Overview

Dataset statistics

Number of variables51
Number of observations160
Missing cells3572
Missing cells (%)43.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory69.0 KiB
Average record size in memory441.8 B

Variable types

Numeric13
Categorical16
DateTime4
Unsupported11
Text7

Dataset

Description23년06월_6270000_대구광역시_09_30_16_P_환경전문공사업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098783&dataSetDetailId=DDI_0000098814&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
개방자치단체코드 has constant value ""Constant
사업장구분명 has constant value ""Constant
실험실도로명특수주소 has constant value ""Constant
실험실산 is highly imbalanced (62.6%)Imbalance
실험실특수주소호 is highly imbalanced (93.1%)Imbalance
실험실도로명주소시군구코드 is highly imbalanced (81.9%)Imbalance
실험실도로명주소읍면동구분 is highly imbalanced (79.4%)Imbalance
실험실도로명주소건물층구분 is highly imbalanced (66.3%)Imbalance
실험실도로명주소건물부번호 is highly imbalanced (82.0%)Imbalance
인허가취소일자 has 160 (100.0%) missing valuesMissing
폐업일자 has 41 (25.6%) missing valuesMissing
휴업시작일자 has 160 (100.0%) missing valuesMissing
휴업종료일자 has 160 (100.0%) missing valuesMissing
재개업일자 has 160 (100.0%) missing valuesMissing
소재지전화 has 160 (100.0%) missing valuesMissing
소재지면적 has 160 (100.0%) missing valuesMissing
소재지우편번호 has 42 (26.2%) missing valuesMissing
소재지전체주소 has 28 (17.5%) missing valuesMissing
도로명전체주소 has 3 (1.9%) missing valuesMissing
도로명우편번호 has 66 (41.2%) missing valuesMissing
업태구분명 has 160 (100.0%) missing valuesMissing
좌표정보(X) has 15 (9.4%) missing valuesMissing
좌표정보(Y) has 15 (9.4%) missing valuesMissing
영업소면적 has 107 (66.9%) missing valuesMissing
위탁업체명 has 160 (100.0%) missing valuesMissing
실험실지역코드 has 143 (89.4%) missing valuesMissing
실험실우편번호 has 143 (89.4%) missing valuesMissing
실험실번지 has 143 (89.4%) missing valuesMissing
실험실호 has 143 (89.4%) missing valuesMissing
실험실통 has 160 (100.0%) missing valuesMissing
실험실반 has 160 (100.0%) missing valuesMissing
실험실특수주소 has 156 (97.5%) missing valuesMissing
실험실특수주소동 has 160 (100.0%) missing valuesMissing
실험실도로명주소읍면동코드 has 152 (95.0%) missing valuesMissing
실험실도로명주소코드 has 152 (95.0%) missing valuesMissing
실험실도로명특수주소 has 159 (99.4%) missing valuesMissing
실험실도로명주소건물본번호 has 152 (95.0%) missing valuesMissing
실험실도로명주소우편번호 has 152 (95.0%) 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
영업소면적 has 43 (26.9%) zerosZeros

Reproduction

Analysis started2023-12-10 19:08:47.441349
Analysis finished2023-12-10 19:08:48.561007
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.5
Minimum1
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:08:48.677713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.95
Q140.75
median80.5
Q3120.25
95-th percentile152.05
Maximum160
Range159
Interquartile range (IQR)79.5

Descriptive statistics

Standard deviation46.332134
Coefficient of variation (CV)0.57555446
Kurtosis-1.2
Mean80.5
Median Absolute Deviation (MAD)40
Skewness0
Sum12880
Variance2146.6667
MonotonicityStrictly increasing
2023-12-11T04:08:48.911779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
82 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
Other values (150) 150
93.8%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
환경전문공사업
160 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 160
100.0%

Length

2023-12-11T04:08:49.141529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:49.289819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 160
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
09_30_16_P
160 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_16_P
2nd row09_30_16_P
3rd row09_30_16_P
4th row09_30_16_P
5th row09_30_16_P

Common Values

ValueCountFrequency (%)
09_30_16_P 160
100.0%

Length

2023-12-11T04:08:49.477875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:49.699433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_16_p 160
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
6270000
160 

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 160
100.0%

Length

2023-12-11T04:08:49.885060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:50.029440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 160
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct160
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 size1.5 KiB
2023-12-11T04:08:50.198928image/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
Range1700001
Interquartile range (IQR)899968

Descriptive statistics

Standard deviation532059.45
Coefficient of variation (CV)8.4857966 × 10-13
Kurtosis-1.0263592
Mean6.2700001 × 1017
Median Absolute Deviation (MAD)400000
Skewness0.56427061
Sum8.0862811 × 1018
Variance2.8308726 × 1011
MonotonicityNot monotonic
2023-12-11T04:08:50.448745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
627000009200600030 1
 
0.6%
627000009200600005 1
 
0.6%
627000009201000008 1
 
0.6%
627000009201100001 1
 
0.6%
627000009201100002 1
 
0.6%
627000009201100003 1
 
0.6%
627000009201100004 1
 
0.6%
627000009201100006 1
 
0.6%
627000009201100007 1
 
0.6%
627000009201200001 1
 
0.6%
Other values (150) 150
93.8%
ValueCountFrequency (%)
627000009200600001 1
0.6%
627000009200600002 1
0.6%
627000009200600003 1
0.6%
627000009200600004 1
0.6%
627000009200600005 1
0.6%
627000009200600006 1
0.6%
627000009200600007 1
0.6%
627000009200600008 1
0.6%
627000009200600009 1
0.6%
627000009200600010 1
0.6%
ValueCountFrequency (%)
627000009202300002 1
0.6%
627000009202300001 1
0.6%
627000009202200002 1
0.6%
627000009202200001 1
0.6%
627000009202100007 1
0.6%
627000009202100006 1
0.6%
627000009202100005 1
0.6%
627000009202100004 1
0.6%
627000009202100003 1
0.6%
627000009202100002 1
0.6%

인허가일자
Date

Distinct150
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2006-08-02 00:00:00
Maximum2023-06-23 00:00:00
2023-12-11T04:08:50.699232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:08:50.926543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
3
122 
1
38 

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 (%)
3 122
76.2%
1 38
 
23.8%

Length

2023-12-11T04:08:51.140539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:51.324923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 122
76.2%
1 38
 
23.8%

영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
122 
영업/정상
38 

Length

Max length5
Median length2
Mean length2.7125
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 122
76.2%
영업/정상 38
 
23.8%

Length

2023-12-11T04:08:51.519650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:51.679182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
76.2%
영업/정상 38
 
