Overview

Dataset statistics

Number of variables48
Number of observations48
Missing cells674
Missing cells (%)29.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory417.8 B

Variable types

Categorical23
Numeric4
DateTime3
Unsupported9
Text9

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),실험실면적,사업장구분명,영업소면적,위탁업체명,실험실지역코드,실험실우편번호,실험실산,실험실번지,실험실호,실험실통,실험실반,실험실특수주소,실험실특수주소동,실험실특수주소호,실험실도로명주소시군구코드,실험실도로명주소읍면동코드,실험실도로명주소읍면동구분,실험실도로명주소코드,실험실도로명특수주소,실험실도로명주소건물층구분,실험실도로명주소건물본번호,실험실도로명주소건물부번호,실험실도로명주소우편번호
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-19518/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
소재지우편번호 is highly imbalanced (81.6%)Imbalance
실험실면적 is highly imbalanced (51.8%)Imbalance
영업소면적 is highly imbalanced (60.9%)Imbalance
실험실지역코드 is highly imbalanced (60.6%)Imbalance
실험실우편번호 is highly imbalanced (78.2%)Imbalance
실험실번지 is highly imbalanced (72.0%)Imbalance
실험실호 is highly imbalanced (75.0%)Imbalance
실험실특수주소호 is highly imbalanced (78.2%)Imbalance
실험실도로명주소시군구코드 is highly imbalanced (51.8%)Imbalance
실험실도로명주소읍면동코드 is highly imbalanced (51.8%)Imbalance
실험실도로명주소읍면동구분 is highly imbalanced (51.8%)Imbalance
실험실도로명주소코드 is highly imbalanced (72.0%)Imbalance
실험실도로명주소건물층구분 is highly imbalanced (51.8%)Imbalance
실험실도로명주소건물본번호 is highly imbalanced (72.0%)Imbalance
실험실도로명주소우편번호 is highly imbalanced (85.4%)Imbalance
인허가취소일자 has 48 (100.0%) missing valuesMissing
폐업일자 has 34 (70.8%) missing valuesMissing
휴업시작일자 has 48 (100.0%) missing valuesMissing
휴업종료일자 has 48 (100.0%) missing valuesMissing
재개업일자 has 48 (100.0%) missing valuesMissing
전화번호 has 1 (2.1%) missing valuesMissing
소재지면적 has 48 (100.0%) missing valuesMissing
도로명주소 has 13 (27.1%) missing valuesMissing
도로명우편번호 has 15 (31.2%) missing valuesMissing
업태구분명 has 47 (97.9%) missing valuesMissing
좌표정보(X) has 2 (4.2%) missing valuesMissing
좌표정보(Y) has 2 (4.2%) missing valuesMissing
위탁업체명 has 42 (87.5%) missing valuesMissing
실험실통 has 48 (100.0%) missing valuesMissing
실험실반 has 48 (100.0%) missing valuesMissing
실험실특수주소 has 43 (89.6%) missing valuesMissing
실험실특수주소동 has 48 (100.0%) missing valuesMissing
실험실도로명특수주소 has 43 (89.6%) missing valuesMissing
실험실도로명주소건물부번호 has 48 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실통 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실반 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실특수주소동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실도로명주소건물부번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 04:41:38.172340
Analysis finished2024-05-11 04:41:39.949474
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
3160000
48 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 48
100.0%

Length

2024-05-11T04:41:40.172708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:40.563656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 48
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1600007 × 1017
Minimum3.1600007 × 1017
Maximum3.1600007 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-11T04:41:40.992653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1600007 × 1017
5-th percentile3.1600007 × 1017
Q13.1600007 × 1017
median3.1600007 × 1017
Q33.1600007 × 1017
95-th percentile3.1600007 × 1017
Maximum3.1600007 × 1017
Range3199999
Interquartile range (IQR)600000

Descriptive statistics

Standard deviation801560.6
Coefficient of variation (CV)2.5365836 × 10-12
Kurtosis0.83929762
Mean3.1600007 × 1017
Median Absolute Deviation (MAD)250048
Skewness-1.0129926
Sum-3.2787408 × 1018
Variance6.424994 × 1011
MonotonicityStrictly increasing
2024-05-11T04:41:41.723161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
316000067199100003 1
 
2.1%
316000067201300002 1
 
2.1%
316000067201400002 1
 
2.1%
316000067201400003 1
 
2.1%
316000067201400004 1
 
2.1%
316000067201400005 1
 
2.1%
316000067201400006 1
 
2.1%
316000067201500001 1
 
2.1%
316000067201500002 1
 
2.1%
316000067201500003 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
316000067199100003 1
2.1%
316000067199100004 1
2.1%
316000067199200100 1
2.1%
316000067199800001 1
2.1%
316000067199900001 1
2.1%
316000067200000008 1
2.1%
316000067200100003 1
2.1%
316000067200400012 1
2.1%
316000067200500013 1
2.1%
316000067200600015 1
2.1%
ValueCountFrequency (%)
316000067202300002 1
2.1%
316000067202300001 1
2.1%
316000067202200002 1
2.1%
316000067202200001 1
2.1%
316000067202000005 1
2.1%
316000067202000004 1
2.1%
316000067202000003 1
2.1%
316000067202000002 1
2.1%
316000067202000001 1
2.1%
316000067201900002 1
2.1%

인허가일자
Date

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum1991-06-13 00:00:00
Maximum2023-03-03 00:00:00
2024-05-11T04:41:42.226324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:41:42.644467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
1
31 
3
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 31
64.6%
3 17
35.4%

Length

2024-05-11T04:41:43.102049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:43.473591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
64.6%
3 17
35.4%

영업상태명
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
영업/정상
31 
폐업
17 

Length

Max length5
Median length5
Mean length3.9375
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 31
64.6%
폐업 17
35.4%

Length

2024-05-11T04:41:44.007761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:44.332688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 31
64.6%
폐업 17
35.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
BBBB
31 
2
17 

Length

Max length4
Median length4
Mean length2.9375
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 31
64.6%
2 17
35.4%

Length

2024-05-11T04:41:44.729349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:45.211763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 31
64.6%
2 17
35.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
영업
31 
폐업
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 31
64.6%
폐업 17
35.4%

