Overview

Dataset statistics

Number of variables52
Number of observations35
Missing cells568
Missing cells (%)31.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory458.8 B

Variable types

Numeric13
Categorical22
Unsupported12
Text4
DateTime1

Dataset

Description2021-02-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123163

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
개방자치단체코드 has constant value ""Constant
사업장구분명 has constant value ""Constant
소재지우편번호 is highly imbalanced (62.7%)Imbalance
영업소면적 is highly imbalanced (60.6%)Imbalance
실험실지역코드 is highly imbalanced (53.0%)Imbalance
실험실우편번호 is highly imbalanced (55.6%)Imbalance
실험실번지 is highly imbalanced (55.6%)Imbalance
실험실호 is highly imbalanced (55.6%)Imbalance
실험실특수주소호 is highly imbalanced (76.5%)Imbalance
실험실도로명특수주소 is highly imbalanced (57.8%)Imbalance
실험실도로명주소건물부번호 is highly imbalanced (51.3%)Imbalance
인허가취소일자 has 35 (100.0%) missing valuesMissing
폐업일자 has 17 (48.6%) missing valuesMissing
휴업시작일자 has 35 (100.0%) missing valuesMissing
휴업종료일자 has 35 (100.0%) missing valuesMissing
재개업일자 has 35 (100.0%) missing valuesMissing
소재지전화 has 35 (100.0%) missing valuesMissing
소재지면적 has 35 (100.0%) missing valuesMissing
소재지전체주소 has 28 (80.0%) missing valuesMissing
도로명우편번호 has 2 (5.7%) missing valuesMissing
업태구분명 has 35 (100.0%) missing valuesMissing
좌표정보(x) has 5 (14.3%) missing valuesMissing
좌표정보(y) has 5 (14.3%) missing valuesMissing
위탁업체명 has 35 (100.0%) missing valuesMissing
실험실통 has 35 (100.0%) missing valuesMissing
실험실반 has 35 (100.0%) missing valuesMissing
실험실특수주소 has 31 (88.6%) missing valuesMissing
실험실특수주소동 has 35 (100.0%) missing valuesMissing
실험실도로명주소시군구코드 has 12 (34.3%) missing valuesMissing
실험실도로명주소읍면동코드 has 12 (34.3%) missing valuesMissing
실험실도로명주소코드 has 12 (34.3%) missing valuesMissing
실험실도로명주소건물본번호 has 12 (34.3%) missing valuesMissing
실험실도로명주소우편번호 has 12 (34.3%) missing valuesMissing
Unnamed: 51 has 35 (100.0%) 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
Unnamed: 51 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 13:38:43.969157
Analysis finished2024-04-16 13:38:44.445121
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:44.499131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2024-04-16T22:38:44.631345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
27 1
 
2.9%
28 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
환경관리대행기관
35 

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 35
100.0%

Length

2024-04-16T22:38:44.744797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:44.828002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경관리대행기관 35
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
09_30_15_P
35 

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 35
100.0%

Length

2024-04-16T22:38:44.920401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:45.013080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_15_p 35
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
6260000
35 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6260000
2nd row6260000
3rd row6260000
4th row6260000
5th row6260000

Common Values

ValueCountFrequency (%)
6260000 35
100.0%

Length

2024-04-16T22:38:45.104169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:45.184581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6260000 35
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2600001 × 1017
Minimum6.2600001 × 1017
Maximum6.2600001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:45.274579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.2600001 × 1017
5-th percentile6.2600001 × 1017
Q16.2600001 × 1017
median6.2600001 × 1017
Q36.2600001 × 1017
95-th percentile6.2600001 × 1017
Maximum6.2600001 × 1017
Range700001
Interquartile range (IQR)400000

Descriptive statistics

Standard deviation260660.72
Coefficient of variation (CV)4.1639092 × 10-13
Kurtosis-0.97912855
Mean6.2600001 × 1017
Median Absolute Deviation (MAD)0
Skewness0.84598266
Sum3.4632563 × 1018
Variance6.7944011 × 1010
MonotonicityNot monotonic
2024-04-16T22:38:45.386744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
626000010201300007 1
 
2.9%
626000010201900001 1
 
2.9%
626000010201300008 1
 
2.9%
626000010201300013 1
 
2.9%
626000010201300014 1
 
2.9%
626000010201300015 1
 
2.9%
626000010201300017 1
 
2.9%
626000010201300019 1
 
2.9%
626000010201500004 1
 
2.9%
626000010201300002 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
626000010201300001 1
2.9%
626000010201300002 1
2.9%
626000010201300003 1
2.9%
626000010201300004 1
2.9%
626000010201300005 1
2.9%
626000010201300006 1
2.9%
626000010201300007 1
2.9%
626000010201300008 1
2.9%
626000010201300009 1
2.9%
626000010201300010 1
2.9%
ValueCountFrequency (%)
626000010202000002 1
2.9%
626000010202000001 1
2.9%
626000010201900005 1
2.9%
626000010201900004 1
2.9%
626000010201900003 1
2.9%
626000010201900002 1
2.9%
626000010201900001 1
2.9%
626000010201800001 1
2.9%
626000010201700003 1
2.9%
626000010201700002 1
2.9%

인허가일자
Real number (ℝ)

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20180203
Minimum20130609
Maximum20201230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:45.525440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130609
5-th percentile20137868
Q120160420
median20190218
Q320200763
95-th percentile20201212
Maximum20201230
Range70621
Interquartile range (IQR)40343

Descriptive statistics

Standard deviation23157.636
Coefficient of variation (CV)0.0011475423
Kurtosis-0.62197786
Mean20180203
Median Absolute Deviation (MAD)10901
Skewness-0.85268293
Sum7.0630709 × 108
Variance5.3627612 × 108
MonotonicityNot monotonic
2024-04-16T22:38:45.666028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20170912 2
 
