Overview

Dataset statistics

Number of variables27
Number of observations59
Missing cells494
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.3 KiB
Average record size in memory231.2 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
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-19071/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
도로명우편번호 is highly imbalanced (87.6%)Imbalance
데이터갱신일자 is highly imbalanced (50.3%)Imbalance
인허가취소일자 has 59 (100.0%) missing valuesMissing
폐업일자 has 44 (74.6%) missing valuesMissing
휴업시작일자 has 55 (93.2%) missing valuesMissing
휴업종료일자 has 55 (93.2%) missing valuesMissing
재개업일자 has 55 (93.2%) missing valuesMissing
전화번호 has 2 (3.4%) missing valuesMissing
소재지면적 has 37 (62.7%) missing valuesMissing
소재지우편번호 has 59 (100.0%) missing valuesMissing
도로명주소 has 4 (6.8%) missing valuesMissing
좌표정보(X) has 3 (5.1%) missing valuesMissing
좌표정보(Y) has 3 (5.1%) missing valuesMissing
자본금 has 59 (100.0%) missing valuesMissing
거래처 has 59 (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 06:45:13.567951
Analysis finished2024-05-11 06:45:13.976951
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
3190000
59 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3190000
2nd row3190000
3rd row3190000
4th row3190000
5th row3190000

Common Values

ValueCountFrequency (%)
3190000 59
100.0%

Length

2024-05-11T15:45:14.054260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:14.167884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3190000 59
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9932004 × 1018
Minimum1.971319 × 1018
Maximum2.019319 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:45:14.322140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.971319 × 1018
5-th percentile1.976319 × 1018
Q11.984819 × 1018
median1.993319 × 1018
Q32.000819 × 1018
95-th percentile2.008619 × 1018
Maximum2.019319 × 1018
Range4.800001 × 1016
Interquartile range (IQR)1.6 × 1016

Descriptive statistics

Standard deviation1.0623795 × 1016
Coefficient of variation (CV)0.0053300184
Kurtosis-0.44848647
Mean1.9932004 × 1018
Median Absolute Deviation (MAD)8 × 1015
Skewness-0.047045511
Sum6.918357 × 1018
Variance1.1286501 × 1032
MonotonicityStrictly increasing
2024-05-11T15:45:14.519321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1971319007201200001 1
 
1.7%
1976319007201500002 1
 
1.7%
1994319007201500002 1
 
1.7%
1994319007201500003 1
 
1.7%
1996319007201200001 1
 
1.7%
1997319007201200001 1
 
1.7%
1997319007201200002 1
 
1.7%
1997319007201214121 1
 
1.7%
1998319007201200001 1
 
1.7%
1998319007201214408 1
 
1.7%
Other values (49) 49
83.1%
ValueCountFrequency (%)
1971319007201200001 1
1.7%
1976319007201500002 1
1.7%
1976319007201500003 1
1.7%
1976319007201500004 1
1.7%
1976319007201500005 1
1.7%
1976319007201500006 1
1.7%
1976319007201500007 1
1.7%
1976319007201500008 1
1.7%
1980319007201200001 1
1.7%
1981319007201200001 1
1.7%
ValueCountFrequency (%)
2019319017701200001 1
1.7%
2011319014201200002 1
1.7%
2011319014201200001 1
1.7%
2008319009901500001 1
1.7%
2007319009901500001 1
1.7%
2006319007201501705 1
1.7%
2005319007201501706 1
1.7%
2005319007201500001 1
1.7%
2004319007201200002 1
1.7%
2004319007201200001 1
1.7%

인허가일자
Date

Distinct51
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum1971-04-24 00:00:00
Maximum2019-06-26 00:00:00
2024-05-11T15:45:14.725350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:14.965201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
3
45 
1
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 45
76.3%
1 14
 
23.7%

Length

2024-05-11T15:45:15.259815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:15.395243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 45
76.3%
1 14
 
23.7%

영업상태명
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
폐업
45 
영업/정상
14 

Length

Max length5
Median length2
Mean length2.7118644
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 45
76.3%
영업/정상 14
 
23.7%

Length

2024-05-11T15:45:15.545061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:15.676586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 45
76.3%
영업/정상 14
 
23.7%

상세영업상태코드
Categorical

Distinct4
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size604.0 B
3
45 
1
10 
6
 
2
7
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 45
76.3%
1 10
 
16.9%
6 2
 
3.4%
7 2
 
3.4%

Length

2024-05-11T15:45:15.821130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:15.969769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 45
76.3%
1 10
 