23.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Q
122 
N
38 

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 122
76.2%
N 38
 
23.8%

Length

2023-12-11T04:08:51.851455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:52.013795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 122
76.2%
n 38
 
23.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐업
122 
신규
38 

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 122
76.2%
신규 38
 
23.8%

Length

2023-12-11T04:08:52.176965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:52.329850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
76.2%
신규 38
 
23.8%

폐업일자
Date

MISSING 

Distinct108
Distinct (%)90.8%
Missing41
Missing (%)25.6%
Memory size1.4 KiB
Minimum2006-11-27 00:00:00
Maximum2023-05-11 00:00:00
2023-12-11T04:08:52.538502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:08:52.736379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Text

MISSING 

Distinct84
Distinct (%)71.2%
Missing42
Missing (%)26.2%
Memory size1.4 KiB
2023-12-11T04:08:53.167983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.3898305
Min length5

Characters and Unicode

Total characters754
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

Unique65 ?
Unique (%)55.1%

Sample

1st row704-944
2nd row703-833
3rd row702-710
4th row703-830
5th row704-919
ValueCountFrequency (%)
702-845 5
 
4.2%
42709 4
 
3.4%
704-919 4
 
3.4%
704-944 3
 
2.5%
704-946 3
 
2.5%
704-220 3
 
2.5%
704-801 3
 
2.5%
42839 3
 
2.5%
704-920 3
 
2.5%
703-833 3
 
2.5%
Other values (74) 84
71.2%
2023-12-11T04:08:53.794364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 130
17.2%
7 109
14.5%
4 107
14.2%
- 82
10.9%
2 71
9.4%
8 63
8.4%
3 57
7.6%
1 49
 
6.5%
9 43
 
5.7%
6 22
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 672
89.1%
Dash Punctuation 82
 
10.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 130
19.3%
7 109
16.2%
4 107
15.9%
2 71
10.6%
8 63
9.4%
3 57
8.5%
1 49
 
7.3%
9 43
 
6.4%
6 22
 
3.3%
5 21
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 754
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 130
17.2%
7 109
14.5%
4 107
14.2%
- 82
10.9%
2 71
9.4%
8 63
8.4%
3 57
7.6%
1 49
 
6.5%
9 43
 
5.7%
6 22
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 754
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 130
17.2%
7 109
14.5%
4 107
14.2%
- 82
10.9%
2 71
9.4%
8 63
8.4%
3 57
7.6%
1 49
 
6.5%
9 43
 
5.7%
6 22
 
2.9%

소재지전체주소
Text

MISSING 

Distinct121
Distinct (%)91.7%
Missing28
Missing (%)17.5%
Memory size1.4 KiB
2023-12-11T04:08:54.265123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36.5
Mean length25.795455
Min length18

Characters and Unicode

Total characters3405
Distinct characters139
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

Unique111 ?
Unique (%)84.1%

Sample

1st row대구 달서구 장기동 173번지 23호
2nd row대구광역시 서구 중리동 1119번지 7호
3rd row대구광역시 북구 산격2동 1629번지 유통단지산업용재관 18동 224호
4th row대구광역시 서구 이현동 42번지 450호
5th row대구광역시 달서구 신당동 1320번지 2호
ValueCountFrequency (%)
대구광역시 123
 
18.1%
달서구 58
 
8.5%
북구 26
 
3.8%
서구 20
 
2.9%
신당동 14
 
2.1%
3호 11
 
1.6%
2호 11
 
1.6%
수성구 10
 
1.5%
호산동 10
 
1.5%
대구 9
 
1.3%
Other values (239) 389
57.1%
2023-12-11T04:08:54.912805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
782
23.0%
구 259
 
7.6%
1 147
 
4.3%
대 138
 
4.1%
동 137
 
4.0%
시 123
 
3.6%
역 123
 
3.6%
광 123
 
3.6%
호 115
 
3.4%
지 111
 
3.3%
Other values (129) 1347
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1877
55.1%
Space Separator 782
23.0%
Decimal Number 697
 
20.5%
Dash Punctuation 32
 
0.9%
Uppercase Letter 10
 
0.3%
Other Punctuation 3
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 259
13.8%
대 138
 
7.4%
동 137
 
7.3%
시 123
 
6.6%
역 123
 
6.6%
광 123
 
6.6%
호 115
 
6.1%
지 111
 
5.9%
번 102
 
5.4%
서 81
 
4.3%
Other values (109) 565
30.1%
Decimal Number
ValueCountFrequency (%)
1 147
21.1%
2 105
15.1%
3 88
12.6%
0 73
10.5%
4 56
 
8.0%
7 53
 
7.6%
8 48
 
6.9%
6 47
 
6.7%
5 43
 
6.2%
9 37
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
D 4
40.0%
T 2
20.0%
B 2
20.0%
C 2
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
782
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1877
55.1%
Common 1518
44.6%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 259
13.8%
대 138
 
7.4%
동 137
 
7.3%
시 123
 
6.6%
역 123
 
6.6%
광 123
 
6.6%
호 115
 
6.1%
지 111
 
5.9%
번 102
 
5.4%
서 81
 
4.3%
Other values (109) 565
30.1%
Common
ValueCountFrequency (%)
782
51.5%
1 147
 
9.7%
2 105
 
6.9%
3 88
 
5.8%
0 73
 
4.8%
4 56
 
3.7%
7 53
 
3.5%
8 48
 
3.2%
6 47
 
3.1%
5 43
 
2.8%
Other values (6) 76
 
5.0%
Latin
ValueCountFrequency (%)
D 4
40.0%
T 2
20.0%
B 2
20.0%
C 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1877
55.1%
ASCII 1528
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
782
51.2%
1 147
 
9.6%
2 105
 
6.9%
3 88
 
5.8%
0 73
 
4.8%
4 56
 
3.7%
7 53
 
3.5%
8 48
 
3.1%
6 47
 
3.1%
5 43
 
2.8%
Other values (10) 86
 
5.6%
Hangul
ValueCountFrequency (%)
구 259
13.8%
대 138
 
7.4%
동 137
 
7.3%
시 123
 
6.6%
역 123
 
6.6%
광 123
 
6.6%
호 115
 
6.1%
지 111
 
5.9%
번 102
 
5.4%
서 81
 
4.3%
Other values (109) 565
30.1%

도로명전체주소
Text

MISSING 

Distinct139
Distinct (%)88.5%
Missing3
Missing (%)1.9%
Memory size1.4 KiB
2023-12-11T04:08:55.384389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length27.878981
Min length19

Characters and Unicode

Total characters4377
Distinct characters172
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

