Overview

Dataset statistics

Number of variables51
Number of observations156
Missing cells3222
Missing cells (%)40.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.1 KiB
Average record size in memory446.8 B

Variable types

Numeric16
Categorical18
Unsupported11
Text5
DateTime1

Dataset

Description22년10월_6270000_대구광역시_09_30_16_P_환경전문공사업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096995&dataSetDetailId=DDI_0000097035&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 (65.6%)Imbalance
실험실특수주소호 is highly imbalanced (94.4%)Imbalance
실험실도로명주소시군구코드 is highly imbalanced (85.4%)Imbalance
실험실도로명주소읍면동코드 is highly imbalanced (86.7%)Imbalance
실험실도로명주소읍면동구분 is highly imbalanced (83.6%)Imbalance
실험실도로명주소건물층구분 is highly imbalanced (70.8%)Imbalance
실험실도로명주소건물부번호 is highly imbalanced (85.6%)Imbalance
실험실도로명주소우편번호 is highly imbalanced (87.6%)Imbalance
인허가취소일자 has 156 (100.0%) missing valuesMissing
폐업일자 has 43 (27.6%) missing valuesMissing
휴업시작일자 has 156 (100.0%) missing valuesMissing
휴업종료일자 has 156 (100.0%) missing valuesMissing
재개업일자 has 156 (100.0%) missing valuesMissing
소재지전화 has 156 (100.0%) missing valuesMissing
소재지면적 has 156 (100.0%) missing valuesMissing
소재지우편번호 has 42 (26.9%) missing valuesMissing
소재지전체주소 has 28 (17.9%) missing valuesMissing
도로명전체주소 has 3 (1.9%) missing valuesMissing
도로명우편번호 has 66 (42.3%) missing valuesMissing
업태구분명 has 156 (100.0%) missing valuesMissing
좌표정보(X) has 21 (13.5%) missing valuesMissing
좌표정보(Y) has 21 (13.5%) missing valuesMissing
영업소면적 has 111 (71.2%) missing valuesMissing
위탁업체명 has 156 (100.0%) missing valuesMissing
실험실지역코드 has 141 (90.4%) missing valuesMissing
실험실우편번호 has 141 (90.4%) missing valuesMissing
실험실번지 has 141 (90.4%) missing valuesMissing
실험실호 has 141 (90.4%) missing valuesMissing
실험실통 has 156 (100.0%) missing valuesMissing
실험실반 has 156 (100.0%) missing valuesMissing
실험실특수주소 has 152 (97.4%) missing valuesMissing
실험실특수주소동 has 156 (100.0%) missing valuesMissing
실험실도로명주소코드 has 150 (96.2%) missing valuesMissing
실험실도로명특수주소 has 155 (99.4%) missing valuesMissing
실험실도로명주소건물본번호 has 150 (96.2%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지전화 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
위탁업체명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실통 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실반 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실특수주소동 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업소면적 has 35 (22.4%) zerosZeros

Reproduction

Analysis started2024-04-18 05:40:47.038429
Analysis finished2024-04-18 05:40:47.660773
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.5
Minimum1
Maximum156
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:47.723125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.75
Q139.75
median78.5
Q3117.25
95-th percentile148.25
Maximum156
Range155
Interquartile range (IQR)77.5

Descriptive statistics

Standard deviation45.177428
Coefficient of variation (CV)0.57550864
Kurtosis-1.2
Mean78.5
Median Absolute Deviation (MAD)39
Skewness0
Sum12246
Variance2041
MonotonicityStrictly increasing
2024-04-18T14:40:47.859376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
109 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
110 1
 
0.6%
Other values (146) 146
93.6%
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 (%)
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
환경전문공사업
156 

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 156
100.0%

Length

2024-04-18T14:40:47.985984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:48.073350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 156
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
09_30_16_P
156 

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 156
100.0%

Length

2024-04-18T14:40:48.176031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:48.277364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_16_p 156
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
6270000
156 

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 156
100.0%

Length

2024-04-18T14:40:48.370161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:48.457017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 156
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct156
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
2024-04-18T14:40:48.557982image/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
Range1500006
Interquartile range (IQR)899968

