Overview

Dataset statistics

Number of variables48
Number of observations22
Missing cells333
Missing cells (%)31.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory422.0 B

Variable types

Categorical22
Numeric5
DateTime3
Unsupported10
Text8

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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-19502/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
실험실특수주소 has constant value ""Constant
실험실지역코드 is highly imbalanced (54.9%)Imbalance
실험실우편번호 is highly imbalanced (66.5%)Imbalance
실험실번지 is highly imbalanced (54.9%)Imbalance
실험실호 is highly imbalanced (60.5%)Imbalance
실험실도로명주소읍면동코드 is highly imbalanced (54.9%)Imbalance
실험실도로명주소코드 is highly imbalanced (54.9%)Imbalance
실험실도로명주소건물본번호 is highly imbalanced (54.9%)Imbalance
실험실도로명주소건물부번호 is highly imbalanced (73.3%)Imbalance
실험실도로명주소우편번호 is highly imbalanced (66.5%)Imbalance
인허가취소일자 has 22 (100.0%) missing valuesMissing
폐업일자 has 13 (59.1%) missing valuesMissing
휴업시작일자 has 22 (100.0%) missing valuesMissing
휴업종료일자 has 22 (100.0%) missing valuesMissing
재개업일자 has 22 (100.0%) missing valuesMissing
전화번호 has 2 (9.1%) missing valuesMissing
소재지면적 has 22 (100.0%) missing valuesMissing
소재지우편번호 has 22 (100.0%) missing valuesMissing
도로명주소 has 8 (36.4%) missing valuesMissing
도로명우편번호 has 8 (36.4%) missing valuesMissing
업태구분명 has 21 (95.5%) missing valuesMissing
좌표정보(X) has 1 (4.5%) missing valuesMissing
좌표정보(Y) has 1 (4.5%) missing valuesMissing
위탁업체명 has 20 (90.9%) missing valuesMissing
실험실통 has 22 (100.0%) missing valuesMissing
실험실반 has 22 (100.0%) missing valuesMissing
실험실특수주소 has 21 (95.5%) missing valuesMissing
실험실특수주소동 has 22 (100.0%) missing valuesMissing
실험실특수주소호 has 22 (100.0%) missing valuesMissing
실험실도로명특수주소 has 18 (81.8%) 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
소재지우편번호 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
실험실특수주소호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 18:35:22.465004
Analysis finished2024-04-17 18:35:22.868323
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
3000000
22 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 22
100.0%

Length

2024-04-18T03:35:22.914321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:22.985629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 22
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0000007 × 1017
Minimum3.0000007 × 1017
Maximum3.0000007 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T03:35:23.057745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000007 × 1017
5-th percentile3.0000007 × 1017
Q13.0000007 × 1017
median3.0000007 × 1017
Q33.0000007 × 1017
95-th percentile3.0000007 × 1017
Maximum3.0000007 × 1017
Range1900002
Interquartile range (IQR)550016

Descriptive statistics

Standard deviation490280.75
Coefficient of variation (CV)1.6342688 × 10-12
Kurtosis0.2452337
Mean3.0000007 × 1017
Median Absolute Deviation (MAD)200000
Skewness0.058991989
Sum6.6000015 × 1018
Variance2.4037521 × 1011
MonotonicityStrictly increasing
2024-04-18T03:35:23.150637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
300000067200200003 1
 
4.5%
300000067201300002 1
 
4.5%
300000067202100005 1
 
4.5%
300000067202100004 1
 
4.5%
300000067202100003 1
 
4.5%
300000067202100002 1
 
4.5%
300000067202100001 1
 
4.5%
300000067201700001 1
 
4.5%
300000067201500001 1
 
4.5%
300000067201400002 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
300000067200200003 1
4.5%
300000067201000001 1
4.5%
300000067201000002 1
4.5%
300000067201000003 1
4.5%
300000067201100001 1
4.5%
300000067201100002 1
4.5%
300000067201100003 1
4.5%
300000067201100004 1
4.5%
300000067201100005 1
4.5%
300000067201100006 1
4.5%
ValueCountFrequency (%)
300000067202100005 1
4.5%
300000067202100004 1
4.5%
300000067202100003 1
4.5%
300000067202100002 1
4.5%
300000067202100001 1
4.5%
300000067201700001 1
4.5%
300000067201500001 1
4.5%
300000067201400002 1
4.5%
300000067201400001 1
4.5%
300000067201300002 1
4.5%

인허가일자
Date

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2002-01-11 00:00:00
Maximum2021-12-02 00:00:00
2024-04-18T03:35:23.237428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:35:23.355239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
11 
3
9 
4
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 11
50.0%
3 9
40.9%
4 2
 
9.1%

Length

2024-04-18T03:35:23.462953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:23.536941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
50.0%
3 9
40.9%
4 2
 
9.1%

영업상태명
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
영업/정상
11 
폐업
9 
취소/말소/만료/정지/중지
2 

Length

Max length14
Median length9.5
Mean length4.5909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row폐업
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 11
50.0%
폐업 9
40.9%
취소/말소/만료/정지/중지 2
 
9.1%

Length

2024-04-18T03:35:23.620856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:23.700164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 11
50.0%
폐업 9
40.9%
취소/말소/만료/정지/중지 2
 
9.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
BBBB
11 
2
9 
4
2 

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row2
4th row2
5th rowBBBB

Common Values

ValueCountFrequency (%)
BBBB 11
50.0%
2 9
40.9%
4 2
 
9.1%

Length

2024-04-18T03:35:23.790126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:23.877081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 11
50.0%
2 9
40.9%
4 2
 