Unique124 ?
Unique (%)79.0%

Sample

1st row대구광역시 달서구 성서동로 315 (장기동)
2nd row대구광역시 달서구 성서로76길 11 (이곡동)
3rd row대구광역시 서구 와룡로72길 8 (중리동)
4th row대구광역시 북구 구암로65길 2-1, 2층 (구암동)
5th row대구광역시 서구 와룡로87길 24 (이현동)
ValueCountFrequency (%)
대구광역시 155
 
18.0%
달서구 69
 
8.0%
북구 31
 
3.6%
서구 19
 
2.2%
2층 15
 
1.7%
달성군 14
 
1.6%
수성구 11
 
1.3%
달서대로 10
 
1.2%
동구 10
 
1.2%
559 9
 
1.0%
Other values (318) 516
60.1%
2023-12-11T04:08:56.038784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
702
 
16.0%
구 317
 
7.2%
대 194
 
4.4%
동 174
 
4.0%
시 158
 
3.6%
광 155
 
3.5%
역 155
 
3.5%
로 155
 
3.5%
( 143
 
3.3%
) 143
 
3.3%
Other values (162) 2081
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2602
59.4%
Space Separator 702
 
16.0%
Decimal Number 682
 
15.6%
Open Punctuation 143
 
3.3%
Close Punctuation 143
 
3.3%
Other Punctuation 72
 
1.6%
Dash Punctuation 26
 
0.6%
Uppercase Letter 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 317
 
12.2%
대 194
 
7.5%
동 174
 
6.7%
시 158
 
6.1%
광 155
 
6.0%
역 155
 
6.0%
로 155
 
6.0%
서 141
 
5.4%
달 106
 
4.1%
길 74
 
2.8%
Other values (144) 973
37.4%
Decimal Number
ValueCountFrequency (%)
1 134
19.6%
2 103
15.1%
3 81
11.9%
5 72
10.6%
4 59
8.7%
0 54
7.9%
6 52
 
7.6%
8 51
 
7.5%
9 44
 
6.5%
7 32
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
C 3
42.9%
D 2
28.6%
T 2
28.6%
Space Separator
ValueCountFrequency (%)
702
100.0%
Open Punctuation
ValueCountFrequency (%)
( 143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 143
100.0%
Other Punctuation
ValueCountFrequency (%)
, 72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2602
59.4%
Common 1768
40.4%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 317
 
12.2%
대 194
 
7.5%
동 174
 
6.7%
시 158
 
6.1%
광 155
 
6.0%
역 155
 
6.0%
로 155
 
6.0%
서 141
 
5.4%
달 106
 
4.1%
길 74
 
2.8%
Other values (144) 973
37.4%
Common
ValueCountFrequency (%)
702
39.7%
( 143
 
8.1%
) 143
 
8.1%
1 134
 
7.6%
2 103
 
5.8%
3 81
 
4.6%
5 72
 
4.1%
, 72
 
4.1%
4 59
 
3.3%
0 54
 
3.1%
Other values (5) 205
 
11.6%
Latin
ValueCountFrequency (%)
C 3
42.9%
D 2
28.6%
T 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2602
59.4%
ASCII 1775
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
702
39.5%
( 143
 
8.1%
) 143
 
8.1%
1 134
 
7.5%
2 103
 
5.8%
3 81
 
4.6%
5 72
 
4.1%
, 72
 
4.1%
4 59
 
3.3%
0 54
 
3.0%
Other values (8) 212
 
11.9%
Hangul
ValueCountFrequency (%)
구 317
 
12.2%
대 194
 
7.5%
동 174
 
6.7%
시 158
 
6.1%
광 155
 
6.0%
역 155
 
6.0%
로 155
 
6.0%
서 141
 
5.4%
달 106
 
4.1%
길 74
 
2.8%
Other values (144) 973
37.4%

도로명우편번호
Text

MISSING 

Distinct75
Distinct (%)79.8%
Missing66
Missing (%)41.2%
Memory size1.4 KiB
2023-12-11T04:08:56.394131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.0212766
Min length5

Characters and Unicode

Total characters566
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

Unique62 ?
Unique (%)66.0%

Sample

1st row704-929
2nd row703-833
3rd row41424
4th row703-830
5th row704-919
ValueCountFrequency (%)
42709 5
 
5.3%
704-948 3
 
3.2%
42839 3
 
3.2%
703-833 3
 
3.2%
42704 2
 
2.1%
704-837 2
 
2.1%
702-845 2
 
2.1%
701-847 2
 
2.1%
702-110 2
 
2.1%
43008 2
 
2.1%
Other values (65) 68
72.3%
2023-12-11T04:08:56.975720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 92
16.3%
0 86
15.2%
7 75
13.3%
2 55
9.7%
1 51
9.0%
- 48
8.5%
3 47
8.3%
8 44
7.8%
9 33
 
5.8%
5 19
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 518
91.5%
Dash Punctuation 48
 
8.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 92
17.8%
0 86
16.6%
7 75
14.5%
2 55
10.6%
1 51
9.8%
3 47
9.1%
8 44
8.5%
9 33
 
6.4%
5 19
 
3.7%
6 16
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 566
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 92
16.3%
0 86
15.2%
7 75
13.3%
2 55
9.7%
1 51
9.0%
- 48
8.5%
3 47
8.3%
8 44
7.8%
9 33
 
5.8%
5 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 92
16.3%
0 86
15.2%
7 75
13.3%
2 55
9.7%
1 51
9.0%
- 48
8.5%
3 47
8.3%
8 44
7.8%
9 33
 
5.8%
5 19
 
3.4%

사업장명
Text

Distinct127
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-11T04:08:57.399005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.24375
Min length2

Characters and Unicode

Total characters1319
Distinct characters137
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)63.7%

Sample

1st row(주)동덕이엔비
2nd row(주)에스엘테크
3rd row(주)청수
4th row유림환경개발(주)
5th row(주)신라엔텍
ValueCountFrequency (%)
주식회사 9
 
5.2%
제이에스엔텍(주 4
 
2.3%
주)세종플랜트 4
 
2.3%
주)동우이엔티 3
 
1.7%
주)지원이엔에스 3
 
1.7%
주)미래엔비텍 3
 
1.7%
주)동서환경개발 3
 
1.7%
주)수성이앤씨 2
 
1.1%
가림 2
 
1.1%
주)아이디알시스템 2
 
1.1%
Other values (122) 139
79.9%
2023-12-11T04:08:58.013297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 139
 
10.5%
( 130
 
9.9%
) 130
 
9.9%
이 53
 
4.0%
엔 52
 
3.9%
경 44
 
3.3%
환 40
 
3.0%
지 34
 
2.6%
에 32
 
2.4%
스 29
 
2.2%
Other values (127) 636
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
78.2%
Open Punctuation 130
 
