Overview

Dataset statistics

Number of variables27
Number of observations131
Missing cells661
Missing cells (%)18.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.7 KiB
Average record size in memory232.0 B

Variable types

Categorical13
Numeric5
DateTime3
Unsupported3
Text3

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),제조구분명,사업장부지용도구분명
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-19017/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (93.5%)Imbalance
휴업종료일자 is highly imbalanced (93.5%)Imbalance
재개업일자 is highly imbalanced (93.5%)Imbalance
소재지면적 is highly imbalanced (91.8%)Imbalance
인허가취소일자 has 131 (100.0%) missing valuesMissing
폐업일자 has 82 (62.6%) missing valuesMissing
전화번호 has 131 (100.0%) missing valuesMissing
소재지우편번호 has 131 (100.0%) missing valuesMissing
지번주소 has 6 (4.6%) missing valuesMissing
도로명주소 has 38 (29.0%) missing valuesMissing
도로명우편번호 has 78 (59.5%) missing valuesMissing
좌표정보(X) has 32 (24.4%) missing valuesMissing
좌표정보(Y) has 32 (24.4%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전화번호 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

Reproduction

Analysis started2024-05-11 06:43:29.753182
Analysis finished2024-05-11 06:43:30.481426
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3150000
131 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 131
100.0%

Length

2024-05-11T15:43:30.599763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:30.783990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 131
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0099715 × 1018
Minimum1.986315 × 1018
Maximum2.024315 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:43:30.959161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.986315 × 1018
5-th percentile2.001315 × 1018
Q12.001315 × 1018
median2.009315 × 1018
Q32.017315 × 1018
95-th percentile2.022315 × 1018
Maximum2.024315 × 1018
Range3.8000013 × 1016
Interquartile range (IQR)1.6000008 × 1016

Descriptive statistics

Standard deviation8.7800265 × 1015
Coefficient of variation (CV)0.0043682343
Kurtosis-1.2029705
Mean2.0099715 × 1018
Median Absolute Deviation (MAD)8.0000049 × 1015
Skewness-0.059854097
Sum5.0518496 × 1018
Variance7.7088866 × 1031
MonotonicityStrictly increasing
2024-05-11T15:43:31.168118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1986315007402150011 1
 
0.8%
2016315015102100006 1
 
0.8%
2017315015102200004 1
 
0.8%
2017315015102200003 1
 
0.8%
2017315015102200002 1
 
0.8%
2017315015102200001 1
 
0.8%
2017315015102100007 1
 
0.8%
2017315015102100006 1
 
0.8%
2017315015102100005 1
 
0.8%
2017315015102100004 1
 
0.8%
Other values (121) 121
92.4%
ValueCountFrequency (%)
1986315007402150011 1
0.8%
1992315007402114535 1
0.8%
1994315007402116510 1
0.8%
1995315007402114312 1
0.8%
1998315015102101437 1
0.8%
2001315007402130001 1
0.8%
2001315007402130002 1
0.8%
2001315007402130003 1
0.8%
2001315007402130004 1
0.8%
2001315007402130005 1
0.8%
ValueCountFrequency (%)
2024315020402200001 1
0.8%
2023315020402100005 1
0.8%
2023315020402100004 1
0.8%
2023315020402100003 1
0.8%
2023315020402100002 1
0.8%
2023315020402100001 1
0.8%
2022315020402200008 1
0.8%
2022315020402200007 1
0.8%
2022315020402200006 1
0.8%
2022315020402200005 1
0.8%

인허가일자
Date

Distinct114
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1969-07-28 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T15:43:31.366410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:31.572834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
78 
3
49 
2
 
3
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 78
59.5%
3 49
37.4%
2 3
 
2.3%
5 1
 
0.8%

Length

2024-05-11T15:43:31.776323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:31.929650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 78
59.5%
3 49
37.4%
2 3
 
2.3%
5 1
 
0.8%

영업상태명
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
78 
폐업
49 
휴업
 
3
제외/삭제/전출
 
1

Length

Max length8
Median length5
Mean length3.8320611
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 78
59.5%
폐업 49
37.4%
휴업 3
 
2.3%
제외/삭제/전출 1
 
0.8%

Length

2024-05-11T15:43:32.402433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:32.563613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 78
59.5%
폐업 49
37.4%
휴업 3
 