Descriptive statistics

Standard deviation507873.82
Coefficient of variation (CV)8.1000608 × 10-13
Kurtosis-1.0480716
Mean6.2700001 × 1017
Median Absolute Deviation (MAD)400000
Skewness0.56414466
Sum5.5782811 × 1018
Variance2.5793582 × 1011
MonotonicityNot monotonic
2024-04-18T14:40:48.691191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
627000009200600030 1
 
0.6%
627000009201100003 1
 
0.6%
627000009201000003 1
 
0.6%
627000009201000005 1
 
0.6%
627000009201000006 1
 
0.6%
627000009201000007 1
 
0.6%
627000009201000008 1
 
0.6%
627000009201100001 1
 
0.6%
627000009201100002 1
 
0.6%
627000009201100004 1
 
0.6%
Other values (146) 146
93.6%
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 (%)
627000009202100007 1
0.6%
627000009202100006 1
0.6%
627000009202100005 1
0.6%
627000009202100004 1
0.6%
627000009202100003 1
0.6%
627000009202100002 1
0.6%
627000009202100001 1
0.6%
627000009202000008 1
0.6%
627000009202000007 1
0.6%
627000009202000006 1
0.6%

인허가일자
Real number (ℝ)

Distinct146
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20151880
Minimum20060802
Maximum20221006
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:48.825004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060802
5-th percentile20070669
Q120110485
median20150759
Q320200843
95-th percentile20220727
Maximum20221006
Range160204
Interquartile range (IQR)90358

Descriptive statistics

Standard deviation51874.152
Coefficient of variation (CV)0.0025741595
Kurtosis-1.2932221
Mean20151880
Median Absolute Deviation (MAD)49560.5
Skewness-0.18429167
Sum3.1436932 × 109
Variance2.6909277 × 109
MonotonicityNot monotonic
2024-04-18T14:40:48.956541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131227 2
 
1.3%
20061127 2
 
1.3%
20070920 2
 
1.3%
20220308 2
 
1.3%
20190618 2
 
1.3%
20070725 2
 
1.3%
20220829 2
 
1.3%
20090318 2
 
1.3%
20220502 2
 
1.3%
20220822 2
 
1.3%
Other values (136) 136
87.2%
ValueCountFrequency (%)
20060802 1
0.6%
20060901 1
0.6%
20061127 2
1.3%
20061227 1
0.6%
20070123 1
0.6%
20070309 1
0.6%
20070501 1
0.6%
20070725 2
1.3%
20070920 2
1.3%
20070921 1
0.6%
ValueCountFrequency (%)
20221006 1
0.6%
20220921 1
0.6%
20220914 1
0.6%
20220829 2
1.3%
20220822 2
1.3%
20220729 1
0.6%
20220726 1
0.6%
20220719 1
0.6%
20220705 1
0.6%
20220627 1
0.6%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
116 
1
40 

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 (%)
3 116
74.4%
1 40
 
25.6%

Length

2024-04-18T14:40:49.094671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:49.205231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 116
74.4%
1 40
 
25.6%

영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
116 
영업/정상
40 

Length

Max length5
Median length2
Mean length2.7692308
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 116
74.4%
영업/정상 40
 
25.6%

Length

2024-04-18T14:40:49.308533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:49.402783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
74.4%
영업/정상 40
 
25.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Q
116 
N
40 

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 116
74.4%
N 40
 
25.6%

Length

2024-04-18T14:40:49.498659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:49.596633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
q 116
74.4%
n 40
 
25.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
116 
신규
40 

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 116
74.4%
신규 40
 
25.6%

Length

2024-04-18T14:40:49.757861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:49.846766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 116
74.4%
신규 40
 
25.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct102
Distinct (%)90.3%
Missing43
Missing (%)27.6%
Infinite0
Infinite (%)0.0%
Mean20143430
Minimum20061127
Maximum20220419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:49.950498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20061127
5-th percentile20071132
Q120100707
median20141201
Q320190710
95-th percentile20220154
Maximum20220419
Range159292
Interquartile range (IQR)90003

Descriptive statistics

Standard deviation47286.844
Coefficient of variation (CV)0.0023475071
Kurtosis-1.2002777
Mean20143430
Median Absolute Deviation (MAD)40577
Skewness0.067790112
Sum2.2762076 × 109
Variance2.2360456 × 109
MonotonicityNot monotonic
2024-04-18T14:40:50.082853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20151026 3
 