Length

2024-05-11T04:41:45.708691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:46.024089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 31
64.6%
폐업 17
35.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)85.7%
Missing34
Missing (%)70.8%
Infinite0
Infinite (%)0.0%
Mean20155153
Minimum20110210
Maximum20221116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-11T04:41:46.317022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20110210
5-th percentile20110542
Q120140617
median20141128
Q320188455
95-th percentile20214617
Maximum20221116
Range110906
Interquartile range (IQR)47838

Descriptive statistics

Standard deviation39016.15
Coefficient of variation (CV)0.0019357903
Kurtosis-0.96792051
Mean20155153
Median Absolute Deviation (MAD)19646
Skewness0.67479161
Sum2.8217215 × 108
Variance1.52226 × 109
MonotonicityNot monotonic
2024-05-11T04:41:46.784703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20141128 3
 
6.2%
20111219 1
 
2.1%
20150511 1
 
2.1%
20140929 1
 
2.1%
20110210 1
 
2.1%
20110721 1
 
2.1%
20140513 1
 
2.1%
20141014 1
 
2.1%
20201103 1
 
2.1%
20211117 1
 
2.1%
Other values (2) 2
 
4.2%
(Missing) 34
70.8%
ValueCountFrequency (%)
20110210 1
 
2.1%
20110721 1
 
2.1%
20111219 1
 
2.1%
20140513 1
 
2.1%
20140929 1
 
2.1%
20141014 1
 
2.1%
20141128 3
6.2%
20150511 1
 
2.1%
20201103 1
 
2.1%
20210311 1
 
2.1%
ValueCountFrequency (%)
20221116 1
 
2.1%
20211117 1
 
2.1%
20210311 1
 
2.1%
20201103 1
 
2.1%
20150511 1
 
2.1%
20141128 3
6.2%
20141014 1
 
2.1%
20140929 1
 
2.1%
20140513 1
 
2.1%
20111219 1
 
2.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

전화번호
Text

MISSING 

Distinct39
Distinct (%)83.0%
Missing1
Missing (%)2.1%
Memory size516.0 B
2024-05-11T04:41:47.458240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.106383
Min length7

Characters and Unicode

Total characters475
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

Unique34 ?
Unique (%)72.3%

Sample

1st row0221095741
2nd row028903905
3rd row02-859-2527
4th row02-2108-1151
5th row21088800
ValueCountFrequency (%)
028520801 4
 
8.5%
02-866-3639 3
 
6.4%
0226305676 2
 
4.3%
028518383 2
 
4.3%
0232895266 2
 
4.3%
02-7475-9100 1
 
2.1%
02-837-1146 1
 
2.1%
0221095741 1
 
2.1%
0221082100 1
 
2.1%
07043344741 1
 
2.1%
Other values (29) 29
61.7%
2024-05-11T04:41:48.371680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100
21.1%
2 81
17.1%
8 44
9.3%
6 41
8.6%
1 39
 
8.2%
- 37
 
7.8%
3 37
 
7.8%
5 34
 
7.2%
9 27
 
5.7%
7 23
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 438
92.2%
Dash Punctuation 37
 
7.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100
22.8%
2 81
18.5%
8 44
10.0%
6 41
9.4%
1 39
 
8.9%
3 37
 
8.4%
5 34
 
7.8%
9 27
 
6.2%
7 23
 
5.3%
4 12
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 475
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100
21.1%
2 81
17.1%
8 44
9.3%
6 41
8.6%
1 39
 
8.2%
- 37
 
7.8%
3 37
 
7.8%
5 34
 
7.2%
9 27
 
5.7%
7 23
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100
21.1%
2 81
17.1%
8 44
9.3%
6 41
8.6%
1 39
 
8.2%
- 37
 
7.8%
3 37
 
7.8%
5 34
 
7.2%
9 27
 
5.7%
7 23
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

소재지우편번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
46 
152775
 
1
152887
 
1

Length

Max length6
Median length4
Mean length4.0833333
Min length4

Unique

Unique2 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 46
95.8%
152775 1
 
2.1%
152887 1
 
2.1%

Length

2024-05-11T04:41:49.048848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:49.635593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 46
95.8%
152775 1
 
2.1%
152887 1
 
2.1%

지번주소
Text

Distinct41
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-05-11T04:41:50.301586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length28.75
Min length18

Characters and Unicode

Total characters1380
Distinct characters95
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)72.9%

Sample

1st row서울특별시 구로구 구로동 197-22 에이스테크노타워5차 508호
2nd row서울특별시 구로구 구로동 184-1 우림 이비지센터2차 713호
3rd row서울특별시 구로구 구로동 212-30 에이스트윈타워2차 401호
4th row서울특별시 구로구 구로동 170-5 우일이비지센터 910호
5th row서울특별시 구로구 구로동 235
ValueCountFrequency (%)
서울특별시 48
18.8%
구로구 47
18.4%
구로동 43
16.9%
552-60 4
 
1.6%
대창빌딩 4
 
1.6%
2층 4
 
1.6%
184-1 4
 
1.6%
197-28 3
 
1.2%
이앤씨벤처드림타워6차 3
 
1.2%
511-1호 3
 
1.2%
Other values (79) 92
36.1%
2024-05-11T04:41:51.453887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229
16.6%
구 138
 
10.0%
로 91
 
6.6%
1 75
 
5.4%
2 66
 
4.8%
동 50
 
3.6%
서 49
 
3.6%
울 48
 
3.5%
시 48
 
3.5%
별 48
 
3.5%
Other values (85) 538
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 807
58.5%
Decimal Number 299
 
21.7%
Space Separator 229
 
16.6%
Dash Punctuation 41
 
3.0%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 138
17.1%
로 91
 
11.3%
동 50
 
6.2%
서 49
 
6.1%
울 48
 
5.9%
시 48
 
5.9%
별 48
 
5.9%
특 48
 
5.9%
호 22
 
2.7%
차 18
 
2.2%
Other values (69) 247
30.6%
Decimal Number
ValueCountFrequency (%)
1 75
25.1%
2 66
22.1%
0 30
 
10.0%
5 25
 
8.4%
8 23
 
7.7%
7 20
 
6.7%
3 16
 
5.4%
6 16
 
5.4%
9 15
 
5.0%
4 13
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
J 1
50.0%
Space Separator
ValueCountFrequency (%)
229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 807
58.5%
Common 570
41.3%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 138
17.1%
로 91
 