2.3%
제외/삭제/전출 1
 
0.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
78 
3
49 
2
 
3
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 78
59.5%
3 49
37.4%
2 3
 
2.3%
4 1
 
0.8%

Length

2024-05-11T15:43:32.756233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:32.957871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 78
59.5%
3 49
37.4%
2 3
 
2.3%
4 1
 
0.8%

상세영업상태명
Categorical

Distinct4
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업중
78 
폐업
49 
휴업
 
3
타시군구이관
 
1

Length

Max length6
Median length3
Mean length2.6259542
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 78
59.5%
폐업 49
37.4%
휴업 3
 
2.3%
타시군구이관 1
 
0.8%

Length

2024-05-11T15:43:33.157745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:33.312755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 78
59.5%
폐업 49
37.4%
휴업 3
 
2.3%
타시군구이관 1
 
0.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)71.4%
Missing82
Missing (%)62.6%
Infinite0
Infinite (%)0.0%
Mean20140031
Minimum20000101
Maximum20221011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:43:33.488943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000101
5-th percentile20010101
Q120100430
median20160602
Q320201123
95-th percentile20220706
Maximum20221011
Range220910
Interquartile range (IQR)100693

Descriptive statistics

Standard deviation71528.4
Coefficient of variation (CV)0.0035515537
Kurtosis-0.75277439
Mean20140031
Median Absolute Deviation (MAD)50083
Skewness-0.65672473
Sum9.868615 × 108
Variance5.116312 × 109
MonotonicityNot monotonic
2024-05-11T15:43:33.686347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
20220706 7
 
5.3%
20010101 4
 
3.1%
20201123 3
 
2.3%
20070928 2
 
1.5%
20161020 2
 
1.5%
20170818 2
 
1.5%
20020307 1
 
0.8%
20131122 1
 
0.8%
20090410 1
 
0.8%
20020620 1
 
0.8%
Other values (25) 25
 
19.1%
(Missing) 82
62.6%
ValueCountFrequency (%)
20000101 1
 
0.8%
20010101 4
3.1%
20020307 1
 
0.8%
20020605 1
 
0.8%
20020620 1
 
0.8%
20070928 2
1.5%
20080610 1
 
0.8%
20090410 1
 
0.8%
20100430 1
 
0.8%
20100719 1
 
0.8%
ValueCountFrequency (%)
20221011 1
 
0.8%
20220706 7
5.3%
20220531 1
 
0.8%
20210524 1
 
0.8%
20210507 1
 
0.8%
20201123 3
2.3%
20201020 1
 
0.8%
20190620 1
 
0.8%
20190318 1
 
0.8%
20170911 1
 
0.8%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
130 
20210531
 
1

Length

Max length8
Median length4
Mean length4.0305344
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 130
99.2%
20210531 1
 
0.8%

Length

2024-05-11T15:43:33.911212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:34.087932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
99.2%
20210531 1
 
0.8%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
130 
20220530
 
1

Length

Max length8
Median length4
Mean length4.0305344
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 130
99.2%
20220530 1
 
0.8%

Length

2024-05-11T15:43:34.293516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:34.476785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
99.2%
20220530 1
 
0.8%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
130 
20180917
 
1

Length

Max length8
Median length4
Mean length4.0305344
Min length4

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 130
99.2%
20180917 1
 
0.8%

Length

2024-05-11T15:43:34.689316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:34.858007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 130
99.2%
20180917 1
 
0.8%

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

소재지면적
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
129 
371
 
1
1184
 
1

Length

Max length4
Median length4
Mean length3.9923664
Min length3

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
98.5%
371 1
 
0.8%
1184 1
 
0.8%

Length

2024-05-11T15:43:34.994170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:35.136465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
98.5%
371 1
 
0.8%
1184 1
 
0.8%

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing131
Missing (%)100.0%
Memory size1.3 KiB

지번주소
Text

MISSING 

Distinct107
Distinct (%)85.6%
Missing6
Missing (%)4.6%
Memory size1.2 KiB
2024-05-11T15:43:35.452280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length23.864
Min length13

Characters and Unicode

Total characters2983
Distinct characters166
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

Unique94 ?
Unique (%)75.2%

Sample

1st row서울특별시 강서구 공항동 1373 대한항공
2nd row서울특별시 강서구 염창동 244-3
3rd row서울특별시 강서구 공항동 281
4th row서울특별시 강서구 화곡동 854-5
5th row서울특별시 강서구 화곡동 380-7
ValueCountFrequency (%)
서울특별시 125
21.8%
강서구 124
21.6%
마곡동 44
 