5.7%
20201119 2
 
5.7%
20200916 1
 
2.9%
20151112 1
 
2.9%
20160509 1
 
2.9%
20150320 1
 
2.9%
20130609 1
 
2.9%
20140724 1
 
2.9%
20141021 1
 
2.9%
20150827 1
 
2.9%
Other values (23) 23
65.7%
ValueCountFrequency (%)
20130609 1
2.9%
20131203 1
2.9%
20140724 1
2.9%
20141021 1
2.9%
20150320 1
2.9%
20150827 1
2.9%
20151112 1
2.9%
20160325 1
2.9%
20160331 1
2.9%
20160509 1
2.9%
ValueCountFrequency (%)
20201230 1
2.9%
20201216 1
2.9%
20201211 1
2.9%
20201207 1
2.9%
20201119 2
5.7%
20201104 1
2.9%
20201008 1
2.9%
20200916 1
2.9%
20200610 1
2.9%
20200515 1
2.9%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
3
18 
1
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 18
51.4%
1 17
48.6%

Length

2024-04-16T22:38:45.784513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:45.873724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 18
51.4%
1 17
48.6%

영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
18 
영업/정상
17 

Length

Max length5
Median length2
Mean length3.4571429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 18
51.4%
영업/정상 17
48.6%

Length

2024-04-16T22:38:46.226394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:46.320849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 18
51.4%
영업/정상 17
48.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
Q
18 
N
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Q 18
51.4%
N 17
48.6%

Length

2024-04-16T22:38:46.418323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:46.523474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 18
51.4%
n 17
48.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
폐업
18 
신규
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 18
51.4%
신규 17
48.6%

Length

2024-04-16T22:38:46.638586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:46.727218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 18
51.4%
신규 17
48.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)77.8%
Missing17
Missing (%)48.6%
Infinite0
Infinite (%)0.0%
Mean20170220
Minimum20131202
Maximum20200703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:46.809266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20131202
5-th percentile20139296
Q120160432
median20175813
Q320181090
95-th percentile20191864
Maximum20200703
Range69501
Interquartile range (IQR)20658.25

Descriptive statistics

Standard deviation19705.16
Coefficient of variation (CV)0.00097694327
Kurtosis-0.62201352
Mean20170220
Median Absolute Deviation (MAD)14448.5
Skewness-0.52664941
Sum3.6306395 × 108
Variance3.8829334 × 108
MonotonicityNot monotonic
2024-04-16T22:38:46.911887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
20181024 4
 
11.4%
20190219 2
 
5.7%
20190304 1
 
2.9%
20131202 1
 
2.9%
20170602 1
 
2.9%
20170329 1
 
2.9%
20161201 1
 
2.9%
20150901 1
 
2.9%
20140724 1
 
2.9%
20141021 1
 
2.9%
Other values (4) 4
 
11.4%
(Missing) 17
48.6%
ValueCountFrequency (%)
20131202 1
 
2.9%
20140724 1
 
2.9%
20141021 1
 
2.9%
20150901 1
 
2.9%
20160204 1
 
2.9%
20161115 1
 
2.9%
20161201 1
 
2.9%
20170329 1
 
2.9%
20170602 1
 
2.9%
20181024 4
11.4%
ValueCountFrequency (%)
20200703 1
 
2.9%
20190304 1
 
2.9%
20190219 2
5.7%
20181112 1
 
2.9%
20181024 4
11.4%
20170602 1
 
2.9%
20170329 1
 
2.9%
20161201 1
 
2.9%
20161115 1
 
2.9%
20160204 1
 
2.9%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

소재지우편번호
Categorical

IMBALANCE 

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
30 
46033
 
2
46917
 
1
48059
 
1
46916
 
1

Length

Max length5
Median length4
Mean length4.1428571
Min length4

Unique

Unique3 ?
Unique (%)8.6%

Sample

1st row<NA>
2nd row46033
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
85.7%
46033 2
 
5.7%
46917 1
 
2.9%
48059 1
 
2.9%
46916 1
 
2.9%

Length

2024-04-16T22:38:47.025635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:47.137528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
85.7%
46033 2
 
5.7%
46917 1
 
2.9%
48059 1
 
2.9%
46916 1
 
2.9%

소재지전체주소
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing28
Missing (%)80.0%
Memory size412.0 B
2024-04-16T22:38:47.285177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length27
Mean length26.428571
Min length19

Characters and Unicode

Total characters185
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row부산광역시 기장군 장안읍 좌천리 520번지 대성전기철물
2nd row부산광역시 기장군 장안읍 좌천리 286-1 좌천슈퍼
3rd row부산광역시 사상구 모라동 283-11
4th row부산광역시 해운대구 재송동 1212번지 큐비이센텀 2403~2406호
5th row부산광역시 동래구 사직동 137-5
ValueCountFrequency (%)
부산광역시 7
19.4%
장안읍 3
 
8.3%
좌천리 3
 
8.3%
기장군 3
 
8.3%
520번지 2
 
5.6%
사상구 2
 
5.6%
모라동 2
 
5.6%
큐비이센텀 1
 
2.8%
282-6 1
 
2.8%
137-5 1
 
2.8%
Other values (11) 11
30.6%
2024-04-16T22:38:47.583495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
15.7%
2 10
 
5.4%
산 8
 
4.3%
부 7
 
3.8%
광 7
 
3.8%
역 7
 
3.8%
시 7
 
3.8%
장 6
 
3.2%
1 6
 
3.2%
동 5
 
2.7%
Other values (46) 93
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
62.7%
Decimal Number 35
 
