Overview

Dataset statistics

Number of variables51
Number of observations43
Missing cells799
Missing cells (%)36.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory444.0 B

Variable types

Numeric14
Categorical15
DateTime4
Unsupported11
Text7

Dataset

Description23년06월_6270000_대구광역시_09_30_15_P_환경관리대행기관
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098783&dataSetDetailId=DDI_0000098808&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
개방자치단체코드 has constant value ""Constant
사업장구분명 has constant value ""Constant
실험실특수주소 has constant value ""Constant
실험실특수주소호 is highly imbalanced (84.1%)Imbalance
인허가취소일자 has 43 (100.0%) missing valuesMissing
폐업일자 has 22 (51.2%) missing valuesMissing
휴업시작일자 has 43 (100.0%) missing valuesMissing
휴업종료일자 has 43 (100.0%) missing valuesMissing
재개업일자 has 43 (100.0%) missing valuesMissing
소재지전화 has 43 (100.0%) missing valuesMissing
소재지면적 has 43 (100.0%) missing valuesMissing
소재지우편번호 has 6 (14.0%) missing valuesMissing
소재지전체주소 has 4 (9.3%) missing valuesMissing
도로명우편번호 has 2 (4.7%) missing valuesMissing
업태구분명 has 43 (100.0%) missing valuesMissing
좌표정보(X) has 2 (4.7%) missing valuesMissing
좌표정보(Y) has 2 (4.7%) missing valuesMissing
실험실면적 has 9 (20.9%) missing valuesMissing
위탁업체명 has 43 (100.0%) missing valuesMissing
실험실지역코드 has 25 (58.1%) missing valuesMissing
실험실우편번호 has 25 (58.1%) missing valuesMissing
실험실번지 has 25 (58.1%) missing valuesMissing
실험실호 has 27 (62.8%) missing valuesMissing
실험실통 has 43 (100.0%) missing valuesMissing
실험실반 has 43 (100.0%) missing valuesMissing
실험실특수주소 has 42 (97.7%) missing valuesMissing
실험실특수주소동 has 43 (100.0%) missing valuesMissing
실험실도로명주소시군구코드 has 19 (44.2%) missing valuesMissing
실험실도로명주소읍면동코드 has 19 (44.2%) missing valuesMissing
실험실도로명주소코드 has 19 (44.2%) missing valuesMissing
실험실도로명특수주소 has 40 (93.0%) missing valuesMissing
실험실도로명주소건물본번호 has 19 (44.2%) missing valuesMissing
실험실도로명주소우편번호 has 19 (44.2%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 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
소재지전화 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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
위탁업체명 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
실험실면적 has 19 (44.2%) zerosZeros
실험실호 has 1 (2.3%) zerosZeros

Reproduction

Analysis started2024-04-21 11:44:16.814687
Analysis finished2024-04-21 11:44:17.725709
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:17.916275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.1
Q111.5
median22
Q332.5
95-th percentile40.9
Maximum43
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.57075176
Kurtosis-1.2
Mean22
Median Absolute Deviation (MAD)11
Skewness0
Sum946
Variance157.66667
MonotonicityStrictly increasing
2024-04-21T20:44:18.324000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1 1
 
2.3%
2 1
 
2.3%
25 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%
34 1
2.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
환경관리대행기관
43 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경관리대행기관 43
100.0%

Length

2024-04-21T20:44:18.718282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:19.021875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경관리대행기관 43
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
09_30_15_P
43 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_15_P
2nd row09_30_15_P
3rd row09_30_15_P
4th row09_30_15_P
5th row09_30_15_P

Common Values

ValueCountFrequency (%)
09_30_15_P 43
100.0%

Length

2024-04-21T20:44:19.345307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:19.649480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_15_p 43
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
6270000
43 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6270000
2nd row6270000
3rd row6270000
4th row6270000
5th row6270000

Common Values

ValueCountFrequency (%)
6270000 43
100.0%

Length

2024-04-21T20:44:19.971534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:20.275434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 43
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2700001 × 1017
Minimum6.2700001 × 1017
Maximum6.2700001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:20.612478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2700001 × 1017
5-th percentile6.2700001 × 1017
Q16.2700001 × 1017
median6.2700001 × 1017
Q36.2700001 × 1017
95-th percentile6.2700001 × 1017
Maximum6.2700001 × 1017
Range900001
Interquartile range (IQR)700032

Descriptive statistics

Standard deviation343550.13
Coefficient of variation (CV)5.4792683 × 10-13
Kurtosis-1.7231414
Mean6.2700001 × 1017
Median Absolute Deviation (MAD)400000
Skewness0.073501969
Sum8.5142564 × 1018
Variance1.1802669 × 1011
MonotonicityNot monotonic
2024-04-21T20:44:21.027749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
627000010201800002 1
 
2.3%
627000010202000004 1
 
2.3%
627000010201300012 1
 
2.3%
627000010201300014 1
 
2.3%
627000010201300016 1
 
2.3%
627000010201900001 1
 
2.3%
627000010201300005 1
 
2.3%
627000010201900002 1
 
2.3%
627000010201900004 1
 
2.3%
627000010202200001 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
627000010201300001 1
2.3%
627000010201300003 1
2.3%
627000010201300004 1
2.3%
627000010201300005 1
2.3%
627000010201300006 1
2.3%
627000010201300007 1
2.3%
627000010201300008 1
2.3%
627000010201300010 1
2.3%
627000010201300011 1
2.3%
627000010201300012 1
2.3%
ValueCountFrequency (%)
627000010202200002 1
2.3%
627000010202200001 1
2.3%
627000010202100007 1
2.3%
627000010202100006 1
2.3%
627000010202100005 1
2.3%
627000010202100004 1
2.3%
627000010202100003 1
2.3%
627000010202100002 1
2.3%
627000010202100001 1
2.3%
627000010202000004 1
2.3%

인허가일자
Date

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
Minimum2013-10-08 00:00:00
Maximum2023-06-23 00:00:00
2024-04-21T20:44:21.405823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T20:44:21.809363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
3
22 
1
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 22
51.2%
1 21
48.8%

Length

2024-04-21T20:44:22.205316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:22.384234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 22
51.2%
1 21
48.8%

영업상태명
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
폐업
22 
영업/정상
21 

Length

Max length5
Median length2
Mean length3.4651163
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
51.2%
영업/정상 21
48.8%

Length

2024-04-21T20:44:22.576806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:22.760092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
51.2%
영업/정상 21
48.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
Q
22 
N
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowN
2nd rowQ
3rd rowN
4th rowN
5th rowN

Common Values

ValueCountFrequency (%)
Q 22
51.2%
N 21
48.8%

Length

2024-04-21T20:44:22.935534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:23.108405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 22
51.2%
n 21
48.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
폐업
22 
신규
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 22
51.2%
신규 21
48.8%