9.9%
Close Punctuation 130
 
9.9%
Space Separator 14
 
1.1%
Uppercase Letter 10
 
0.8%
Other Symbol 2
 
0.2%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 139
 
13.5%
이 53
 
5.1%
엔 52
 
5.0%
경 44
 
4.3%
환 40
 
3.9%
지 34
 
3.3%
에 32
 
3.1%
스 29
 
2.8%
텍 25
 
2.4%
어 17
 
1.6%
Other values (114) 566
54.9%
Uppercase Letter
ValueCountFrequency (%)
N 2
20.0%
G 2
20.0%
E 2
20.0%
S 1
10.0%
V 1
10.0%
I 1
10.0%
D 1
10.0%
Open Punctuation
ValueCountFrequency (%)
( 130
100.0%
Close Punctuation
ValueCountFrequency (%)
) 130
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1033
78.3%
Common 276
 
20.9%
Latin 10
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 139
 
13.5%
이 53
 
5.1%
엔 52
 
5.0%
경 44
 
4.3%
환 40
 
3.9%
지 34
 
3.3%
에 32
 
3.1%
스 29
 
2.8%
텍 25
 
2.4%
어 17
 
1.6%
Other values (115) 568
55.0%
Latin
ValueCountFrequency (%)
N 2
20.0%
G 2
20.0%
E 2
20.0%
S 1
10.0%
V 1
10.0%
I 1
10.0%
D 1
10.0%
Common
ValueCountFrequency (%)
( 130
47.1%
) 130
47.1%
14
 
5.1%
- 1
 
0.4%
& 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
78.2%
ASCII 286
 
21.7%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 139
 
13.5%
이 53
 
5.1%
엔 52
 
5.0%
경 44
 
4.3%
환 40
 
3.9%
지 34
 
3.3%
에 32
 
3.1%
스 29
 
2.8%
텍 25
 
2.4%
어 17
 
1.6%
Other values (114) 566
54.9%
ASCII
ValueCountFrequency (%)
( 130
45.5%
) 130
45.5%
14
 
4.9%
N 2
 
0.7%
G 2
 
0.7%
E 2
 
0.7%
S 1
 
0.3%
V 1
 
0.3%
I 1
 
0.3%
- 1
 
0.3%
Other values (2) 2
 
0.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정시점
Date

UNIQUE 

Distinct160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2006-11-27 17:27:53
Maximum2023-06-24 10:39:26
2023-12-11T04:08:58.246159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:08:58.462460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
I
90 
U
70 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 90
56.2%
U 70
43.8%

Length

2023-12-11T04:08:58.676419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:08:58.821818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 90
56.2%
u 70
43.8%

데이터갱신일자
Date

Distinct57
Distinct (%)35.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2018-11-14 02:37:29
Maximum2023-06-26 02:40:00
2023-12-11T04:08:59.335434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:08:59.546338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)77.9%
Missing15
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean339471.68
Minimum326800.48
Maximum355572.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:08:59.754926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326800.48
5-th percentile332225.75
Q1335144.21
median338859.53
Q3344150.99
95-th percentile347958.84
Maximum355572.84
Range28772.362
Interquartile range (IQR)9006.771

Descriptive statistics

Standard deviation5533.5197
Coefficient of variation (CV)0.016300387
Kurtosis0.15302604
Mean339471.68
Median Absolute Deviation (MAD)4135.2927
Skewness0.45744885
Sum49223394
Variance30619840
MonotonicityNot monotonic
2023-12-11T04:08:59.969700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
334621.225167521 8
 
5.0%
344912.358902194 3
 
1.9%
336839.695094646 3
 
1.9%
339654.246783658 3
 
1.9%
335199.688361276 3
 
1.9%
339800.928911095 2
 
1.2%
355572.842839327 2
 
1.2%
333767.924522664 2
 
1.2%
340791.949967042 2
 
1.2%
333204.185268404 2
 
1.2%
Other values (103) 115
71.9%
(Missing) 15
 
9.4%
ValueCountFrequency (%)
326800.480422801 1
0.6%
328448.180043678 1
0.6%
328580.780049187 1
0.6%
328923.524847654 1
0.6%
329454.216845471 1
0.6%
330363.440564036 1
0.6%
331535.063936148 1
0.6%
332153.42037492 1
0.6%
332515.045012596 1
0.6%
332777.254719991 1
0.6%
ValueCountFrequency (%)
355572.842839327 2
1.2%
352880.636818819 2
1.2%
352557.368726693 1
0.6%
348879.460410359 1
0.6%
348378.873769193 1
0.6%
347959.493732757 1
0.6%
347956.202203295 2
1.2%
346986.540457003 1
0.6%
346849.475750126 1
0.6%
346621.319604807 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct113
Distinct (%)77.9%
Missing15
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean262947.85
Minimum239148.37
Maximum272987.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:00.221824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239148.37
5-th percentile257300.58
Q1261216.92
median262368.4
Q3266261.21
95-th percentile270243.37
Maximum272987.62
Range33839.246
Interquartile range (IQR)5044.2875

Descriptive statistics

Standard deviation5764.8706
Coefficient of variation (CV)0.021924008
Kurtosis5.6751648
Mean262947.85
Median Absolute Deviation (MAD)2354.6569
Skewness-1.7002405
Sum38127438
Variance33233733
MonotonicityNot monotonic
2023-12-11T04:09:00.429756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262044.332357665 8
 
5.0%
268253.830252935 3
 
1.9%
262065.487156084 3
 
1.9%
269791.354544299 3
 
1.9%
259343.910784361 3
 
1.9%
257478.612944775 2
 
1.2%
265554.461449021 2
 
1.2%
261432.342597954 2
 
1.2%
266416.563189782 2
 
1.2%
261826.715046489 2
 
1.2%
Other values (103) 115
71.9%
(Missing) 15
 
9.4%
ValueCountFrequency (%)
239148.373812982 1
0.6%
239455.19135582 1
0.6%
239903.424058142 1
0.6%
243324.557766307 1
0.6%
243957.688388711 1
0.6%
249109.478388043 1
0.6%
253850.094740318 1
0.6%
257280.684298351 1
0.6%
257380.142480684 1
0.6%
257478.612944775 2
1.2%
ValueCountFrequency (%)
272987.619728676 2
1.2%
272670.290639843 1
0.6%
272573.101385976 1
0.6%
272436.922124699 1
0.6%
272405.875051244 1
0.6%
271184.17603601 1
0.6%
270243.374480009 2
1.2%
270239.599990274 1
0.6%
270209.502990167 1
0.6%
270013.374391896 2
1.2%