18.9%
Space Separator 29
 
15.7%
Dash Punctuation 4
 
2.2%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 8
 
6.9%
부 7
 
6.0%
광 7
 
6.0%
역 7
 
6.0%
시 7
 
6.0%
장 6
 
5.2%
동 5
 
4.3%
좌 4
 
3.4%
천 4
 
3.4%
구 4
 
3.4%
Other values (34) 57
49.1%
Decimal Number
ValueCountFrequency (%)
2 10
28.6%
1 6
17.1%
0 4
 
11.4%
6 3
 
8.6%
8 3
 
8.6%
3 3
 
8.6%
5 3
 
8.6%
4 2
 
5.7%
7 1
 
2.9%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116
62.7%
Common 69
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 8
 
6.9%
부 7
 
6.0%
광 7
 
6.0%
역 7
 
6.0%
시 7
 
6.0%
장 6
 
5.2%
동 5
 
4.3%
좌 4
 
3.4%
천 4
 
3.4%
구 4
 
3.4%
Other values (34) 57
49.1%
Common
ValueCountFrequency (%)
29
42.0%
2 10
 
14.5%
1 6
 
8.7%
0 4
 
5.8%
- 4
 
5.8%
6 3
 
4.3%
8 3
 
4.3%
3 3
 
4.3%
5 3
 
4.3%
4 2
 
2.9%
Other values (2) 2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116
62.7%
ASCII 69
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
42.0%
2 10
 
14.5%
1 6
 
8.7%
0 4
 
5.8%
- 4
 
5.8%
6 3
 
4.3%
8 3
 
4.3%
3 3
 
4.3%
5 3
 
4.3%
4 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
산 8
 
6.9%
부 7
 
6.0%
광 7
 
6.0%
역 7
 
6.0%
시 7
 
6.0%
장 6
 
5.2%
동 5
 
4.3%
좌 4
 
3.4%
천 4
 
3.4%
구 4
 
3.4%
Other values (34) 57
49.1%

도로명전체주소
Text

Distinct30
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-04-16T22:38:47.842322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length27.657143
Min length19

Characters and Unicode

Total characters968
Distinct characters121
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)74.3%

Sample

1st row부산광역시 사상구 백양대로 539-35 (주례동)
2nd row부산광역시 기장군 장안읍 좌천로 40, 대성전기철물
3rd row부산광역시 사상구 백양대로 483 (주례동)
4th row부산광역시 동래구 여고로 61 (사직동)
5th row부산광역시 금정구 동부곡로23번길 30 (부곡동)
ValueCountFrequency (%)
부산광역시 35
 
18.2%
사상구 8
 
4.2%
기장군 6
 
3.1%
장안읍 5
 
2.6%
동래구 5
 
2.6%
3층 4
 
2.1%
금정구 4
 
2.1%
새벽로 3
 
1.6%
183 3
 
1.6%
좌천로 3
 
1.6%
Other values (88) 116
60.4%
2024-04-16T22:38:48.231157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
157
 
16.2%
부 39
 
4.0%
산 39
 
4.0%
동 36
 
3.7%
광 35
 
3.6%
역 35
 
3.6%
시 35
 
3.6%
로 34
 
3.5%
( 29
 
3.0%
) 29
 
3.0%
Other values (111) 500
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 581
60.0%
Space Separator 157
 
16.2%
Decimal Number 151
 
15.6%
Open Punctuation 29
 
3.0%
Close Punctuation 29
 
3.0%
Other Punctuation 18
 
1.9%
Dash Punctuation 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 39
 
6.7%
산 39
 
6.7%
동 36
 
6.2%
광 35
 
6.0%
역 35
 
6.0%
시 35
 
6.0%
로 34
 
5.9%
구 29
 
5.0%
대 16
 
2.8%
사 16
 
2.8%
Other values (95) 267
46.0%
Decimal Number
ValueCountFrequency (%)
1 28
18.5%
3 28
18.5%
2 24
15.9%
0 16
10.6%
5 12
7.9%
4 12
7.9%
7 9
 
6.0%
9 9
 
6.0%
8 7
 
4.6%
6 6
 
4.0%
Space Separator
ValueCountFrequency (%)
157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 581
60.0%
Common 387
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 39
 
6.7%
산 39
 
6.7%
동 36
 
6.2%
광 35
 
6.0%
역 35
 
6.0%
시 35
 
6.0%
로 34
 
5.9%
구 29
 
5.0%
대 16
 
2.8%
사 16
 
2.8%
Other values (95) 267
46.0%
Common
ValueCountFrequency (%)
157
40.6%
( 29
 
7.5%
) 29
 
7.5%
1 28
 
7.2%
3 28
 
7.2%
2 24
 
6.2%
, 18
 
4.7%
0 16
 
4.1%
5 12
 
3.1%
4 12
 
3.1%
Other values (6) 34
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 581
60.0%
ASCII 387
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
157
40.6%
( 29
 
7.5%
) 29
 
7.5%
1 28
 
7.2%
3 28
 
7.2%
2 24
 
6.2%
, 18
 
4.7%
0 16
 
4.1%
5 12
 
3.1%
4 12
 
3.1%
Other values (6) 34
 
8.8%
Hangul
ValueCountFrequency (%)
부 39
 
6.7%
산 39
 
6.7%
동 36
 
6.2%
광 35
 
6.0%
역 35
 
6.0%
시 35
 
6.0%
로 34
 
5.9%
구 29
 
5.0%
대 16
 
2.8%
사 16
 
2.8%
Other values (95) 267
46.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean338041.58
Minimum46033
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:48.357360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46033
5-th percentile46033
Q146980
median600012
Q3609843
95-th percentile619262.6
Maximum619952
Range573919
Interquartile range (IQR)562863