9.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
영업
11 
폐업
9 
폐쇄
2 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 11
50.0%
폐업 9
40.9%
폐쇄 2
 
9.1%

Length

2024-04-18T03:35:23.961496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:24.034543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 11
50.0%
폐업 9
40.9%
폐쇄 2
 
9.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)88.9%
Missing13
Missing (%)59.1%
Infinite0
Infinite (%)0.0%
Mean20188312
Minimum20130212
Maximum20230126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T03:35:24.106610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130212
5-th percentile20138609
Q120180308
median20180918
Q320220404
95-th percentile20226566
Maximum20230126
Range99914
Interquartile range (IQR)40096

Descriptive statistics

Standard deviation33421.654
Coefficient of variation (CV)0.0016554952
Kurtosis-0.57566902
Mean20188312
Median Absolute Deviation (MAD)29714
Skewness-0.45286388
Sum1.8169481 × 108
Variance1.1170069 × 109
MonotonicityNot monotonic
2024-04-18T03:35:24.186064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20180308 2
 
9.1%
20180918 1
 
4.5%
20151204 1
 
4.5%
20130212 1
 
4.5%
20220404 1
 
4.5%
20200102 1
 
4.5%
20221226 1
 
4.5%
20230126 1
 
4.5%
(Missing) 13
59.1%
ValueCountFrequency (%)
20130212 1
4.5%
20151204 1
4.5%
20180308 2
9.1%
20180918 1
4.5%
20200102 1
4.5%
20220404 1
4.5%
20221226 1
4.5%
20230126 1
4.5%
ValueCountFrequency (%)
20230126 1
4.5%
20221226 1
4.5%
20220404 1
4.5%
20200102 1
4.5%
20180918 1
4.5%
20180308 2
9.1%
20151204 1
4.5%
20130212 1
4.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

전화번호
Text

MISSING 

Distinct18
Distinct (%)90.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-04-18T03:35:24.336199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8
Min length7

Characters and Unicode

Total characters196
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

Unique16 ?
Unique (%)80.0%

Sample

1st row027402436
2nd row7197452
3rd row0263511960
4th row02-746-2762
5th row7355249
ValueCountFrequency (%)
7355249 2
 
10.0%
02-3700-8509 2
 
10.0%
027402436 1
 
5.0%
32103050 1
 
5.0%
02-370-8509 1
 
5.0%
2011-7446 1
 
5.0%
032-340-8114 1
 
5.0%
0221341935 1
 
5.0%
07082296484 1
 
5.0%
21541205 1
 
5.0%
Other values (8) 8
40.0%
2024-04-18T03:35:24.570080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
17.3%
2 28
14.3%
5 20
10.2%
- 18
9.2%
3 17
8.7%
7 16
8.2%
4 16
8.2%
1 15
7.7%
9 14
7.1%
8 9
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 178
90.8%
Dash Punctuation 18
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
19.1%
2 28
15.7%
5 20
11.2%
3 17
9.6%
7 16
9.0%
4 16
9.0%
1 15
8.4%
9 14
7.9%
8 9
 
5.1%
6 9
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 196
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
17.3%
2 28
14.3%
5 20
10.2%
- 18
9.2%
3 17
8.7%
7 16
8.2%
4 16
8.2%
1 15
7.7%
9 14
7.1%
8 9
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
17.3%
2 28
14.3%
5 20
10.2%
- 18
9.2%
3 17
8.7%
7 16
8.2%
4 16
8.2%
1 15
7.7%
9 14
7.1%
8 9
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

지번주소
Text

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-18T03:35:24.730212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25.5
Mean length21.863636
Min length16

Characters and Unicode

Total characters481
Distinct characters72
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

Unique18 ?
Unique (%)81.8%

Sample

1st row서울특별시 종로구 운니동 98-20
2nd row서울특별시 종로구 내자동 198
3rd row서울특별시 종로구 홍파동 152-5 4층
4th row서울특별시 종로구 신문로2가 92 엘지광화문빌딩
5th row서울특별시 종로구 계동 140-2 현대빌딩
ValueCountFrequency (%)
서울특별시 22
21.4%
종로구 22
21.4%
수송동 4
 
3.9%
92 3
 
2.9%
연지동 2
 
1.9%
관훈동 2
 
1.9%
내자동 2
 
1.9%
140-2 2
 
1.9%
계동 2
 
1.9%
엘지광화문빌딩 2
 
1.9%
Other values (34) 40
38.8%
2024-04-18T03:35:24.992690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
19.3%
로 24
 
5.0%
서 23
 
4.8%
울 22
 
4.6%
종 22
 
4.6%
구 22
 
4.6%
시 22
 
4.6%
별 22
 
4.6%
특 22
 
4.6%
동 20
 
4.2%
Other values (62) 189
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
61.1%
Space Separator 93
 
19.3%
Decimal Number 78
 
16.2%
Dash Punctuation 12
 
2.5%
Uppercase Letter 2
 
0.4%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 24
 
8.2%
서 23
 
7.8%
울 22
 
7.5%
종 22
 
7.5%
구 22
 
7.5%
시 22
 
7.5%
별 22
 
7.5%
특 22
 
7.5%
동 20
 
6.8%
딩 6
 
2.0%
Other values (47) 89
30.3%
Decimal Number
ValueCountFrequency (%)
2 19
24.4%
1 18
23.1%
9 8
10.3%
8 8
10.3%
4 7
 