16.9%
6 2
 
3.4%
7 2
 
3.4%

상세영업상태명
Categorical

Distinct4
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size604.0 B
폐지
45 
신규등록
10 
휴지사업재개
 
2
영업개시
 
2

Length

Max length6
Median length2
Mean length2.5423729
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐지 45
76.3%
신규등록 10
 
16.9%
휴지사업재개 2
 
3.4%
영업개시 2
 
3.4%

Length

2024-05-11T15:45:16.424814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:16.605157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 45
76.3%
신규등록 10
 
16.9%
휴지사업재개 2
 
3.4%
영업개시 2
 
3.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)93.3%
Missing44
Missing (%)74.6%
Infinite0
Infinite (%)0.0%
Mean20130716
Minimum20060613
Maximum20220615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:45:16.757643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060613
5-th percentile20074333
Q120091061
median20130610
Q320160664
95-th percentile20220615
Maximum20220615
Range160002
Interquartile range (IQR)69603

Descriptive statistics

Standard deviation50182.877
Coefficient of variation (CV)0.0024928511
Kurtosis-0.58139345
Mean20130716
Median Absolute Deviation (MAD)40414
Skewness0.56843083
Sum3.0196074 × 108
Variance2.5183211 × 109
MonotonicityNot monotonic
2024-05-11T15:45:16.961616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20220615 2
 
3.4%
20081031 1
 
1.7%
20171024 1
 
1.7%
20101015 1
 
1.7%
20081107 1
 
1.7%
20130621 1
 
1.7%
20180326 1
 
1.7%
20130610 1
 
1.7%
20060613 1
 
1.7%
20111116 1
 
1.7%
Other values (4) 4
 
6.8%
(Missing) 44
74.6%
ValueCountFrequency (%)
20060613 1
1.7%
20080213 1
1.7%
20081031 1
1.7%
20081107 1
1.7%
20101015 1
1.7%
20101217 1
1.7%
20111116 1
1.7%
20130610 1
1.7%
20130621 1
1.7%
20140313 1
1.7%
ValueCountFrequency (%)
20220615 2
3.4%
20180326 1
1.7%
20171024 1
1.7%
20150304 1
1.7%
20140313 1
1.7%
20130621 1
1.7%
20130610 1
1.7%
20111116 1
1.7%
20101217 1
1.7%
20101015 1
1.7%

휴업시작일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing55
Missing (%)93.2%
Memory size604.0 B
Minimum2008-10-01 00:00:00
Maximum2013-04-05 00:00:00
2024-05-11T15:45:17.148577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:17.305669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

휴업종료일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing55
Missing (%)93.2%
Memory size604.0 B
Minimum2008-10-31 00:00:00
Maximum2013-05-31 00:00:00
2024-05-11T15:45:17.492717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:17.661907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

재개업일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing55
Missing (%)93.2%
Memory size604.0 B
Minimum2007-12-14 00:00:00
Maximum2016-11-28 00:00:00
2024-05-11T15:45:17.805437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:17.950520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

전화번호
Text

MISSING 

Distinct50
Distinct (%)87.7%
Missing2
Missing (%)3.4%
Memory size604.0 B
2024-05-11T15:45:18.314531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.210526
Min length7

Characters and Unicode

Total characters582
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

Unique43 ?
Unique (%)75.4%

Sample

1st row02 8131630
2nd row02 5213618
3rd row02 8152354
4th row02 8141919
5th row02 8229010
ValueCountFrequency (%)
02 55
45.5%
5826409 4
 
3.3%
8139054 2
 
1.7%
8325577 2
 
1.7%
8152354 2
 
1.7%
8140981 2
 
1.7%
8217009 2
 
1.7%
825 2
 
1.7%
8201888 1
 
0.8%
5828105 1
 
0.8%
Other values (48) 48
39.7%
2024-05-11T15:45:18.964284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 101
17.4%
0 93
16.0%
73
12.5%
8 68
11.7%
1 59
10.1%
5 52
8.9%
9 32
 
5.5%
4 31
 
5.3%
3 29
 
5.0%
6 25
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 509
87.5%
Space Separator 73
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 101
19.8%
0 93
18.3%
8 68
13.4%
1 59
11.6%
5 52
10.2%
9 32
 
