Overview

Dataset statistics

Number of variables27
Number of observations74
Missing cells579
Missing cells (%)29.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.7 KiB
Average record size in memory230.8 B

Variable types

Categorical9
Numeric5
DateTime5
Unsupported4
Text4

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),자본금,거래처
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-19066/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
도로명우편번호 is highly imbalanced (87.0%)Imbalance
인허가취소일자 has 74 (100.0%) missing valuesMissing
폐업일자 has 45 (60.8%) missing valuesMissing
휴업시작일자 has 62 (83.8%) missing valuesMissing
휴업종료일자 has 62 (83.8%) missing valuesMissing
재개업일자 has 67 (90.5%) missing valuesMissing
소재지면적 has 36 (48.6%) missing valuesMissing
소재지우편번호 has 74 (100.0%) missing valuesMissing
지번주소 has 1 (1.4%) missing valuesMissing
도로명주소 has 4 (5.4%) missing valuesMissing
좌표정보(X) has 3 (4.1%) missing valuesMissing
좌표정보(Y) has 3 (4.1%) missing valuesMissing
자본금 has 74 (100.0%) missing valuesMissing
거래처 has 74 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자본금 is an unsupported type, check if it needs cleaning or further analysisUnsupported
거래처 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 06:47:13.346004
Analysis finished2024-05-11 06:47:13.760358
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size724.0 B
3140000
74 

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 74
100.0%

Length

2024-05-11T15:47:13.846603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:13.963988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 74
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct74
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9939356 × 1018
Minimum1.977314 × 1018
Maximum2.017314 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-05-11T15:47:14.107911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.977314 × 1018
5-th percentile1.980314 × 1018
Q11.988564 × 1018
median1.992314 × 1018
Q31.996314 × 1018
95-th percentile2.009314 × 1018
Maximum2.017314 × 1018
Range4.0000011 × 1016
Interquartile range (IQR)7.75 × 1015

Descriptive statistics

Standard deviation8.1571946 × 1015
Coefficient of variation (CV)0.004091002
Kurtosis0.37215354
Mean1.9939356 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.52277167
Sum-2.2716005 × 1016
Variance6.6539823 × 1031
MonotonicityStrictly increasing
2024-05-11T15:47:14.311295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1977314007001500002 1
 
1.4%
1997314007001500042 1
 
1.4%
1996314007001500038 1
 
1.4%
1995314007001500037 1
 
1.4%
1995314007001200052 1
 
1.4%
1994314007001500036 1
 
1.4%
1994314007001200051 1
 
1.4%
1994314007001200050 1
 
1.4%
1994314007001200049 1
 
1.4%
1994314007001200048 1
 
1.4%
Other values (64) 64
86.5%
ValueCountFrequency (%)
1977314007001500002 1
1.4%
1977314011401500002 1
1.4%
1980314007001500003 1
1.4%
1980314007001500004 1
1.4%
1980314007001500005 1
1.4%
1981314007001500006 1
1.4%
1981314007001500007 1
1.4%
1988314007001200002 1
1.4%
1988314007001200005 1
1.4%
1988314007001200008 1
1.4%
ValueCountFrequency (%)
2017314017901500001 1
1.4%
2010314011401500001 1
1.4%
2009314011401500003 1
1.4%
2009314011401500002 1
1.4%
2009314011401500001 1
1.4%
2008314011401500001 1
1.4%
2007314011401500001 1
1.4%
2006314011401500001 1
1.4%
2006314010201500001 1
1.4%
2004314011401500003 1
1.4%

인허가일자
Date

Distinct53
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum1977-09-10 00:00:00
Maximum2017-01-16 00:00:00
2024-05-11T15:47:14.535627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:14.749584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
3
43 
1
28 
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 43
58.1%
1 28
37.8%
2 3
 
4.1%

Length

2024-05-11T15:47:14.889185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:14.993770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 43
58.1%
1 28
37.8%
2 3
 
4.1%

영업상태명
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
폐업
43 
영업/정상
28 
휴업
 
3

Length

Max length5
Median length2
Mean length3.1351351
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 43
58.1%
영업/정상 28
37.8%
휴업 3
 
4.1%

Length

2024-05-11T15:47:15.122481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:15.237876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 43
58.1%
영업/정상 28
37.8%
휴업 3
 
4.1%

상세영업상태코드
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
3
43 
1
17 
6
8 
5
 
3
7
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row1
3rd row1
4th row6
5th row3

Common Values

ValueCountFrequency (%)
3 43
58.1%
1 17
 
23.0%
6 8
 
10.8%
5 3
 
4.1%
7 3
 
4.1%

Length

2024-05-11T15:47:15.356679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:15.468375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 43
58.1%
1 17
 