Descriptive statistics

Standard deviation286529.11
Coefficient of variation (CV)0.84761501
Kurtosis-2.1280008
Mean338041.58
Median Absolute Deviation (MAD)19940
Skewness-0.062844232
Sum11155372
Variance8.2098933 × 1010
MonotonicityNot monotonic
2024-04-16T22:38:48.467683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
46980 3
 
8.6%
46033 3
 
8.6%
49514 2
 
5.7%
46607 2
 
5.7%
619952 2
 
5.7%
607840 2
 
5.7%
609843 2
 
5.7%
617807 1
 
2.9%
46700 1
 
2.9%
47537 1
 
2.9%
Other values (14) 14
40.0%
(Missing) 2
 
5.7%
ValueCountFrequency (%)
46033 3
8.6%
46607 2
5.7%
46700 1
 
2.9%
46916 1
 
2.9%
46917 1
 
2.9%
46980 3
8.6%
47537 1
 
2.9%
48059 1
 
2.9%
48409 1
 
2.9%
49514 2
5.7%
ValueCountFrequency (%)
619952 2
5.7%
618803 1
2.9%
617836 1
2.9%
617833 1
2.9%
617807 1
2.9%
614866 1
2.9%
609852 1
2.9%
609843 2
5.7%
609822 1
2.9%
607840 2
5.7%

사업장명
Text

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-04-16T22:38:48.654752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.7714286
Min length4

Characters and Unicode

Total characters272
Distinct characters72
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

Unique19 ?
Unique (%)54.3%

Sample

1st row(주)영동엔지니어링
2nd row동부환경
3rd row금호환경(주)
4th row(주)한서엔텍
5th row(주)한신환경
ValueCountFrequency (%)
초석환경기술단 3
 
8.6%
동부환경 3
 
8.6%
주)홍익환경 2
 
5.7%
금호환경(주 2
 
5.7%
세영환경산업(주 2
 
5.7%
천호환경(주 2
 
5.7%
주)대한환경이엔지 2
 
5.7%
주)동진에코 1
 
2.9%
주)태진엔지니어링 1
 
2.9%
주)고성인텍 1
 
2.9%
Other values (16) 16
45.7%
2024-04-16T22:38:48.940467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 28
 
10.3%
( 28
 
10.3%
) 28
 
10.3%
환 23
 
8.5%
경 23
 
8.5%
이 7
 
2.6%
기 6
 
2.2%
술 6
 
2.2%
동 6
 
2.2%
엔 6
 
2.2%
Other values (62) 111
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
79.4%
Open Punctuation 28
 
10.3%
Close Punctuation 28
 
10.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 28
 
13.0%
환 23
 
10.6%
경 23
 
10.6%
이 7
 
3.2%
기 6
 
2.8%
술 6
 
2.8%
동 6
 
2.8%
엔 6
 
2.8%
지 5
 
2.3%
영 5
 
2.3%
Other values (60) 101
46.8%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
79.4%
Common 56
 
20.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 28
 
13.0%
환 23
 
10.6%
경 23
 
10.6%
이 7
 
3.2%
기 6
 
2.8%
술 6
 
2.8%
동 6
 
2.8%
엔 6
 
2.8%
지 5
 
2.3%
영 5
 
2.3%
Other values (60) 101
46.8%
Common
ValueCountFrequency (%)
( 28
50.0%
) 28
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
79.4%
ASCII 56
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 28
 
13.0%
환 23
 
10.6%
경 23
 
10.6%
이 7
 
3.2%
기 6
 
2.8%
술 6
 
2.8%
동 6
 
2.8%
엔 6
 
2.8%
지 5
 
2.3%
영 5
 
2.3%
Other values (60) 101
46.8%
ASCII
ValueCountFrequency (%)
( 28
50.0%
) 28
50.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0185585 × 1013
Minimum2.0140724 × 1013
Maximum2.020123 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:49.067844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0140724 × 1013
5-th percentile2.0150995 × 1013
Q12.0175811 × 1013
median2.0190219 × 1013
Q32.0200817 × 1013
95-th percentile2.0201213 × 1013
Maximum2.020123 × 1013
Range6.050603 × 1010
Interquartile range (IQR)2.5006029 × 1010

Descriptive statistics

Standard deviation1.7577936 × 1010
Coefficient of variation (CV)0.00087081629
Kurtosis0.19099535
Mean2.0185585 × 1013
Median Absolute Deviation (MAD)1.0697001 × 1010
Skewness-1.0287437
Sum7.0649548 × 1014
Variance3.0898384 × 1020
MonotonicityNot monotonic
2024-04-16T22:38:49.211813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
20200916113229 1
 
2.9%
20190117183426 1
 
2.9%
20170613103919 1
 
2.9%
20170329160125 1
 
2.9%
20170206190058 1
 
2.9%
20151202164608 1
 
2.9%
20140724144403 1
 
2.9%
20151202164711 1
 
2.9%
20170206185824 1
 
2.9%
20170206190214 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
20140724144403 1
2.9%
20150511092306 1
2.9%
20151202164608 1
2.9%
20151202164711 1
2.9%
20170206185824 1
2.9%
20170206190058 1
2.9%
20170206190214 1
2.9%
20170329160125 1
2.9%
20170613103919 1
2.9%
20181008111019 1
2.9%
ValueCountFrequency (%)
20201230174208 1
2.9%
20201216105229 1
2.9%
20201211125629 1
2.9%
20201207104032 1
2.9%
20201119100202 1
2.9%
20201119094038 1
2.9%
20201104172146 1
2.9%
20201008173422 1
2.9%
20200916113229 1
2.9%
20200717160008 1
2.9%

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
I
18 
U
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 18
51.4%
U 17
48.6%