6.3%
4 31
 
6.1%
3 29
 
5.7%
6 25
 
4.9%
7 19
 
3.7%
Space Separator
ValueCountFrequency (%)
73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 582
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 101
17.4%
0 93
16.0%
73
12.5%
8 68
11.7%
1 59
10.1%
5 52
8.9%
9 32
 
5.5%
4 31
 
5.3%
3 29
 
5.0%
6 25
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 582
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 101
17.4%
0 93
16.0%
73
12.5%
8 68
11.7%
1 59
10.1%
5 52
8.9%
9 32
 
5.5%
4 31
 
5.3%
3 29
 
5.0%
6 25
 
4.3%

소재지면적
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)86.4%
Missing37
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean726.76909
Minimum21.6
Maximum2481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:45:19.204792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21.6
5-th percentile21.82
Q1510.905
median718.4
Q3924
95-th percentile1404.25
Maximum2481
Range2459.4
Interquartile range (IQR)413.095

Descriptive statistics

Standard deviation547.10105
Coefficient of variation (CV)0.75278525
Kurtosis4.1480221
Mean726.76909
Median Absolute Deviation (MAD)218.5
Skewness1.3847927
Sum15988.92
Variance299319.56
MonotonicityNot monotonic
2024-05-11T15:45:19.419144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
26.0 2
 
3.4%
21.6 2
 
3.4%
819.0 2
 
3.4%
953.0 1
 
1.7%
861.0 1
 
1.7%
762.0 1
 
1.7%
1419.0 1
 
1.7%
508.0 1
 
1.7%
717.0 1
 
1.7%
1124.0 1
 
1.7%
Other values (9) 9
 
15.3%
(Missing) 37
62.7%
ValueCountFrequency (%)
21.6 2
3.4%
26.0 2
3.4%
238.7 1
1.7%
508.0 1
1.7%
519.62 1
1.7%
634.0 1
1.7%
643.0 1
1.7%
669.7 1
1.7%
717.0 1
1.7%
719.8 1
1.7%
ValueCountFrequency (%)
2481.0 1
1.7%
1419.0 1
1.7%
1124.0 1
1.7%
1060.9 1
1.7%
953.0 1
1.7%
945.0 1
1.7%
861.0 1
1.7%
819.0 2
3.4%
762.0 1
1.7%
719.8 1
1.7%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

지번주소
Text

Distinct53
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size604.0 B
2024-05-11T15:45:19.805622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length21.40678
Min length16

Characters and Unicode

Total characters1263
Distinct characters49
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

Unique47 ?
Unique (%)79.7%

Sample

1st row서울특별시 동작구 흑석동 248-51
2nd row서울특별시 동작구 사당동 1007-47
3rd row서울특별시 동작구 노량진동 148-8
4th row서울특별시 동작구 대방동 341-3
5th row서울특별시 동작구 상도동 353-2
ValueCountFrequency (%)
서울특별시 59
23.9%
동작구 59
23.9%
상도동 17
 
6.9%
사당동 15
 
6.1%
노량진동 9
 
3.6%
신대방동 6
 
2.4%
대방동 5
 
2.0%
흑석동 5
 
2.0%
외 3
 
1.2%
상도1동 2
 
0.8%
Other values (56) 67
27.1%
2024-05-11T15:45:20.321957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
18.4%
동 118
 
9.3%
서 59
 
4.7%
특 59
 
4.7%
별 59
 
4.7%
시 59
 
4.7%
작 59
 
4.7%
구 59
 
4.7%
울 59
 
4.7%
- 56
 
4.4%
Other values (39) 444
35.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 684
54.2%
Decimal Number 287
22.7%
Space Separator 232
 
18.4%
Dash Punctuation 56
 
4.4%
Uppercase Letter 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 118
17.3%
서 59
8.6%
특 59
8.6%
별 59
8.6%
시 59
8.6%
작 59
8.6%
구 59
8.6%
울 59
8.6%
도 19
 
2.8%
상 19
 
2.8%
Other values (23) 115
16.8%
Decimal Number
ValueCountFrequency (%)
1 49
17.1%
3 40
13.9%
2 35
12.2%
5 35
12.2%
0 30
10.5%
4 25
8.7%
8 23
8.0%
6 23
8.0%
7 17
 
5.9%
9 10
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
D 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 684
54.2%
Common 576
45.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 118
17.3%
서 59
8.6%
특 59
8.6%
별 59
8.6%
시 59
8.6%
작 59
8.6%
구 59
8.6%
울 59
8.6%
도 19
 