Length

2024-04-21T20:44:23.291183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:23.463603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 22
51.2%
신규 21
48.8%

폐업일자
Date

MISSING 

Distinct19
Distinct (%)90.5%
Missing22
Missing (%)51.2%
Memory size472.0 B
Minimum2013-10-08 00:00:00
Maximum2022-02-16 00:00:00
2024-04-21T20:44:23.629110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T20:44:23.831159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

소재지우편번호
Text

MISSING 

Distinct24
Distinct (%)64.9%
Missing6
Missing (%)14.0%
Memory size472.0 B
2024-04-21T20:44:24.342514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.1891892
Min length5

Characters and Unicode

Total characters229
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

Unique17 ?
Unique (%)45.9%

Sample

1st row703-830
2nd row43008
3rd row704-932
4th row704-919
5th row702-817
ValueCountFrequency (%)
703-830 7
18.9%
703-829 3
 
8.1%
702-817 2
 
5.4%
41701 2
 
5.4%
703-834 2
 
5.4%
43008 2
 
5.4%
41841 2
 
5.4%
43013 1
 
2.7%
41845 1
 
2.7%
41480 1
 
2.7%
Other values (14) 14
37.8%
2024-04-21T20:44:25.100222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40
17.5%
3 34
14.8%
7 28
12.2%
8 27
11.8%
4 26
11.4%
1 25
10.9%
- 22
9.6%
2 11
 
4.8%
9 10
 
4.4%
5 4
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 207
90.4%
Dash Punctuation 22
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40
19.3%
3 34
16.4%
7 28
13.5%
8 27
13.0%
4 26
12.6%
1 25
12.1%
2 11
 
5.3%
9 10
 
4.8%
5 4
 
1.9%
6 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 229
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40
17.5%
3 34
14.8%
7 28
12.2%
8 27
11.8%
4 26
11.4%
1 25
10.9%
- 22
9.6%
2 11
 
4.8%
9 10
 
4.4%
5 4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40
17.5%
3 34
14.8%
7 28
12.2%
8 27
11.8%
4 26
11.4%
1 25
10.9%
- 22
9.6%
2 11
 
4.8%
9 10
 
4.4%
5 4
 
1.7%

소재지전체주소
Text

MISSING 

Distinct30
Distinct (%)76.9%
Missing4
Missing (%)9.3%
Memory size472.0 B
2024-04-21T20:44:25.860239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length27
Mean length22.871795
Min length18

Characters and Unicode

Total characters892
Distinct characters66
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

Unique23 ?
Unique (%)59.0%

Sample

1st row대구광역시 서구 이현동 44번지 110호
2nd row대구광역시 달성군 구지면 응암리 1278-10
3rd row대구광역시 달서구 죽전동 372번지
4th row대구광역시 달서구 신당동 1320번지 2호 이앤씨이노비즈타워 609호
5th row대구광역시 북구 노원3가 550번지 1호
ValueCountFrequency (%)
대구광역시 39
21.1%
서구 21
 
11.4%
이현동 10
 
5.4%
달성군 6
 
3.2%
중리동 5
 
2.7%
북구 4
 
2.2%
달서구 4
 
2.2%
42번지 4
 
2.2%
비산동 3
 
1.6%
1호 3
 
1.6%
Other values (66) 86
46.5%
2024-04-21T20:44:26.894371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
20.4%
구 75
 
8.4%
1 46
 
5.2%
대 41
 
4.6%
시 39
 
4.4%
광 39
 
4.4%
역 39
 
4.4%
동 34
 
3.8%
지 26
 
2.9%
2 26
 
2.9%
Other values (56) 345
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 496
55.6%
Decimal Number 198
 
22.2%
Space Separator 182
 
20.4%
Dash Punctuation 16
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 75
15.1%
대 41
 
8.3%
시 39
 
7.9%
광 39
 
7.9%
역 39
 
7.9%
동 34
 
6.9%
지 26
 
5.2%
서 26
 
5.2%
번 23
 
4.6%
호 21
 
4.2%
Other values (44) 133
26.8%
Decimal Number
ValueCountFrequency (%)
1 46
23.2%
2 26
13.1%
4 26
13.1%
0 25
12.6%
7 16
 
8.1%
6 15
 
7.6%
5 15
 
7.6%
9 10
 
5.1%
3 10
 
5.1%
8 9
 
4.5%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 496
55.6%
Common 396
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 75
15.1%
대 41
 
8.3%
시 39
 
7.9%
광 39
 
7.9%
역 39
 
7.9%
동 34
 
6.9%
지 26
 
5.2%
서 26
 
5.2%
번 23
 
4.6%
호 21
 
4.2%
Other values (44) 133
26.8%
Common
ValueCountFrequency (%)
182
46.0%
1 46
 
11.6%
2 26
 
6.6%
4 26
 
6.6%
0 25
 
6.3%
- 16
 
4.0%
7 16
 
4.0%
6 15
 
3.8%
5 15
 
3.8%
9 10
 
2.5%
Other values (2) 19
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 496
55.6%
ASCII 396
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
46.0%
1 46
 
11.6%
2 26
 
6.6%
4 26
 
6.6%
0 25
 
6.3%
- 16
 
4.0%
7 16
 
4.0%
6 15
 
3.8%
5 15
 
3.8%
9 10
 
2.5%
Other values (2) 19
 
4.8%
Hangul
ValueCountFrequency (%)
구 75
15.1%
대 41
 
8.3%
시 39
 
7.9%
광 39
 
7.9%
역 39
 
7.9%
동 34
 
6.9%
지 26
 
5.2%
서 26
 
5.2%
번 23
 
4.6%
호 21
 
4.2%
Other values (44) 133
26.8%

도로명전체주소
Text

Distinct34
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-21T20:44:27.931100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length25.906977
Min length20

Characters and Unicode

Total characters1114
Distinct characters96
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

Unique27 ?
Unique (%)62.8%

Sample

1st row대구광역시 서구 국채보상로19길 15 (이현동)
2nd row대구광역시 달성군 구지면 국가산단대로46길 63
3rd row대구광역시 달서구 평리로 92 (죽전동)
4th row대구광역시 달서구 달서대로 559, 609호 (신당동,이앤씨이노비즈타워)
5th row대구광역시 북구 팔달북로15길 12 (노원동3가)
ValueCountFrequency (%)
대구광역시 43
 
19.3%
서구 22
 
9.9%
이현동 10
 
4.5%
달성군 7
 
3.1%
달서구 5
 
2.2%
북구 4
 
1.8%
중리동 4
 
1.8%
평리동 3
 
1.3%
구지면 3
 
1.3%
9-7 3
 
1.3%
Other values (94) 119
53.4%
2024-04-21T20:44:29.052860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
 