9.0%
5 6
 
7.7%
3 6
 
7.7%
6 3
 
3.8%
0 3
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
61.1%
Common 185
38.5%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 24
 
8.2%
서 23
 
7.8%
울 22
 
7.5%
종 22
 
7.5%
구 22
 
7.5%
시 22
 
7.5%
별 22
 
7.5%
특 22
 
7.5%
동 20
 
6.8%
딩 6
 
2.0%
Other values (47) 89
30.3%
Common
ValueCountFrequency (%)
93
50.3%
2 19
 
10.3%
1 18
 
9.7%
- 12
 
6.5%
9 8
 
4.3%
8 8
 
4.3%
4 7
 
3.8%
5 6
 
3.2%
3 6
 
3.2%
6 3
 
1.6%
Other values (3) 5
 
2.7%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
61.1%
ASCII 187
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
93
49.7%
2 19
 
10.2%
1 18
 
9.6%
- 12
 
6.4%
9 8
 
4.3%
8 8
 
4.3%
4 7
 
3.7%
5 6
 
3.2%
3 6
 
3.2%
6 3
 
1.6%
Other values (5) 7
 
3.7%
Hangul
ValueCountFrequency (%)
로 24
 
8.2%
서 23
 
7.8%
울 22
 
7.5%
종 22
 
7.5%
구 22
 
7.5%
시 22
 
7.5%
별 22
 
7.5%
특 22
 
7.5%
동 20
 
6.8%
딩 6
 
2.0%
Other values (47) 89
30.3%

도로명주소
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing8
Missing (%)36.4%
Memory size308.0 B
2024-04-18T03:35:25.164542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30.5
Mean length28.642857
Min length21

Characters and Unicode

Total characters401
Distinct characters80
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

Unique12 ?
Unique (%)85.7%

Sample

1st row서울특별시 종로구 사직로8길 21-2 (내자동)
2nd row서울특별시 종로구 송월길 101, 4층 (홍파동)
3rd row서울특별시 종로구 율곡로 75, 현대빌딩 (계동)
4th row서울특별시 종로구 사직로 109 (내자동)
5th row서울특별시 종로구 통일로 134, 센터포인트 돈의문 (평동)
ValueCountFrequency (%)
서울특별시 14
 
16.3%
종로구 14
 
16.3%
6층 2
 
2.3%
율곡로 2
 
2.3%
수송동 2
 
2.3%
내자동 2
 
2.3%
수송스퀘어 2
 
2.3%
19 2
 
2.3%
율곡로2길 2
 
2.3%
경운동 1
 
1.2%
Other values (43) 43
50.0%
2024-04-18T03:35:25.457624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
18.0%
로 26
 
6.5%
동 17
 
4.2%
종 16
 
4.0%
서 15
 
3.7%
) 14
 
3.5%
특 14
 
3.5%
별 14
 
3.5%
시 14
 
3.5%
구 14
 
3.5%
Other values (70) 185
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
60.3%
Space Separator 72
 
18.0%
Decimal Number 46
 
11.5%
Close Punctuation 14
 
3.5%
Open Punctuation 14
 
3.5%
Other Punctuation 9
 
2.2%
Uppercase Letter 3
 
0.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 26
 
10.7%
동 17
 
7.0%
종 16
 
6.6%
서 15
 
6.2%
특 14
 
5.8%
별 14
 
5.8%
시 14
 
5.8%
구 14
 
5.8%
울 14
 
5.8%
길 6
 
2.5%
Other values (52) 92
38.0%
Decimal Number
ValueCountFrequency (%)
1 11
23.9%
3 7
15.2%
2 7
15.2%
6 4
 
8.7%
9 4
 
8.7%
0 4
 
8.7%
4 4
 
8.7%
5 2
 
4.3%
7 2
 
4.3%
8 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
S 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
60.3%
Common 156
38.9%
Latin 3
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 26
 
10.7%
동 17
 
7.0%
종 16
 
6.6%
서 15
 
6.2%
특 14
 
5.8%
별 14
 
5.8%
시 14
 
5.8%
구 14
 
5.8%
울 14
 
5.8%
길 6
 
2.5%
Other values (52) 92
38.0%
Common
ValueCountFrequency (%)
72
46.2%
) 14
 
9.0%
( 14
 
9.0%
1 11
 
7.1%
, 9
 
5.8%
3 7
 
4.5%
2 7
 
4.5%
6 4
 
2.6%
9 4
 
2.6%
0 4
 
2.6%
Other values (5) 10
 
6.4%
Latin
ValueCountFrequency (%)
B 1
33.3%
S 1
33.3%
K 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
60.3%
ASCII 159
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
45.3%
) 14
 
8.8%
( 14
 
8.8%
1 11
 
6.9%
, 9
 
5.7%
3 7
 
4.4%
2 7
 
4.4%
6 4
 
2.5%
9 4
 
2.5%
0 4
 
2.5%
Other values (8) 13
 
8.2%
Hangul
ValueCountFrequency (%)
로 26
 
10.7%
동 17
 
7.0%
종 16
 
6.6%
서 15
 
6.2%
특 14
 
5.8%
별 14
 
5.8%
시 14
 
5.8%
구 14
 
5.8%
울 14
 
5.8%
길 6
 
2.5%
Other values (52) 92
38.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)85.7%
Missing8
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean49061.429
Minimum3027
Maximum110776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T03:35:25.555692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3027
5-th percentile3047.15
Q13143
median3184.5
Q3110082.25
95-th percentile110742.85
Maximum110776
Range107749
Interquartile range (IQR)106939.25