23.0%
6 8
 
10.8%
5 3
 
4.1%
7 3
 
4.1%

상세영업상태명
Categorical

Distinct5
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size724.0 B
폐지
43 
신규등록
17 
휴지사업재개
8 
사업휴지
 
3
영업개시
 
3

Length

Max length6
Median length2
Mean length3.0540541
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴지사업재개
2nd row신규등록
3rd row신규등록
4th row휴지사업재개
5th row폐지

Common Values

ValueCountFrequency (%)
폐지 43
58.1%
신규등록 17
 
23.0%
휴지사업재개 8
 
10.8%
사업휴지 3
 
4.1%
영업개시 3
 
4.1%

Length

2024-05-11T15:47:15.598594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:15.724174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 43
58.1%
신규등록 17
 
23.0%
휴지사업재개 8
 
10.8%
사업휴지 3
 
4.1%
영업개시 3
 
4.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing45
Missing (%)60.8%
Infinite0
Infinite (%)0.0%
Mean20101992
Minimum20030407
Maximum20210916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-05-11T15:47:15.856227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030407
5-th percentile20034823
Q120050319
median20090311
Q320140331
95-th percentile20210600
Maximum20210916
Range180509
Interquartile range (IQR)90012

Descriptive statistics

Standard deviation58316.931
Coefficient of variation (CV)0.0029010523
Kurtosis-0.70073998
Mean20101992
Median Absolute Deviation (MAD)40204
Skewness0.64160262
Sum5.8295778 × 108
Variance3.4008645 × 109
MonotonicityNot monotonic
2024-05-11T15:47:16.013757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
20070316 1
 
1.4%
20140331 1
 
1.4%
20100511 1
 
1.4%
20110412 1
 
1.4%
20121031 1
 
1.4%
20090311 1
 
1.4%
20120330 1
 
1.4%
20050319 1
 
1.4%
20050107 1
 
1.4%
20070601 1
 
1.4%
Other values (19) 19
25.7%
(Missing) 45
60.8%
ValueCountFrequency (%)
20030407 1
1.4%
20031029 1
1.4%
20040514 1
1.4%
20040623 1
1.4%
20040807 1
1.4%
20041013 1
1.4%
20050107 1
1.4%
20050319 1
1.4%
20050802 1
1.4%
20070306 1
1.4%
ValueCountFrequency (%)
20210916 1
1.4%
20210728 1
1.4%
20210407 1
1.4%
20200522 1
1.4%
20180703 1
1.4%
20141128 1
1.4%
20141031 1
1.4%
20140331 1
1.4%
20130104 1
1.4%
20121031 1
1.4%

휴업시작일자
Date

MISSING 

Distinct12
Distinct (%)100.0%
Missing62
Missing (%)83.8%
Memory size724.0 B
Minimum2008-04-24 00:00:00
Maximum2023-07-01 00:00:00
2024-05-11T15:47:16.158172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:16.305589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

휴업종료일자
Date

MISSING 

Distinct11
Distinct (%)91.7%
Missing62
Missing (%)83.8%
Memory size724.0 B
Minimum2008-10-23 00:00:00
Maximum2024-07-01 00:00:00
2024-05-11T15:47:16.423145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:16.557861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

재개업일자
Date

MISSING 

Distinct7
Distinct (%)100.0%
Missing67
Missing (%)90.5%
Memory size724.0 B
Minimum2009-06-08 00:00:00
Maximum2021-10-28 00:00:00
2024-05-11T15:47:16.787166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:16.952840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

전화번호
Text

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-05-11T15:47:17.237016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.972973
Min length8

Characters and Unicode

Total characters738
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

Unique70 ?
Unique (%)94.6%

Sample

1st row0226065189
2nd row26065189
3rd row0226140047
4th row0226051359
5th row0226540051
ValueCountFrequency (%)
02 12
 
14.0%
0226924511 2
 
2.3%
0226536071 2
 
2.3%
0226530207 1
 
1.2%
6906090 1
 
1.2%
0226466121 1
 
1.2%
0226972774 1
 
1.2%
6985151 1
 
1.2%
6939919 1
 
1.2%
0226428903 1
 
1.2%
Other values (63) 63
73.3%
2024-05-11T15:47:17.820694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 170
23.0%
0 117
15.9%
6 102
13.8%
5 63
 
8.5%
1 60
 
8.1%
4 57
 
7.7%
9 50
 
6.8%
3 39
 
5.3%
8 35
 
4.7%
7 29
 
3.9%
Other values (2) 16
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 722
97.8%
Space Separator 14
 