Length

2024-04-16T22:38:49.332520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:49.429088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 18
51.4%
u 17
48.6%

데이터갱신일자
Date

Distinct23
Distinct (%)65.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2018-10-10 02:37:31
Maximum2021-01-01 02:40:00
2024-04-16T22:38:49.518860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T22:38:49.643839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)80.0%
Missing5
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean388837.85
Minimum378026
Maximum405926.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:49.752505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum378026
5-th percentile380437.6
Q1381194.91
median388316.45
Q3390230.41
95-th percentile404744.88
Maximum405926.8
Range27900.804
Interquartile range (IQR)9035.4924

Descriptive statistics

Standard deviation8214.1743
Coefficient of variation (CV)0.021124935
Kurtosis0.061943511
Mean388837.85
Median Absolute Deviation (MAD)4068.7434
Skewness0.96416751
Sum11665135
Variance67472659
MonotonicityNot monotonic
2024-04-16T22:38:49.855642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
380645.672312821 3
 
8.6%
403947.265423154 3
 
8.6%
388316.452069542 2
 
5.7%
385468.443590649 2
 
5.7%
378026.0 1
 
2.9%
390027.195360975 1
 
2.9%
389000.736159624 1
 
2.9%
390298.143755228 1
 
2.9%
388022.481221191 1
 
2.9%
385591.248001476 1
 
2.9%
Other values (14) 14
40.0%
(Missing) 5
 
14.3%
ValueCountFrequency (%)
378026.0 1
 
2.9%
380267.363894927 1
 
2.9%
380645.672312821 3
8.6%
380798.838967553 1
 
2.9%
380810.22770681 1
 
2.9%
380903.012198435 1
 
2.9%
382070.620479643 1
 
2.9%
385468.443590649 2
5.7%
385562.010254537 1
 
2.9%
385591.248001476 1
 
2.9%
ValueCountFrequency (%)
405926.804044414 1
 
2.9%
405397.470560958 1
 
2.9%
403947.265423154 3
8.6%
393605.930358633 1
 
2.9%
390624.256291267 1
 
2.9%
390298.143755228 1
 
2.9%
390027.195360975 1
 
2.9%
389635.415888168 1
 
2.9%
389563.586926279 1
 
2.9%
389153.361849672 1
 
2.9%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)80.0%
Missing5
Missing (%)14.3%
Infinite0
Infinite (%)0.0%
Mean192173.51
Minimum179969.55
Maximum206746.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:49.964868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum179969.55
5-th percentile182934.38
Q1186106.65
median191178.01
Q3194470.24
95-th percentile205201.96
Maximum206746.79
Range26777.244
Interquartile range (IQR)8363.5821

Descriptive statistics

Standard deviation7221.8345
Coefficient of variation (CV)0.037579761
Kurtosis-0.33842465
Mean192173.51
Median Absolute Deviation (MAD)5038.0648
Skewness0.62129611
Sum5765205.3
Variance52154894
MonotonicityNot monotonic
2024-04-16T22:38:50.086023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
186073.362666348 3
 
8.6%
203667.051343927 3
 
8.6%
191178.011028057 2
 
5.7%
192213.626512424 2
 
5.7%
192626.0 1
 
2.9%
199378.846451463 1
 
2.9%
189574.207456438 1
 
2.9%
194640.53698599 1
 
2.9%
185844.723433596 1
 
2.9%
181425.423838974 1
 
2.9%
Other values (14) 14
40.0%
(Missing) 5
 
14.3%
ValueCountFrequency (%)
179969.546905958 1
 
2.9%
181425.423838974 1
 
2.9%
184778.657753035 1
 
2.9%
185570.898130941 1
 
2.9%
185844.723433596 1
 
2.9%
186073.362666348 3
8.6%
186206.529740488 1
 
2.9%
188324.973749177 1
 
2.9%
189574.207456438 1
 
2.9%
189958.115183768 1
 
2.9%
ValueCountFrequency (%)
206746.790462324 1
 
2.9%
206457.785803911 1
 
2.9%
203667.051343927 3
8.6%
199385.436227116 1
 
2.9%
199378.846451463 1
 
2.9%
194640.53698599 1
 
2.9%
193959.335175462 1
 
2.9%
192626.0 1
 
2.9%
192333.059006559 1
 
2.9%
192213.626512424 2
5.7%

실험실면적
Categorical

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
27 
42.5
3 
83.38
 
2
0.0
 
2
46.2
 
1

Length

Max length5
Median length4
Mean length4
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 27
77.1%
42.5 3
 
8.6%
83.38 2
 
5.7%
0.0 2
 
5.7%
46.2 1
 
2.9%

Length

2024-04-16T22:38:50.219939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:50.329486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 27
77.1%
42.5 3
 
8.6%
83.38 2
 
5.7%
0.0 2
 
5.7%
46.2 1
 
2.9%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
환경관리대행기관
35 

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 35
100.0%

Length

2024-04-16T22:38:50.430231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:50.516488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경관리대행기관 35
100.0%

영업소면적
Categorical

IMBALANCE 

Distinct4
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
30 
433.44
 
3
23.0
 
1
0.0
 
1

Length

Max length6
Median length4
Mean length4.1428571
Min length3

Unique

Unique2 ?
Unique (%)5.7%

Sample

1st row<NA>
2nd row23.0
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 30
85.7%
433.44 3
 
8.6%
23.0 1
 
2.9%
0.0 1
 
2.9%

Length

2024-04-16T22:38:50.618087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:50.720830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
85.7%
433.44 3
 
8.6%
23.0 1
 
2.9%
0.0 1
 
2.9%

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

실험실지역코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
28 
2632010300
3 
4833010400
 