2.8%
상 19
 
2.8%
Other values (23) 115
16.8%
Common
ValueCountFrequency (%)
232
40.3%
- 56
 
9.7%
1 49
 
8.5%
3 40
 
6.9%
2 35
 
6.1%
5 35
 
6.1%
0 30
 
5.2%
4 25
 
4.3%
8 23
 
4.0%
6 23
 
4.0%
Other values (3) 28
 
4.9%
Latin
ValueCountFrequency (%)
B 1
33.3%
D 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 684
54.2%
ASCII 579
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
40.1%
- 56
 
9.7%
1 49
 
8.5%
3 40
 
6.9%
2 35
 
6.0%
5 35
 
6.0%
0 30
 
5.2%
4 25
 
4.3%
8 23
 
4.0%
6 23
 
4.0%
Other values (6) 31
 
5.4%
Hangul
ValueCountFrequency (%)
동 118
17.3%
서 59
8.6%
특 59
8.6%
별 59
8.6%
시 59
8.6%
작 59
8.6%
구 59
8.6%
울 59
8.6%
도 19
 
2.8%
상 19
 
2.8%
Other values (23) 115
16.8%

도로명주소
Text

MISSING 

Distinct47
Distinct (%)85.5%
Missing4
Missing (%)6.8%
Memory size604.0 B
2024-05-11T15:45:20.682202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length40
Mean length25.363636
Min length22

Characters and Unicode

Total characters1395
Distinct characters78
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

Unique40 ?
Unique (%)72.7%

Sample

1st row서울특별시 동작구 동작대로 73 (사당동)
2nd row서울특별시 동작구 노량진로 172 (노량진동)
3rd row서울특별시 동작구 노량진로 2 (대방동)
4th row서울특별시 동작구 상도로 120 (상도동)
5th row서울특별시 동작구 현충로 101 (흑석동)
ValueCountFrequency (%)
서울특별시 55
19.6%
동작구 55
19.6%
상도동 16
 
5.7%
사당동 16
 
5.7%
상도로 7
 
2.5%
노량진동 7
 
2.5%
신대방동 6
 
2.1%
대방동 5
 
1.8%
노량진로 5
 
1.8%
흑석동 4
 
1.4%
Other values (73) 104
37.1%
2024-05-11T15:45:21.229573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
237
17.0%
동 118
 
8.5%
작 61
 
4.4%
서 57
 
4.1%
시 56
 
4.0%
) 55
 
3.9%
울 55
 
3.9%
구 55
 
3.9%
별 55
 
3.9%
특 55
 
3.9%
Other values (68) 591
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 865
62.0%
Space Separator 237
 
17.0%
Decimal Number 174
 
12.5%
Close Punctuation 55
 
3.9%
Open Punctuation 55
 
3.9%
Dash Punctuation 3
 
0.2%
Other Punctuation 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 118
13.6%
작 61
 
7.1%
서 57
 
6.6%
시 56
 
6.5%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
로 54
 
6.2%
도 27
 
3.1%
Other values (49) 272
31.4%
Decimal Number
ValueCountFrequency (%)
1 41
23.6%
2 32
18.4%
4 23
13.2%
7 17
9.8%
3 15
 
8.6%
5 14
 
8.0%
0 10
 
5.7%
9 9
 
5.2%
6 7
 
4.0%
8 6
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
D 1
33.3%
T 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
237
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 865
62.0%
Common 527
37.8%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 118
13.6%
작 61
 
7.1%
서 57
 
6.6%
시 56
 
6.5%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
로 54
 
6.2%
도 27
 
3.1%
Other values (49) 272
31.4%
Common
ValueCountFrequency (%)
237
45.0%
) 55
 
10.4%
( 55
 
10.4%
1 41
 
7.8%
2 32
 
6.1%
4 23
 
4.4%
7 17
 
3.2%
3 15
 
2.8%
5 14
 
2.7%
0 10
 
1.9%
Other values (6) 28
 
5.3%
Latin
ValueCountFrequency (%)
B 1
33.3%
D 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 865
62.0%
ASCII 530
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
237
44.7%
) 55
 