1.9%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 170
23.5%
0 117
16.2%
6 102
14.1%
5 63
 
8.7%
1 60
 
8.3%
4 57
 
7.9%
9 50
 
6.9%
3 39
 
5.4%
8 35
 
4.8%
7 29
 
4.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 738
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 170
23.0%
0 117
15.9%
6 102
13.8%
5 63
 
8.5%
1 60
 
8.1%
4 57
 
7.7%
9 50
 
6.8%
3 39
 
5.3%
8 35
 
4.7%
7 29
 
3.9%
Other values (2) 16
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 170
23.0%
0 117
15.9%
6 102
13.8%
5 63
 
8.5%
1 60
 
8.1%
4 57
 
7.7%
9 50
 
6.8%
3 39
 
5.3%
8 35
 
4.7%
7 29
 
3.9%
Other values (2) 16
 
2.2%

소재지면적
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)97.4%
Missing36
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean1013.5663
Minimum81.92
Maximum2464.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-05-11T15:47:18.109855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum81.92
5-th percentile329.05
Q1596.275
median891.4
Q31392.75
95-th percentile2212.16
Maximum2464.6
Range2382.68
Interquartile range (IQR)796.475

Descriptive statistics

Standard deviation600.23593
Coefficient of variation (CV)0.59220193
Kurtosis0.087829721
Mean1013.5663
Median Absolute Deviation (MAD)360.4
Skewness0.8865933
Sum38515.52
Variance360283.17
MonotonicityNot monotonic
2024-05-11T15:47:18.370103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1412.0 2
 
2.7%
542.8 1
 
1.4%
997.6 1
 
1.4%
443.0 1
 
1.4%
385.0 1
 
1.4%
2464.6 1
 
1.4%
708.7 1
 
1.4%
817.0 1
 
1.4%
1445.0 1
 
1.4%
942.9 1
 
1.4%
Other values (27) 27
36.5%
(Missing) 36
48.6%
ValueCountFrequency (%)
81.92 1
1.4%
316.3 1
1.4%
331.3 1
1.4%
385.0 1
1.4%
393.0 1
1.4%
405.0 1
1.4%
443.0 1
1.4%
519.2 1
1.4%
542.8 1
1.4%
594.7 1
1.4%
ValueCountFrequency (%)
2464.6 1
1.4%
2309.4 1
1.4%
2195.0 1
1.4%
2056.0 1
1.4%
1984.5 1
1.4%
1744.0 1
1.4%
1445.0 1
1.4%
1439.0 1
1.4%
1412.0 2
2.7%
1335.0 1
1.4%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

지번주소
Text

MISSING 

Distinct72
Distinct (%)98.6%
Missing1
Missing (%)1.4%
Memory size724.0 B
2024-05-11T15:47:18.757839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length22
Min length18

Characters and Unicode

Total characters1606
Distinct characters71
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

Unique71 ?
Unique (%)97.3%

Sample

1st row서울특별시 양천구 신월동 206-1
2nd row서울특별시 양천구 신월동 206-1
3rd row서울특별시 양천구 신정동 1315 서부트럭터미널
4th row서울특별시 양천구 신월동 52-1
5th row서울특별시 양천구 신정동 1027-4
ValueCountFrequency (%)
서울특별시 72
22.9%
양천구 70
22.2%
신정동 28
 
8.9%
신월동 25
 
7.9%
목동 17
 
5.4%
206-1 2
 
0.6%
438-1 2
 
0.6%
302호 1
 
0.3%
공항동 1
 
0.3%
1362-7 1
 
0.3%
Other values (96) 96
30.5%
2024-05-11T15:47:19.418099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
296
18.4%
1 88
 
5.5%
동 76
 
4.7%
서 74
 
4.6%
시 73
 
4.5%
양 73
 
4.5%
구 73
 
4.5%
특 72
 
4.5%
별 72
 
4.5%
울 72
 
4.5%
Other values (61) 637
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 841
52.4%
Decimal Number 391
24.3%
Space Separator 296
 
18.4%
Dash Punctuation 69
 
4.3%
Other Punctuation 8
 
0.5%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 76
9.0%
서 74
8.8%
시 73
8.7%
양 73
8.7%
구 73
8.7%
특 72
8.6%
별 72
8.6%
울 72
8.6%
천 70
8.3%
신 53
 
6.3%
Other values (46) 133
15.8%
Decimal Number
ValueCountFrequency (%)
1 88
22.5%
2 56
14.3%
4 41
10.5%
5 40
10.2%
0 39
10.0%
9 28
 