11.3%
동 50
 
6.2%
서 49
 
6.1%
울 48
 
5.9%
시 48
 
5.9%
별 48
 
5.9%
특 48
 
5.9%
호 22
 
2.7%
차 18
 
2.2%
Other values (69) 247
30.6%
Common
ValueCountFrequency (%)
229
40.2%
1 75
 
13.2%
2 66
 
11.6%
- 41
 
7.2%
0 30
 
5.3%
5 25
 
4.4%
8 23
 
4.0%
7 20
 
3.5%
3 16
 
2.8%
6 16
 
2.8%
Other values (3) 29
 
5.1%
Latin
ValueCountFrequency (%)
K 1
33.3%
J 1
33.3%
n 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 807
58.5%
ASCII 573
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229
40.0%
1 75
 
13.1%
2 66
 
11.5%
- 41
 
7.2%
0 30
 
5.2%
5 25
 
4.4%
8 23
 
4.0%
7 20
 
3.5%
3 16
 
2.8%
6 16
 
2.8%
Other values (6) 32
 
5.6%
Hangul
ValueCountFrequency (%)
구 138
17.1%
로 91
 
11.3%
동 50
 
6.2%
서 49
 
6.1%
울 48
 
5.9%
시 48
 
5.9%
별 48
 
5.9%
특 48
 
5.9%
호 22
 
2.7%
차 18
 
2.2%
Other values (69) 247
30.6%

도로명주소
Text

MISSING 

Distinct29
Distinct (%)82.9%
Missing13
Missing (%)27.1%
Memory size516.0 B
2024-05-11T04:41:52.248585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length37.257143
Min length23

Characters and Unicode

Total characters1304
Distinct characters103
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)74.3%

Sample

1st row서울특별시 구로구 디지털로31길 20 (구로동)
2nd row서울특별시 구로구 디지털로 273, 401호 (구로동, 에이스트윈타워2차)
3rd row서울특별시 구로구 디지털로33길 28, 910호 (구로동, 우일이비지센터)
4th row서울특별시 구로구 경인로 576 (구로동)
5th row서울특별시 구로구 디지털로27길 24, 411호 (구로동, 벽산디지털밸리)
ValueCountFrequency (%)
서울특별시 35
 
15.3%
구로구 34
 
14.8%
구로동 32
 
14.0%
디지털로33길 7
 
3.1%
12 6
 
2.6%
2층 5
 
2.2%
디지털로31길 5
 
2.2%
공원로11길 4
 
1.7%
4 4
 
1.7%
대창빌딩 4
 
1.7%
Other values (75) 93
40.6%
2024-05-11T04:41:53.452032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
194
 
14.9%
로 103
 
7.9%
구 102
 
7.8%
1 69
 
5.3%
, 42
 
3.2%
2 39
 
3.0%
서 36
 
2.8%
) 36
 
2.8%
( 36
 
2.8%
동 36
 
2.8%
Other values (93) 611
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 758
58.1%
Decimal Number 231
 
17.7%
Space Separator 194
 
14.9%
Other Punctuation 42
 
3.2%
Close Punctuation 36
 
2.8%
Open Punctuation 36
 
2.8%
Dash Punctuation 6
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 103
 
13.6%
구 102
 
13.5%
서 36
 
4.7%
동 36
 
4.7%
울 35
 
4.6%
시 35
 
4.6%
별 35
 
4.6%
특 35
 
4.6%
지 31
 
4.1%
길 28
 
3.7%
Other values (77) 282
37.2%
Decimal Number
ValueCountFrequency (%)
1 69
29.9%
2 39
16.9%
3 33
14.3%
5 20
 
8.7%
4 18
 
7.8%
0 17
 
7.4%
6 14
 
6.1%
7 9
 
3.9%
9 6
 
2.6%
8 6
 
2.6%
Space Separator
ValueCountFrequency (%)
194
100.0%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 758
58.1%
Common 546
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 103
 
13.6%
구 102
 
13.5%
서 36
 
4.7%
동 36
 
4.7%
울 35
 
4.6%
시 35
 
4.6%
별 35
 
4.6%
특 35
 
4.6%
지 31
 
4.1%
길 28
 
3.7%
Other values (77) 282
37.2%
Common
ValueCountFrequency (%)
194
35.5%
1 69
 
12.6%
, 42
 
7.7%
2 39
 
7.1%
) 36
 
6.6%
( 36
 
6.6%
3 33
 
6.0%
5 20
 
3.7%
4 18
 
3.3%
0 17
 
3.1%
Other values (6) 42
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 758
58.1%
ASCII 546
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
194
35.5%
1 69
 
12.6%
, 42
 
7.7%
2 39
 
7.1%
) 36
 
6.6%
( 36
 
6.6%
3 33
 
6.0%
5 20
 
3.7%
4 18
 
3.3%
0 17
 
3.1%
Other values (6) 42
 
7.7%
Hangul
ValueCountFrequency (%)
로 103
 
13.6%
구 102
 
13.5%
서 36
 
4.7%
동 36
 
4.7%
울 35
 
4.6%
시 35
 
4.6%
별 35
 
4.6%
특 35
 
4.6%
지 31
 
4.1%
길 28
 
3.7%
Other values (77) 282
37.2%

도로명우편번호
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing15
Missing (%)31.2%
Memory size516.0 B
2024-05-11T04:41:54.144229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.6969697
Min length5

Characters and Unicode

Total characters188
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

Unique21 ?
Unique (%)63.6%

Sample

1st row152766
2nd row152779
3rd row152-847
4th row152862
5th row152775
ValueCountFrequency (%)
152862 4
 
12.1%
08377 3
 
9.1%
08375 3
 
9.1%
152848 2
 
6.1%
100814 1
 
3.0%
152766 1
 
3.0%
08294 1
 
3.0%
08390 1
 
3.0%
08378 1
 
3.0%
08380 1
 
3.0%
Other values (15) 15
45.5%
2024-05-11T04:41:55.376906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 36
19.1%
2 26
13.8%
7 25
13.3%
5 22
11.7%
1 21
11.2%
0 19
10.1%
3 12
 
6.4%
6 9
 
4.8%
4 8
 
4.3%
9 6
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 184
97.9%
Dash Punctuation 4
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 36
19.6%
2 26
14.1%
7 25
13.6%
5 22
12.0%
1 21
11.4%
0 19
10.3%
3 12
 
6.5%
6 9
 
4.9%
4 8
 
4.3%
9 6
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 188
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 36
19.1%
2 26
13.8%
7 25
13.3%
5 22
11.7%
1 21
11.2%
0 19
10.1%
3 12
 