10.4%
( 55
 
10.4%
1 41
 
7.7%
2 32
 
6.0%
4 23
 
4.3%
7 17
 
3.2%
3 15
 
2.8%
5 14
 
2.6%
0 10
 
1.9%
Other values (9) 31
 
5.8%
Hangul
ValueCountFrequency (%)
동 118
13.6%
작 61
 
7.1%
서 57
 
6.6%
시 56
 
6.5%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
로 54
 
6.2%
도 27
 
3.1%
Other values (49) 272
31.4%

도로명우편번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
<NA>
58 
6959
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 58
98.3%
6959 1
 
1.7%

Length

2024-05-11T15:45:21.410636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:21.516102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 58
98.3%
6959 1
 
1.7%

사업장명
Text

Distinct50
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size604.0 B
2024-05-11T15:45:21.775227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length7.8305085
Min length4

Characters and Unicode

Total characters462
Distinct characters105
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

Unique44 ?
Unique (%)74.6%

Sample

1st row만물상회
2nd row에이치디현대오일뱅크(주) 직영 사당셀프주유소
3rd row대성산업(주) 노량진주유소
4th row서울석유(주) 팔각정주유소
5th row화신주유소
ValueCountFrequency (%)
팔팔석유 4
 
5.0%
쌍용석유 3
 
3.8%
지에스칼텍스(주 3
 
3.8%
노량진주유소 2
 
2.5%
직영 2
 
2.5%
주)세경에너지 2
 
2.5%
에이치디현대오일뱅크(주)직영 2
 
2.5%
남성주유소 2
 
2.5%
동작석유 2
 
2.5%
중앙에너지 2
 
2.5%
Other values (54) 56
70.0%
2024-05-11T15:45:22.362443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 44
 
9.5%
주 39
 
8.4%
석 23
 
5.0%
소 21
 
4.5%
21
 
4.5%
에 18
 
3.9%
) 17
 
3.7%
( 17
 
3.7%
대 13
 
2.8%
지 12
 
2.6%
Other values (95) 237
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
87.4%
Space Separator 21
 
4.5%
Close Punctuation 17
 
3.7%
Open Punctuation 17
 
3.7%
Uppercase Letter 2
 
0.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 44
 
10.9%
주 39
 
9.7%
석 23
 
5.7%
소 21
 
5.2%
에 18
 
4.5%
대 13
 
3.2%
지 12
 
3.0%
팔 11
 
2.7%
동 9
 
2.2%
스 9
 
2.2%
Other values (89) 205
50.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 404
87.4%
Common 56
 
12.1%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 44
 
10.9%
주 39
 
9.7%
석 23
 
5.7%
소 21
 
5.2%
에 18
 
4.5%
대 13
 
3.2%
지 12
 
3.0%
팔 11
 
2.7%
동 9
 
2.2%
스 9
 
2.2%
Other values (89) 205
50.7%
Common
ValueCountFrequency (%)
21
37.5%
) 17
30.4%
( 17
30.4%
9 1
 
1.8%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
87.4%
ASCII 58
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 44
 
10.9%
주 39
 
9.7%
석 23
 
5.7%
소 21
 
5.2%
에 18
 
4.5%
대 13
 
3.2%
지 12
 
3.0%
팔 11
 
2.7%
동 9
 
2.2%
스 9
 
2.2%
Other values (89) 205
50.7%
ASCII
ValueCountFrequency (%)
21
36.2%
) 17
29.3%
( 17
29.3%
S 1
 
1.7%
K 1
 
1.7%
9 1
 
1.7%

최종수정일자
Date

Distinct57
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size604.0 B
Minimum2001-04-13 00:00:00
Maximum2024-03-25 18:04:14
2024-05-11T15:45:22.530355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:45:22.721451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
I
42 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 42
71.2%
U 17
28.8%

Length

2024-05-11T15:45:22.917286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:23.038149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 42
71.2%
u 17
28.8%

데이터갱신일자
Categorical

IMBALANCE 

Distinct15
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size604.0 B
2018-08-31 23:59:59.0
42 
2022-10-30 22:08:00.0
 
2
2022-11-01 00:05:00.0
 
2
2023-12-02 22:07:00.0
 
2
2022-12-03 23:03:00.0
 
1
Other values (10)
10 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique11 ?
Unique (%)18.6%

Sample

1st row2018-08-31 23:59:59.0
2nd row2022-12-03 23:03:00.0
3rd row2021-12-05 23:07:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 42
71.2%
2022-10-30 22:08:00.0 2
 