1.9%
20150204 3
 
1.9%
20080814 3
 
1.9%
20061127 2
 
1.3%
20151109 2
 
1.3%
20120508 2
 
1.3%
20091130 2
 
1.3%
20150203 2
 
1.3%
20181112 1
 
0.6%
20141029 1
 
0.6%
Other values (92) 92
59.0%
(Missing) 43
27.6%
ValueCountFrequency (%)
20061127 2
1.3%
20070907 1
 
0.6%
20070920 1
 
0.6%
20070921 1
 
0.6%
20071010 1
 
0.6%
20071213 1
 
0.6%
20080221 1
 
0.6%
20080514 1
 
0.6%
20080714 1
 
0.6%
20080814 3
1.9%
ValueCountFrequency (%)
20220419 1
0.6%
20220223 1
0.6%
20220216 1
0.6%
20220215 1
0.6%
20220211 1
0.6%
20220207 1
0.6%
20220118 1
0.6%
20211209 1
0.6%
20211201 1
0.6%
20210518 1
0.6%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct81
Distinct (%)71.1%
Missing42
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean518520.26
Minimum41003
Maximum711883
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:50.220018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41003
5-th percentile41434.35
Q143008
median703826.5
Q3704914.75
95-th percentile706819.85
Maximum711883
Range670880
Interquartile range (IQR)661906.75

Descriptive statistics

Standard deviation298853.86
Coefficient of variation (CV)0.57635908
Kurtosis-1.0401666
Mean518520.26
Median Absolute Deviation (MAD)1116
Skewness-0.98906962
Sum59111310
Variance8.931363 × 1010
MonotonicityNot monotonic
2024-04-18T14:40:50.351933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702845 5
 
3.2%
704919 4
 
2.6%
42709 4
 
2.6%
42839 3
 
1.9%
704946 3
 
1.9%
703833 3
 
1.9%
704801 3
 
1.9%
704920 3
 
1.9%
704220 3
 
1.9%
704944 3
 
1.9%
Other values (71) 80
51.3%
(Missing) 42
26.9%
ValueCountFrequency (%)
41003 1
0.6%
41028 2
1.3%
41067 1
0.6%
41251 1
0.6%
41409 1
0.6%
41448 1
0.6%
41475 1
0.6%
41518 1
0.6%
41561 1
0.6%
41752 1
0.6%
ValueCountFrequency (%)
711883 1
0.6%
711834 1
0.6%
706853 1
0.6%
706837 1
0.6%
706829 1
0.6%
706827 1
0.6%
706816 1
0.6%
706813 1
0.6%
706803 1
0.6%
706032 1
0.6%

소재지전체주소
Text

MISSING 

Distinct118
Distinct (%)92.2%
Missing28
Missing (%)17.9%
Memory size1.3 KiB
2024-04-18T14:40:50.697654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length25.929688
Min length18

Characters and Unicode

Total characters3319
Distinct characters136
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

Unique109 ?
Unique (%)85.2%

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 119
 
17.9%
달서구 57
 
8.6%
북구 26
 
3.9%
서구 19
 
2.9%
신당동 14
 
2.1%
2호 11
 
1.7%
3호 11
 
1.7%
수성구 10
 
1.5%
대구 9
 
1.4%
호산동 9
 
1.4%
Other values (232) 378
57.0%
2024-04-18T14:40:51.173706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
768
23.1%
구 252
 
7.6%
1 143
 
4.3%
대 134
 
4.0%
동 133
 
4.0%
광 119
 
3.6%
역 119
 
3.6%
시 119
 
3.6%
호 113
 
3.4%
지 110
 
3.3%
Other values (126) 1309
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1829
55.1%
Space Separator 768
23.1%
Decimal Number 676
 
20.4%
Dash Punctuation 29
 
0.9%
Uppercase Letter 10
 
0.3%
Other Punctuation 3
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 252
13.8%
대 134
 
7.3%
동 133
 
7.3%
광 119
 
6.5%
역 119
 
6.5%
시 119
 
6.5%
호 113
 
6.2%
지 110
 
6.0%
번 101
 
5.5%
서 79
 
4.3%
Other values (106) 550
30.1%
Decimal Number
ValueCountFrequency (%)
1 143
21.2%
2 103
15.2%
3 86
12.7%
0 67
9.9%
4 55
 