실험실면적
Categorical

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
112 
0
48 

Length

Max length4
Median length4
Mean length3.1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 112
70.0%
0 48
30.0%

Length

2023-12-11T04:09:00.678810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:00.858370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 112
70.0%
0 48
30.0%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
환경전문공사업
160 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 160
100.0%

Length

2023-12-11T04:09:01.034663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:01.188365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 160
100.0%

영업소면적
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)20.8%
Missing107
Missing (%)66.9%
Infinite0
Infinite (%)0.0%
Mean116.13019
Minimum0
Maximum4390
Zeros43
Zeros (%)26.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:01.346075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile295.34
Maximum4390
Range4390
Interquartile range (IQR)0

Descriptive statistics

Standard deviation604.56319
Coefficient of variation (CV)5.2059089
Kurtosis50.728088
Mean116.13019
Median Absolute Deviation (MAD)0
Skewness7.0573596
Sum6154.9
Variance365496.65
MonotonicityNot monotonic
2023-12-11T04:09:01.522321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 43
26.9%
115.0 1
 
0.6%
364.0 1
 
0.6%
76.15 1
 
0.6%
66.0 1
 
0.6%
309.35 1
 
0.6%
280.0 1
 
0.6%
115.4 1
 
0.6%
286.0 1
 
0.6%
4390.0 1
 
0.6%
(Missing) 107
66.9%
ValueCountFrequency (%)
0.0 43
26.9%
66.0 1
 
0.6%
76.15 1
 
0.6%
115.0 1
 
0.6%
115.4 1
 
0.6%
153.0 1
 
0.6%
280.0 1
 
0.6%
286.0 1
 
0.6%
309.35 1
 
0.6%
364.0 1
 
0.6%
ValueCountFrequency (%)
4390.0 1
0.6%
364.0 1
0.6%
309.35 1
0.6%
286.0 1
0.6%
280.0 1
0.6%
153.0 1
0.6%
115.4 1
0.6%
115.0 1
0.6%
76.15 1
0.6%
66.0 1
0.6%

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

실험실지역코드
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)70.6%
Missing143
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean2.7281313 × 109
Minimum2.7140111 × 109
Maximum2.771038 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:01.688580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7140111 × 109
5-th percentile2.7140111 × 109
Q12.7170106 × 109
median2.7230126 × 109
Q32.7290116 × 109
95-th percentile2.7710281 × 109
Maximum2.771038 × 109
Range57026922
Interquartile range (IQR)12001000

Descriptive statistics

Standard deviation17068518
Coefficient of variation (CV)0.0062564868
Kurtosis3.7651059
Mean2.7281313 × 109
Median Absolute Deviation (MAD)5999900
Skewness2.0850101
Sum4.6378233 × 1010
Variance2.913343 × 1014
MonotonicityNot monotonic
2023-12-11T04:09:01.865396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2717010600 2
 
1.2%
2717010300 2
 
1.2%
2729011600 2
 
1.2%
2714011100 2
 
1.2%
2723012600 2
 
1.2%
2723011200 1
 
0.6%
2729010700 1
 
0.6%
2771025626 1
 
0.6%
2729012500 1
 
0.6%
2726011300 1
 
0.6%
Other values (2) 2
 
1.2%
(Missing) 143
89.4%
ValueCountFrequency (%)
2714011100 2
1.2%
2717010300 2
1.2%
2717010600 2
1.2%
2723011200 1
0.6%
2723012600 2
1.2%
2726011300 1
0.6%
2729010700 1
0.6%
2729010900 1
0.6%
2729011600 2
1.2%
2729012500 1
0.6%
ValueCountFrequency (%)
2771038022 1
0.6%
2771025626 1
0.6%
2729012500 1
0.6%
2729011600 2
1.2%
2729010900 1
0.6%
2729010700 1
0.6%
2726011300 1
0.6%
2723012600 2
1.2%
2723011200 1
0.6%
2717010600 2
1.2%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)76.5%
Missing143
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean431380.53
Minimum41749
Maximum706813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:02.048442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41749
5-th percentile42517
Q142839
median701804
Q3703830
95-th percentile704714.6
Maximum706813
Range665064
Interquartile range (IQR)660991

Descriptive statistics

Standard deviation335217.03
Coefficient of variation (CV)0.77707965
Kurtosis-2.1093544
Mean431380.53
Median Absolute Deviation (MAD)2386
Skewness-0.39421126
Sum7333469
Variance1.1237046 × 1011
MonotonicityNot monotonic
2023-12-11T04:09:02.226250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
703830 2
 
1.2%
42839 2
 
1.2%
701804 2
 
1.2%
702865 2
 
1.2%
703849 1
 
0.6%
702828 1
 
0.6%
42709 1
 
0.6%
42930 1
 
0.6%
42712 1
 
0.6%
706813 1
 
0.6%
Other values (3) 3
 
1.9%
(Missing) 143
89.4%
ValueCountFrequency (%)
41749 1
0.6%
42709 1
0.6%
42712 1
0.6%
42839 2
1.2%
42930 1
0.6%
43013 1
0.6%
701804 2
1.2%
702828 1
0.6%
702865 2
1.2%
703830 2
1.2%
ValueCountFrequency (%)
706813 1
0.6%
704190 1
0.6%
703849 1
0.6%
703830 2
1.2%
702865 2
1.2%
702828 1
0.6%
701804 2
1.2%
43013 1
0.6%
42930 1
0.6%
42839 2
1.2%

실험실산
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
143 
1
 
10
0
 
7

Length

Max length4
Median length4
Mean length3.68125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 143
89.4%
1 10
 
6.2%
0 7
 
4.4%

Length

2023-12-11T04:09:02.416952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:02.615523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 143
89.4%
1 10
 
6.2%
0 7
 
4.4%

실험실번지
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)82.4%
Missing143
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean792.35294
Minimum42
Maximum1702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:02.764857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile42
Q1539
median597
Q31261
95-th percentile1534
Maximum1702
Range1660
Interquartile range (IQR)722

Descriptive statistics

Standard deviation500.97392
Coefficient of variation (CV)0.63226107
Kurtosis-0.99192731
Mean792.35294
Median Absolute Deviation (MAD)487
Skewness0.22224188
Sum13470
Variance250974.87
MonotonicityNot monotonic
2023-12-11T04:09:02.960039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
42 2
 