7.7%
화곡동 15
 
2.6%
외발산동 12
 
2.1%
방화동 10
 
1.7%
가양동 10
 
1.7%
770-1 9
 
1.6%
등촌동 9
 
1.6%
엘지사이언스파크 8
 
1.4%
Other values (143) 208
36.2%
2024-05-11T15:43:35.934005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
17.9%
서 262
 
8.8%
시 134
 
4.5%
강 132
 
4.4%
구 129
 
4.3%
울 129
 
4.3%
동 129
 
4.3%
특 125
 
4.2%
별 125
 
4.2%
1 93
 
3.1%
Other values (156) 1190
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1800
60.3%
Space Separator 535
 
17.9%
Decimal Number 507
 
17.0%
Dash Punctuation 84
 
2.8%
Lowercase Letter 21
 
0.7%
Uppercase Letter 19
 
0.6%
Other Punctuation 9
 
0.3%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 262
14.6%
시 134
 
7.4%
강 132
 
7.3%
구 129
 
7.2%
울 129
 
7.2%
동 129
 
7.2%
특 125
 
6.9%
별 125
 
6.9%
곡 65
 
3.6%
마 50
 
2.8%
Other values (127) 520
28.9%
Decimal Number
ValueCountFrequency (%)
1 93
18.3%
7 89
17.6%
2 60
11.8%
4 47
9.3%
8 44
8.7%
6 40
7.9%
0 40
7.9%
5 32
 
6.3%
3 32
 
6.3%
9 30
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
G 6
31.6%
L 5
26.3%
K 2
 
10.5%
E 2
 
10.5%
N 1
 
5.3%
C 1
 
5.3%
P 1
 
5.3%
D 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
n 6
28.6%
o 6
28.6%
e 3
14.3%
l 3
14.3%
y 3
14.3%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
& 3
33.3%
Space Separator
ValueCountFrequency (%)
535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1800
60.3%
Common 1143
38.3%
Latin 40
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 262
14.6%
시 134
 
7.4%
강 132
 
7.3%
구 129
 
7.2%
울 129
 
7.2%
동 129
 
7.2%
특 125
 
6.9%
별 125
 
6.9%
곡 65
 
3.6%
마 50
 
2.8%
Other values (127) 520
28.9%
Common
ValueCountFrequency (%)
535
46.8%
1 93
 
8.1%
7 89
 
7.8%
- 84
 
7.3%
2 60
 
5.2%
4 47
 
4.1%
8 44
 
3.8%
6 40
 
3.5%
0 40
 
3.5%
5 32
 
2.8%
Other values (6) 79
 
6.9%
Latin
ValueCountFrequency (%)
G 6
15.0%
n 6
15.0%
o 6
15.0%
L 5
12.5%
e 3
7.5%
l 3
7.5%
y 3
7.5%
K 2
 
5.0%
E 2
 
5.0%
N 1
 
2.5%
Other values (3) 3
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1800
60.3%
ASCII 1183
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
45.2%
1 93
 
7.9%
7 89
 
7.5%
- 84
 
7.1%
2 60
 
5.1%
4 47
 
4.0%
8 44
 
3.7%
6 40
 
3.4%
0 40
 
3.4%
5 32
 
2.7%
Other values (19) 119
 
10.1%
Hangul
ValueCountFrequency (%)
서 262
14.6%
시 134
 
7.4%
강 132
 
7.3%
구 129
 
7.2%
울 129
 
7.2%
동 129
 
7.2%
특 125
 
6.9%
별 125
 
6.9%
곡 65
 
3.6%
마 50
 
2.8%
Other values (127) 520
28.9%

도로명주소
Text

MISSING 

Distinct77
Distinct (%)82.8%
Missing38
Missing (%)29.0%
Memory size1.2 KiB
2024-05-11T15:43:36.367071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length29.516129
Min length22

Characters and Unicode

Total characters2745
Distinct characters169
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

Unique65 ?
Unique (%)69.9%

Sample

1st row서울특별시 강서구 양천로 643 (염창동)
2nd row서울특별시 강서구 국회대로7길 113 (화곡동)
3rd row서울특별시 강서구 강서로29길 72 (화곡동)
4th row서울특별시 강서구 초원로 81 (방화동)
5th row서울특별시 강서구 양천로 543 (가양동)
ValueCountFrequency (%)
서울특별시 93
 