3.4%
2022-11-01 00:05:00.0 2
 
3.4%
2023-12-02 22:07:00.0 2
 
3.4%
2022-12-03 23:03:00.0 1
 
1.7%
2021-12-05 23:07:00.0 1
 
1.7%
2020-11-11 02:40:00.0 1
 
1.7%
2019-07-03 02:40:00.0 1
 
1.7%
2018-12-07 02:40:00.0 1
 
1.7%
2022-12-08 23:04:00.0 1
 
1.7%
Other values (5) 5
 
8.5%

Length

2024-05-11T15:45:23.155291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 42
35.6%
23:59:59.0 42
35.6%
02:40:00.0 3
 
2.5%
22:08:00.0 2
 
1.7%
00:05:00.0 2
 
1.7%
2023-12-02 2
 
1.7%
22:07:00.0 2
 
1.7%
2022-10-30 2
 
1.7%
2022-11-01 2
 
1.7%
00:04:00.0 2
 
1.7%
Other values (17) 17
14.4%

업태구분명
Categorical

Distinct3
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size604.0 B
일반판매소
29 
주유소
23 
용제판매소
7 

Length

Max length5
Median length5
Mean length4.220339
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반판매소 29
49.2%
주유소 23
39.0%
용제판매소 7
 
11.9%

Length

2024-05-11T15:45:23.333391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:45:23.476532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반판매소 29
49.2%
주유소 23
39.0%
용제판매소 7
 
11.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)80.4%
Missing3
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean195429.89
Minimum191585.3
Maximum198335.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:45:23.614157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191585.3
5-th percentile192910.84
Q1194076.69
median195059.62
Q3197094.78
95-th percentile198192.51
Maximum198335.33
Range6750.0288
Interquartile range (IQR)3018.0847

Descriptive statistics

Standard deviation1867.4083
Coefficient of variation (CV)0.0095553875
Kurtosis-1.069624
Mean195429.89
Median Absolute Deviation (MAD)1533.3408
Skewness0.097124548
Sum10944074
Variance3487213.9
MonotonicityNot monotonic
2024-05-11T15:45:23.792343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
198157.5148145 3
 
5.1%
193490.555442565 2
 
3.4%
195059.618060479 2
 
3.4%
194076.692856266 2
 
3.4%
195195.900838544 2
 
3.4%
194217.497606154 2
 
3.4%
197094.777584478 2
 
3.4%
198335.327466772 2
 
3.4%
197874.440760301 2
 
3.4%
194052.281602581 2
 
3.4%
Other values (35) 35
59.3%
(Missing) 3
 
5.1%
ValueCountFrequency (%)
191585.298671366 1
1.7%
191822.49280009 1
1.7%
192891.081475855 1
1.7%
192917.428244737 1
1.7%
193118.419195314 1
1.7%
193300.832515956 1
1.7%
193346.680399178 1
1.7%
193369.116473006 1
1.7%
193490.555442565 2
3.4%
194052.281602581 2
3.4%
ValueCountFrequency (%)
198335.327466772 2
3.4%
198297.486035411 1
 
1.7%
198157.5148145 3
5.1%
198133.6452158 1
 
1.7%
197998.977492969 1
 
1.7%
197874.440760301 2
3.4%
197685.52184057 1
 
1.7%
197583.714249931 1
 
1.7%
197477.315759087 1
 
1.7%
197094.777584478 2
3.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)80.4%
Missing3
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean443951.09
Minimum441543.54
Maximum445706.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2024-05-11T15:45:23.977462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441543.54
5-th percentile441948.5
Q1442842.26
median444184.38
Q3444849.37
95-th percentile445641.71
Maximum445706.96
Range4163.4214
Interquartile range (IQR)2007.1091

Descriptive statistics

Standard deviation1169.4015
Coefficient of variation (CV)0.0026340773
Kurtosis-1.0524464
Mean443951.09
Median Absolute Deviation (MAD)893.23353
Skewness-0.30234289
Sum24861261
Variance1367499.9
MonotonicityNot monotonic
2024-05-11T15:45:24.186143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
441948.500908632 3
 