Descriptive statistics

Standard deviation55040.927
Coefficient of variation (CV)1.1218778
Kurtosis-2.2403963
Mean49061.429
Median Absolute Deviation (MAD)142
Skewness0.32458684
Sum686860
Variance3.0295036 × 109
MonotonicityNot monotonic
2024-04-18T03:35:25.633944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
110053 2
 
9.1%
3143 2
 
9.1%
110092 1
 
4.5%
3058 1
 
4.5%
3181 1
 
4.5%
3149 1
 
4.5%
110776 1
 
4.5%
110130 1
 
4.5%
110725 1
 
4.5%
3027 1
 
4.5%
Other values (2) 2
 
9.1%
(Missing) 8
36.4%
ValueCountFrequency (%)
3027 1
4.5%
3058 1
4.5%
3142 1
4.5%
3143 2
9.1%
3149 1
4.5%
3181 1
4.5%
3188 1
4.5%
110053 2
9.1%
110092 1
4.5%
110130 1
4.5%
ValueCountFrequency (%)
110776 1
4.5%
110725 1
4.5%
110130 1
4.5%
110092 1
4.5%
110053 2
9.1%
3188 1
4.5%
3181 1
4.5%
3149 1
4.5%
3143 2
9.1%
3142 1
4.5%

사업장명
Text

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-18T03:35:25.772641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length9.5909091
Min length6

Characters and Unicode

Total characters211
Distinct characters59
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)68.2%

Sample

1st row삼환기업(주)
2nd row(주)아시아소음진동연구소
3rd row(주)한빛플랜트
4th row주식회사 서브원
5th row현대건설(주)
ValueCountFrequency (%)
주식회사 5
18.5%
에스케이에코엔지니어링 3
 
11.1%
주)대한콘설탄트 2
 
7.4%
대림산업(주 2
 
7.4%
삼환기업(주 1
 
3.7%
주)청명하이텍 1
 
3.7%
주)삼양홀딩스 1
 
3.7%
현대엔지니어링(주 1
 
3.7%
지에스건설(주 1
 
3.7%
삼양에코너지(주 1
 
3.7%
Other values (9) 9
33.3%
2024-04-18T03:35:26.007728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 22
 
10.4%
( 17
 
8.1%
) 17
 
8.1%
에 11
 
5.2%
이 9
 
4.3%
스 7
 
3.3%
지 6
 
2.8%
대 6
 
2.8%
코 5
 
2.4%
사 5
 
2.4%
Other values (49) 106
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
81.5%
Open Punctuation 17
 
8.1%
Close Punctuation 17
 
8.1%
Space Separator 5
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 22
 
12.8%
에 11
 
6.4%
이 9
 
5.2%
스 7
 
4.1%
지 6
 
3.5%
대 6
 
3.5%
코 5
 
2.9%
사 5
 
2.9%
설 5
 
2.9%
케 5
 
2.9%
Other values (46) 91
52.9%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
81.5%
Common 39
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 22
 
12.8%
에 11
 
6.4%
이 9
 
5.2%
스 7
 
4.1%
지 6
 
3.5%
대 6
 
3.5%
코 5
 
2.9%
사 5
 
2.9%
설 5
 
2.9%
케 5
 
2.9%
Other values (46) 91
52.9%
Common
ValueCountFrequency (%)
( 17
43.6%
) 17
43.6%
5
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
81.5%
ASCII 39
 
18.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 22
 
12.8%
에 11
 
6.4%
이 9
 
5.2%
스 7
 
4.1%
지 6
 
3.5%
대 6
 
3.5%
코 5
 
2.9%
사 5
 
2.9%
설 5
 
2.9%
케 5
 
2.9%
Other values (46) 91
52.9%
ASCII
ValueCountFrequency (%)
( 17
43.6%
) 17
43.6%
5
 
12.8%

최종수정일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2012-04-12 08:56:43
Maximum2024-02-06 14:52:23
2024-04-18T03:35:26.114518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:35:26.212925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
U
16 
I
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 16
72.7%
I 6
 
27.3%

Length

2024-04-18T03:35:26.303874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:26.376396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 16
72.7%
i 6
 
27.3%

데이터갱신일자
Date

Distinct15
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2019-03-30 02:20:09
Maximum2023-12-02 00:08:00
2024-04-18T03:35:26.445058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:35:26.525588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

업태구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing21
Missing (%)95.5%
Memory size308.0 B
2024-04-18T03:35:26.620672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters6
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 row토목 건설업
ValueCountFrequency (%)
토목 1
50.0%
건설업 1
50.0%
2024-04-18T03:35:26.798410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
토 1
16.7%
목 1
16.7%
1
16.7%
건 1
16.7%
설 1
16.7%
업 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
83.3%
Space Separator 1
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
토 1
20.0%
목 1
20.0%
건 1
20.0%
설 1
20.0%
업 1
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
83.3%
Common 1
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
토 1
20.0%
목 1
20.0%
건 1
20.0%
설 1
20.0%
업 1
20.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
83.3%
ASCII 1
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
토 1
20.0%
목 1
20.0%
건 1
20.0%
설 1
20.0%
업 1
20.0%
ASCII
ValueCountFrequency (%)
1
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)76.2%
Missing1
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean198258.38
Minimum196785.48
Maximum200029.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T03:35:26.885195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196785.48
5-th percentile197188.88
Q1197413.26
median198279.79
Q3198715.78
95-th percentile199963.38
Maximum200029.66
Range3244.1752
Interquartile range (IQR)1302.5199