17.9%
강서구 92
 
17.7%
마곡동 31
 
6.0%
양천로 17
 
3.3%
화곡동 11
 
2.1%
가양동 8
 
1.5%
마곡중앙8로 8
 
1.5%
마곡중앙10로 8
 
1.5%
공항대로 7
 
1.3%
엘지사이언스파크 7
 
1.3%
Other values (145) 238
45.8%
2024-05-11T15:43:37.008734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
442
 
16.1%
서 202
 
7.4%
강 104
 
3.8%
동 102
 
3.7%
시 99
 
3.6%
울 97
 
3.5%
구 96
 
3.5%
( 94
 
3.4%
) 94
 
3.4%
별 93
 
3.4%
Other values (159) 1322
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1720
62.7%
Space Separator 442
 
16.1%
Decimal Number 309
 
11.3%
Open Punctuation 94
 
3.4%
Close Punctuation 94
 
3.4%
Other Punctuation 49
 
1.8%
Lowercase Letter 21
 
0.8%
Uppercase Letter 9
 
0.3%
Dash Punctuation 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 202
 
11.7%
강 104
 
6.0%
동 102
 
5.9%
시 99
 
5.8%
울 97
 
5.6%
구 96
 
5.6%
별 93
 
5.4%
특 93
 
5.4%
로 87
 
5.1%
곡 76
 
4.4%
Other values (134) 671
39.0%
Decimal Number
ValueCountFrequency (%)
1 63
20.4%
3 43
13.9%
0 39
12.6%
2 34
11.0%
4 33
10.7%
8 24
 
7.8%
5 23
 
7.4%
7 23
 
7.4%
6 17
 
5.5%
9 10
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
o 6
28.6%
n 6
28.6%
l 3
14.3%
e 3
14.3%
y 3
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 3
33.3%
G 3
33.3%
K 2
22.2%
E 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 46
93.9%
& 3
 
6.1%
Space Separator
ValueCountFrequency (%)
442
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1720
62.7%
Common 995
36.2%
Latin 30
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 202
 
11.7%
강 104
 
6.0%
동 102
 
5.9%
시 99
 
5.8%
울 97
 
5.6%
구 96
 
5.6%
별 93
 
5.4%
특 93
 
5.4%
로 87
 
5.1%
곡 76
 
4.4%
Other values (134) 671
39.0%
Common
ValueCountFrequency (%)
442
44.4%
( 94
 
9.4%
) 94
 
9.4%
1 63
 
6.3%
, 46
 
4.6%
3 43
 
4.3%
0 39
 
3.9%
2 34
 
3.4%
4 33
 
3.3%
8 24
 
2.4%
Other values (6) 83
 
8.3%
Latin
ValueCountFrequency (%)
o 6
20.0%
n 6
20.0%
l 3
10.0%
e 3
10.0%
y 3
10.0%
L 3
10.0%
G 3
10.0%
K 2
 
6.7%
E 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1720
62.7%
ASCII 1025
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
442
43.1%
( 94
 
9.2%
) 94
 
9.2%
1 63
 
6.1%
, 46
 
4.5%
3 43
 
4.2%
0 39
 
3.8%
2 34
 
3.3%
4 33
 
3.2%
8 24
 
2.3%
Other values (15) 113
 
11.0%
Hangul
ValueCountFrequency (%)
서 202
 
11.7%
강 104
 
6.0%
동 102
 
5.9%
시 99
 
5.8%
울 97
 
5.6%
구 96
 
5.6%
별 93
 
5.4%
특 93
 
5.4%
로 87
 
5.1%
곡 76
 
4.4%
Other values (134) 671
39.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)54.7%
Missing78
Missing (%)59.5%
Infinite0
Infinite (%)0.0%
Mean7589.5283
Minimum2586
Maximum7805
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:43:37.221642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2586
5-th percentile7505
Q17537
median7788
Q37796
95-th percentile7802.8
Maximum7805
Range5219
Interquartile range (IQR)259

Descriptive statistics

Standard deviation711.63362
Coefficient of variation (CV)0.093765197
Kurtosis49.571097
Mean7589.5283
Median Absolute Deviation (MAD)17
Skewness-6.9332165
Sum402245
Variance506422.41
MonotonicityNot monotonic
2024-05-11T15:43:37.417154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
7505 8
 