6.4%
6 9
 
4.8%
4 8
 
4.3%
9 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 188
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 36
19.1%
2 26
13.8%
7 25
13.3%
5 22
11.7%
1 21
11.2%
0 19
10.1%
3 12
 
6.4%
6 9
 
4.8%
4 8
 
4.3%
9 6
 
3.2%

사업장명
Text

Distinct37
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-05-11T04:41:56.205247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.9791667
Min length5

Characters and Unicode

Total characters431
Distinct characters105
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)62.5%

Sample

1st row(주)에코빅
2nd row한성크린텍(주)
3rd row유니엔스(주)
4th row블루버드환경(주)
5th row제일종합기술(주)
ValueCountFrequency (%)
주)재성환경 4
 
7.7%
주)우림환경엔지니어링 3
 
5.8%
주식회사 3
 
5.8%
주)엑사이엔씨 3
 
5.8%
한성크린텍(주 2
 
3.8%
지에스네오텍(주 2
 
3.8%
주)광일종합프랜트 2
 
3.8%
웰크론강원 2
 
3.8%
우진에너지(주 1
 
1.9%
에스지신성건설주식회사 1
 
1.9%
Other values (29) 29
55.8%
2024-05-11T04:41:57.382307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 47
 
10.9%
( 42
 
9.7%
) 42
 
9.7%
엔 14
 
3.2%
지 14
 
3.2%
에 11
 
2.6%
환 10
 
2.3%
경 10
 
2.3%
스 9
 
2.1%
사 9
 
2.1%
Other values (95) 223
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 341
79.1%
Open Punctuation 42
 
9.7%
Close Punctuation 42
 
9.7%
Space Separator 4
 
0.9%
Decimal Number 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 47
 
13.8%
엔 14
 
4.1%
지 14
 
4.1%
에 11
 
3.2%
환 10
 
2.9%
경 10
 
2.9%
스 9
 
2.6%
사 9
 
2.6%
이 8
 
2.3%
성 8
 
2.3%
Other values (90) 201
58.9%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 341
79.1%
Common 90
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 47
 
13.8%
엔 14
 
4.1%
지 14
 
4.1%
에 11
 
3.2%
환 10
 
2.9%
경 10
 
2.9%
스 9
 
2.6%
사 9
 
2.6%
이 8
 
2.3%
성 8
 
2.3%
Other values (90) 201
58.9%
Common
ValueCountFrequency (%)
( 42
46.7%
) 42
46.7%
4
 
4.4%
2 1
 
1.1%
1 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 341
79.1%
ASCII 90
 
20.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 47
 
13.8%
엔 14
 
4.1%
지 14
 
4.1%
에 11
 
3.2%
환 10
 
2.9%
경 10
 
2.9%
스 9
 
2.6%
사 9
 
2.6%
이 8
 
2.3%
성 8
 
2.3%
Other values (90) 201
58.9%
ASCII
ValueCountFrequency (%)
( 42
46.7%
) 42
46.7%
4
 
4.4%
2 1
 
1.1%
1 1
 
1.1%

최종수정일자
Date

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2015-07-23 13:53:41
Maximum2024-04-18 17:44:58
2024-05-11T04:41:57.898345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:41:58.378109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
U
26 
I
22 

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 26
54.2%
I 22
45.8%

Length

2024-05-11T04:41:58.966335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:41:59.666901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 26
54.2%
i 22
45.8%

데이터갱신일자
Date

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
Minimum2019-03-30 02:20:09
Maximum2023-12-03 22:00:00
2024-05-11T04:42:00.129686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:42:00.696097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

업태구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing47
Missing (%)97.9%
Memory size516.0 B
2024-05-11T04:42:01.207071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters16
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row기타 건물건설관련 전문 공사업
ValueCountFrequency (%)
기타 1
25.0%
건물건설관련 1
25.0%
전문 1
25.0%
공사업 1
25.0%
2024-05-11T04:42:02.126189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
18.8%
건 2
12.5%
기 1
 
6.2%
타 1
 
6.2%
물 1
 
6.2%
설 1
 
6.2%
관 1
 
6.2%
련 1
 
6.2%
전 1
 
6.2%
문 1
 
6.2%
Other values (3) 3
18.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
81.2%
Space Separator 3
 
18.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
건 2
15.4%
기 1
7.7%
타 1
7.7%
물 1
7.7%
설 1
7.7%
관 1
7.7%
련 1
7.7%
전 1
7.7%
문 1
7.7%
공 1
7.7%
Other values (2) 2
15.4%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
81.2%
Common 3
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
건 2
15.4%
기 1
7.7%
타 1
7.7%
물 1
7.7%
설 1
7.7%
관 1
7.7%
련 1
7.7%
전 1
7.7%
문 1
7.7%
공 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
81.2%
ASCII 3
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3
100.0%
Hangul
ValueCountFrequency (%)
건 2
15.4%
기 1
7.7%
타 1
7.7%
물 1
7.7%
설 1
7.7%
관 1
7.7%
련 1
7.7%
전 1
7.7%
문 1
7.7%
공 1
7.7%
Other values (2) 2
15.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)69.6%
Missing2
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean190382.6
Minimum183644.17
Maximum197531.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-11T04:42:02.477240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183644.17
5-th percentile189448.24
Q1190123.65
median190510.49
Q3190686.69
95-th percentile190871.05
Maximum197531.5
Range13887.329
Interquartile range (IQR)563.04703

Descriptive statistics

Standard deviation1554.2467
Coefficient of variation (CV)0.0081638067
Kurtosis17.297464
Mean190382.6
Median Absolute Deviation (MAD)230.66854
Skewness0.26631696
Sum8757599.6
Variance2415682.9
MonotonicityNot monotonic
2024-05-11T04:42:02.904605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
189965.688330036 4
 