Descriptive statistics

Standard deviation831.46117
Coefficient of variation (CV)0.004193826
Kurtosis0.30245761
Mean198258.38
Median Absolute Deviation (MAD)537.50167
Skewness0.40672834
Sum4163426
Variance691327.68
MonotonicityNot monotonic
2024-04-18T03:35:27.175189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
197413.260397461 2
 
9.1%
198817.289034611 2
 
9.1%
198550.794581565 2
 
9.1%
198087.664844665 2
 
9.1%
198279.787364709 2
 
9.1%
198884.743439112 1
 
4.5%
200029.656712659 1
 
4.5%
198351.818737482 1
 
4.5%
198176.159239663 1
 
4.5%
197188.883635689 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
196785.481471697 1
4.5%
197188.883635689 1
4.5%
197362.232927644 1
4.5%
197384.008252239 1
4.5%
197413.260397461 2
9.1%
198087.664844665 2
9.1%
198176.159239663 1
4.5%
198279.787364709 2
9.1%
198286.311784052 1
4.5%
198351.818737482 1
4.5%
ValueCountFrequency (%)
200029.656712659 1
4.5%
199963.38074965 1
4.5%
198884.743439112 1
4.5%
198817.289034611 2
9.1%
198715.780286168 1
4.5%
198550.794581565 2
9.1%
198351.818737482 1
4.5%
198286.311784052 1
4.5%
198279.787364709 2
9.1%
198176.159239663 1
4.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)76.2%
Missing1
Missing (%)4.5%
Infinite0
Infinite (%)0.0%
Mean452384.99
Minimum451896.03
Maximum452901.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-18T03:35:27.255754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451896.03
5-th percentile451896.03
Q1452199.62
median452355.92
Q3452574.67
95-th percentile452901.79
Maximum452901.79
Range1005.7595
Interquartile range (IQR)375.05235

Descriptive statistics

Standard deviation308.39473
Coefficient of variation (CV)0.00068170858
Kurtosis-0.76365151
Mean452384.99
Median Absolute Deviation (MAD)218.75171
Skewness0.017289766
Sum9500084.8
Variance95107.31
MonotonicityNot monotonic
2024-04-18T03:35:27.338549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
451896.027279239 2
 
9.1%
452901.786745273 2
 
9.1%
452315.522758616 2
 
9.1%
452355.919806244 2
 
9.1%
452430.699653992 2
 
9.1%
452765.921671768 1
 
4.5%
452241.852291232 1
 
4.5%
451921.60302604 1
 
4.5%
452574.67151361 1
 
4.5%
452742.011967313 1
 
4.5%
Other values (6) 6
27.3%
ValueCountFrequency (%)
451896.027279239 2
9.1%
451921.60302604 1
4.5%
452067.521992348 1
4.5%
452091.444332546 1
4.5%
452199.619160761 1
4.5%
452241.852291232 1
4.5%
452315.522758616 2
9.1%
452355.919806244 2
9.1%
452430.699653992 2
9.1%
452490.443583788 1
4.5%
ValueCountFrequency (%)
452901.786745273 2
9.1%
452765.921671768 1
4.5%
452742.011967313 1
4.5%
452665.504273907 1
4.5%
452574.67151361 1
4.5%
452524.28971473 1
4.5%
452490.443583788 1
4.5%
452430.699653992 2
9.1%
452355.919806244 2
9.1%
452315.522758616 2
9.1%

실험실면적
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
0
4 

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
0 4
 
18.2%

Length

2024-04-18T03:35:27.431770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:27.517233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
0 4
 
18.2%

사업장구분명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
환경전문공사업
12 
<NA>
10 

Length

Max length7
Median length7
Mean length5.6363636
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 12
54.5%
<NA> 10
45.5%

Length

2024-04-18T03:35:27.603564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:27.682818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 12
54.5%
na 10
45.5%

영업소면적
Categorical

Distinct4
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
17 
0
3 
108
 
1
953
 
1

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row<NA>
2nd row108
3rd row0
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 17
77.3%
0 3
 
13.6%
108 1
 
4.5%
953 1
 
4.5%

Length

2024-04-18T03:35:27.768677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:27.852999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
77.3%
0 3
 
13.6%
108 1
 
4.5%
953 1
 
4.5%

위탁업체명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing20
Missing (%)90.9%
Memory size308.0 B
2024-04-18T03:35:27.960300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9
Min length8

Characters and Unicode

Total characters18
Distinct characters15
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 (%)100.0%

Sample

1st row(주)하이텍환경
2nd row(주)산업공해연구소
ValueCountFrequency (%)
주)하이텍환경 1
50.0%
주)산업공해연구소 1
50.0%
2024-04-18T03:35:28.179625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 2
 
11.1%
주 2
 
11.1%
) 2
 
11.1%
하 1
 
5.6%
이 1
 
5.6%
텍 1
 
5.6%
환 1
 
5.6%
경 1
 
5.6%
산 1
 
5.6%
업 1
 
5.6%
Other values (5) 5
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
77.8%
Open Punctuation 2
 
11.1%
Close Punctuation 2
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2
14.3%
하 1
 
7.1%
이 1
 
7.1%
텍 1
 
7.1%
환 1
 
7.1%
경 1
 
7.1%
산 1
 
7.1%
업 1
 
7.1%
공 1
 
7.1%
해 1
 
7.1%
Other values (3) 3
21.4%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
77.8%
Common 4
 