7.2%
3 28
 
7.2%
7 26
 
6.6%
8 23
 
5.9%
6 22
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
@ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 841
52.4%
Common 764
47.6%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 76
9.0%
서 74
8.8%
시 73
8.7%
양 73
8.7%
구 73
8.7%
특 72
8.6%
별 72
8.6%
울 72
8.6%
천 70
8.3%
신 53
 
6.3%
Other values (46) 133
15.8%
Common
ValueCountFrequency (%)
296
38.7%
1 88
 
11.5%
- 69
 
9.0%
2 56
 
7.3%
4 41
 
5.4%
5 40
 
5.2%
0 39
 
5.1%
9 28
 
3.7%
3 28
 
3.7%
7 26
 
3.4%
Other values (4) 53
 
6.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 841
52.4%
ASCII 765
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
296
38.7%
1 88
 
11.5%
- 69
 
9.0%
2 56
 
7.3%
4 41
 
5.4%
5 40
 
5.2%
0 39
 
5.1%
9 28
 
3.7%
3 28
 
3.7%
7 26
 
3.4%
Other values (5) 54
 
7.1%
Hangul
ValueCountFrequency (%)
동 76
9.0%
서 74
8.8%
시 73
8.7%
양 73
8.7%
구 73
8.7%
특 72
8.6%
별 72
8.6%
울 72
8.6%
천 70
8.3%
신 53
 
6.3%
Other values (46) 133
15.8%

도로명주소
Text

MISSING 

Distinct68
Distinct (%)97.1%
Missing4
Missing (%)5.4%
Memory size724.0 B
2024-05-11T15:47:19.813718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length41.5
Mean length25.957143
Min length22

Characters and Unicode

Total characters1817
Distinct characters92
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

Unique66 ?
Unique (%)94.3%

Sample

1st row서울특별시 양천구 남부순환로 442 (신월동)
2nd row서울특별시 양천구 남부순환로 442 (신월동)
3rd row서울특별시 양천구 신정로 167 (신정동)
4th row서울특별시 양천구 남부순환로 317 (신월동)
5th row서울특별시 양천구 신월로 328 (신정동)
ValueCountFrequency (%)
서울특별시 69
19.1%
양천구 67
18.6%
신월동 25
 
6.9%
신정동 22
 
6.1%
목동 15
 
4.2%
남부순환로 11
 
3.0%
안양천로 4
 
1.1%
국회대로 4
 
1.1%
14 3
 
0.8%
신월로 3
 
0.8%
Other values (121) 138
38.2%
2024-05-11T15:47:20.399683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
 
17.2%
동 89
 
4.9%
양 76
 
4.2%
서 73
 
4.0%
천 71
 
3.9%
( 70
 
3.9%
) 70
 
3.9%
로 70
 
3.9%
구 70
 
3.9%
시 70
 
3.9%
Other values (82) 845
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1104
60.8%
Space Separator 313
 
17.2%
Decimal Number 244
 
13.4%
Open Punctuation 70
 
3.9%
Close Punctuation 70
 
3.9%
Other Punctuation 11
 
0.6%
Dash Punctuation 4
 
0.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 89
 
8.1%
양 76
 
6.9%
서 73
 
6.6%
천 71
 
6.4%
로 70
 
6.3%
구 70
 
6.3%
시 70
 
6.3%
울 69
 
6.2%
별 69
 
6.2%
특 69
 
6.2%
Other values (65) 378
34.2%
Decimal Number
ValueCountFrequency (%)
1 46
18.9%
2 37
15.2%
3 30
12.3%
7 24
9.8%
0 23
9.4%
4 21
8.6%
6 21
8.6%
5 18
 
7.4%
9 15
 
6.1%
8 9
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
@ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
313
100.0%
Open Punctuation
ValueCountFrequency (%)
( 70
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1104
60.8%
Common 712
39.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 89
 
8.1%
양 76
 
6.9%
서 73
 
6.6%
천 71
 
6.4%
로 70
 
6.3%
구 70
 
6.3%
시 70
 
6.3%
울 69
 
6.2%
별 69
 
6.2%
특 69
 
6.2%
Other values (65) 378
34.2%
Common
ValueCountFrequency (%)
313
44.0%
( 70
 
9.8%
) 70
 
9.8%
1 46
 
6.5%
2 37
 
5.2%
3 30
 
4.2%
7 24
 
3.4%
0 23
 
3.2%
4 21
 
2.9%
6 21
 
2.9%
Other values (6) 57
 
8.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1104
60.8%
ASCII 713
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
43.9%
( 70
 