8.3%
190741.158117503 4
 
8.3%
190447.24866829 3
 
6.2%
190493.215596281 2
 
4.2%
190565.126077805 2
 
4.2%
190666.864354145 2
 
4.2%
190822.851419439 2
 
4.2%
189448.242617296 2
 
4.2%
190680.536850936 2
 
4.2%
189851.590964125 1
 
2.1%
Other values (22) 22
45.8%
(Missing) 2
 
4.2%
ValueCountFrequency (%)
183644.168046816 1
 
2.1%
187918.667297764 1
 
2.1%
189448.242617296 2
4.2%
189745.929883088 1
 
2.1%
189851.590964125 1
 
2.1%
189943.958564583 1
 
2.1%
189965.688330036 4
8.3%
190107.045415333 1
 
2.1%
190173.455 1
 
2.1%
190233.906023967 1
 
2.1%
ValueCountFrequency (%)
197531.497488927 1
 
2.1%
191020.264430044 1
 
2.1%
190887.117653337 1
 
2.1%
190822.851419439 2
4.2%
190776.468544178 1
 
2.1%
190741.158117503 4
8.3%
190734.812272237 1
 
2.1%
190688.747501289 1
 
2.1%
190680.536850936 2
4.2%
190676.946162959 1
 
2.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)69.6%
Missing2
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean443263.2
Minimum442071.45
Maximum451068.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-05-11T04:42:03.323260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442071.45
5-th percentile442253.13
Q1442392.65
median442661.05
Q3443915.52
95-th percentile445007.38
Maximum451068.83
Range8997.3781
Interquartile range (IQR)1522.8795

Descriptive statistics

Standard deviation1505.7521
Coefficient of variation (CV)0.0033969707
Kurtosis15.441567
Mean443263.2
Median Absolute Deviation (MAD)357.50875
Skewness3.3250191
Sum20390107
Variance2267289.3
MonotonicityNot monotonic
2024-05-11T04:42:03.734403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
444628.911198986 4
 
8.3%
442703.311770946 4
 
8.3%
442558.310755613 3
 
6.2%
442301.849150765 2
 
4.2%
442423.390398015 2
 
4.2%
442750.016695612 2
 
4.2%
442253.132895893 2
 
4.2%
444598.488329138 2
 
4.2%
442392.645303533 2
 
4.2%
443550.958203462 1
 
2.1%
Other values (22) 22
45.8%
(Missing) 2
 
4.2%
ValueCountFrequency (%)
442071.447779897 1
2.1%
442113.916061607 1
2.1%
442253.132895893 2
4.2%
442261.654499191 1
2.1%
442301.849150765 2
4.2%
442305.230860115 1
2.1%
442324.745872584 1
2.1%
442368.090413171 1
2.1%
442370.143700207 1
2.1%
442392.645303533 2
4.2%
ValueCountFrequency (%)
451068.82589543 1
 
2.1%
445157.626366229 1
 
2.1%
445133.538343434 1
 
2.1%
444628.911198986 4
8.3%
444598.488329138 2
4.2%
444244.808913646 1
 
2.1%
444219.7107371 1
 
2.1%
443953.502895004 1
 
2.1%
443801.5906166 1
 
2.1%
443642.42 1
 
2.1%

실험실면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
0
5 

Length

Max length4
Median length4
Mean length3.6875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
0 5
 
10.4%

Length

2024-05-11T04:42:04.208002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:04.514293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
0 5
 
10.4%

사업장구분명
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
환경전문공사업
33 
<NA>
15 

Length

Max length7
Median length7
Mean length6.0625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 33
68.8%
<NA> 15
31.2%

Length

2024-05-11T04:42:04.920265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:05.319820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 33
68.8%
na 15
31.2%

영업소면적
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
40 
0
5 
35
 
1
17966
 
1
129
 
1

Length

Max length5
Median length4
Mean length3.6458333
Min length1

Unique

Unique3 ?
Unique (%)6.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 40
83.3%
0 5
 
10.4%
35 1
 
2.1%
17966 1
 
2.1%
129 1
 
2.1%

Length

2024-05-11T04:42:05.802799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:06.170353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
83.3%
0 5
 
10.4%
35 1
 
2.1%
17966 1
 
2.1%
129 1
 
2.1%

위탁업체명
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing42
Missing (%)87.5%
Memory size516.0 B
2024-05-11T04:42:06.533601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length8.1666667
Min length7

Characters and Unicode

Total characters49
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row(주)청명기연환경
2nd row한국에너지환경(주)
3rd row(주)청명기연환경
4th row(주)청룡환경
5th row(주)청룡환경
ValueCountFrequency (%)
주)청명기연환경 2
33.3%
주)청룡환경 2
33.3%
한국에너지환경(주 1
16.7%
주)대일환경 1
16.7%
2024-05-11T04:42:07.487130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 6
12.2%
환 6
12.2%
주 6
12.2%
경 6
12.2%
) 6
12.2%
청 4
8.2%
명 2
 
4.1%
기 2
 
4.1%
연 2
 
4.1%
룡 2
 
4.1%
Other values (7) 7
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
75.5%
Open Punctuation 6
 
12.2%
Close Punctuation 6
 
12.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
환 6
16.2%
주 6
16.2%
경 6
16.2%
청 4
10.8%
명 2
 
5.4%
기 2
 
5.4%
연 2
 
5.4%
룡 2
 
5.4%
한 1
 
2.7%
국 1
 
2.7%
Other values (5) 5
13.5%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37
75.5%
Common 12
 
24.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
환 6
16.2%
주 6
16.2%
경 6
16.2%
청 4
10.8%
명 2
 
5.4%
기 2
 
5.4%
연 2
 
5.4%
룡 2
 
5.4%
한 1
 
2.7%
국 1
 
2.7%
Other values (5) 5
13.5%
Common
ValueCountFrequency (%)
( 6
50.0%
) 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37
75.5%
ASCII 12
 
24.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 6
50.0%
) 6
50.0%
Hangul
ValueCountFrequency (%)
환 6
16.2%
주 6
16.2%
경 6
16.2%
청 4
10.8%
명 2
 
5.4%
기 2
 
5.4%
연 2
 
5.4%
룡 2
 
5.4%
한 1
 
2.7%
국 1
 
2.7%
Other values (5) 5
13.5%

실험실지역코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
42 
1153010200
5 
1156011400
 
1

Length

Max length10
Median length4
Mean length4.75
Min length4

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row<NA>
2nd row1153010200
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
87.5%
1153010200 5
 
10.4%
1156011400 1
 
2.1%

Length

2024-05-11T04:42:07.995265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:08.332991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
87.5%
1153010200 5
 
10.4%
1156011400 1
 
2.1%

실험실우편번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
45 
152790
 
1
152848
 
1
150044
 
1

Length

Max length6
Median length4
Mean length4.125
Min length4

Unique

Unique3 ?
Unique (%)6.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
93.8%
152790 1
 