6.1%
7796 8
 
6.1%
7793 4
 
3.1%
7802 3
 
2.3%
7506 2
 
1.5%
7804 2
 
1.5%
7801 2
 
1.5%
7795 2
 
1.5%
7653 2
 
1.5%
7520 1
 
0.8%
Other values (19) 19
 
14.5%
(Missing) 78
59.5%
ValueCountFrequency (%)
2586 1
 
0.8%
7504 1
 
0.8%
7505 8
6.1%
7506 2
 
1.5%
7520 1
 
0.8%
7537 1
 
0.8%
7550 1
 
0.8%
7557 1
 
0.8%
7560 1
 
0.8%
7570 1
 
0.8%
ValueCountFrequency (%)
7805 1
 
0.8%
7804 2
 
1.5%
7802 3
 
2.3%
7801 2
 
1.5%
7800 1
 
0.8%
7797 1
 
0.8%
7796 8
6.1%
7795 2
 
1.5%
7794 1
 
0.8%
7793 4
3.1%

사업장명
Text

Distinct107
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-11T15:43:37.775671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length9.8854962
Min length4

Characters and Unicode

Total characters1295
Distinct characters225
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

Unique90 ?
Unique (%)68.7%

Sample

1st row(주)대한항공
2nd row(주)국민은행 서염창지점
3rd row(주)아시아나항공 화물청사
4th row(주)MS가스서울영업소
5th row명성특수가스
ValueCountFrequency (%)
lg전자(주)외 7
 
4.0%
lg전자(주 5
 
2.8%
4개사 5
 
2.8%
서울특별시농수산식품공사 4
 
2.3%
한국공항공사 4
 
2.3%
김포공항 4
 
2.3%
가양점 4
 
2.3%
5개사 4
 
2.3%
정림개발(주 3
 
1.7%
주식회사 3
 
1.7%
Other values (119) 133
75.6%
2024-05-11T15:43:38.393362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 87
 
6.7%
) 87
 
6.7%
주 85
 
6.6%
45
 
3.5%
스 43
 
3.3%
공 36
 
2.8%
사 33
 
2.5%
서 29
 
2.2%
항 21
 
1.6%
가 19
 
1.5%
Other values (215) 810
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1010
78.0%
Open Punctuation 88
 
6.8%
Close Punctuation 88
 
6.8%
Space Separator 45
 
3.5%
Uppercase Letter 42
 
3.2%
Decimal Number 18
 
1.4%
Dash Punctuation 3
 
0.2%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 85
 
8.4%
스 43
 
4.3%
공 36
 
3.6%
사 33
 
3.3%
서 29
 
2.9%
항 21
 
2.1%
가 19
 
1.9%
전 19
 
1.9%
아 17
 
1.7%
이 17
 
1.7%
Other values (192) 691
68.4%
Uppercase Letter
ValueCountFrequency (%)
G 15
35.7%
L 14
33.3%
N 3
 
7.1%
C 3
 
7.1%
S 2
 
4.8%
P 1
 
2.4%
E 1
 
2.4%
M 1
 
2.4%
I 1
 
2.4%
O 1
 
2.4%
Decimal Number
ValueCountFrequency (%)
5 6
33.3%
4 5
27.8%
2 2
 
11.1%
0 2
 
11.1%
6 2
 
11.1%
1 1
 
5.6%
Open Punctuation
ValueCountFrequency (%)
( 87
98.9%
[ 1
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 87
98.9%
] 1
 
1.1%
Space Separator
ValueCountFrequency (%)
45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1010
78.0%
Common 243
 
18.8%
Latin 42
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 85
 
8.4%
스 43
 
4.3%
공 36
 
3.6%
사 33
 
3.3%
서 29
 
2.9%
항 21
 
2.1%
가 19
 
1.9%
전 19
 
1.9%
아 17
 
1.7%
이 17
 
1.7%
Other values (192) 691
68.4%
Common
ValueCountFrequency (%)
( 87
35.8%
) 87
35.8%
45
18.5%
5 6
 
2.5%
4 5
 
2.1%
- 3
 
1.2%
2 2
 
0.8%
0 2
 
0.8%
6 2
 
0.8%
1 1
 
0.4%
Other values (3) 3
 
1.2%
Latin
ValueCountFrequency (%)
G 15
35.7%
L 14
33.3%
N 3
 
7.1%
C 3
 
7.1%
S 2
 
4.8%
P 1
 
2.4%
E 1
 
2.4%
M 1
 
2.4%
I 1
 
2.4%
O 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1010
78.0%
ASCII 285
 
22.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 87
30.5%
) 87
30.5%
45
15.8%
G 15
 