1.2%
1084 2
 
1.2%
539 2
 
1.2%
1492 1
 
0.6%
340 1
 
0.6%
597 1
 
0.6%
1261 1
 
0.6%
1702 1
 
0.6%
700 1
 
0.6%
1287 1
 
0.6%
Other values (4) 4
 
2.5%
(Missing) 143
89.4%
ValueCountFrequency (%)
42 2
1.2%
333 1
0.6%
340 1
0.6%
539 2
1.2%
565 1
0.6%
573 1
0.6%
597 1
0.6%
700 1
0.6%
1084 2
1.2%
1261 1
0.6%
ValueCountFrequency (%)
1702 1
0.6%
1492 1
0.6%
1290 1
0.6%
1287 1
0.6%
1261 1
0.6%
1084 2
1.2%
700 1
0.6%
597 1
0.6%
573 1
0.6%
565 1
0.6%

실험실호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)76.5%
Missing143
Missing (%)89.4%
Infinite0
Infinite (%)0.0%
Mean138.94118
Minimum0
Maximum697
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:03.149267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.8
Q12
median7
Q334
95-th percentile697
Maximum697
Range697
Interquartile range (IQR)32

Descriptive statistics

Standard deviation251.65042
Coefficient of variation (CV)1.8112012
Kurtosis1.1643072
Mean138.94118
Median Absolute Deviation (MAD)6
Skewness1.632966
Sum2362
Variance63327.934
MonotonicityNot monotonic
2023-12-11T04:09:03.332267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 3
 
1.9%
3 2
 
1.2%
697 2
 
1.2%
450 1
 
0.6%
34 1
 
0.6%
30 1
 
0.6%
2 1
 
0.6%
0 1
 
0.6%
7 1
 
0.6%
406 1
 
0.6%
Other values (3) 3
 
1.9%
(Missing) 143
89.4%
ValueCountFrequency (%)
0 1
 
0.6%
1 3
1.9%
2 1
 
0.6%
3 2
1.2%
5 1
 
0.6%
7 1
 
0.6%
11 1
 
0.6%
14 1
 
0.6%
30 1
 
0.6%
34 1
 
0.6%
ValueCountFrequency (%)
697 2
1.2%
450 1
0.6%
406 1
0.6%
34 1
0.6%
30 1
0.6%
14 1
0.6%
11 1
0.6%
7 1
0.6%
5 1
0.6%
3 2
1.2%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

실험실특수주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing156
Missing (%)97.5%
Memory size1.4 KiB
2023-12-11T04:09:03.559611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8.5
Mean length7.75
Min length7

Characters and Unicode

Total characters31
Distinct characters25
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

Unique4 ?
Unique (%)100.0%

Sample

1st row일신테크노밸리
2nd row우림빌딩 301호
3rd row범물아파트형공장
4th row우림빌딩 3층
ValueCountFrequency (%)
우림빌딩 2
33.3%
일신테크노밸리 1
16.7%
301호 1
16.7%
범물아파트형공장 1
16.7%
3층 1
16.7%
2023-12-11T04:09:04.000962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 2
 
6.5%
우 2
 
6.5%
림 2
 
6.5%
빌 2
 
6.5%
딩 2
 
6.5%
2
 
6.5%
호 1
 
3.2%
장 1
 
3.2%
공 1
 
3.2%
형 1
 
3.2%
Other values (15) 15
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25
80.6%
Decimal Number 4
 
12.9%
Space Separator 2
 
6.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 2
 
8.0%
림 2
 
8.0%
빌 2
 
8.0%
딩 2
 
8.0%
호 1
 
4.0%
장 1
 
4.0%
공 1
 
4.0%
형 1
 
4.0%
트 1
 
4.0%
파 1
 
4.0%
Other values (11) 11
44.0%
Decimal Number
ValueCountFrequency (%)
3 2
50.0%
1 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25
80.6%
Common 6
 
19.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 2
 
8.0%
림 2
 
8.0%
빌 2
 
8.0%
딩 2
 
8.0%
호 1
 
4.0%
장 1
 
4.0%
공 1
 
4.0%
형 1
 
4.0%
트 1
 
4.0%
파 1
 
4.0%
Other values (11) 11
44.0%
Common
ValueCountFrequency (%)
3 2
33.3%
2
33.3%
1 1
16.7%
0 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25
80.6%
ASCII 6
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 2
33.3%
2
33.3%
1 1
16.7%
0 1
16.7%
Hangul
ValueCountFrequency (%)
우 2
 
8.0%
림 2
 
8.0%
빌 2
 
8.0%
딩 2
 
8.0%
호 1
 
4.0%
장 1
 
4.0%
공 1
 
4.0%
형 1
 
4.0%
트 1
 
4.0%
파 1
 
4.0%
Other values (11) 11
44.0%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing160
Missing (%)100.0%
Memory size1.5 KiB

실험실특수주소호
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
158 
402
 
1
801
 
1

Length

Max length4
Median length4
Mean length3.9875
Min length3

Unique

Unique2 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 158
98.8%
402 1
 
0.6%
801 1
 
0.6%

Length

2023-12-11T04:09:04.326826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:04.522924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 158
98.8%
402 1
 
0.6%
801 1
 
0.6%

실험실도로명주소시군구코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
152 
27290
 
4
27170
 
2
27710
 
2

Length

Max length5
Median length4
Mean length4.05
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
95.0%
27290 4
 
2.5%
27170 2
 
1.2%
27710 2
 
1.2%

Length

2023-12-11T04:09:04.763399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:05.048785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
95.0%
27290 4
 
2.5%
27170 2
 
1.2%
27710 2
 
1.2%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing152
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean2.7365163 × 109
Minimum2.7170103 × 109
Maximum2.771038 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:05.230333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7170103 × 109
5-th percentile2.7170103 × 109
Q12.7260106 × 109
median2.7290116 × 109
Q32.7395158 × 109
95-th percentile2.7710337 × 109
Maximum2.771038 × 109
Range54027722
Interquartile range (IQR)13505182

Descriptive statistics

Standard deviation21937877
Coefficient of variation (CV)0.0080167169
Kurtosis-0.25096657
Mean2.7365163 × 109
Median Absolute Deviation (MAD)6001100
Skewness1.1853511
Sum2.1892131 × 1010
Variance4.8127043 × 1014
MonotonicityNot monotonic
2023-12-11T04:09:05.425530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2717010300 2
 
1.2%
2729011600 2
 
1.2%
2729010700 1
 
0.6%
2771025626 1
 
0.6%
2729012500 1
 
0.6%
2771038022 1
 
0.6%
(Missing) 152
95.0%
ValueCountFrequency (%)
2717010300 2
1.2%
2729010700 1
0.6%
2729011600 2
1.2%
2729012500 1
0.6%
2771025626 1
0.6%
2771038022 1
0.6%
ValueCountFrequency (%)
2771038022 1
0.6%
2771025626 1
0.6%
2729012500 1
0.6%
2729011600 2
1.2%
2729010700 1
0.6%
2717010300 2
1.2%