2.1%
152848 1
 
2.1%
150044 1
 
2.1%

Length

2024-05-11T04:42:08.774334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:09.145264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
93.8%
152790 1
 
2.1%
152848 1
 
2.1%
150044 1
 
2.1%

실험실산
Categorical

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
42 
1
6 

Length

Max length4
Median length4
Mean length3.625
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
87.5%
1 6
 
12.5%

Length

2024-05-11T04:42:09.409131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:09.687943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
87.5%
1 6
 
12.5%

실험실번지
Categorical

IMBALANCE 

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
184
 
1
588
 
1
197
 
1
222
 
1

Length

Max length4
Median length4
Mean length3.875
Min length2

Unique

Unique5 ?
Unique (%)10.4%

Sample

1st row<NA>
2nd row184
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
184 1
 
2.1%
588 1
 
2.1%
197 1
 
2.1%
222 1
 
2.1%
32 1
 
2.1%

Length

2024-05-11T04:42:10.060837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:10.391064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
184 1
 
2.1%
588 1
 
2.1%
197 1
 
2.1%
222 1
 
2.1%
32 1
 
2.1%

실험실호
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
44 
1
 
1
7
 
1
31
 
1
47
 
1

Length

Max length4
Median length4
Mean length3.7916667
Min length1

Unique

Unique4 ?
Unique (%)8.3%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 44
91.7%
1 1
 
2.1%
7 1
 
2.1%
31 1
 
2.1%
47 1
 
2.1%

Length

2024-05-11T04:42:10.751436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:11.053104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 44
91.7%
1 1
 
2.1%
7 1
 
2.1%
31 1
 
2.1%
47 1
 
2.1%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

실험실특수주소
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing43
Missing (%)89.6%
Memory size516.0 B
2024-05-11T04:42:11.426339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.4
Min length7

Characters and Unicode

Total characters52
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row우림 이비지센터2차
2nd row대륭포스트타워1차 15층
3rd row에이스타워2차
4th row지플러스코오롱디지털타워
5th row한국에너지환경(주)
ValueCountFrequency (%)
우림 1
14.3%
이비지센터2차 1
14.3%
대륭포스트타워1차 1
14.3%
15층 1
14.3%
에이스타워2차 1
14.3%
지플러스코오롱디지털타워 1
14.3%
한국에너지환경(주 1
14.3%
2024-05-11T04:42:12.333924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 4
 
7.7%
타 3
 
5.8%
차 3
 
5.8%
워 3
 
5.8%
스 3
 
5.8%
2
 
3.8%
이 2
 
3.8%
에 2
 
3.8%
2 2
 
3.8%
1 2
 
3.8%
Other values (26) 26
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43
82.7%
Decimal Number 5
 
9.6%
Space Separator 2
 
3.8%
Open Punctuation 1
 
1.9%
Close Punctuation 1
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4
 
9.3%
타 3
 
7.0%
차 3
 
7.0%
워 3
 
7.0%
스 3
 
7.0%
이 2
 
4.7%
에 2
 
4.7%
우 1
 
2.3%
롱 1
 
2.3%
디 1
 
2.3%
Other values (20) 20
46.5%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 2
40.0%
5 1
20.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43
82.7%
Common 9
 
17.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4
 
9.3%
타 3
 
7.0%
차 3
 
7.0%
워 3
 
7.0%
스 3
 
7.0%
이 2
 
4.7%
에 2
 
4.7%
우 1
 
2.3%
롱 1
 
2.3%
디 1
 
2.3%
Other values (20) 20
46.5%
Common
ValueCountFrequency (%)
2
22.2%
2 2
22.2%
1 2
22.2%
( 1
11.1%
5 1
11.1%
) 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43
82.7%
ASCII 9
 
17.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 4
 
9.3%
타 3
 
7.0%
차 3
 
7.0%
워 3
 
7.0%
스 3
 
7.0%
이 2
 
4.7%
에 2
 
4.7%
우 1
 
2.3%
롱 1
 
2.3%
디 1
 
2.3%
Other values (20) 20
46.5%
ASCII
ValueCountFrequency (%)
2
22.2%
2 2
22.2%
1 2
22.2%
( 1
11.1%
5 1
11.1%
) 1
11.1%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

실험실특수주소호
Categorical

IMBALANCE 

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
45 
713
 
1
401
 
1
1708
 
1

Length

Max length4
Median length4
Mean length3.9583333
Min length3

Unique

Unique3 ?
Unique (%)6.2%

Sample

1st row<NA>
2nd row713
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 45
93.8%
713 1
 
2.1%
401 1
 
2.1%
1708 1
 
2.1%

Length

2024-05-11T04:42:12.704882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:12.957210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
93.8%
713 1
 
2.1%
401 1
 
2.1%
1708 1
 
2.1%

실험실도로명주소시군구코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
11530
5 

Length

Max length5
Median length4
Mean length4.1041667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11530
2nd row11530
3rd row11530
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
11530 5
 
10.4%

Length

2024-05-11T04:42:13.277467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:13.592778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
11530 5
 
10.4%

실험실도로명주소읍면동코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
1153010200
5 

Length

Max length10
Median length4
Mean length4.625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1153010200
2nd row1153010200
3rd row1153010200
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
1153010200 5
 
10.4%

Length

2024-05-11T04:42:13.953039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:14.354692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
1153010200 5
 
10.4%

실험실도로명주소읍면동구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
1
5 

Length

Max length4
Median length4
Mean length3.6875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
1 5
 
10.4%

Length

2024-05-11T04:42:14.783587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:15.096397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
1 5
 
10.4%

실험실도로명주소코드
Categorical

IMBALANCE 

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
4148335
 
1
4148340
 
1
3000026
 
1
3000028
 
1

Length

Max length7
Median length4
Mean length4.3125
Min length4

Unique

Unique5 ?
Unique (%)10.4%

Sample

1st row4148335
2nd row4148340
3rd row3000026
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
4148335 1
 
2.1%
4148340 1
 
2.1%
3000026 1
 
2.1%
3000028 1
 
2.1%
4148327 1
 
2.1%

Length

2024-05-11T04:42:15.459528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:15.859356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
4148335 1
 