22.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2
14.3%
하 1
 
7.1%
이 1
 
7.1%
텍 1
 
7.1%
환 1
 
7.1%
경 1
 
7.1%
산 1
 
7.1%
업 1
 
7.1%
공 1
 
7.1%
해 1
 
7.1%
Other values (3) 3
21.4%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
77.8%
ASCII 4
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%
Hangul
ValueCountFrequency (%)
주 2
14.3%
하 1
 
7.1%
이 1
 
7.1%
텍 1
 
7.1%
환 1
 
7.1%
경 1
 
7.1%
산 1
 
7.1%
업 1
 
7.1%
공 1
 
7.1%
해 1
 
7.1%
Other values (3) 3
21.4%

실험실지역코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
1111013200
 
1
1111011400
 
1
1111017900
 
1
4127310100
 
1

Length

Max length10
Median length4
Mean length5.0909091
Min length4

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row1111013200
2nd row1111011400
3rd row1111017900
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
1111013200 1
 
4.5%
1111011400 1
 
4.5%
1111017900 1
 
4.5%
4127310100 1
 
4.5%

Length

2024-04-18T03:35:28.285129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:28.379886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
1111013200 1
 
4.5%
1111011400 1
 
4.5%
1111017900 1
 
4.5%
4127310100 1
 
4.5%

실험실우편번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
20 
110350
 
1
110092
 
1

Length

Max length6
Median length4
Mean length4.1818182
Min length4

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row110350
2nd row<NA>
3rd row110092
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
90.9%
110350 1
 
4.5%
110092 1
 
4.5%

Length

2024-04-18T03:35:28.476829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:28.571720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
90.9%
110350 1
 
4.5%
110092 1
 
4.5%

실험실산
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
1
4 

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
1 4
 
18.2%

Length

2024-04-18T03:35:28.676683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:28.774651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
1 4
 
18.2%

실험실번지
Categorical

IMBALANCE 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
98
 
1
198
 
1
152
 
1
727
 
1

Length

Max length4
Median length4
Mean length3.7727273
Min length2

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row98
2nd row198
3rd row152
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
98 1
 
4.5%
198 1
 
4.5%
152 1
 
4.5%
727 1
 
4.5%

Length

2024-04-18T03:35:28.860642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:28.952212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
98 1
 
4.5%
198 1
 
4.5%
152 1
 
4.5%
727 1
 
4.5%

실험실호
Categorical

IMBALANCE 

Distinct4
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
19 
20
 
1
5
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.6363636
Min length1

Unique

Unique3 ?
Unique (%)13.6%

Sample

1st row20
2nd row<NA>
3rd row5
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 19
86.4%
20 1
 
4.5%
5 1
 
4.5%
2 1
 
4.5%

Length

2024-04-18T03:35:29.041651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:29.126666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
86.4%
20 1
 
4.5%
5 1
 
4.5%
2 1
 
4.5%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

실험실특수주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing21
Missing (%)95.5%
Memory size308.0 B
2024-04-18T03:35:29.175072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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 row4층
ValueCountFrequency (%)
4층 1
100.0%
2024-04-18T03:35:29.331475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
50.0%
층 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
50.0%
Other Letter 1
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%
Other Letter
ValueCountFrequency (%)
층 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
50.0%
Hangul 1
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%
Hangul
ValueCountFrequency (%)
층 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
50.0%
Hangul 1
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%
Hangul
ValueCountFrequency (%)
층 1
100.0%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

실험실특수주소호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

실험실도로명주소시군구코드
Categorical

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
11110
3 
41273
 
1

Length

Max length5
Median length4
Mean length4.1818182
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row11110
2nd row11110
3rd row11110
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
11110 3
 
13.6%
41273 1
 
4.5%

Length

2024-04-18T03:35:29.450895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:29.533097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
11110 3
 
13.6%
41273 1
 
4.5%

실험실도로명주소읍면동코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
1111013200
 
1
1111011400
 
1
1111017900
 
1
4127310100
 
1

Length

Max length10
Median length4
Mean length5.0909091
Min length4

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row1111013200
2nd row1111011400
3rd row1111017900
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
1111013200 1
 
4.5%
1111011400 1
 
4.5%
1111017900 1
 
4.5%
4127310100 1
 
4.5%

Length

2024-04-18T03:35:29.627833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:29.716117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
1111013200 1
 
4.5%
1111011400 1
 
4.5%
1111017900 1
 
4.5%
4127310100 1
 
4.5%

실험실도로명주소읍면동구분
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
1
4 

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
1 4
 
18.2%

Length

2024-04-18T03:35:29.807877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:29.887912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
1 4
 
18.2%

실험실도로명주소코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
3100010
 
1
4100135
 
1
4100192
 
1
3191004
 
1

Length

Max length7
Median length4
Mean length4.5454545
Min length4

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row3100010
2nd row4100135
3rd row4100192
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
3100010 1
 
4.5%
4100135 1
 
4.5%
4100192 1
 
4.5%
3191004 1
 
4.5%

Length

2024-04-18T03:35:29.971477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:30.056256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
3100010 1
 
4.5%
4100135 1
 
4.5%
4100192 1
 
4.5%
3191004 1
 
4.5%

실험실도로명특수주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing18
Missing (%)81.8%
Memory size308.0 B
2024-04-18T03:35:30.169207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.5
Min length5

Characters and Unicode

Total characters34
Distinct characters21
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