16.2%
구 85
 
7.6%
대 54
 
4.8%
광 43
 
3.9%
역 43
 
3.9%
시 43
 
3.9%
로 42
 
3.8%
동 39
 
3.5%
( 36
 
3.2%
) 36
 
3.2%
Other values (86) 513
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 667
59.9%
Space Separator 180
 
16.2%
Decimal Number 175
 
15.7%
Open Punctuation 36
 
3.2%
Close Punctuation 36
 
3.2%
Other Punctuation 10
 
0.9%
Dash Punctuation 7
 
0.6%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 85
 
12.7%
대 54
 
8.1%
광 43
 
6.4%
역 43
 
6.4%
시 43
 
6.4%
로 42
 
6.3%
동 39
 
5.8%
서 32
 
4.8%
길 29
 
4.3%
달 17
 
2.5%
Other values (68) 240
36.0%
Decimal Number
ValueCountFrequency (%)
1 33
18.9%
2 31
17.7%
3 21
12.0%
5 18
10.3%
6 16
9.1%
7 15
8.6%
4 15
8.6%
9 12
 
6.9%
0 9
 
5.1%
8 5
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
33.3%
T 1
33.3%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 667
59.9%
Common 444
39.9%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 85
 
12.7%
대 54
 
8.1%
광 43
 
6.4%
역 43
 
6.4%
시 43
 
6.4%
로 42
 
6.3%
동 39
 
5.8%
서 32
 
4.8%
길 29
 
4.3%
달 17
 
2.5%
Other values (68) 240
36.0%
Common
ValueCountFrequency (%)
180
40.5%
( 36
 
8.1%
) 36
 
8.1%
1 33
 
7.4%
2 31
 
7.0%
3 21
 
4.7%
5 18
 
4.1%
6 16
 
3.6%
7 15
 
3.4%
4 15
 
3.4%
Other values (5) 43
 
9.7%
Latin
ValueCountFrequency (%)
C 1
33.3%
T 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 667
59.9%
ASCII 447
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
40.3%
( 36
 
8.1%
) 36
 
8.1%
1 33
 
7.4%
2 31
 
6.9%
3 21
 
4.7%
5 18
 
4.0%
6 16
 
3.6%
7 15
 
3.4%
4 15
 
3.4%
Other values (8) 46
 
10.3%
Hangul
ValueCountFrequency (%)
구 85
 
12.7%
대 54
 
8.1%
광 43
 
6.4%
역 43
 
6.4%
시 43
 
6.4%
로 42
 
6.3%
동 39
 
5.8%
서 32
 
4.8%
길 29
 
4.3%
달 17
 
2.5%
Other values (68) 240
36.0%

도로명우편번호
Text

MISSING 

Distinct28
Distinct (%)68.3%
Missing2
Missing (%)4.7%
Memory size472.0 B
2024-04-21T20:44:29.701991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.1219512
Min length5

Characters and Unicode

Total characters251
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 (%)51.2%

Sample

1st row703-830
2nd row43008
3rd row42627
4th row704-919
5th row702-817
ValueCountFrequency (%)
703-830 7
 
17.1%
703-829 3
 
7.3%
43008 2
 
4.9%
703-834 2
 
4.9%
41701 2
 
4.9%
41841 2
 
4.9%
702-817 2
 
4.9%
703-833 1
 
2.4%
43013 1
 
2.4%
711-821 1
 
2.4%
Other values (18) 18
43.9%
2024-04-21T20:44:30.782542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
16.3%
3 33
13.1%
7 31
12.4%
1 30
12.0%
8 29
11.6%
4 29
11.6%
- 23
9.2%
2 15
 
6.0%
9 9
 
3.6%
5 6
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 228
90.8%
Dash Punctuation 23
 
9.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
18.0%
3 33
14.5%
7 31
13.6%
1 30
13.2%
8 29
12.7%
4 29
12.7%
2 15
 
6.6%
9 9
 
3.9%
5 6
 
2.6%
6 5
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
16.3%
3 33
13.1%
7 31
12.4%
1 30
12.0%
8 29
11.6%
4 29
11.6%
- 23
9.2%
2 15
 
6.0%
9 9
 
3.6%
5 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
16.3%
3 33
13.1%
7 31
12.4%
1 30
12.0%
8 29
11.6%
4 29
11.6%
- 23
9.2%
2 15
 
6.0%
9 9
 
3.6%
5 6
 
2.4%

사업장명
Text

Distinct34
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Memory size472.0 B
2024-04-21T20:44:31.568538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.8372093
Min length4

Characters and Unicode

Total characters337
Distinct characters73
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

Unique27 ?
Unique (%)62.8%

Sample

1st row에이치디이엔씨(주)
2nd row(주)지이테크
3rd row대동환경측정(주)
4th row(주)대일환경기술
5th row(주)삼안환경측정
ValueCountFrequency (%)
주)신라엔텍 3
 
6.8%
국일공해측정(주 3
 
6.8%
주)지이테크 2
 
4.5%
대명환경화학 2
 
4.5%
주)삼안환경측정 2
 
4.5%
주)한국이앤씨 2
 
4.5%
주)정도엔지니어링 2
 
4.5%
우영엔텍 1
 
2.3%
현대공해측정(주 1
 
2.3%
대구에코(주 1
 
2.3%
Other values (25) 25
56.8%
2024-04-21T20:44:32.748559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 34
 
10.1%
( 33
 
9.8%
) 33
 
9.8%
경 19
 
5.6%
환 19
 
5.6%
엔 12
 
3.6%
이 12
 
3.6%
정 12
 
3.6%
대 11
 
3.3%
측 9
 
2.7%
Other values (63) 143
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 270
80.1%
Open Punctuation 33
 
9.8%
Close Punctuation 33
 
9.8%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
12.6%
경 19
 
7.0%
환 19
 
7.0%
엔 12
 
4.4%
이 12
 
4.4%
정 12
 
4.4%
대 11
 
4.1%
측 9
 
3.3%
지 8
 
3.0%
일 8
 
3.0%
Other values (60) 126
46.7%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 270
80.1%
Common 67
 
19.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
12.6%
경 19
 
7.0%
환 19
 
7.0%
엔 12
 
4.4%
이 12
 
4.4%
정 12
 
4.4%
대 11
 
4.1%
측 9
 
3.3%
지 8
 
3.0%
일 8
 
3.0%
Other values (60) 126
46.7%
Common
ValueCountFrequency (%)
( 33
49.3%
) 33
49.3%
1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 270
80.1%
ASCII 67
 
19.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 34
 
12.6%
경 19
 
7.0%
환 19
 
7.0%
엔 12
 
4.4%
이 12
 
4.4%
정 12
 
4.4%
대 11
 
4.1%
측 9
 
3.3%
지 8
 
3.0%
일 8
 
3.0%
Other values (60) 126
46.7%
ASCII
ValueCountFrequency (%)
( 33
49.3%
) 33
49.3%
1
 