2.1%
4148340 1
 
2.1%
3000026 1
 
2.1%
3000028 1
 
2.1%
4148327 1
 
2.1%

실험실도로명특수주소
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing43
Missing (%)89.6%
Memory size516.0 B
2024-05-11T04:42:16.170501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length15.6
Min length5

Characters and Unicode

Total characters78
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row(구로동)
2nd row713호 (구로동, 우림 이비지센터2차)
3rd row401호 (구로동, 에이스트윈타워2차)
4th row(구로동)
5th row1708호 (구로동, 지플러스코오롱디지털타워)
ValueCountFrequency (%)
구로동 5
41.7%
713호 1
 
8.3%
우림 1
 
8.3%
이비지센터2차 1
 
8.3%
401호 1
 
8.3%
에이스트윈타워2차 1
 
8.3%
1708호 1
 
8.3%
지플러스코오롱디지털타워 1
 
8.3%
2024-05-11T04:42:16.989184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
9.0%
( 5
 
6.4%
로 5
 
6.4%
동 5
 
6.4%
) 5
 
6.4%
구 5
 
6.4%
지 3
 
3.8%
1 3
 
3.8%
호 3
 
3.8%
, 3
 
3.8%
Other values (26) 34
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
59.0%
Decimal Number 12
 
15.4%
Space Separator 7
 
9.0%
Open Punctuation 5
 
6.4%
Close Punctuation 5
 
6.4%
Other Punctuation 3
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 5
 
10.9%
동 5
 
10.9%
구 5
 
10.9%
지 3
 
6.5%
호 3
 
6.5%
워 2
 
4.3%
타 2
 
4.3%
스 2
 
4.3%
차 2
 
4.3%
이 2
 
4.3%
Other values (15) 15
32.6%
Decimal Number
ValueCountFrequency (%)
1 3
25.0%
0 2
16.7%
2 2
16.7%
7 2
16.7%
8 1
 
8.3%
3 1
 
8.3%
4 1
 
8.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46
59.0%
Common 32
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 5
 
10.9%
동 5
 
10.9%
구 5
 
10.9%
지 3
 
6.5%
호 3
 
6.5%
워 2
 
4.3%
타 2
 
4.3%
스 2
 
4.3%
차 2
 
4.3%
이 2
 
4.3%
Other values (15) 15
32.6%
Common
ValueCountFrequency (%)
7
21.9%
( 5
15.6%
) 5
15.6%
1 3
9.4%
, 3
9.4%
0 2
 
6.2%
2 2
 
6.2%
7 2
 
6.2%
8 1
 
3.1%
3 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46
59.0%
ASCII 32
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
21.9%
( 5
15.6%
) 5
15.6%
1 3
9.4%
, 3
9.4%
0 2
 
6.2%
2 2
 
6.2%
7 2
 
6.2%
8 1
 
3.1%
3 1
 
3.1%
Hangul
ValueCountFrequency (%)
로 5
 
10.9%
동 5
 
10.9%
구 5
 
10.9%
지 3
 
6.5%
호 3
 
6.5%
워 2
 
4.3%
타 2
 
4.3%
스 2
 
4.3%
차 2
 
4.3%
이 2
 
4.3%
Other values (15) 15
32.6%

실험실도로명주소건물층구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
0
5 

Length

Max length4
Median length4
Mean length3.6875
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
0 5
 
10.4%

Length

2024-05-11T04:42:17.450623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:17.796189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
0 5
 
10.4%

실험실도로명주소건물본번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
43 
20
 
1
12
 
1
273
 
1
576
 
1

Length

Max length4
Median length4
Mean length3.8541667
Min length2

Unique

Unique5 ?
Unique (%)10.4%

Sample

1st row20
2nd row12
3rd row273
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 43
89.6%
20 1
 
2.1%
12 1
 
2.1%
273 1
 
2.1%
576 1
 
2.1%
123 1
 
2.1%

Length

2024-05-11T04:42:18.164678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:18.561459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 43
89.6%
20 1
 
2.1%
12 1
 
2.1%
273 1
 
2.1%
576 1
 
2.1%
123 1
 
2.1%

실험실도로명주소건물부번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

실험실도로명주소우편번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
<NA>
47 
152766
 
1

Length

Max length6
Median length4
Mean length4.0416667
Min length4

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row152766
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 47
97.9%
152766 1
 
2.1%

Length

2024-05-11T04:42:19.005797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:19.369807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
97.9%
152766 1
 