Unique4 ?
Unique (%)100.0%

Sample

1st row(운니동)
2nd row(내자동)
3rd row4층 (홍파동)
4th row403호 (고잔동, 현대타운)
ValueCountFrequency (%)
운니동 1
14.3%
내자동 1
14.3%
4층 1
14.3%
홍파동 1
14.3%
403호 1
14.3%
고잔동 1
14.3%
현대타운 1
14.3%
2024-04-18T03:35:30.389889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4
 
11.8%
동 4
 
11.8%
) 4
 
11.8%
3
 
8.8%
4 2
 
5.9%
운 2
 
5.9%
3 1
 
2.9%
대 1
 
2.9%
현 1
 
2.9%
, 1
 
2.9%
Other values (11) 11
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
52.9%
Open Punctuation 4
 
11.8%
Close Punctuation 4
 
11.8%
Decimal Number 4
 
11.8%
Space Separator 3
 
8.8%
Other Punctuation 1
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4
22.2%
운 2
11.1%
대 1
 
5.6%
현 1
 
5.6%
잔 1
 
5.6%
고 1
 
5.6%
호 1
 
5.6%
홍 1
 
5.6%
파 1
 
5.6%
층 1
 
5.6%
Other values (4) 4
22.2%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
3 1
25.0%
0 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
52.9%
Common 16
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4
22.2%
운 2
11.1%
대 1
 
5.6%
현 1
 
5.6%
잔 1
 
5.6%
고 1
 
5.6%
호 1
 
5.6%
홍 1
 
5.6%
파 1
 
5.6%
층 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
( 4
25.0%
) 4
25.0%
3
18.8%
4 2
12.5%
3 1
 
6.2%
, 1
 
6.2%
0 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
52.9%
ASCII 16
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4
25.0%
) 4
25.0%
3
18.8%
4 2
12.5%
3 1
 
6.2%
, 1
 
6.2%
0 1
 
6.2%
Hangul
ValueCountFrequency (%)
동 4
22.2%
운 2
11.1%
대 1
 
5.6%
현 1
 
5.6%
잔 1
 
5.6%
고 1
 
5.6%
호 1
 
5.6%
홍 1
 
5.6%
파 1
 
5.6%
층 1
 
5.6%
Other values (4) 4
22.2%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
0
4 

Length

Max length4
Median length4
Mean length3.4545455
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
0 4
 
18.2%

Length

2024-04-18T03:35:30.490301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:30.572315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
0 4
 
18.2%

실험실도로명주소건물본번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
18 
82
 
1
21
 
1
101
 
1
99
 
1

Length

Max length4
Median length4
Mean length3.6818182
Min length2

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st row82
2nd row21
3rd row101
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
81.8%
82 1
 
4.5%
21 1
 
4.5%
101 1
 
4.5%
99 1
 
4.5%

Length

2024-04-18T03:35:30.662162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:30.750193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
81.8%
82 1
 
4.5%
21 1
 
4.5%
101 1
 
4.5%
99 1
 
4.5%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
2
 
1

Length

Max length4
Median length4
Mean length3.8636364
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row<NA>
2nd row2
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
2 1
 
4.5%

Length

2024-04-18T03:35:30.836562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:30.914289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
2 1
 
4.5%

실험실도로명주소우편번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
20 
110742
 
1
110092
 
1

Length

Max length6
Median length4
Mean length4.1818182
Min length4

Unique

Unique2 ?
Unique (%)9.1%

Sample

1st row110742
2nd row<NA>
3rd row110092
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
90.9%
110742 1
 
4.5%
110092 1
 
4.5%

Length

2024-04-18T03:35:30.999970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:35:31.118995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
90.9%
110742 1
 