5.1%
444035.157877691 2
 
3.4%
445706.958977345 2
 
3.4%
444318.185903254 2
 
3.4%
444513.085616898 2
 
3.4%
444612.59147173 2
 
3.4%
442591.687247738 2
 
3.4%
442942.8646713 2
 
3.4%
442639.026715362 2
 
3.4%
444337.583039184 2
 
3.4%
Other values (35) 35
59.3%
(Missing) 3
 
5.1%
ValueCountFrequency (%)
441543.537610587 1
 
1.7%
441948.500908632 3
5.1%
442324.299286581 1
 
1.7%
442332.338269125 1
 
1.7%
442369.73564888 1
 
1.7%
442530.225836018 1
 
1.7%
442591.687247738 2
3.4%
442639.026715362 2
3.4%
442688.174250385 1
 
1.7%
442773.741552274 1
 
1.7%
ValueCountFrequency (%)
445706.958977345 2
3.4%
445650.971372726 1
1.7%
445638.624998984 1
1.7%
445628.940499705 1
1.7%
445563.76978392 1
1.7%
445452.215952179 1
1.7%
445255.446537264 1
1.7%
445120.376288573 1
1.7%
445088.884741478 1
1.7%
445044.416854416 1
1.7%

자본금
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

거래처
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing59
Missing (%)100.0%
Memory size663.0 B