1.5%

최종수정시점
Date

UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
Minimum2013-12-09 14:42:45
Maximum2023-06-23 15:26:49
2024-04-21T20:44:33.134687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T20:44:33.548083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
U
29 
I
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 29
67.4%
I 14
32.6%

Length

2024-04-21T20:44:33.945780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:34.255656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 29
67.4%
i 14
32.6%

데이터갱신일자
Date

Distinct37
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
Minimum2018-10-04 02:37:36
Maximum2023-06-25 02:40:00
2024-04-21T20:44:34.561898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T20:44:34.957671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)75.6%
Missing2
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean338723.52
Minimum326925.06
Maximum355172.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:35.332561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326925.06
5-th percentile328923.52
Q1338570.77
median339171.11
Q3340141.63
95-th percentile345314.86
Maximum355172.29
Range28247.232
Interquartile range (IQR)1570.8533

Descriptive statistics

Standard deviation5190.9576
Coefficient of variation (CV)0.015325058
Kurtosis2.2423851
Mean338723.52
Median Absolute Deviation (MAD)970.51894
Skewness0.19543072
Sum13887664
Variance26946041
MonotonicityNot monotonic
2024-04-21T20:44:35.710273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
339211.707883262 3
 
7.0%
338615.861318646 3
 
7.0%
339130.306851299 2
 
4.7%
340008.783916204 2
 
4.7%
339171.10866603 2
 
4.7%
328923.524847654 2
 
4.7%
338570.774277792 2
 
4.7%
340487.815300421 2
 
4.7%
342283.3111782 1
 
2.3%
335519.727647765 1
 
2.3%
Other values (21) 21
48.8%
(Missing) 2
 
4.7%
ValueCountFrequency (%)
326925.056113926 1
2.3%
328580.780049187 1
2.3%
328923.524847654 2
4.7%
332716.873207973 1
2.3%
333417.650199885 1
2.3%
334621.225167521 1
2.3%
335023.196036028 1
2.3%
335519.727647765 1
2.3%
335525.948846587 1
2.3%
338570.774277792 2
4.7%
ValueCountFrequency (%)
355172.28775207 1
2.3%
347956.202203295 1
2.3%
345314.862155412 1
2.3%
344912.358902194 1
2.3%
344442.19601587 1
2.3%
343919.789889734 1
2.3%
342283.3111782 1
2.3%
340487.815300421 2
4.7%
340371.264861843 1
2.3%
340141.627610679 1
2.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)75.6%
Missing2
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean262533.8
Minimum239148.37
Maximum270013.37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:36.074517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239148.37
5-th percentile239903.42
Q1262913.13
median264420.56
Q3265447.98
95-th percentile268253.83
Maximum270013.37
Range30865.001
Interquartile range (IQR)2534.8542

Descriptive statistics

Standard deviation7026.4204
Coefficient of variation (CV)0.02676387
Kurtosis6.7134345
Mean262533.8
Median Absolute Deviation (MAD)1099.3501
Skewness-2.6501334
Sum10763886
Variance49370583
MonotonicityNot monotonic
2024-04-21T20:44:36.462774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
265438.542003308 3
 
7.0%
264602.381540101 3
 
7.0%
264420.555300691 2
 
4.7%
265447.982845799 2
 
4.7%
263934.488502096 2
 
4.7%
239903.424058142 2
 
4.7%
263464.295873622 2
 
4.7%
266848.895377862 2
 
4.7%
260627.073987253 1
 
2.3%
262291.965458637 1
 
2.3%
Other values (21) 21
48.8%
(Missing) 2
 
4.7%
ValueCountFrequency (%)
239148.373812982 1
2.3%
239903.424058142 2
4.7%
255443.694381648 1
2.3%
257280.684298351 1
2.3%
260627.073987253 1
2.3%
261271.159386719 1
2.3%
262044.332357665 1
2.3%
262291.965458637 1
2.3%
262370.37656075 1
2.3%
262913.128620388 1
2.3%
ValueCountFrequency (%)
270013.374391896 1
 
2.3%
268905.627155818 1
 
2.3%
268253.830252935 1
 
2.3%
266911.884251114 1
 
2.3%
266848.895377862 2
4.7%
266709.189457441 1
 
2.3%
266688.38114492 1
 
2.3%
265519.90541336 1
 
2.3%
265447.982845799 2
4.7%
265438.542003308 3
7.0%

실험실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)29.4%
Missing9
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean57.170294
Minimum0
Maximum223
Zeros19
Zeros (%)44.2%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:36.817761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q375
95-th percentile214.55
Maximum223
Range223
Interquartile range (IQR)75

Descriptive statistics

Standard deviation78.769496
Coefficient of variation (CV)1.3778046
Kurtosis0.047449833
Mean57.170294
Median Absolute Deviation (MAD)0
Skewness1.1829132
Sum1943.79
Variance6204.6335
MonotonicityNot monotonic
2024-04-21T20:44:37.161848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 19
44.2%
75.0 3
 
7.0%
210.0 3
 
7.0%
71.0 2
 
4.7%
223.0 2
 
4.7%
74.9 1
 
2.3%
90.0 1
 
2.3%
90.4 1
 
2.3%
173.49 1
 
2.3%
72.0 1
 
2.3%
(Missing) 9
20.9%
ValueCountFrequency (%)
0.0 19
44.2%
71.0 2
 
4.7%
72.0 1
 
2.3%
74.9 1
 
2.3%
75.0 3
 
7.0%
90.0 1
 
2.3%
90.4 1
 
2.3%
173.49 1
 
2.3%
210.0 3
 
7.0%
223.0 2
 
4.7%
ValueCountFrequency (%)
223.0 2
 
4.7%
210.0 3
 
7.0%
173.49 1
 
2.3%
90.4 1
 
2.3%
90.0 1
 
2.3%
75.0 3
 
7.0%
74.9 1
 
2.3%
72.0 1
 
2.3%
71.0 2
 
4.7%
0.0 19
44.2%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
환경관리대행기관
43 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경관리대행기관 43
100.0%

Length

2024-04-21T20:44:37.526693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:37.830627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경관리대행기관 43
100.0%

영업소면적
Categorical

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size472.0 B
0.0
26 
<NA>
15 
116.0
 
1
29.39
 
1

Length

Max length5
Median length3
Mean length3.4418605
Min length3

Unique

Unique2 ?
Unique (%)4.7%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row<NA>
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 26
60.5%
<NA> 15
34.9%
116.0 1
 
2.3%
29.39 1
 
2.3%

Length

2024-04-21T20:44:38.191673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:38.546812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 26
60.5%
na 15
34.9%
116.0 1
 