9.8%
) 70
 
9.8%
1 46
 
6.5%
2 37
 
5.2%
3 30
 
4.2%
7 24
 
3.4%
0 23
 
3.2%
4 21
 
2.9%
6 21
 
2.9%
Other values (7) 58
 
8.1%
Hangul
ValueCountFrequency (%)
동 89
 
8.1%
양 76
 
6.9%
서 73
 
6.6%
천 71
 
6.4%
로 70
 
6.3%
구 70
 
6.3%
시 70
 
6.3%
울 69
 
6.2%
별 69
 
6.2%
특 69
 
6.2%
Other values (65) 378
34.2%

도로명우편번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
<NA>
72 
8055
 
1
7907
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)2.7%

Sample

1st row<NA>
2nd row<NA>
3rd row8055
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 72
97.3%
8055 1
 
1.4%
7907 1
 
1.4%

Length

2024-05-11T15:47:20.608042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:20.740011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 72
97.3%
8055 1
 
1.4%
7907 1
 
1.4%

사업장명
Text

Distinct72
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size724.0 B
2024-05-11T15:47:21.072347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length9.3783784
Min length2

Characters and Unicode

Total characters694
Distinct characters130
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

Unique70 ?
Unique (%)94.6%

Sample

1st row동일석유(주)개나리주유소
2nd row동일석유(주)개나리주유소
3rd row(주)서부티엔디
4th row플라트(주) 서호주유소
5th row(주) 한주에너지 신정주유소
ValueCountFrequency (%)
에이치디현대오일뱅크(주)직영 6
 
6.3%
신정주유소 3
 
3.2%
동일석유(주)개나리주유소 2
 
2.1%
현대오일뱅크(주)직영 2
 
2.1%
주)케미맥스 2
 
2.1%
목동주유소 2
 
2.1%
백조석유 1
 
1.1%
금강점 1
 
1.1%
직영 1
 
1.1%
지에스칼텍스(주 1
 
1.1%
Other values (74) 74
77.9%
2024-05-11T15:47:21.720648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 67
 
9.7%
유 63
 
9.1%
소 34
 
4.9%
( 32
 
4.6%
) 32
 
4.6%
에 25
 
3.6%
석 21
 
3.0%
지 21
 
3.0%
21
 
3.0%
대 16
 
2.3%
Other values (120) 362
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 591
85.2%
Open Punctuation 32
 
4.6%
Close Punctuation 32
 
4.6%
Space Separator 21
 
3.0%
Uppercase Letter 13
 
1.9%
Other Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 67
 
11.3%
유 63
 
10.7%
소 34
 
5.8%
에 25
 
4.2%
석 21
 
3.6%
지 21
 
3.6%
대 16
 
2.7%
신 15
 
2.5%
너 15
 
2.5%
일 14
 
2.4%
Other values (110) 300
50.8%
Uppercase Letter
ValueCountFrequency (%)
K 4
30.8%
S 4
30.8%
C 2
15.4%
M 1
 
7.7%
A 1
 
7.7%
I 1
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 591
85.2%
Common 90
 
13.0%
Latin 13
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 67
 
11.3%
유 63
 
10.7%
소 34
 
5.8%
에 25
 
4.2%
석 21
 
3.6%
지 21
 
3.6%
대 16
 
2.7%
신 15
 
2.5%
너 15
 
2.5%
일 14
 
2.4%
Other values (110) 300
50.8%
Latin
ValueCountFrequency (%)
K 4
30.8%
S 4
30.8%
C 2
15.4%
M 1
 
7.7%
A 1
 
7.7%
I 1
 
7.7%
Common
ValueCountFrequency (%)
( 32
35.6%
) 32
35.6%
21
23.3%
, 5
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 591
85.2%
ASCII 103
 
14.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 67
 
11.3%
유 63
 
10.7%
소 34
 
5.8%
에 25
 
4.2%
석 21
 
3.6%
지 21
 
3.6%
대 16
 
2.7%
신 15
 
2.5%
너 15
 
2.5%
일 14
 
2.4%
Other values (110) 300
50.8%
ASCII
ValueCountFrequency (%)
( 32
31.1%
) 32
31.1%
21
20.4%
, 5
 
4.9%
K 4
 
3.9%
S 4
 
3.9%
C 2
 
1.9%
M 1
 
1.0%
A 1
 
1.0%
I 1
 
1.0%

최종수정일자
Date

Distinct73
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size724.0 B
Minimum2002-07-23 00:00:00
Maximum2024-05-08 17:08:31
2024-05-11T15:47:21.912875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:47:22.106036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size724.0 B
I
48 
U
26 

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 48
64.9%
U 26
35.1%

Length

2024-05-11T15:47:22.351689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:22.820449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 48
64.9%
u 26
35.1%