실험실도로명주소읍면동구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
152 
1
 
6
0
 
2

Length

Max length4
Median length4
Mean length3.85
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 152
95.0%
1 6
 
3.8%
0 2
 
1.2%

Length

2023-12-11T04:09:05.653933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:05.835448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 152
95.0%
1 6
 
3.8%
0 2
 
1.2%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing152
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean3395379.9
Minimum2147001
Maximum4854691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:05.974397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2147001
5-th percentile2495602.4
Q13143005.8
median3146522
Q33566075
95-th percentile4639999.9
Maximum4854691
Range2707690
Interquartile range (IQR)423069.25

Descriptive statistics

Standard deviation815720.78
Coefficient of variation (CV)0.24024433
Kurtosis0.90135595
Mean3395379.9
Median Absolute Deviation (MAD)98999.5
Skewness0.59810567
Sum27163039
Variance6.6540039 × 1011
MonotonicityNot monotonic
2023-12-11T04:09:06.191406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3143006 1
 
0.6%
3147029 1
 
0.6%
2147001 1
 
0.6%
3341004 1
 
0.6%
4241288 1
 
0.6%
4854691 1
 
0.6%
3146015 1
 
0.6%
3143005 1
 
0.6%
(Missing) 152
95.0%
ValueCountFrequency (%)
2147001 1
0.6%
3143005 1
0.6%
3143006 1
0.6%
3146015 1
0.6%
3147029 1
0.6%
3341004 1
0.6%
4241288 1
0.6%
4854691 1
0.6%
ValueCountFrequency (%)
4854691 1
0.6%
4241288 1
0.6%
3341004 1
0.6%
3147029 1
0.6%
3146015 1
0.6%
3143006 1
0.6%
3143005 1
0.6%
2147001 1
0.6%

실험실도로명특수주소
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing159
Missing (%)99.4%
Memory size1.4 KiB
2023-12-11T04:09:06.394357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
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 row일신테크노밸리
ValueCountFrequency (%)
일신테크노밸리 1
100.0%
2023-12-11T04:09:06.918810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
일 1
14.3%
신 1
14.3%
테 1
14.3%
크 1
14.3%
노 1
14.3%
밸 1
14.3%
리 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 1
14.3%
신 1
14.3%
테 1
14.3%
크 1
14.3%
노 1
14.3%
밸 1
14.3%
리 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 1
14.3%
신 1
14.3%
테 1
14.3%
크 1
14.3%
노 1
14.3%
밸 1
14.3%
리 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
일 1
14.3%
신 1
14.3%
테 1
14.3%
크 1
14.3%
노 1
14.3%
밸 1
14.3%
리 1
14.3%

실험실도로명주소건물층구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
150 
0
 
10

Length

Max length4
Median length4
Mean length3.8125
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
93.8%
0 10
 
6.2%

Length

2023-12-11T04:09:07.208158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:07.407373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
93.8%
0 10
 
6.2%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing152
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean173.375
Minimum6
Maximum555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:07.544187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile15.1
Q141.75
median132
Q3213.75
95-th percentile465.75
Maximum555
Range549
Interquartile range (IQR)172

Descriptive statistics

Standard deviation181.90809
Coefficient of variation (CV)1.0492175
Kurtosis2.2862459
Mean173.375
Median Absolute Deviation (MAD)93.5
Skewness1.5062439
Sum1387
Variance33090.554
MonotonicityNot monotonic
2023-12-11T04:09:07.728934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
185 1
 
0.6%
101 1
 
0.6%
555 1
 
0.6%
32 1
 
0.6%
6 1
 
0.6%
45 1
 
0.6%
300 1
 
0.6%
163 1
 
0.6%
(Missing) 152
95.0%
ValueCountFrequency (%)
6 1
0.6%
32 1
0.6%
45 1
0.6%
101 1
0.6%
163 1
0.6%
185 1
0.6%
300 1
0.6%
555 1
0.6%
ValueCountFrequency (%)
555 1
0.6%
300 1
0.6%
185 1
0.6%
163 1
0.6%
101 1
0.6%
45 1
0.6%
32 1
0.6%
6 1
0.6%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
<NA>
153 
0
 
6
23
 
1

Length

Max length4
Median length4
Mean length3.875
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 153
95.6%
0 6
 
3.8%
23 1
 
0.6%

Length

2023-12-11T04:09:07.924213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:09:08.090211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 153
95.6%
0 6
 
3.8%
23 1
 
0.6%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing152
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean125330
Minimum41749
Maximum703849
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T04:09:08.248873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41749
5-th percentile42085
Q142711.25
median42839
Q342950.75
95-th percentile472556.4
Maximum703849
Range662100
Interquartile range (IQR)239.5

Descriptive statistics

Standard deviation233757.31
Coefficient of variation (CV)1.8651345
Kurtosis7.9999315
Mean125330
Median Absolute Deviation (MAD)128.5
Skewness2.828411
Sum1002640
Variance5.464248 × 1010
MonotonicityNot monotonic
2023-12-11T04:09:08.426255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
42839 2
 