2
2641010900
 
1
2653010500
 
1

Length

Max length10
Median length4
Mean length5.2
Min length4

Unique

Unique2 ?
Unique (%)5.7%

Sample

1st row2632010300
2nd row<NA>
3rd row<NA>
4th row2632010300
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 28
80.0%
2632010300 3
 
8.6%
4833010400 2
 
5.7%
2641010900 1
 
2.9%
2653010500 1
 
2.9%

Length

2024-04-16T22:38:50.835247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:50.932911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
80.0%
2632010300 3
 
8.6%
4833010400 2
 
5.7%
2641010900 1
 
2.9%
2653010500 1
 
2.9%

실험실우편번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
28 
46607
3 
50616
 
1
609822
 
1
46980
 
1

Length

Max length6
Median length4
Mean length4.2571429
Min length4

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row46607
2nd row<NA>
3rd row<NA>
4th row46607
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 28
80.0%
46607 3
 
8.6%
50616 1
 
2.9%
609822 1
 
2.9%
46980 1
 
2.9%
626800 1
 
2.9%

Length

2024-04-16T22:38:51.057393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:51.203026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
80.0%
46607 3
 
8.6%
50616 1
 
2.9%
609822 1
 
2.9%
46980 1
 
2.9%
626800 1
 
2.9%

실험실산
Categorical

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
25 
0
5 
1
5 

Length

Max length4
Median length4
Mean length3.1428571
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 25
71.4%
0 5
 
14.3%
1 5
 
14.3%

Length

2024-04-16T22:38:51.315100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:51.412193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
71.4%
0 5
 
14.3%
1 5
 
14.3%

실험실번지
Categorical

IMBALANCE 

Distinct6
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
28 
302
3 
687
 
1
280
 
1
122
 
1

Length

Max length4
Median length4
Mean length3.8
Min length3

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row302
2nd row<NA>
3rd row<NA>
4th row302
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 28
80.0%
302 3
 
8.6%
687 1
 
2.9%
280 1
 
2.9%
122 1
 
2.9%
318 1
 
2.9%

Length

2024-04-16T22:38:51.532272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:51.639519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
80.0%
302 3
 
8.6%
687 1
 
2.9%
280 1
 
2.9%
122 1
 
2.9%
318 1
 
2.9%

실험실호
Categorical

IMBALANCE 

Distinct6
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
28 
0
3 
7
 
1
2
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.4285714
Min length1

Unique

Unique4 ?
Unique (%)11.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
80.0%
0 3
 
8.6%
7 1
 
2.9%
2 1
 
2.9%
15 1
 
2.9%
3 1
 
2.9%

Length

2024-04-16T22:38:51.766567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:51.891127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
80.0%
0 3
 
8.6%
7 1
 
2.9%
2 1
 
2.9%
15 1
 
2.9%
3 1
 
2.9%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

실험실특수주소
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-04-16T22:38:52.004538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.5
Min length4

Characters and Unicode

Total characters18
Distinct characters10
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 (%)25.0%

Sample

1st row다산타워
2nd row다산타워
3rd row다산타워
4th row세종빌딩6층
ValueCountFrequency (%)
다산타워 3
75.0%
세종빌딩6층 1
 
25.0%
2024-04-16T22:38:52.263568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
다 3
16.7%
산 3
16.7%
타 3
16.7%
워 3
16.7%
세 1
 
5.6%
종 1
 
5.6%
빌 1
 
5.6%
딩 1
 
5.6%
6 1
 
5.6%
층 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17
94.4%
Decimal Number 1
 
5.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 3
17.6%
산 3
17.6%
타 3
17.6%
워 3
17.6%
세 1
 
5.9%
종 1
 
5.9%
빌 1
 
5.9%
딩 1
 
5.9%
층 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17
94.4%
Common 1
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 3
17.6%
산 3
17.6%
타 3
17.6%
워 3
17.6%
세 1
 
5.9%
종 1
 
5.9%
빌 1
 
5.9%
딩 1
 
5.9%
층 1
 
5.9%
Common
ValueCountFrequency (%)
6 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17
94.4%
ASCII 1
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
다 3
17.6%
산 3
17.6%
타 3
17.6%
워 3
17.6%
세 1
 
5.9%
종 1
 
5.9%
빌 1
 
5.9%
딩 1
 
5.9%
층 1
 
5.9%
ASCII
ValueCountFrequency (%)
6 1
100.0%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

실험실특수주소호
Categorical

IMBALANCE 

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
33 
402
 
1
401
 
1

Length

Max length4
Median length4
Mean length3.9428571
Min length3

Unique

Unique2 ?
Unique (%)5.7%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row402
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 33
94.3%
402 1
 
2.9%
401 1
 
2.9%

Length

2024-04-16T22:38:52.380432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:52.473866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
94.3%
402 1
 
2.9%
401 1
 
2.9%

실험실도로명주소시군구코드
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)43.5%
Missing12
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean27381.304
Minimum26260
Maximum48330
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:52.554002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26260
5-th percentile26293
Q126320
median26410
Q326530
95-th percentile26710
Maximum48330
Range22070
Interquartile range (IQR)210

Descriptive statistics

Standard deviation4568.2902
Coefficient of variation (CV)0.16683976
Kurtosis22.962373
Mean27381.304
Median Absolute Deviation (MAD)90
Skewness4.7902121
Sum629770
Variance20869275
MonotonicityNot monotonic
2024-04-16T22:38:52.639613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
26320 5
14.3%
26530 5
14.3%
26410 3
 