5.3%
L 14
 
4.9%
5 6
 
2.1%
4 5
 
1.8%
N 3
 
1.1%
C 3
 
1.1%
- 3
 
1.1%
Other values (13) 17
 
6.0%
Hangul
ValueCountFrequency (%)
주 85
 
8.4%
스 43
 
4.3%
공 36
 
3.6%
사 33
 
3.3%
서 29
 
2.9%
항 21
 
2.1%
가 19
 
1.9%
전 19
 
1.9%
아 17
 
1.7%
이 17
 
1.7%
Other values (192) 691
68.4%

최종수정일자
Date

UNIQUE 

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2001-12-28 00:00:00
Maximum2024-04-25 16:42:20
2024-05-11T15:43:38.600619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:38.807945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
U
78 
I
53 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 78
59.5%
I 53
40.5%

Length

2024-05-11T15:43:38.994460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:39.140054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 78
59.5%
i 53
40.5%

데이터갱신일자
Date

Distinct68
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-11T15:43:39.308100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:43:39.515683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
제조
104 
저장소
18 
판매
 
9

Length

Max length3
Median length2
Mean length2.1374046
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제조
2nd row제조
3rd row제조
4th row판매
5th row판매

Common Values

ValueCountFrequency (%)
제조 104
79.4%
저장소 18
 
13.7%
판매 9
 
6.9%

Length

2024-05-11T15:43:39.741606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:39.991549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조 104
79.4%
저장소 18
 
13.7%
판매 9
 
6.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct67
Distinct (%)67.7%
Missing32
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean185323.49
Minimum179450.36
Maximum202232.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:43:40.162593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179450.36
5-th percentile182135.72
Q1183863.69
median185102.93
Q3186795.35
95-th percentile188304.22
Maximum202232.55
Range22782.197
Interquartile range (IQR)2931.6533

Descriptive statistics

Standard deviation2575.8505
Coefficient of variation (CV)0.013899212
Kurtosis17.930533
Mean185323.49
Median Absolute Deviation (MAD)1584.2059
Skewness2.7800535
Sum18347026
Variance6635005.9
MonotonicityNot monotonic
2024-05-11T15:43:40.389165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186687.131804431 5
 
3.8%
187582.14468071 4
 
3.1%
185102.925888382 4
 
3.1%
182086.388313239 4
 
3.1%
184148.571466974 4
 
3.1%
182974.850127567 3
 
2.3%
184841.846415698 3
 
2.3%
185617.085005907 2
 
1.5%
183007.220061564 2
 
1.5%
185824.428508883 2
 
1.5%
Other values (57) 66
50.4%
(Missing) 32
24.4%
ValueCountFrequency (%)
179450.357527221 1
 
0.8%
182086.388313239 4
3.1%
182141.205465089 2
1.5%
182162.406429892 1
 
0.8%
182524.823835629 2
1.5%
182538.334871813 1
 
0.8%
182735.786874703 1
 
0.8%
182739.232010141 1
 
0.8%
182974.850127567 3
2.3%
183007.220061564 2
1.5%
ValueCountFrequency (%)
202232.554341254 1
 
0.8%
189124.441211963 1
 
0.8%
189029.460526202 1
 
0.8%
188978.087856355 1
 
0.8%
188385.790412096 1
 
0.8%
188295.158516659 1
 
0.8%
187731.084393625 1
 
0.8%
187655.629899389 1
 
0.8%
187582.14468071 4
3.1%
187569.817399726 1
 
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct67
Distinct (%)67.7%
Missing32
Missing (%)24.4%
Infinite0
Infinite (%)0.0%
Mean450613.93
Minimum447447.71
Maximum453136.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-11T15:43:40.599616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447447.71
5-th percentile448423.97
Q1450018.41
median450728.9
Q3451342.77
95-th percentile452484.35
Maximum453136.45
Range5688.7419
Interquartile range (IQR)1324.3665

Descriptive statistics

Standard deviation1264.279
Coefficient of variation (CV)0.0028056811
Kurtosis0.21808782
Mean450613.93
Median Absolute Deviation (MAD)643.88394
Skewness-0.42107071
Sum44610779
Variance1598401.4
MonotonicityNot monotonic
2024-05-11T15:43:40.797657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451342.773451086 5
 