데이터갱신일자
Categorical

Distinct23
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
2018-08-31 23:59:59.0
48 
2022-12-03 22:03:00.0
 
3
2022-12-04 00:08:00.0
 
2
2021-11-01 00:02:00.0
 
2
2022-02-26 02:40:00.0
 
1
Other values (18)
18 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique19 ?
Unique (%)25.7%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-12-21 02:40:00.0
4th row2021-11-01 23:01:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 48
64.9%
2022-12-03 22:03:00.0 3
 
4.1%
2022-12-04 00:08:00.0 2
 
2.7%
2021-11-01 00:02:00.0 2
 
2.7%
2022-02-26 02:40:00.0 1
 
1.4%
2021-11-01 23:01:00.0 1
 
1.4%
2021-11-01 23:05:00.0 1
 
1.4%
2020-05-27 02:40:00.0 1
 
1.4%
2022-11-30 22:01:00.0 1
 
1.4%
2021-04-21 02:40:00.0 1
 
1.4%
Other values (13) 13
 
17.6%

Length

2024-05-11T15:47:22.982249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:59:59.0 49
33.1%
2018-08-31 48
32.4%
02:40:00.0 8
 
5.4%
2021-11-01 4
 
2.7%
2022-12-03 3
 
2.0%
22:03:00.0 3
 
2.0%
22:01:00.0 3
 
2.0%
21:00:00.0 2
 
1.4%
2023-12-04 2
 
1.4%
00:05:00.0 2
 
1.4%
Other values (21) 24
16.2%

업태구분명
Categorical

Distinct3
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size724.0 B
주유소
37 
일반판매소
24 
용제판매소
13 

Length

Max length5
Median length4
Mean length4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주유소 37
50.0%
일반판매소 24
32.4%
용제판매소 13
 
17.6%

Length

2024-05-11T15:47:23.196497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:47:23.403520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주유소 37
50.0%
일반판매소 24
32.4%
용제판매소 13
 
17.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct68
Distinct (%)95.8%
Missing3
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean186905.77
Minimum183842.84
Maximum189635.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-05-11T15:47:23.657441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183842.84
5-th percentile184756.6
Q1185569.39
median187009.33
Q3188229.69
95-th percentile189230.72
Maximum189635.49
Range5792.6447
Interquartile range (IQR)2660.3068

Descriptive statistics

Standard deviation1533.6925
Coefficient of variation (CV)0.0082056991
Kurtosis-1.2557458
Mean186905.77
Median Absolute Deviation (MAD)1421.2196
Skewness0.030662636
Sum13270310
Variance2352212.7
MonotonicityNot monotonic
2024-05-11T15:47:23.885702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184990.887799484 2
 
2.7%
185588.112351415 2
 
2.7%
185164.07240776 2
 
2.7%
185679.940724601 1
 
1.4%
184673.718438326 1
 
1.4%
188845.378146136 1
 
1.4%
187328.575796091 1
 
1.4%
189059.685922739 1
 
1.4%
188618.911096586 1
 
1.4%
185899.043498814 1
 
1.4%
Other values (58) 58
78.4%
(Missing) 3
 
4.1%
ValueCountFrequency (%)
183842.842485447 1
1.4%
184626.053521926 1
1.4%
184649.336667603 1
1.4%
184673.718438326 1
1.4%
184839.474782908 1
1.4%
184990.887799484 2
2.7%
185043.828144117 1
1.4%
185044.782770876 1
1.4%
185058.585298312 1
1.4%
185060.029130323 1
1.4%
ValueCountFrequency (%)
189635.487139725 1
1.4%
189512.187911002 1
1.4%
189438.071744985 1
1.4%
189401.752379557 1
1.4%
189059.685922739 1
1.4%
188954.524397407 1
1.4%
188953.066831076 1
1.4%
188927.645388223 1
1.4%
188845.378146136 1
1.4%
188696.181418205 1
1.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct68
Distinct (%)95.8%
Missing3
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean447343.71
Minimum444866.08
Maximum458555.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size798.0 B
2024-05-11T15:47:24.085028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444866.08
5-th percentile445256.63
Q1446455.47
median447004.31
Q3448071.7
95-th percentile449290.58
Maximum458555.93
Range13689.86
Interquartile range (IQR)1616.2264

Descriptive statistics

Standard deviation1810.572
Coefficient of variation (CV)0.0040473844
Kurtosis20.308267
Mean447343.71
Median Absolute Deviation (MAD)708.16236
Skewness3.4507975
Sum31761403
Variance3278170.8
MonotonicityNot monotonic
2024-05-11T15:47:24.274133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447668.60828576 2
 