2.3%
29.39 1
 
2.3%

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

실험실지역코드
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)55.6%
Missing25
Missing (%)58.1%
Infinite0
Infinite (%)0.0%
Mean2.8421274 × 109
Minimum2.7110157 × 109
Maximum4.7290111 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:38.860984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7110157 × 109
5-th percentile2.716111 × 109
Q12.7170103 × 109
median2.7170106 × 109
Q32.7605219 × 109
95-th percentile3.064734 × 109
Maximum4.7290111 × 109
Range2.0179954 × 109
Interquartile range (IQR)43511620

Descriptive statistics

Standard deviation4.7144364 × 108
Coefficient of variation (CV)0.16587703
Kurtosis17.902169
Mean2.8421274 × 109
Median Absolute Deviation (MAD)2997650
Skewness4.2264123
Sum5.1158293 × 1010
Variance2.222591 × 1017
MonotonicityNot monotonic
2024-04-21T20:44:39.236665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2771038022 3
 
7.0%
2717010600 3
 
7.0%
2717010300 3
 
7.0%
2717010200 2
 
4.7%
2729010800 2
 
4.7%
2723010900 1
 
2.3%
2711015700 1
 
2.3%
2771025626 1
 
2.3%
2717010500 1
 
2.3%
4729011100 1
 
2.3%
(Missing) 25
58.1%
ValueCountFrequency (%)
2711015700 1
 
2.3%
2717010200 2
4.7%
2717010300 3
7.0%
2717010500 1
 
2.3%
2717010600 3
7.0%
2723010900 1
 
2.3%
2729010800 2
4.7%
2771025626 1
 
2.3%
2771038022 3
7.0%
4729011100 1
 
2.3%
ValueCountFrequency (%)
4729011100 1
 
2.3%
2771038022 3
7.0%
2771025626 1
 
2.3%
2729010800 2
4.7%
2723010900 1
 
2.3%
2717010600 3
7.0%
2717010500 1
 
2.3%
2717010300 3
7.0%
2717010200 2
4.7%
2711015700 1
 
2.3%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)77.8%
Missing25
Missing (%)58.1%
Infinite0
Infinite (%)0.0%
Mean336181.5
Minimum38652
Maximum704938
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:39.574738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38652
5-th percentile41243.65
Q142142.75
median43010.5
Q3703829
95-th percentile704003.85
Maximum704938
Range666286
Interquartile range (IQR)661686.25

Descriptive statistics

Standard deviation338382.34
Coefficient of variation (CV)1.0065466
Kurtosis-2.1993368
Mean336181.5
Median Absolute Deviation (MAD)2834
Skewness0.24444705
Sum6051267
Variance1.1450261 × 1011
MonotonicityNot monotonic
2024-04-21T20:44:39.923455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
703829 3
 
7.0%
43008 2
 
4.7%
703834 2
 
4.7%
702817 1
 
2.3%
41956 1
 
2.3%
42930 1
 
2.3%
41702 1
 
2.3%
41701 1
 
2.3%
41845 1
 
2.3%
704938 1
 
2.3%
Other values (4) 4
 
9.3%
(Missing) 25
58.1%
ValueCountFrequency (%)
38652 1
2.3%
41701 1
2.3%
41702 1
2.3%
41845 1
2.3%
41956 1
2.3%
42703 1
2.3%
42930 1
2.3%
43008 2
4.7%
43013 1
2.3%
702817 1
2.3%
ValueCountFrequency (%)
704938 1
 
2.3%
703839 1
 
2.3%
703834 2
4.7%
703829 3
7.0%
702817 1
 
2.3%
43013 1
 
2.3%
43008 2
4.7%
42930 1
 
2.3%
42703 1
 
2.3%
41956 1
 
2.3%

실험실산
Categorical

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
<NA>
24 
0
10 
1
9 

Length

Max length4
Median length4
Mean length2.6744186
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 24
55.8%
0 10
23.3%
1 9
 
20.9%

Length

2024-04-21T20:44:40.174524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:40.364748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
55.8%
0 10
23.3%
1 9
 
20.9%

실험실번지
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)72.2%
Missing25
Missing (%)58.1%
Infinite0
Infinite (%)0.0%
Mean822.77778
Minimum82
Maximum2028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:40.656297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum82
5-th percentile150
Q1279.25
median567
Q31278
95-th percentile1821.45
Maximum2028
Range1946
Interquartile range (IQR)998.75

Descriptive statistics

Standard deviation615.54563
Coefficient of variation (CV)0.74813108
Kurtosis-0.86682217
Mean822.77778
Median Absolute Deviation (MAD)390
Skewness0.59513629
Sum14810
Variance378896.42
MonotonicityNot monotonic
2024-04-21T20:44:41.032326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
192 3
 
7.0%
1278 2
 
4.7%
541 2
 
4.7%
567 2
 
4.7%
550 1
 
2.3%
162 1
 
2.3%
1702 1
 
2.3%
1785 1
 
2.3%
2028 1
 
2.3%
1144 1
 
2.3%
Other values (3) 3
 
7.0%
(Missing) 25
58.1%
ValueCountFrequency (%)
82 1
 
2.3%
162 1
 
2.3%
192 3
7.0%
541 2
4.7%
550 1
 
2.3%
567 2
4.7%
719 1
 
2.3%
1144 1
 
2.3%
1278 2
4.7%
1290 1
 
2.3%
ValueCountFrequency (%)
2028 1
2.3%
1785 1
2.3%
1702 1
2.3%
1290 1
2.3%
1278 2
4.7%
1144 1
2.3%
719 1
2.3%
567 2
4.7%
550 1
2.3%
541 2
4.7%

실험실호
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)56.2%
Missing27
Missing (%)62.8%
Infinite0
Infinite (%)0.0%
Mean11.3125
Minimum0
Maximum56
Zeros1
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:41.366415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.75
Q12.5
median8
Q310
95-th percentile39.5
Maximum56
Range56
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation14.360681
Coefficient of variation (CV)1.2694525
Kurtosis6.3849336
Mean11.3125
Median Absolute Deviation (MAD)3.5
Skewness2.4549585
Sum181
Variance206.22917
MonotonicityNot monotonic
2024-04-21T20:44:41.682670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
10 4
 
9.3%
1 3
 
7.0%
8 3
 
7.0%
34 1
 
2.3%
7 1
 
2.3%
0 1
 
2.3%
56 1
 
2.3%
14 1
 
2.3%
3 1
 
2.3%
(Missing) 27
62.8%
ValueCountFrequency (%)
0 1
 
2.3%
1 3
7.0%
3 1
 
2.3%
7 1
 
2.3%
8 3
7.0%
10 4
9.3%
14 1
 
2.3%
34 1
 
2.3%
56 1
 
2.3%
ValueCountFrequency (%)
56 1
 
2.3%
34 1
 
2.3%
14 1
 
2.3%
10 4
9.3%
8 3
7.0%
7 1
 
2.3%
3 1
 
2.3%
1 3
7.0%
0 1
 
2.3%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

실험실특수주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing42
Missing (%)97.7%
Memory size472.0 B
2024-04-21T20:44:42.108920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row대천빌딩
ValueCountFrequency (%)
대천빌딩 1
100.0%
2024-04-21T20:44:42.634762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 1
25.0%
천 1
25.0%
빌 1
25.0%
딩 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1
25.0%
천 1
25.0%
빌 1
25.0%
딩 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1
25.0%
천 1
25.0%
빌 1
25.0%
딩 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 1
25.0%
천 1
25.0%
빌 1
25.0%
딩 1
25.0%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing43
Missing (%)100.0%
Memory size515.0 B