4.5%
110092 1
 
4.5%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
0300000030000006720020000320020111<NA>4취소/말소/만료/정지/중지4폐쇄20180918<NA><NA><NA>027402436<NA><NA>서울특별시 종로구 운니동 98-20<NA><NA>삼환기업(주)2018-11-01 06:32:42I2019-03-30 02:20:09.0<NA>198884.743439452765.921672<NA>환경전문공사업<NA><NA>111101320011035019820<NA><NA><NA><NA><NA>11110111101320013100010(운니동)082<NA>110742
1300000030000006720100000120100317<NA>3폐업2폐업20151204<NA><NA><NA>7197452<NA><NA>서울특별시 종로구 내자동 198서울특별시 종로구 사직로8길 21-2 (내자동)110053(주)아시아소음진동연구소2016-03-10 16:27:38I2019-03-30 02:20:09.0<NA>197384.008252452490.443584<NA>환경전문공사업108<NA>1111011400<NA>1198<NA><NA><NA><NA><NA><NA>11110111101140014100135(내자동)0212<NA>
2300000030000006720100000220100708<NA>3폐업2폐업20130212<NA><NA><NA>0263511960<NA><NA>서울특별시 종로구 홍파동 152-5 4층서울특별시 종로구 송월길 101, 4층 (홍파동)110092(주)한빛플랜트2021-11-15 18:10:01U2021-11-17 02:40:00.0<NA>196785.481472452067.5219920환경전문공사업0<NA>111101790011009211525<NA><NA>4층<NA><NA>111101111017900141001924층 (홍파동)0101<NA>110092
3300000030000006720100000320101028<NA>3폐업2폐업20180308<NA><NA><NA><NA><NA><NA>서울특별시 종로구 신문로2가 92 엘지광화문빌딩<NA><NA>주식회사 서브원2020-03-10 15:28:05U2020-03-12 02:40:00.0<NA>197413.260397451896.027279<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4300000030000006720110000120110929<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-746-2762<NA><NA>서울특별시 종로구 계동 140-2 현대빌딩서울특별시 종로구 율곡로 75, 현대빌딩 (계동)3058현대건설(주)2022-07-27 07:54:45U2021-12-06 21:00:00.0<NA>198817.289035452901.786745<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5300000030000006720110000220111217<NA>3폐업2폐업<NA><NA><NA><NA>7355249<NA><NA>서울특별시 종로구 내자동 25-1서울특별시 종로구 사직로 109 (내자동)110053(주)대한콘설탄트2014-07-15 18:12:36I2019-03-30 02:20:09.0<NA>197362.232928452665.504274<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6300000030000006720110000320110119<NA>3폐업2폐업20180308<NA><NA><NA>69245855<NA><NA>서울특별시 종로구 신문로2가 92 엘지광화문빌딩 4층<NA><NA>(주)서브원2021-11-15 18:09:41U2021-11-17 02:40:00.0<NA>197413.260397451896.0272790환경전문공사업0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730000003000000672011000042011-09-16<NA>1영업/정상BBBB영업<NA><NA><NA><NA>2011-7459<NA><NA>서울특별시 종로구 평동 222 센터포인트 돈의문서울특별시 종로구 통일로 134, 센터포인트 돈의문 (평동)3181디엘이앤씨(주)2023-12-11 18:02:58U2022-11-01 23:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830000003000000672011000052011-06-26<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-3700-9238<NA><NA>서울특별시 종로구 관훈동 192-18 SK건설빌딩서울특별시 종로구 인사동7길 32, SK건설빌딩 (관훈동)3149에스케이에코플랜트(주)2024-02-06 14:52:23U2023-12-02 00:08:00.0<NA>198550.794582452315.522759<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9300000030000006720110000620110825<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 수송동 146-12<NA><NA>대림산업(주)2012-04-12 08:56:43I2019-03-30 02:20:09.0<NA>198087.664845452355.919806<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
12300000030000006720130000220130528<NA>3폐업2폐업<NA><NA><NA><NA>32103050<NA><NA>서울특별시 종로구 경운동 85서울특별시 종로구 삼일대로 461, 102동 205호 (경운동)110776삼양에코너지(주)2015-12-30 17:52:17I2019-03-30 02:20:09.0<NA>198715.780286452524.289715<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13300000030000006720140000120140129<NA>1영업/정상BBBB영업<NA><NA><NA><NA>21541205<NA><NA>서울특별시 종로구 청진동 92서울특별시 종로구 종로 33 (청진동)110130지에스건설(주)2022-11-23 15:40:29U2021-10-31 22:05:00.0<NA>198286.311784452091.444333<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1430000003000000672014000022014-03-26<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0221341935<NA><NA>서울특별시 종로구 계동 140-2<NA><NA>현대엔지니어링(주)2024-01-17 14:39:43U2023-11-30 23:09:00.0<NA>198817.289035452901.786745<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15300000030000006720150000120150325<NA>3폐업2폐업20200102<NA><NA><NA>032-340-8114<NA><NA>서울특별시 종로구 연지동 263서울특별시 종로구 종로33길 31 (연지동)110725(주)삼양홀딩스2021-11-15 18:09:16U2021-11-17 02:40:00.0<NA>200029.656713452241.8522910환경전문공사업0(주)하이텍환경4127310100<NA>17272<NA><NA><NA><NA><NA>41273412731010013191004403호 (고잔동, 현대타운)099<NA><NA>
16300000030000006720170000120170519<NA>1영업/정상BBBB영업<NA><NA><NA><NA>2011-7446<NA><NA>서울특별시 종로구 수송동 146-12<NA><NA>대림산업(주)2019-11-05 15:30:59U2019-11-07 02:40:00.0<NA>198087.664845452355.919806<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17300000030000006720210000120210928<NA>1영업/정상BBBB영업<NA><NA><NA><NA>7355249<NA><NA>서울특별시 종로구 필운동 115서울특별시 종로구 필운대로 9 (필운동)3027(주)대한콘설탄트2021-11-22 14:10:09U2021-11-24 02:40:00.0<NA>197188.883636452742.0119670환경전문공사업953(주)산업공해연구소<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18300000030000006720210000220211123<NA>3폐업2폐업20221226<NA><NA><NA>02-3700-8509<NA><NA>서울특별시 종로구 수송동 83-1 수송스퀘어서울특별시 종로구 율곡로2길 19, 수송스퀘어 6층 (수송동)3143에스케이에코엔지니어링 주식회사2022-12-27 17:33:45U2021-11-01 22:09:00.0<NA>198279.787365452430.699654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1930000003000000672021000032021-11-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-3700-8509<NA><NA>서울특별시 종로구 중학동 14 트윈 트리 빌딩서울특별시 종로구 율곡로 6, 트윈 트리 빌딩 B동 (중학동)3142에스케이에코엔지니어링 주식회사2023-10-13 14:33:59U2022-10-30 23:05:00.0<NA>198176.15924452574.671514<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20300000030000006720210000420211124<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-370-8509<NA><NA>서울특별시 종로구 수송동 83-1 수송스퀘어서울특별시 종로구 율곡로2길 19, 수송스퀘어 6층 (수송동)3143에스케이에코엔지니어링 주식회사2022-12-30 09:22:12U2022-12-01 00:01:00.0토목 건설업198279.787365452430.699654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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