2.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
0316000031600006719910000319910613<NA>3폐업2폐업<NA><NA><NA><NA>0221095741<NA><NA>서울특별시 구로구 구로동 197-22 에이스테크노타워5차 508호서울특별시 구로구 디지털로31길 20 (구로동)152766(주)에코빅2018-11-19 17:42:14I2019-03-30 02:20:09.0<NA>190571.928128442598.144799<NA>환경전문공사업<NA>(주)청명기연환경<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11530115301020014148335(구로동)020<NA>152766
1316000031600006719910000419910925<NA>1영업/정상BBBB영업<NA><NA><NA><NA>028903905<NA><NA>서울특별시 구로구 구로동 184-1 우림 이비지센터2차 713호<NA><NA>한성크린텍(주)2019-12-16 11:39:19U2019-12-18 02:40:00.0<NA>190741.158118442703.311771<NA>환경전문공사업<NA><NA>1153010200<NA>11841<NA><NA>우림 이비지센터2차<NA>71311530115301020014148340713호 (구로동, 우림 이비지센터2차)012<NA><NA>
2316000031600006719920010019920602<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-859-2527<NA><NA>서울특별시 구로구 구로동 212-30 에이스트윈타워2차 401호서울특별시 구로구 디지털로 273, 401호 (구로동, 에이스트윈타워2차)152779유니엔스(주)2018-09-13 13:11:45I2019-03-30 02:20:09.0<NA>190565.126078442423.390398<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>11530115301020013000026401호 (구로동, 에이스트윈타워2차)0273<NA><NA>
331600003160000671998000011998-10-31<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2108-1151<NA><NA>서울특별시 구로구 구로동 170-5 우일이비지센터 910호서울특별시 구로구 디지털로33길 28, 910호 (구로동, 우일이비지센터)152-847블루버드환경(주)2024-04-18 17:44:50U2023-12-03 22:00:00.0<NA>190666.864354442750.016696<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4316000031600006719990000119991129<NA>3폐업2폐업20111219<NA><NA><NA>21088800<NA><NA>서울특별시 구로구 구로동 235<NA><NA>제일종합기술(주)2015-07-23 14:00:49I2019-03-30 02:20:09.0<NA>190594.904646442261.654499<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5316000031600006720000000820001031<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0226305676<NA><NA>서울특별시 구로구 구로동 588서울특별시 구로구 경인로 576 (구로동)152862지에스네오텍(주)2016-01-26 10:27:18I2019-03-30 02:20:09.0<NA>189448.242617444598.488329<NA>환경전문공사업<NA><NA>1153010200<NA>1588<NA><NA><NA><NA><NA><NA>11530115301020013000028(구로동)0576<NA><NA>
6316000031600006720010000320011220<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0226012612<NA>152775서울특별시 구로구 구로동 212-16 벽산디지털밸리 411호서울특별시 구로구 디지털로27길 24, 411호 (구로동, 벽산디지털밸리)152775(주)두합크린텍2015-07-23 15:42:27I2019-03-30 02:20:09.0<NA>190461.790473442368.090413<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7316000031600006720040001220041215<NA>3폐업2폐업20141128<NA><NA><NA>0232895266<NA><NA>서울특별시 구로구 구로동 212-8 대륭포스트타워1차 15층<NA><NA>(주)엑사이엔씨2015-07-23 13:56:24I2019-03-30 02:20:09.0<NA>190680.536851442392.645304<NA>환경전문공사업<NA><NA>11530102001527901<NA><NA><NA><NA>대륭포스트타워1차 15층<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831600003160000672005000132005-04-26<NA>1영업/정상BBBB영업<NA><NA><NA><NA>028520801<NA><NA>서울특별시 구로구 구로동 552-60 대창빌딩 2층서울특별시 구로구 공원로11길 4, 2층 (구로동, 대창빌딩)152-862(주)재성환경2023-08-25 17:52:31U2022-12-07 22:07:00.0<NA>189965.68833444628.911199<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9316000031600006720060001520060626<NA>3폐업2폐업20150511<NA><NA><NA>20251900<NA><NA>서울특별시 구로구 구로동 271 벽산3차디지털밸리 1201외호<NA><NA>(주)웹솔루스2015-07-23 13:53:41I2019-03-30 02:20:09.0<NA><NA><NA><NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
38316000031600006720190000220190730<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-850-3103<NA><NA>서울특별시 구로구 구로동 811 코오롱싸이언스밸리2차서울특별시 구로구 디지털로34길 55, 코오롱싸이언스밸리2차 14층 1414,1415호 (구로동)08378(주)에코센스2020-12-15 16:39:17U2020-12-17 02:40:00.0<NA>191020.26443442460.919022<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
39316000031600006720200000120200316<NA>3폐업2폐업20211117<NA><NA><NA>02-588-0365<NA><NA>서울특별시 구로구 구로동 222-3 제이앤케이디지털타워 607호서울특별시 구로구 디지털로26길 111, 제이앤케이디지털타워 607호 (구로동)08390에너지관리기술(주)2021-11-18 15:14:44U2021-11-20 02:40:00.0<NA>190822.851419442253.1328960환경전문공사업0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
40316000031600006720200000220200427<NA>3폐업2폐업20210311<NA><NA><NA>02-890-3950<NA><NA>서울특별시 구로구 구로동 184-1 우림이비지센터2차 604,6호서울특별시 구로구 디지털로33길 12, 우림이비지센터2차 604,605호 (구로동)08377네오엔비텍주식회사2021-03-11 14:52:36U2021-03-13 02:40:00.0<NA>190741.158118442703.311771<NA>환경전문공사업<NA>(주)청룡환경<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
41316000031600006720200000320200910<NA>1영업/정상BBBB영업<NA><NA><NA><NA>028520801<NA><NA>서울특별시 구로구 구로동 552-60 대창빌딩 2층서울특별시 구로구 공원로11길 4, 2층 (구로동, 대창빌딩)152862(주)재성환경2021-12-30 16:58:50U2022-01-01 02:40:00.0<NA>189965.68833444628.9111990환경전문공사업0(주)대일환경<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
42316000031600006720200000420201028<NA>3폐업2폐업20221116<NA><NA><NA>02-866-3639<NA><NA>서울특별시 구로구 구로동 197-28 이앤씨벤처드림타워6차 511-1호서울특별시 구로구 디지털로31길 41, 이앤씨벤처드림타워6차 5층 511-1호 (구로동)08375(주)우림환경엔지니어링2022-11-16 18:52:10U2021-10-31 23:08:00.0<NA>190447.248668442558.310756<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
43316000031600006720200000520201204<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 184-1서울특별시 구로구 디지털로33길 12 (구로동)<NA>한성크린텍(주)2021-07-20 13:59:19U2021-07-22 02:40:00.0<NA>190741.158118442703.3117710환경전문공사업0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
44316000031600006720220000120220817<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6330-25020<NA><NA>서울특별시 구로구 구로동 197-10 이앤씨벤처드림타워2차서울특별시 구로구 디지털로33길 55, 이앤씨벤처드림타워2차 901호 (구로동)08376(주)지오그린212023-01-20 10:06:18U2022-11-30 22:02:00.0<NA>190479.902194442751.41954<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4531600003160000672022000022022-09-07<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-890-3591<NA><NA>서울특별시 구로구 구로동 184-1 우림이비지센터2차서울특별시 구로구 디지털로33길 12, 우림이비지센터2차 501호 (구로동)08377동문이엔티(주)2024-04-18 17:44:58U2023-12-03 22:00:00.0<NA>190741.158118442703.311771<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4631600003160000672023000012023-03-03<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-866-3639<NA><NA>서울특별시 구로구 구로동 197-28 이앤씨벤처드림타워6차 511-1호서울특별시 구로구 디지털로31길 41, 이앤씨벤처드림타워6차 5층 511-1호 (구로동)08375(주)우림환경엔지니어링2023-03-03 16:57:20I2022-12-03 00:05:00.0<NA>190447.248668442558.310756<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4731600003160000672023000022023-03-03<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-866-3639<NA><NA>서울특별시 구로구 구로동 197-28 이앤씨벤처드림타워6차 511-1호서울특별시 구로구 디지털로31길 41, 이앤씨벤처드림타워6차 5층 511-1호 (구로동)08375(주)우림환경엔지니어링2023-05-04 10:56:58U2022-12-05 00:07:00.0<NA>190447.248668442558.310756<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>