2.7%
446611.369232718 2
 
2.7%
447351.284284049 2
 
2.7%
446374.736454938 1
 
1.4%
448643.137215214 1
 
1.4%
448603.372537117 1
 
1.4%
446582.446566821 1
 
1.4%
449392.317334492 1
 
1.4%
446384.264683214 1
 
1.4%
445526.721204765 1
 
1.4%
Other values (58) 58
78.4%
(Missing) 3
 
4.1%
ValueCountFrequency (%)
444866.075006676 1
1.4%
444934.266388016 1
1.4%
444958.276659499 1
1.4%
445249.033483384 1
1.4%
445264.23483344 1
1.4%
445382.168341974 1
1.4%
445390.869067966 1
1.4%
445526.721204765 1
1.4%
445959.667219293 1
1.4%
446054.829386474 1
1.4%
ValueCountFrequency (%)
458555.934730144 1
1.4%
450289.219677982 1
1.4%
449392.317334492 1
1.4%
449327.872565076 1
1.4%
449253.287873881 1
1.4%
449236.066690526 1
1.4%
449173.821341764 1
1.4%
449077.195070137 1
1.4%
448951.046584761 1
1.4%
448770.755575648 1
1.4%

자본금
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

거래처
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing74
Missing (%)100.0%
Memory size798.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
03140000197731400700150000219770910<NA>1영업/정상6휴지사업재개<NA><NA><NA><NA>02260651891412.0<NA>서울특별시 양천구 신월동 206-1서울특별시 양천구 남부순환로 442 (신월동)<NA>동일석유(주)개나리주유소2017-11-28 10:51:09I2018-08-31 23:59:59.0주유소185164.072408447351.284284<NA><NA>
13140000197731401140150000219770910<NA>1영업/정상1신규등록<NA><NA><NA><NA>260651891412.0<NA>서울특별시 양천구 신월동 206-1서울특별시 양천구 남부순환로 442 (신월동)<NA>동일석유(주)개나리주유소2014-04-07 17:23:11I2018-08-31 23:59:59.0주유소185164.072408447351.284284<NA><NA>
23140000198031400700150000319800728<NA>1영업/정상1신규등록<NA><NA><NA><NA>02261400472056.0<NA>서울특별시 양천구 신정동 1315 서부트럭터미널서울특별시 양천구 신정로 167 (신정동)8055(주)서부티엔디2018-12-19 17:02:03U2018-12-21 02:40:00.0주유소185716.749051445264.234833<NA><NA>
33140000198031400700150000419801106<NA>1영업/정상6휴지사업재개<NA>2010100120101231<NA>0226051359542.8<NA>서울특별시 양천구 신월동 52-1서울특별시 양천구 남부순환로 317 (신월동)<NA>플라트(주) 서호주유소2022-12-09 08:55:44U2021-11-01 23:01:00.0주유소184626.053522448504.146187<NA><NA>
43140000198031400700150000519801106<NA>3폐업3폐지<NA><NA><NA><NA>0226540051997.6<NA>서울특별시 양천구 신정동 1027-4서울특별시 양천구 신월로 328 (신정동)<NA>(주) 한주에너지 신정주유소2015-06-25 12:07:33I2018-08-31 23:59:59.0주유소187328.575796446582.446567<NA><NA>
53140000198131400700150000619810701<NA>3폐업3폐지<NA><NA><NA><NA>02264616891171.0<NA>서울특별시 양천구 목동 405-271<NA><NA>SK네트웍스(주)신평주유소2007-08-20 16:39:23I2018-08-31 23:59:59.0주유소<NA><NA><NA><NA>
6314000019813140070015000071981-08-31<NA>2휴업5사업휴지<NA>2012-08-292013-02-28<NA>02269050012309.4<NA>서울특별시 양천구 신월동 525-1서울특별시 양천구 남부순환로 553 (신월동)<NA>에이치디현대오일뱅크(주)직영 남부순환셀프주유소2023-04-21 09:42:14U2022-12-03 22:03:00.0주유소185679.940725446374.736455<NA><NA>
73140000198831400700120000219880329<NA>3폐업3폐지<NA><NA><NA><NA>0226450388<NA><NA>서울특별시 양천구 신정동 183-2<NA><NA>(주)태성에너지2002-08-12 00:00:00I2018-08-31 23:59:59.0일반판매소<NA><NA><NA><NA>