실험실특수주소호
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
<NA>
42 
402
 
1

Length

Max length4
Median length4
Mean length3.9767442
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 42
97.7%
402 1
 
2.3%

Length

2024-04-21T20:44:42.842671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:43.133892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
97.7%
402 1
 
2.3%

실험실도로명주소시군구코드
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)29.2%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean28137.083
Minimum27110
Maximum47290
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:43.419830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27110
5-th percentile27170
Q127170
median27170
Q327395
95-th percentile27710
Maximum47290
Range20180
Interquartile range (IQR)225

Descriptive statistics

Standard deviation4085.3806
Coefficient of variation (CV)0.1451956
Kurtosis23.844578
Mean28137.083
Median Absolute Deviation (MAD)15
Skewness4.8763534
Sum675290
Variance16690335
MonotonicityNot monotonic
2024-04-21T20:44:43.768265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
27170 12
27.9%
27710 5
 
11.6%
27290 3
 
7.0%
27230 1
 
2.3%
27110 1
 
2.3%
27200 1
 
2.3%
47290 1
 
2.3%
(Missing) 19
44.2%
ValueCountFrequency (%)
27110 1
 
2.3%
27170 12
27.9%
27200 1
 
2.3%
27230 1
 
2.3%
27290 3
 
7.0%
27710 5
11.6%
47290 1
 
2.3%
ValueCountFrequency (%)
47290 1
 
2.3%
27710 5
11.6%
27290 3
 
7.0%
27230 1
 
2.3%
27200 1
 
2.3%
27170 12
27.9%
27110 1
 
2.3%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)50.0%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean2.8137241 × 109
Minimum2.7110157 × 109
Maximum4.7290111 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:44.122344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7110157 × 109
5-th percentile2.7170102 × 109
Q12.7170104 × 109
median2.7170106 × 109
Q32.7395145 × 109
95-th percentile2.771038 × 109
Maximum4.7290111 × 109
Range2.0179954 × 109
Interquartile range (IQR)22504056

Descriptive statistics

Standard deviation4.0853757 × 108
Coefficient of variation (CV)0.14519461
Kurtosis23.844442
Mean2.8137241 × 109
Median Absolute Deviation (MAD)1500050
Skewness4.8763337
Sum6.7529378 × 1010
Variance1.6690295 × 1017
MonotonicityNot monotonic
2024-04-21T20:44:44.498426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2717010600 6
 
14.0%
2771038022 3
 
7.0%
2729010800 3
 
7.0%
2717010300 3
 
7.0%
2717010200 2
 
4.7%
2723010900 1
 
2.3%
2711015700 1
 
2.3%
2720010300 1
 
2.3%
2771025626 1
 
2.3%
2717010500 1
 
2.3%
Other values (2) 2
 
4.7%
(Missing) 19
44.2%
ValueCountFrequency (%)
2711015700 1
 
2.3%
2717010200 2
 
4.7%
2717010300 3
7.0%
2717010500 1
 
2.3%
2717010600 6
14.0%
2720010300 1
 
2.3%
2723010900 1
 
2.3%
2729010800 3
7.0%
2771025626 1
 
2.3%
2771033000 1
 
2.3%
ValueCountFrequency (%)
4729011100 1
 
2.3%
2771038022 3
7.0%
2771033000 1
 
2.3%
2771025626 1
 
2.3%
2729010800 3
7.0%
2723010900 1
 
2.3%
2720010300 1
 
2.3%
2717010600 6
14.0%
2717010500 1
 
2.3%
2717010300 3
7.0%

실험실도로명주소읍면동구분
Categorical

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size472.0 B
<NA>
19 
1
19 
0
5 

Length

Max length4
Median length1
Mean length2.3255814
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 19
44.2%
1 19
44.2%
0 5
 
11.6%

Length

2024-04-21T20:44:44.922619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:45.257518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
44.2%
1 19
44.2%
0 5
 
11.6%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)66.7%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean3833531.1
Minimum2007002
Maximum4854696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:45.464645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007002
5-th percentile2007002
Q13143753
median4229218.5
Q34230876
95-th percentile4854695.2
Maximum4854696
Range2847694
Interquartile range (IQR)1087123

Descriptive statistics

Standard deviation884587.81
Coefficient of variation (CV)0.23075013
Kurtosis0.1237635
Mean3833531.1
Median Absolute Deviation (MAD)262684.5
Skewness-1.0297272
Sum92004746
Variance7.824956 × 1011
MonotonicityNot monotonic
2024-04-21T20:44:45.884863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4229173 3
 
7.0%
4229291 3
 
7.0%
2007002 3
 
7.0%
3143005 2
 
4.7%
4854696 2
 
4.7%
3341004 1
 
2.3%
4229269 1
 
2.3%
4235466 1
 
2.3%
4229346 1
 
2.3%
4244552 1
 
2.3%
Other values (6) 6
 
14.0%
(Missing) 19
44.2%
ValueCountFrequency (%)
2007002 3
7.0%
3143005 2
4.7%
3143006 1
 
2.3%
3144002 1
 
2.3%
3341004 1
 
2.3%
4223092 1
 
2.3%
4229173 3
7.0%
4229264 1
 
2.3%
4229269 1
 
2.3%
4229291 3
7.0%
ValueCountFrequency (%)
4854696 2
4.7%
4854691 1
 
2.3%
4739254 1
 
2.3%
4244552 1
 
2.3%
4235466 1
 
2.3%
4229346 1
 
2.3%
4229291 3
7.0%
4229269 1
 
2.3%
4229264 1
 
2.3%
4229173 3
7.0%

실험실도로명특수주소
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing40
Missing (%)93.0%
Memory size472.0 B
2024-04-21T20:44:46.439466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length7.3333333
Min length4

Characters and Unicode

Total characters22
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

Unique3 ?
Unique (%)100.0%

Sample

1st row대천빌딩
2nd row제일환경측정(주)
3rd row(주)중앙환경기술
ValueCountFrequency (%)
대천빌딩 1
33.3%
제일환경측정(주 1
33.3%
주)중앙환경기술 1
33.3%
2024-04-21T20:44:47.133487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 2
 
