지하층 101호 (신정동, 목동신시가지아파트9단지)8089조엘플러스 마트2020-12-08 14:40:31U2020-12-10 02:40:00.0기타식품판매업187766.276178446265.890841기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
10431400003140000-114-2021-0000120210308<NA>1영업/정상1영업<NA><NA><NA><NA>0226552437813.85158050서울특별시 양천구 목동 966 목동에버하임서울특별시 양천구 목동중앙북로 68, 제비층 B01~09호 (목동, 목동에버하임)7948상훈자연마트2023-01-09 15:50:56U2022-11-30 23:02:00.0기타식품판매업188502.886822449377.638804<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10531400003140000-114-2021-0000220210621<NA>1영업/정상1영업<NA><NA><NA><NA>0226444296359.00158849서울특별시 양천구 신정동 128-113서울특별시 양천구 신목로 34, 지하1층 (신정동)8015팝마트2021-06-21 15:33:19I2021-06-23 00:23:04.0기타식품판매업188793.497547446277.050684기타식품판매업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>임대<NA><NA>N0.0<NA><NA><NA>
10631400003140000-114-2021-000032021-07-05<NA>3폐업2폐업2023-08-14<NA><NA><NA><NA>300.00158-851서울특별시 양천구 신정동 201-1 세양청마루2차 주상복합서울특별시 양천구 목동남로4길 2, 지하1층 101호 (신정동, 세양청마루2차 주상복합)8104하모니마트2023-08-14 10:15:42U2022-12-07 23:07:00.0기타식품판매업187954.189632445124.131589<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10731400003140000-114-2021-0000420210713<NA>3폐업2폐업20220111<NA><NA><NA><NA>360.00158858서울특별시 양천구 신정동 929-26 영림아파트서울특별시 양천구 오목로 135, 지하1층 (신정동, 영림아파트)7942제일할인마트2022-01-11 18:04:32U2022-01-13 02:40:00.0기타식품판매업186885.128807446952.439144기타식품판매업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
10831400003140000-114-2021-000052021-08-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>393.58158-860서울특별시 양천구 신정동 995-2서울특별시 양천구 목동로 183, 1층 (신정동)8022(주)이마트에브리데이 목동역점2024-04-30 15:42:12U2023-12-05 00:02:00.0기타식품판매업187929.395107446964.609091<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
10931400003140000-114-2022-000012022-02-17<NA>3폐업2폐업2023-11-20<NA><NA><NA>0226903490349.60158-860서울특별시 양천구 신정동 973-31서울특별시 양천구 신월로 299, 1,2,3층 (신정동)8027(주)카라스인터내셔널 신정네거리역2023-11-20 10:59:54U2022-10-31 22:02:00.0기타식품판매업187045.608935446598.791467<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
11031400003140000-114-2023-000012023-01-18<NA>1영업/정상1영업<NA><NA><NA><NA>0226490297353.10158-886서울특별시 양천구 신정동 327 목동신시가지아파트13단지 상가 비동 101호서울특별시 양천구 목동동로 100, 상가 비동 101호 (신정동, 목동신시가지아파트13단지)8096지에스 더 프레시 목동13점2023-06-19 11:33:58U2022-12-05 22:01:00.0기타식품판매업187995.261632445782.650927<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>