8.6%
26440 2
 
5.7%
26710 2
 
5.7%
26380 2
 
5.7%
48330 1
 
2.9%
26350 1
 
2.9%
26290 1
 
2.9%
26260 1
 
2.9%
(Missing) 12
34.3%
ValueCountFrequency (%)
26260 1
 
2.9%
26290 1
 
2.9%
26320 5
14.3%
26350 1
 
2.9%
26380 2
 
5.7%
26410 3
8.6%
26440 2
 
5.7%
26530 5
14.3%
26710 2
 
5.7%
48330 1
 
2.9%
ValueCountFrequency (%)
48330 1
 
2.9%
26710 2
 
5.7%
26530 5
14.3%
26440 2
 
5.7%
26410 3
8.6%
26380 2
 
5.7%
26350 1
 
2.9%
26320 5
14.3%
26290 1
 
2.9%
26260 1
 
2.9%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)52.2%
Missing12
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean2.7381422 × 109
Minimum2.6260108 × 109
Maximum4.8330104 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:52.726970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6260108 × 109
5-th percentile2.6293108 × 109
Q12.6320103 × 109
median2.6410109 × 109
Q32.6530105 × 109
95-th percentile2.6710253 × 109
Maximum4.8330104 × 109
Range2.2069996 × 109
Interquartile range (IQR)21000200

Descriptive statistics

Standard deviation4.5682881 × 108
Coefficient of variation (CV)0.16683896
Kurtosis22.962354
Mean2.7381422 × 109
Median Absolute Deviation (MAD)9000600
Skewness4.7902092
Sum6.2977271 × 1010
Variance2.0869256 × 1017
MonotonicityNot monotonic
2024-04-16T22:38:52.812790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2632010300 5
14.3%
2653010500 4
 
11.4%
2641010900 2
 
5.7%
2644010100 2
 
5.7%
2671025300 2
 
5.7%
2638010600 2
 
5.7%
4833010400 1
 
2.9%
2635010500 1
 
2.9%
2629010900 1
 
2.9%
2653010400 1
 
2.9%
Other values (2) 2
 
5.7%
(Missing) 12
34.3%
ValueCountFrequency (%)
2626010800 1
 
2.9%
2629010900 1
 
2.9%
2632010300 5
14.3%
2635010500 1
 
2.9%
2638010600 2
 
5.7%
2641010300 1
 
2.9%
2641010900 2
 
5.7%
2644010100 2
 
5.7%
2653010400 1
 
2.9%
2653010500 4
11.4%
ValueCountFrequency (%)
4833010400 1
 
2.9%
2671025300 2
 
5.7%
2653010500 4
11.4%
2653010400 1
 
2.9%
2644010100 2
 
5.7%
2641010900 2
 
5.7%
2641010300 1
 
2.9%
2638010600 2
 
5.7%
2635010500 1
 
2.9%
2632010300 5
14.3%

실험실도로명주소읍면동구분
Categorical

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
1
21 
<NA>
12 
0
 
2

Length

Max length4
Median length1
Mean length2.0285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 21
60.0%
<NA> 12
34.3%
0 2
 
5.7%

Length

2024-04-16T22:38:52.913878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:53.004642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
60.0%
na 12
34.3%
0 2
 
5.7%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)52.2%
Missing12
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean3793702.1
Minimum3133020
Maximum4217302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:53.102400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3133020
5-th percentile3135446.2
Q13139539.5
median4196163
Q34202202
95-th percentile4208262
Maximum4217302
Range1084282
Interquartile range (IQR)1062662.5

Descriptive statistics

Standard deviation520884.61
Coefficient of variation (CV)0.13730245
Kurtosis-1.90924
Mean3793702.1
Median Absolute Deviation (MAD)12099
Skewness-0.49438152
Sum87255149
Variance2.7132078 × 1011
MonotonicityNot monotonic
2024-04-16T22:38:53.470405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4196163 5
14.3%
3139012 4
 
11.4%
4205140 2
 
5.7%
4208262 2
 
5.7%
3140067 2
 
5.7%
4202202 2
 
5.7%
3338098 1
 
2.9%
3133020 1
 
2.9%
4193094 1
 
2.9%
4217302 1
 
2.9%
Other values (2) 2
 
5.7%
(Missing) 12
34.3%
ValueCountFrequency (%)
3133020 1
 
2.9%
3135050 1
 
2.9%
3139012 4
11.4%
3140067 2
 
5.7%
3338098 1
 
2.9%
4190380 1
 
2.9%
4193094 1
 
2.9%
4196163 5
14.3%
4202202 2
 
5.7%
4205140 2
 
5.7%
ValueCountFrequency (%)
4217302 1
 
2.9%
4208262 2
 
5.7%
4205140 2
 
5.7%
4202202 2
 
5.7%
4196163 5
14.3%
4193094 1
 
2.9%
4190380 1
 
2.9%
3338098 1
 
2.9%
3140067 2
 
5.7%
3139012 4
11.4%

실험실도로명특수주소
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
32 
다산타워
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 32
91.4%
다산타워 3
 
8.6%

Length

2024-04-16T22:38:53.587507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:53.674546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 32
91.4%
다산타워 3
 
8.6%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
23 
<NA>
12 

Length

Max length4
Median length1
Mean length2.0285714
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 23
65.7%
<NA> 12
34.3%

Length

2024-04-16T22:38:53.788146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:53.887918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
65.7%
na 12
34.3%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)52.2%
Missing12
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean60.173913
Minimum1
Maximum203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:53.967627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q110.5
median30
Q373
95-th percentile183
Maximum203
Range202
Interquartile range (IQR)62.5

Descriptive statistics

Standard deviation71.84937
Coefficient of variation (CV)1.1940286
Kurtosis-0.28398505
Mean60.173913
Median Absolute Deviation (MAD)24
Skewness1.1700816
Sum1384
Variance5162.332
MonotonicityNot monotonic
2024-04-16T22:38:54.068499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 5
14.3%
183 4
 