9.1%
) 2
 
9.1%
환 2
 
9.1%
경 2
 
9.1%
주 2
 
9.1%
대 1
 
4.5%
기 1
 
4.5%
앙 1
 
4.5%
중 1
 
4.5%
측 1
 
4.5%
Other values (7) 7
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18
81.8%
Open Punctuation 2
 
9.1%
Close Punctuation 2
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
환 2
 
11.1%
경 2
 
11.1%
주 2
 
11.1%
대 1
 
5.6%
기 1
 
5.6%
앙 1
 
5.6%
중 1
 
5.6%
측 1
 
5.6%
정 1
 
5.6%
천 1
 
5.6%
Other values (5) 5
27.8%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18
81.8%
Common 4
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
환 2
 
11.1%
경 2
 
11.1%
주 2
 
11.1%
대 1
 
5.6%
기 1
 
5.6%
앙 1
 
5.6%
중 1
 
5.6%
측 1
 
5.6%
정 1
 
5.6%
천 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18
81.8%
ASCII 4
 
18.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%
Hangul
ValueCountFrequency (%)
환 2
 
11.1%
경 2
 
11.1%
주 2
 
11.1%
대 1
 
5.6%
기 1
 
5.6%
앙 1
 
5.6%
중 1
 
5.6%
측 1
 
5.6%
정 1
 
5.6%
천 1
 
5.6%
Other values (5) 5
27.8%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size472.0 B
0
24 
<NA>
19 

Length

Max length4
Median length1
Mean length2.3255814
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 24
55.8%
<NA> 19
44.2%

Length

2024-04-21T20:44:47.544710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:47.872631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
55.8%
na 19
44.2%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)66.7%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean202.95833
Minimum1
Maximum1222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:48.178699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q112.75
median38.5
Q3161.25
95-th percentile1221.85
Maximum1222
Range1221
Interquartile range (IQR)148.5

Descriptive statistics

Standard deviation398.06679
Coefficient of variation (CV)1.9613227
Kurtosis3.869393
Mean202.95833
Median Absolute Deviation (MAD)28
Skewness2.313617
Sum4871
Variance158457.17
MonotonicityNot monotonic
2024-04-21T20:44:48.558847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
24 3
 
7.0%
9 3
 
7.0%
12 2
 
4.7%
165 2
 
4.7%
1222 2
 
4.7%
63 2
 
4.7%
15 1
 
2.3%
32 1
 
2.3%
49 1
 
2.3%
160 1
 
2.3%
Other values (6) 6
 
14.0%
(Missing) 19
44.2%
ValueCountFrequency (%)
1 1
 
2.3%
9 3
7.0%
12 2
4.7%
13 1
 
2.3%
15 1
 
2.3%
24 3
7.0%
32 1
 
2.3%
45 1
 
2.3%
49 1
 
2.3%
63 2
4.7%
ValueCountFrequency (%)
1222 2
4.7%
1221 1
2.3%
230 1
2.3%
165 2
4.7%
160 1
2.3%
82 1
2.3%
63 2
4.7%
49 1
2.3%
45 1
2.3%
32 1
2.3%

실험실도로명주소건물부번호
Categorical

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size472.0 B
<NA>
30 
0
8 
7
 
3
1
 
1
10
 
1

Length

Max length4
Median length4
Mean length3.1162791
Min length1

Unique

Unique2 ?
Unique (%)4.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
69.8%
0 8
 
18.6%
7 3
 
7.0%
1 1
 
2.3%
10 1
 
2.3%

Length

2024-04-21T20:44:48.972789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T20:44:49.320509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
69.8%
0 8
 
18.6%
7 3
 
7.0%
1 1
 
2.3%
10 1
 
2.3%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)75.0%
Missing19
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean400958.08
Minimum38652
Maximum711821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size515.0 B
2024-04-21T20:44:49.635852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38652
5-th percentile41701.15
Q142680.25
median703323
Q3703831
95-th percentile705674.1
Maximum711821
Range673169
Interquartile range (IQR)661150.75

Descriptive statistics

Standard deviation337203.68
Coefficient of variation (CV)0.84099484
Kurtosis-2.1555323
Mean400958.08
Median Absolute Deviation (MAD)5489.5
Skewness-0.17855417
Sum9622994
Variance1.1370632 × 1011
MonotonicityNot monotonic
2024-04-21T20:44:50.000572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
703829 3
 
7.0%
703830 3
 
7.0%
703834 2
 
4.7%
43008 2
 
4.7%
705804 1
 
2.3%
42930 1
 
2.3%
41702 1
 
2.3%
41701 1
 
2.3%
702817 1
 
2.3%
711821 1
 
2.3%
Other values (8) 8
18.6%
(Missing) 19
44.2%
ValueCountFrequency (%)
38652 1
2.3%
41701 1
2.3%
41702 1
2.3%
41845 1
2.3%
41956 1
2.3%
42612 1
2.3%
42703 1
2.3%
42930 1
2.3%
43008 2
4.7%
43013 1
2.3%
ValueCountFrequency (%)
711821 1
 