8.1%
7 50
 
7.4%
8 48
 
7.1%
6 47
 
7.0%
5 41
 
6.1%
9 36
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
D 4
40.0%
B 2
20.0%
T 2
20.0%
C 2
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
768
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1829
55.1%
Common 1480
44.6%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 252
13.8%
대 134
 
7.3%
동 133
 
7.3%
광 119
 
6.5%
역 119
 
6.5%
시 119
 
6.5%
호 113
 
6.2%
지 110
 
6.0%
번 101
 
5.5%
서 79
 
4.3%
Other values (106) 550
30.1%
Common
ValueCountFrequency (%)
768
51.9%
1 143
 
9.7%
2 103
 
7.0%
3 86
 
5.8%
0 67
 
4.5%
4 55
 
3.7%
7 50
 
3.4%
8 48
 
3.2%
6 47
 
3.2%
5 41
 
2.8%
Other values (6) 72
 
4.9%
Latin
ValueCountFrequency (%)
D 4
40.0%
B 2
20.0%
T 2
20.0%
C 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1829
55.1%
ASCII 1490
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
768
51.5%
1 143
 
9.6%
2 103
 
6.9%
3 86
 
5.8%
0 67
 
4.5%
4 55
 
3.7%
7 50
 
3.4%
8 48
 
3.2%
6 47
 
3.2%
5 41
 
2.8%
Other values (10) 82
 
5.5%
Hangul
ValueCountFrequency (%)
구 252
13.8%
대 134
 
7.3%
동 133
 
7.3%
광 119
 
6.5%
역 119
 
6.5%
시 119
 
6.5%
호 113
 
6.2%
지 110
 
6.0%
번 101
 
5.5%
서 79
 
4.3%
Other values (106) 550
30.1%

도로명전체주소
Text

MISSING 

Distinct135
Distinct (%)88.2%
Missing3
Missing (%)1.9%
Memory size1.3 KiB
2024-04-18T14:40:51.508469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length27.895425
Min length19

Characters and Unicode

Total characters4268
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

Unique120 ?
Unique (%)78.4%

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 151
 
18.0%
달서구 68
 
8.1%
북구 31
 
3.7%
서구 18
 
2.1%
2층 15
 
1.8%
달성군 13
 
1.5%
수성구 11
 
1.3%
달서대로 10
 
1.2%
동구 9
 
1.1%
559 9
 
1.1%
Other values (313) 504
60.1%
2024-04-18T14:40:52.016503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
686
 
16.1%
구 310
 
7.3%
대 190
 
4.5%
동 170
 
4.0%
시 154
 
3.6%
광 151
 
3.5%
역 151
 
3.5%
로 151
 
3.5%
( 140
 
3.3%
) 140
 
3.3%
Other values (162) 2025
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2537
59.4%
Space Separator 686
 
16.1%
Decimal Number 664
 
15.6%
Open Punctuation 140
 
3.3%
Close Punctuation 140
 
3.3%
Other Punctuation 69
 
1.6%
Dash Punctuation 25
 
0.6%
Uppercase Letter 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 310
 
12.2%
대 190
 
7.5%
동 170
 
6.7%
시 154
 
6.1%
광 151
 
6.0%
역 151
 
6.0%
로 151
 
6.0%
서 136
 
5.4%
달 103
 
4.1%
길 71
 
2.8%
Other values (144) 950
37.4%
Decimal Number
ValueCountFrequency (%)
1 131
19.7%
2 99
14.9%
3 79
11.9%
5 69
10.4%
4 57
8.6%
0 53
8.0%
6 51
 
7.7%
8 50
 
7.5%
9 43
 
6.5%
7 32
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
42.9%
T 2
28.6%
D 2
28.6%
Space Separator
ValueCountFrequency (%)
686
100.0%
Open Punctuation
ValueCountFrequency (%)
( 140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 140
100.0%
Other Punctuation
ValueCountFrequency (%)
, 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2537
59.4%
Common 1724
40.4%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 310
 