11.4%
30 3
 
8.6%
54 2
 
5.7%
14 2
 
5.7%
203 1
 
2.9%
48 1
 
2.9%
11 1
 
2.9%
10 1
 
2.9%
92 1
 
2.9%
Other values (2) 2
 
5.7%
(Missing) 12
34.3%
ValueCountFrequency (%)
1 5
14.3%
10 1
 
2.9%
11 1
 
2.9%
14 2
 
5.7%
20 1
 
2.9%
30 3
8.6%
37 1
 
2.9%
48 1
 
2.9%
54 2
 
5.7%
92 1
 
2.9%
ValueCountFrequency (%)
203 1
 
2.9%
183 4
11.4%
92 1
 
2.9%
54 2
5.7%
48 1
 
2.9%
37 1
 
2.9%
30 3
8.6%
20 1
 
2.9%
14 2
5.7%
11 1
 
2.9%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
<NA>
29 
0
5 
1
 
1

Length

Max length4
Median length4
Mean length3.4857143
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 29
82.9%
0 5
 
14.3%
1 1
 
2.9%

Length

2024-04-16T22:38:54.210022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:38:54.328680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
82.9%
0 5
 
14.3%
1 1
 
2.9%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)52.2%
Missing12
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean244170.3
Minimum46607
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-04-16T22:38:54.412988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46607
5-th percentile46607
Q146700
median48059
Q3609321.5
95-th percentile619737.5
Maximum619952
Range573345
Interquartile range (IQR)562621.5

Descriptive statistics

Standard deviation275413.68
Coefficient of variation (CV)1.1279573
Kurtosis-1.68542
Mean244170.3
Median Absolute Deviation (MAD)1452
Skewness0.68482813
Sum5615917
Variance7.5852693 × 1010
MonotonicityNot monotonic
2024-04-16T22:38:54.512268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
46607 5
14.3%
46980 4
 
11.4%
609822 2
 
5.7%
46700 2
 
5.7%
619952 2
 
5.7%
49514 2
 
5.7%
50616 1
 
2.9%
48059 1
 
2.9%
608821 1
 
2.9%
617807 1
 
2.9%
Other values (2) 2
 
5.7%
(Missing) 12
34.3%
ValueCountFrequency (%)
46607 5
14.3%
46700 2
 
5.7%
46980 4
11.4%
48059 1
 
2.9%
49514 2
 
5.7%
50616 1
 
2.9%
607840 1
 
2.9%
608821 1
 
2.9%
609822 2
 
5.7%
609843 1
 
2.9%
ValueCountFrequency (%)
619952 2
5.7%
617807 1
 
2.9%
609843 1
 
2.9%
609822 2
5.7%
608821 1
 
2.9%
607840 1
 
2.9%
50616 1
 
2.9%
49514 2
5.7%
48059 1
 
2.9%
46980 4
11.4%

Unnamed: 51
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호Unnamed: 51
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45환경관리대행기관09_30_15_P626000062600001020130001020191008<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 동부곡로23번길 30 (부곡동)609822(주)한신환경20200224183238U2020-02-26 02:40:00.0<NA>390624.256291193959.335175<NA>환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26410264101090014205140<NA>030<NA>609822<NA>
56환경관리대행기관09_30_15_P626000062600001020150000320200610<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 북구 만덕2로17번길 1, 402호 (만덕동)46607세영환경산업(주)20200717160008U2020-07-19 02:40:00.0<NA>385468.443591192213.62651283.38환경관리대행기관<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>26320263201030014196163<NA>01<NA>46607<NA>
67환경관리대행기관09_30_15_P626000062600001020190000520191104<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 장안읍 좌천리 286-1 좌천슈퍼부산광역시 기장군 장안읍 좌천2길 36, 좌천슈퍼<NA>비제이엔지니어링20200103161514U2020-01-05 02:40:00.0<NA><NA><NA><NA>환경관리대행기관<NA><NA>26320103004660703020<NA><NA>다산타워<NA>40126320263201030014196163다산타워01046607<NA>
78환경관리대행기관09_30_15_P626000062600001020200000120201207<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>46917부산광역시 사상구 모라동 283-11부산광역시 사상구 사상로525번길 54, 2층 (모라동)46917(주)세영환경기술20201207104032U2020-12-09 02:40:00.0<NA>380810.227707189958.115184<NA>환경관리대행기관<NA><NA>48330104005061606877<NA><NA><NA><NA><NA>48330483301040013338098<NA>0203050616<NA>
89환경관리대행기관09_30_15_P626000062600001020130002020200401<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>48059부산광역시 해운대구 재송동 1212번지 큐비이센텀 2403~2406호부산광역시 해운대구 센텀중앙로 90, 큐비이센텀 2403~2406호 (재송동)48059청우에이스(주)20200401153846U2020-04-03 02:40:00.0<NA>393605.930359188324.973749<NA>환경관리대행기관<NA><NA><NA><NA>1<NA><NA><NA><NA><NA><NA><NA>26350263501050013133020<NA>048<NA>48059<NA>
910환경관리대행기관09_30_15_P626000062600001020200000220201008<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA>부산광역시 동래구 사직동 137-5부산광역시 동래구 미남로 70, 지하 1층 (사직동)<NA>(주)디에이치환경측정연구소20201008173422I2020-10-10 00:23:11.0<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><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호Unnamed: 51
2526환경관리대행기관09_30_15_P626000062600001020130001920141021<NA>3폐업Q폐업20141021<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 중앙대로 1663 (부곡동)609852블루워터(주)20151202164711I2019-03-23 02:20:03.0<NA>390298.143755194640.536986<NA>환경관리대행기관<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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