3.8%
450728.898515109 4
 
3.1%
451165.579794021 4
 
3.1%
449251.768967194 4
 
3.1%
450166.360534543 4
 
3.1%
450419.684560487 3
 
2.3%
452316.417141747 3
 
2.3%
448489.902453665 2
 
1.5%
450515.642035894 2
 
1.5%
450866.252126246 2
 
1.5%
Other values (57) 66
50.4%
(Missing) 32
24.4%
ValueCountFrequency (%)
447447.706246304 2
1.5%
447512.72698915 1
 
0.8%
447554.856131045 1
 
0.8%
447830.610425962 1
 
0.8%
448489.902453665 2
1.5%
448612.836468294 1
 
0.8%
449063.504577474 2
1.5%
449077.48408662 1
 
0.8%
449251.768967194 4
3.1%
449330.107139552 1
 
0.8%
ValueCountFrequency (%)
453136.448166169 1
 
0.8%
453130.815651695 1
 
0.8%
452899.475862536 1
 
0.8%
452733.565237078 1
 
0.8%
452537.665730014 1
 
0.8%
452478.427026385 1
 
0.8%
452448.293703049 1
 
0.8%
452397.732552095 1
 
0.8%
452319.790099839 1
 
0.8%
452316.417141747 3
2.3%

제조구분명
Categorical

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
냉동
58 
<NA>
44 
일반
19 
충전
8 
특정
 
2

Length

Max length4
Median length2
Mean length2.6717557
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
냉동 58
44.3%
<NA> 44
33.6%
일반 19
 
14.5%
충전 8
 
6.1%
특정 2
 
1.5%

Length

2024-05-11T15:43:41.000496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:43:41.160468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
냉동 58
44.3%
na 44
33.6%
일반 19
 
14.5%
충전 8
 
6.1%
특정 2
 
1.5%

사업장부지용도구분명
Categorical

Distinct14
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
85 
지정되지않음
13 
상업.업무용
 
7
주상기타
 
5
공업용
 
4
Other values (9)
17 

Length

Max length6
Median length4
Mean length4.1832061
Min length2

Unique

Unique4 ?
Unique (%)3.1%

Sample

1st row공업용
2nd row업무용
3rd row상업.업무용
4th row상업용
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 85
64.9%
지정되지않음 13
 
9.9%
상업.업무용 7
 
5.3%
주상기타 5
 
3.8%
공업용 4
 
3.1%
주거용 4
 
3.1%
상업기타 3
 
2.3%
상업용 2
 
1.5%
공업기타 2
 
1.5%
기타 2
 
1.5%
Other values (4) 4
 
3.1%

Length

2024-05-11T15:43:41.350816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 85
64.9%
지정되지않음 13
 