83140000198831400700120000519880101<NA>1영업/정상1신규등록<NA><NA><NA><NA>0226458929<NA><NA>서울특별시 양천구 신정동 1029-45서울특별시 양천구 은행정로5길 52 (신정동)<NA>신정석유2016-01-07 14:14:55I2018-08-31 23:59:59.0일반판매소187050.834665446473.900805<NA><NA>
93140000198831400700120000819880101<NA>3폐업3폐지<NA><NA><NA><NA>26982577<NA><NA>서울특별시 양천구 신정동 884-2서울특별시 양천구 은행정로20길 2 (신정동)<NA>SK석유(석유,등유,보일러등유,실내등유,난방유,백등유)배달2022-12-13 15:16:34U2021-11-01 23:05:00.0일반판매소187477.476438447312.0184<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
643140000200431401140150000320041112<NA>3폐업3폐지20090311<NA><NA><NA>02 26551434<NA><NA>서울특별시 양천구 신정동 1014-2 도림빌딩 601서울특별시 양천구 신월로 374 (신정동,도림빌딩 601)<NA>(주)삼양화인2009-03-11 15:27:40I2018-08-31 23:59:59.0용제판매소187777.022416446645.116372<NA><NA>
653140000200631401020150000120060526<NA>3폐업3폐지<NA><NA><NA><NA>0226536071<NA><NA>경기도 고양시 덕양구 화정동 1127 31통10반 옥빛마을 1509동 1904호경기도 고양시 덕양구 화신로 233, 1509동 1904호 (화정동,옥빛마을)<NA>(주)케미맥스2007-08-06 17:09:00I2018-08-31 23:59:59.0용제판매소185356.900292458555.93473<NA><NA>
663140000200631401140150000120060526<NA>3폐업3폐지20121031<NA><NA><NA>0226536071<NA><NA>서울특별시 양천구 목동 917-9서울특별시 양천구 목동동로 293 (목동)<NA>(주)케미맥스2012-10-31 11:19:24I2018-08-31 23:59:59.0용제판매소188953.066831447333.569188<NA><NA>
673140000200731401140150000120070316<NA>3폐업3폐지20110412<NA><NA><NA>0226998195<NA><NA>서울특별시 양천구 신정동 1305 힐탑이루미@ B103호서울특별시 양천구 은행정로17길 80 (신정동,힐탑이루미@ B103호)<NA>유니언 마켓팅2011-04-12 13:23:59I2018-08-31 23:59:59.0용제판매소186693.241313447277.626432<NA><NA>
683140000200831401140150000120080429<NA>3폐업3폐지<NA><NA><NA><NA>0226542182<NA><NA>서울특별시 양천구 신정동 318-6 동문비젼 1009서울특별시 양천구 목동서로 287 (신정동,동문비젼 1009)<NA>(주)제이켐2008-10-30 13:44:31I2018-08-31 23:59:59.0용제판매소188357.547218446596.052396<NA><NA>
693140000200931401140150000120090708<NA>1영업/정상6휴지사업재개<NA>20141010201412152014121926465145405.0<NA>서울특별시 양천구 신정동 162-40서울특별시 양천구 안양천로 663 (신정동)<NA>신정동주유소2018-04-10 17:12:30I2018-08-31 23:59:59.0주유소188537.926194444934.266388<NA><NA>
703140000200931401140150000220090423<NA>3폐업3폐지20100511<NA><NA><NA>2603224681.92<NA>서울특별시 양천구 신월동 98-41서울특별시 양천구 곰달래로5길 64-1 (신월동)<NA>엘림크린재료상사2010-05-11 11:17:10I2018-08-31 23:59:59.0용제판매소185058.585298448102.683649<NA><NA>
713140000200931401140150000320091218<NA>3폐업3폐지20140331<NA><NA><NA>26632107<NA><NA>서울특별시 양천구 신월동 98-44서울특별시 양천구 곰달래로5길 66 (신월동)<NA>한음2014-04-01 10:02:15I2018-08-31 23:59:59.0용제판매소185043.828144448111.398641<NA><NA>
72314000020103140114015000012011-07-15<NA>1영업/정상1신규등록<NA><NA><NA><NA>02 26915185316.3<NA>서울특별시 양천구 신정동 872-1서울특별시 양천구 국회대로 158 (신정동)<NA>에이치디현대오일뱅크(주)직영 양정주유소2023-04-21 09:41:53U2022-12-03 22:03:00.0주유소186899.144773447323.512776<NA><NA>
73314000020173140179015000012017-01-16<NA>1영업/정상1신규등록<NA><NA><NA><NA>02-2690-58371439.0<NA><NA>서울특별시 양천구 남부순환로 408 (신월동)<NA>형산석유(주)원주유소2024-04-03 13:15:55U2023-12-04 00:05:00.0주유소184990.887799447668.608286<NA><NA>