2.3%
705804 1
 
2.3%
704938 1
 
2.3%
703839 1
 
2.3%
703834 2
4.7%
703830 3
7.0%
703829 3
7.0%
702817 1
 
2.3%
43013 1
 
2.3%
43008 2
4.7%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
01환경관리대행기관09_30_15_P62700006270000102018000022023-04-06<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-830대구광역시 서구 이현동 44번지 110호대구광역시 서구 국채보상로19길 15 (이현동)703-830에이치디이엔씨(주)2023-04-06 09:48:59U2023-04-08 02:40:00<NA>339130.306851264420.55530171.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12환경관리대행기관09_30_15_P62700006270000102020000042021-08-13<NA>3폐업Q폐업2022-02-16<NA><NA><NA><NA><NA>43008대구광역시 달성군 구지면 응암리 1278-10대구광역시 달성군 구지면 국가산단대로46길 6343008(주)지이테크2022-02-18 08:34:42U2022-02-20 02:40:00<NA>328923.524848239903.4240580.0환경관리대행기관0.0<NA>2771038022430080127810<NA><NA><NA><NA><NA>27710277103802204854696<NA>063043008
23환경관리대행기관09_30_15_P62700006270000102013000152022-09-20<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704-932대구광역시 달서구 죽전동 372번지대구광역시 달서구 평리로 92 (죽전동)42627대동환경측정(주)2022-09-20 10:35:03U2022-09-22 02:40:00<NA>338701.951391262918.24444974.9환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34환경관리대행기관09_30_15_P62700006270000102013000172018-06-29<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704-919대구광역시 달서구 신당동 1320번지 2호 이앤씨이노비즈타워 609호대구광역시 달서구 달서대로 559, 609호 (신당동,이앤씨이노비즈타워)704-919(주)대일환경기술2018-06-29 10:20:49I2019-03-23 02:20:03<NA>334621.225168262044.332358<NA>환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45환경관리대행기관09_30_15_P62700006270000102014000012023-06-19<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>702-817대구광역시 북구 노원3가 550번지 1호대구광역시 북구 팔달북로15길 12 (노원동3가)702-817(주)삼안환경측정2023-06-19 10:04:54U2023-06-21 02:40:00<NA>340487.8153266848.8953780.0환경관리대행기관0.0<NA>272301090070281715501<NA><NA><NA><NA><NA>27230272301090014235466<NA>012<NA>702817
56환경관리대행기관09_30_15_P62700006270000102019000032022-05-26<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>42156대구광역시 수성구 중동 584-1대구광역시 수성구 청수로 10, 3층 (중동)42156기림환경산업(주)2022-05-26 14:47:48U2022-05-28 02:40:00<NA>345314.862155261271.1593870.0환경관리대행기관116.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
67환경관리대행기관09_30_15_P62700006270000102019000052020-02-04<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA>대구광역시 서구 중리동 1044-2대구광역시 서구 와룡로69길 34 (중리동)<NA>(주)티피엘환경2020-02-04 10:03:14U2020-02-06 02:40:00<NA><NA><NA><NA>환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78환경관리대행기관09_30_15_P62700006270000102020000022023-05-23<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-830대구광역시 서구 이현동 42번지 450호대구광역시 서구 와룡로87길 24 (이현동)703-830(주)신라엔텍2023-05-23 11:39:22U2023-05-25 02:40:00<NA>338615.861319264602.3815475.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27170271701060014229291<NA>024<NA>703830
89환경관리대행기관09_30_15_P62700006270000102021000052023-06-23<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>41956대구광역시 중구 대봉동 162-34 대천빌딩대구광역시 중구 명덕로55길 1, 대천빌딩 6층(대봉동)41956(주)대림종합환경2023-06-23 15:26:49U2023-06-25 02:40:00<NA>344442.196016262913.128620.0환경관리대행기관0.0<NA>271101570041956016234<NA><NA>대천빌딩<NA><NA>27110271101570014223092대천빌딩01041956
910환경관리대행기관09_30_15_P62700006270000102015000012023-06-21<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 남구 대명남로 160 (대명동)705-804(주)대영종합환경2023-06-21 18:41:58U2023-06-23 02:40:00<NA>342283.311178260627.0739870.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27200272001030013144002<NA>0160<NA>705804
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
3334환경관리대행기관09_30_15_P62700006270000102021000062021-09-06<NA>3폐업Q폐업2021-10-27<NA><NA><NA><NA><NA>41841대구광역시 서구 중리동 1076-14대구광역시 서구 와룡로72길 37-4(중리동)41841(주)정도엔지니어링2022-05-12 10:54:07U2022-05-14 02:40:00<NA>339171.108666263934.4885020.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3435환경관리대행기관09_30_15_P62700006270000102018000032020-01-21<NA>3폐업Q폐업2020-03-30<NA><NA><NA><NA><NA>41028대구광역시 동구 봉무동 1560-1대구광역시 동구 팔공로 227, DTC 404호 (봉무동)41028우영엔텍2020-10-22 16:59:09U2020-10-24 02:40:00<NA>347956.202203270013.374392<NA>환경관리대행기관<NA><NA>4729011100386520823<NA><NA><NA><NA><NA>47290472901110014739254(주)중앙환경기술082038652
3536환경관리대행기관09_30_15_P62700006270000102013000112017-08-29<NA>3폐업Q폐업2018-10-02<NA><NA><NA><NA><NA>703-829대구광역시 서구 이현동 192번지 8호대구광역시 서구 북비산로17길 9-7 (이현동)703-829국일공해측정(주)2018-10-02 09:19:50I2018-10-04 02:37:36<NA>339211.707883265438.542003210.0환경관리대행기관<NA><NA>271701060070382911928<NA><NA><NA><NA><NA>27170271701060014229173<NA>097703829
3637환경관리대행기관09_30_15_P62700006270000102020000032020-09-18<NA>3폐업Q폐업2021-05-03<NA><NA><NA><NA><NA>41081대구광역시 동구 각산동 301-9대구광역시 동구 안심로59길 6 (각산동)41081(주)주연물산2021-07-05 11:07:02U2021-07-07 02:40:00<NA>355172.287752264325.197625<NA>환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3738환경관리대행기관09_30_15_P62700006270000102021000032021-03-30<NA>3폐업Q폐업2021-10-29<NA><NA><NA><NA><NA>41480대구광역시 북구 서변동 1290-4대구광역시 북구 조야로2길 209 (서변동)41480대구에코(주) 신천사업소2022-01-03 18:03:05U2022-01-05 02:40:00<NA>343919.78989268905.6271560.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3839환경관리대행기관09_30_15_P62700006270000102013000072021-02-25<NA>3폐업Q폐업2021-03-18<NA><NA><NA><NA><NA>702-817대구광역시 북구 노원3가 550번지 1호대구광역시 북구 팔달북로15길 12 (노원동3가)702-817(주)삼안환경측정2021-03-18 14:03:38U2021-03-20 02:40:00<NA>340487.8153266848.895378173.49환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3940환경관리대행기관09_30_15_P62700006270000102013000082018-03-02<NA>3폐업Q폐업2018-10-20<NA><NA><NA><NA><NA>703-830대구광역시 서구 이현동 44번지 110호대구광역시 서구 국채보상로19길 15 (이현동)703-830현대공해측정(주)2018-10-20 13:47:49I2018-11-03 13:17:14<NA>339130.306851264420.55530171.0환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4041환경관리대행기관09_30_15_P62700006270000102017000012017-07-07<NA>3폐업Q폐업2018-12-13<NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 달구벌대로 1221, 3층 (이곡동)42612(주)정도환경2018-12-20 08:47:54I2018-12-22 02:20:24<NA>335525.948847262370.376561<NA>환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27290272901080012007002<NA>01221<NA>42612
4142환경관리대행기관09_30_15_P62700006270000102018000012020-08-05<NA>3폐업Q폐업2020-08-21<NA><NA><NA><NA><NA>703-830대구광역시 서구 이현동 42번지 450호대구광역시 서구 와룡로87길 24 (이현동)703-830(주)신라엔텍2020-08-21 13:15:50U2020-08-23 02:40:00<NA>338615.861319264602.3815475.0환경관리대행기관0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>27170271701060014229291<NA>024<NA>703830
4243환경관리대행기관09_30_15_P62700006270000102013000132023-05-19<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-839대구광역시 서구 평리3동 719번지 1호대구광역시 서구 서대구로 230 (평리동)703-839케이지엔텍2023-05-19 10:26:10U2023-05-21 02:40:00<NA>340371.264862265362.72131872.0환경관리대행기관0.0<NA>271701030070383917191<NA><NA><NA><NA><NA>27170271701030013143006<NA>0230<NA>703839