1.2%
703849 1
 
0.6%
42709 1
 
0.6%
42930 1
 
0.6%
42712 1
 
0.6%
43013 1
 
0.6%
41749 1
 
0.6%
(Missing) 152
95.0%
ValueCountFrequency (%)
41749 1
0.6%
42709 1
0.6%
42712 1
0.6%
42839 2
1.2%
42930 1
0.6%
43013 1
0.6%
703849 1
0.6%
ValueCountFrequency (%)
703849 1
0.6%
43013 1
0.6%
42930 1
0.6%
42839 2
1.2%
42712 1
0.6%
42709 1
0.6%
41749 1
0.6%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
01환경전문공사업09_30_16_P62700006270000092006000302019-05-14<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704-944대구 달서구 장기동 173번지 23호대구광역시 달서구 성서동로 315 (장기동)<NA>(주)동덕이엔비2019-05-14 13:34:01U2019-05-16 02:40:00<NA>336840.979381262022.093027<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
12환경전문공사업09_30_16_P62700006270000092015000022021-05-26<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 성서로76길 11 (이곡동)704-929(주)에스엘테크2021-05-26 17:25:33U2021-05-28 02:40:00<NA>336163.993897262205.16244<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23환경전문공사업09_30_16_P62700006270000092006000262022-09-14<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-833대구광역시 서구 중리동 1119번지 7호대구광역시 서구 와룡로72길 8 (중리동)703-833(주)청수2022-09-14 12:00:37U2022-09-16 02:40:00<NA>338894.893096263822.5791680환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34환경전문공사업09_30_16_P62700006270000092006000292020-03-16<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>702-710대구광역시 북구 산격2동 1629번지 유통단지산업용재관 18동 224호대구광역시 북구 구암로65길 2-1, 2층 (구암동)41424유림환경개발(주)2023-06-24 10:39:26U2023-06-26 02:40:00<NA>344912.358902268253.8302530환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45환경전문공사업09_30_16_P62700006270000092006000342022-03-08<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-830대구광역시 서구 이현동 42번지 450호대구광역시 서구 와룡로87길 24 (이현동)703-830(주)신라엔텍2022-03-08 14:22:11U2022-03-10 02:40:00<NA>338615.861319264602.381540환경전문공사업0.0<NA>2717010600703830142450<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56환경전문공사업09_30_16_P62700006270000092006000482019-10-31<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704-919대구광역시 달서구 신당동 1320번지 2호대구광역시 달서구 달서대로 559, 이앤씨동 (신당동,이노비즈타워609호)704-919(주)대일환경기술2019-10-31 10:07:21U2019-11-02 02:40:00<NA>334621.225168262044.332358<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
67환경전문공사업09_30_16_P62700006270000092006000012023-05-04<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>706-853대구광역시 수성구 황금2동 847번지 2호대구광역시 수성구 동대구로 111 (황금동)706-853화성산업(주)2023-05-04 09:49:18U2023-05-07 02:40:00<NA>346621.319605261243.1215180환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78환경전문공사업09_30_16_P62700006270000092006000022019-11-07<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703-849대구광역시 서구 평리5동 1492번지 34호대구광역시 서구 서대구로 185 (평리동)703-849(주)대산엔지니어링2022-07-21 15:59:19U2022-07-23 02:40:00<NA>340320.175876264946.0182470환경전문공사업0.0<NA>27170103007038491149234<NA><NA><NA><NA><NA>27170271701030013143006<NA>0185<NA>703849
89환경전문공사업09_30_16_P62700006270000092006000042017-07-10<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>702-828대구광역시 북구 복현2동 340번지 30호대구광역시 북구 동북로 287 (복현동)<NA>금오환경개발(주)2017-07-10 10:50:41I2019-03-23 02:20:03<NA>346361.653327267069.785731<NA>환경전문공사업<NA><NA>2723011200702828134030<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
910환경전문공사업09_30_16_P62700006270000092006000102023-04-05<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704-919대구광역시 달서구 신당동 1320번지 2호 이앤씨 이노비즈타워 1206호대구광역시 달서구 달서대로 559 (신당동,이앤씨 이노비즈타워 1206호)<NA>(주)신세계엔텍2023-04-05 10:58:50U2023-04-07 02:40:00<NA>334621.225168262044.3323580환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
150151환경전문공사업09_30_16_P62700006270000092011000052018-10-25<NA>3폐업Q폐업2020-02-05<NA><NA><NA><NA><NA>702-866대구광역시 북구 태전동 995번지 4호 (2충)대구광역시 북구 연암로 151-43 (산격동)702-846동방이엠아이(주)2020-02-05 13:12:17U2020-02-07 02:40:00<NA>339710.006607271184.176036<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
151152환경전문공사업09_30_16_P62700006270000092017000062018-10-15<NA>3폐업Q폐업2019-08-08<NA><NA><NA><NA><NA><NA><NA>대구시 달성군 유가면 테크노순환로8길9<NA>(주)아이지에스피2019-08-08 09:01:59U2019-08-10 02:40:00<NA><NA><NA><NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
152153환경전문공사업09_30_16_P62700006270000092017000012023-01-10<NA>3폐업Q폐업2023-01-10<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 오봉로2길 17 (노원동1가)41553(주)에스에프에스2023-01-10 16:23:41U2023-05-26 08:48:36<NA>342444.886486266547.7761760환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
153154환경전문공사업09_30_16_P62700006270000092008000082017-09-13<NA>3폐업Q폐업2018-11-12<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 칠곡중앙대로 250-1 (태전동,4층)<NA>(주)세종플랜트2018-11-12 09:59:31I2018-11-14 02:37:29<NA>339654.246784269791.354544<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
154155환경전문공사업09_30_16_P62700006270000092006000232021-08-11<NA>3폐업Q폐업2022-02-16<NA><NA><NA><NA><NA>43008대구광역시 달성군 구지면 응암리 1278-10대구광역시 달성군 구지면 국가산단대로46길 6343008(주)지이테크2022-02-18 08:33:38U2022-02-20 02:40:00<NA>328923.524848239903.4240580환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
155156환경전문공사업09_30_16_P62700006270000092006000132020-09-08<NA>3폐업Q폐업2020-12-17<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 호국로 227 (서변동,5층)<NA>(주)수성이앤씨2020-12-28 15:20:12U2020-12-30 02:40:00<NA>344255.865358270243.37448<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
156157환경전문공사업09_30_16_P62700006270000092008000052016-11-14<NA>3폐업Q폐업2018-07-10<NA><NA><NA><NA><NA>711-834대구광역시 달성군 화원읍 천내리 107번지 3호대구광역시 달성군 화원읍 성천로 122<NA>(주)금창엔지니어링2018-11-30 15:10:33I2018-12-02 02:20:04<NA>335023.196036257280.6842980환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
157158환경전문공사업09_30_16_P62700006270000092011000082019-12-30<NA>3폐업Q폐업2021-01-29<NA><NA><NA><NA><NA>42709대구광역시 달서구 신당동 1320-2 이앤씨이노비즈타워 503호대구광역시 달서구 달서대로 559, 이앤씨이노비즈타워 503호 (신당동)42709엔테크원(주)2021-01-29 09:32:58U2021-01-31 02:40:00<NA>334621.225168262044.332358<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
158159환경전문공사업09_30_16_P62700006270000092018000022018-07-29<NA>3폐업Q폐업2018-12-31<NA><NA><NA><NA><NA><NA>대구광역시 동구 율하동 1447번지 율하동우체국대구광역시 동구 안심로16길 49 (율하동)<NA>주식회사 지엔비2018-12-31 15:11:44I2019-01-02 02:20:35<NA><NA><NA><NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
159160환경전문공사업09_30_16_P62700006270000092021000022022-12-06<NA>3폐업Q폐업2023-01-17<NA><NA><NA><NA><NA>42711대구광역시 달서구 파호동 200-4대구광역시 달서구 성서공단북로2길 18 (파호동)42711신한환경기술(주)2023-01-25 13:16:06U2023-05-26 08:48:36<NA>333010.938174261277.4614050환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>