9.9%
상업.업무용 7
 
5.3%
주상기타 5
 
3.8%
공업용 4
 
3.1%
주거용 4
 
3.1%
상업기타 3
 
2.3%
상업용 2
 
1.5%
공업기타 2
 
1.5%
기타 2
 
1.5%
Other values (4) 4
 
3.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)제조구분명사업장부지용도구분명
03150000198631500740215001119860410<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 1373 대한항공<NA><NA>(주)대한항공2011-04-11 16:12:47I2021-09-16 00:22:48.0제조182974.850128450419.68456냉동공업용
13150000199231500740211453519920211<NA>3폐업3폐업20190620<NA><NA><NA><NA><NA><NA>서울특별시 강서구 염창동 244-3서울특별시 강서구 양천로 643 (염창동)<NA>(주)국민은행 서염창지점2019-06-19 14:20:05U2019-06-21 02:40:00.0제조188385.790412450185.534717냉동업무용
23150000199431500740211651019941205<NA>3폐업3폐업20161020<NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 281<NA><NA>(주)아시아나항공 화물청사2016-10-20 10:49:05I2018-08-31 23:59:59.0제조<NA><NA>냉동상업.업무용
33150000199531500740211431220100422<NA>3폐업3폐업20150601<NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 854-5서울특별시 강서구 국회대로7길 113 (화곡동)<NA>(주)MS가스서울영업소2020-11-18 17:20:09U2020-11-20 02:40:00.0판매187078.660577447447.706246일반상업용
43150000199831501510210143719980813<NA>3폐업3폐업20160602<NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 380-7서울특별시 강서구 강서로29길 72 (화곡동)<NA>명성특수가스2016-06-02 13:51:04I2018-08-31 23:59:59.0판매185617.085006448489.902454<NA><NA>
53150000200131500740213000119720727<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 방화동 247-92서울특별시 강서구 초원로 81 (방화동)<NA>영일상회2001-12-28 00:00:00I2018-08-31 23:59:59.0저장소183545.950071451727.75796일반지정되지않음
63150000200131500740213000219771104<NA>3폐업3폐업20170911<NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 449-12서울특별시 강서구 양천로 543 (가양동)<NA>대한의산(주)2017-09-12 14:33:24I2018-08-31 23:59:59.0저장소187582.144681450728.898515일반지정되지않음
73150000200131500740213000319780322<NA>3폐업3폐업20170303<NA><NA><NA><NA><NA><NA>서울특별시 강서구 가양동 449-12서울특별시 강서구 양천로 543 (가양동)<NA>신양산소공업(주)2020-11-06 11:05:38U2020-11-08 02:40:00.0판매187582.144681450728.898515일반지정되지않음
83150000200131500740213000419900917<NA>3폐업3폐업20121210<NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 354-50서울특별시 강서구 강서로17길 78 (화곡동)<NA>한원산업가스2012-12-14 17:46:15I2018-08-31 23:59:59.0저장소185916.087832447830.610426일반지정되지않음
93150000200131500740213000519790623<NA>3폐업3폐업20010101<NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 1019-27서울특별시 강서구 강서로41길 52 (화곡동)<NA>제일종합가스2020-11-18 20:32:09U2020-11-20 02:40:00.0저장소185356.453127449077.484087일반지정되지않음
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)제조구분명사업장부지용도구분명
121315000020223150204022000052022-05-26<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 772-1서울특별시 강서구 마곡중앙8로 38 (마곡동)7802씨지인바이츠 주식회사2023-12-11 11:32:28I2022-11-01 23:03:00.0제조185045.363289450991.625475<NA><NA>
1223150000202231502040220000620220526<NA>3폐업3폐업20220706<NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 772 스페이스K 서울서울특별시 강서구 마곡중앙8로 32, 스페이스K 서울 (마곡동)7802크리스탈지노믹스(주)2022-07-06 11:15:06I2021-12-07 00:08:00.0제조<NA><NA><NA><NA>
1233150000202231502040220000720220526<NA>5제외/삭제/전출4타시군구이관<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 772 스페이스K 서울서울특별시 강서구 마곡중앙8로 32, 스페이스K 서울 (마곡동)7802크리스탈지노믹스(주)2022-05-27 09:00:02I2021-12-04 22:09:00.0제조<NA><NA><NA><NA>
1243150000202231502040220000820220922<NA>2휴업2휴업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 외발산동 245-13서울특별시 강서구 남부순환로 277 (외발산동)7641육군 제5602부대2022-09-22 14:23:10I2021-12-08 22:04:00.0제조184399.030562449063.504577<NA><NA>
125315000020233150204021000012023-01-31<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 770-1 LG사이언스파크<NA><NA>LG전자(주) 외 5개사2024-04-24 09:09:11U2023-12-03 22:06:00.0제조185102.925888451165.579794<NA><NA>
126315000020233150204021000022023-01-31<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 770-1 LG사이언스파크서울특별시 강서구 마곡중앙10로 30, LG사이언스파크 (마곡동)7796LG전자(주) 외 5개사2023-06-09 16:12:40U2022-12-05 23:01:00.0제조185102.925888451165.579794<NA><NA>
127315000020233150204021000032023-06-16<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 770 LG사이언스파크 DP2서울특별시 강서구 마곡중앙10로 10, LG사이언스파크 (마곡동)7796LG전자(주)2023-06-16 17:15:17I2022-12-05 23:08:00.0제조184825.577234451201.280251<NA><NA>
128315000020233150204021000042023-08-08<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 780-2 ,6,7<NA><NA>에쓰-오일(S-OIL)(주)2023-08-08 17:57:35I2022-12-07 23:00:00.0저장소185393.024174451531.147412<NA><NA>
129315000020233150204021000052023-12-19<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 공항동 1370 대한항공서울특별시 강서구 하늘길 260, 대한항공 (공항동)7505(주)대한항공2023-12-19 15:37:02I2022-11-01 22:01:00.0제조183340.570263449522.97896<NA><NA>
130315000020243150204022000012024-04-25<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 마곡동 769서울특별시 강서구 공항대로 165 (마곡동)7800마곡씨피포피에프브이 주식회사2024-04-25 16:42:20I2023-12-03 22:07:00.0제조184449.736274451015.135227<NA><NA>