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
03190000197131900720120000119710424<NA>3폐업3폐지<NA><NA><NA><NA>02 8131630<NA><NA>서울특별시 동작구 흑석동 248-51<NA><NA>만물상회2001-09-18 00:00:00I2018-08-31 23:59:59.0일반판매소<NA><NA><NA><NA>
1319000019763190072015000021976-05-01<NA>1영업/정상6휴지사업재개<NA><NA><NA><NA>02 5213618<NA><NA>서울특별시 동작구 사당동 1007-47서울특별시 동작구 동작대로 73 (사당동)<NA>에이치디현대오일뱅크(주) 직영 사당셀프주유소2023-04-11 09:29:05U2022-12-03 23:03:00.0주유소198297.486035442324.299287<NA><NA>
23190000197631900720150000319760501<NA>3폐업3폐지20220615<NA><NA><NA>02 8152354819.0<NA>서울특별시 동작구 노량진동 148-8서울특별시 동작구 노량진로 172 (노량진동)<NA>대성산업(주) 노량진주유소2022-06-15 16:42:14U2021-12-05 23:07:00.0주유소195059.61806445706.958977<NA><NA>
33190000197631900720150000419760502<NA>3폐업3폐지<NA><NA><NA><NA>02 8141919<NA><NA>서울특별시 동작구 대방동 341-3서울특별시 동작구 노량진로 2 (대방동)<NA>서울석유(주) 팔각정주유소2004-05-17 00:00:00I2018-08-31 23:59:59.0주유소193369.116473445563.769784<NA><NA>
43190000197631900720150000519760526<NA>3폐업3폐지<NA><NA><NA><NA>02 8229010<NA><NA>서울특별시 동작구 상도동 353-2서울특별시 동작구 상도로 120 (상도동)<NA>화신주유소2016-06-17 09:52:17I2018-08-31 23:59:59.0주유소194052.281603444337.583039<NA><NA>
5319000019763190072015000061976-05-26<NA>1영업/정상7영업개시<NA>2012-01-132012-05-30<NA>02 81507241124.0<NA>서울특별시 동작구 흑석동 9-46서울특별시 동작구 현충로 101 (흑석동)<NA>에이치디현대오일뱅크(주)직영 흑석동 셀프주유소2023-10-26 16:57:01U2022-10-30 22:08:00.0주유소196859.494514445088.884741<NA><NA>
63190000197631900720150000719760528<NA>3폐업3폐지200810312008100120081031<NA>02 8154292<NA><NA>서울특별시 동작구 상도동 33-1서울특별시 동작구 상도로 254 (상도동)<NA>상도동주유소2008-10-31 11:17:58I2018-08-31 23:59:59.0주유소195198.453405444672.650735<NA><NA>
7319000019763190072015000081976-04-02<NA>1영업/정상1신규등록<NA><NA><NA><NA>02 832 79262481.0<NA>서울특별시 동작구 신대방동 686-44서울특별시 동작구 시흥대로 616 (신대방동)<NA>에이치디현대오일뱅크(주)직영 신대방 셀프 주유소2023-11-03 14:02:44U2022-11-01 00:05:00.0주유소191585.298671442773.741552<NA><NA>
83190000198031900720120000119800214<NA>3폐업3폐지<NA><NA><NA><NA>02 8130435<NA><NA>서울특별시 동작구 흑석동 84-33서울특별시 동작구 서달로10길 74 (흑석동)<NA>흑석석유2016-07-11 11:45:09I2018-08-31 23:59:59.0일반판매소196663.34605444615.348868<NA><NA>
93190000198131900720120000119810629<NA>3폐업3폐지20171024<NA><NA><NA>02 8154158<NA><NA>서울특별시 동작구 흑석동 205-3서울특별시 동작구 흑석로7길 3 (흑석동)<NA>중앙에너지2017-10-24 14:30:32I2018-08-31 23:59:59.0일반판매소196235.146385444977.885168<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자본금거래처
493190000200431900720120000120040129<NA>3폐업3폐지<NA><NA><NA><NA>02 8325577<NA><NA>서울특별시 동작구 신대방동 352-13서울특별시 동작구 여의대방로24차길 24-2 (신대방동)<NA>라이프상사2012-05-23 20:45:59I2018-08-31 23:59:59.0일반판매소193490.555443444035.157878<NA><NA>
503190000200431900720120000220040129<NA>3폐업3폐지<NA><NA><NA><NA>02 8325577<NA><NA>서울특별시 동작구 신대방동 352-13서울특별시 동작구 여의대방로24차길 24-2 (신대방동)<NA>라이프상사2012-05-23 20:44:42I2018-08-31 23:59:59.0일반판매소193490.555443444035.157878<NA><NA>
513190000200531900720150000120050630<NA>3폐업3폐지20080213<NA><NA><NA>02 8345100<NA><NA>서울특별시 동작구 신대방동 395-73 캐릭터그린빌 1007호서울특별시 동작구 보라매로5가길 7, 케릭터그린빌동 1007호 (신대방동)<NA>메타켐주식회사2012-05-23 20:42:55I2018-08-31 23:59:59.0용제판매소193300.832516443302.417673<NA><NA>
523190000200531900720150170620051128<NA>3폐업3폐지20140313<NA><NA><NA>02 822 9010<NA><NA>서울특별시 동작구 상도동 353-2서울특별시 동작구 상도로 120 (상도동)<NA>현대주유소2014-03-13 09:48:53I2018-08-31 23:59:59.0주유소194052.281603444337.583039<NA><NA>
53319000020063190072015017051993-01-07<NA>1영업/정상6휴지사업재개<NA>2012-08-202013-02-282013-01-2902 532 0606634.0<NA>서울특별시 동작구 사당동 86-3서울특별시 동작구 동작대로 135 (사당동)<NA>지에스칼텍스(주) 남성주유소2024-03-25 18:04:14U2023-12-02 22:07:00.0주유소198335.327467442942.864671<NA><NA>
543190000200731900990150000120070322<NA>3폐업3폐지20101217<NA><NA><NA>02 821 3657<NA><NA>서울특별시 동작구 상도1동 546서울특별시 동작구 강남초등길 12 (상도1동)<NA>케미코트랜스(주)2012-05-23 20:38:56I2018-08-31 23:59:59.0용제판매소195681.593865444896.424239<NA><NA>
553190000200831900990150000120080507<NA>3폐업3폐지20150304<NA><NA><NA>02 598 7883<NA><NA>서울특별시 동작구 사당동 1051-25 옥암B/D 5층 T호서울특별시 동작구 남부순환로 2011, 옥암B/D동 5층 T호 (사당동)<NA>동양피앤씨2015-03-04 11:39:22I2018-08-31 23:59:59.0용제판매소197477.315759441543.537611<NA><NA>
563190000201131901420120000120111207<NA>3폐업3폐지<NA><NA><NA><NA>582640921.6<NA>서울특별시 동작구 사당동 708-554서울특별시 동작구 사당로27길 51 (사당동)<NA>팔팔석유2016-07-11 11:48:24I2018-08-31 23:59:59.0일반판매소197874.44076442639.026715<NA><NA>
573190000201131901420120000220111209<NA>3폐업3폐지<NA><NA><NA><NA>582640921.6<NA>서울특별시 동작구 사당동 708-554서울특별시 동작구 사당로27길 51 (사당동)<NA>팔팔석유2022-07-29 09:30:26U2021-12-06 21:01:00.0일반판매소197874.44076442639.026715<NA><NA>
58319000020193190177012000012019-06-26<NA>1영업/정상1신규등록<NA><NA><NA><NA><NA>26.0<NA>서울특별시 동작구 상도동 355-20서울특별시 동작구 성대로1길 17 (상도동)6959남양에너지2023-03-10 17:20:58U2022-12-02 23:02:00.0일반판매소194076.692856444318.185903<NA><NA>