12.2%
대 190
 
7.5%
동 170
 
6.7%
시 154
 
6.1%
광 151
 
6.0%
역 151
 
6.0%
로 151
 
6.0%
서 136
 
5.4%
달 103
 
4.1%
길 71
 
2.8%
Other values (144) 950
37.4%
Common
ValueCountFrequency (%)
686
39.8%
( 140
 
8.1%
) 140
 
8.1%
1 131
 
7.6%
2 99
 
5.7%
3 79
 
4.6%
, 69
 
4.0%
5 69
 
4.0%
4 57
 
3.3%
0 53
 
3.1%
Other values (5) 201
 
11.7%
Latin
ValueCountFrequency (%)
C 3
42.9%
T 2
28.6%
D 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2537
59.4%
ASCII 1731
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
686
39.6%
( 140
 
8.1%
) 140
 
8.1%
1 131
 
7.6%
2 99
 
5.7%
3 79
 
4.6%
, 69
 
4.0%
5 69
 
4.0%
4 57
 
3.3%
0 53
 
3.1%
Other values (8) 208
 
12.0%
Hangul
ValueCountFrequency (%)
구 310
 
12.2%
대 190
 
7.5%
동 170
 
6.7%
시 154
 
6.1%
광 151
 
6.0%
역 151
 
6.0%
로 151
 
6.0%
서 136
 
5.4%
달 103
 
4.1%
길 71
 
2.8%
Other values (144) 950
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct72
Distinct (%)80.0%
Missing66
Missing (%)42.3%
Infinite0
Infinite (%)0.0%
Mean395353.86
Minimum41003
Maximum711855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:52.152984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41003
5-th percentile41322.1
Q142705.25
median701847
Q3703846.25
95-th percentile706461.55
Maximum711855
Range670852
Interquartile range (IQR)661141

Descriptive statistics

Standard deviation332131.76
Coefficient of variation (CV)0.84008732
Kurtosis-2.0270045
Mean395353.86
Median Absolute Deviation (MAD)4987.5
Skewness-0.13584822
Sum35581847
Variance1.1031151 × 1011
MonotonicityNot monotonic
2024-04-18T14:40:52.285997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42709 5
 
3.2%
704948 3
 
1.9%
703833 3
 
1.9%
42839 3
 
1.9%
41028 2
 
1.3%
702845 2
 
1.3%
701847 2
 
1.3%
702110 2
 
1.3%
43008 2
 
1.3%
704900 2
 
1.3%
Other values (62) 64
41.0%
(Missing) 66
42.3%
ValueCountFrequency (%)
41003 1
0.6%
41028 2
1.3%
41067 1
0.6%
41251 1
0.6%
41409 1
0.6%
41424 1
0.6%
41448 1
0.6%
41475 1
0.6%
41518 1
0.6%
41553 1
0.6%
ValueCountFrequency (%)
711855 1
 
0.6%
711821 1
 
0.6%
706853 1
 
0.6%
706816 1
 
0.6%
706813 1
 
0.6%
706032 1
 
0.6%
704948 3
1.9%
704944 1
 
0.6%
704929 1
 
0.6%
704920 1
 
0.6%

사업장명
Text

Distinct125
Distinct (%)80.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-18T14:40:52.507100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.2628205
Min length2

Characters and Unicode

Total characters1289
Distinct characters134
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 (%)65.4%

Sample

1st row(주)동덕이엔비
2nd row(주)에스엘테크
3rd row(주)청수
4th row유림환경개발(주)
5th row(주)신라엔텍
ValueCountFrequency (%)
주식회사 8
 
4.7%
제이에스엔텍(주 4
 
2.4%
주)세종플랜트 4
 
2.4%
주)동서환경개발 3
 
1.8%
주)지원이엔에스 3
 
1.8%
주)동우이엔티 3
 
1.8%
주)미래엔비텍 3
 
1.8%
주)에이치케이파워텍 2
 
1.2%
주)한성플랜트 2
 
1.2%
주)수성이앤씨 2
 
1.2%
Other values (121) 135
79.9%
2024-04-18T14:40:52.869899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 136
 
10.6%
( 128
 
9.9%
) 128
 
9.9%
이 51
 
4.0%
엔 51
 
4.0%
경 42
 
3.3%
환 38
 
2.9%
지 33
 
2.6%
에 32
 
2.5%
스 29
 
2.2%
Other values (124) 621
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1006
78.0%
Open Punctuation 128
 
9.9%
Close Punctuation 128
 
9.9%
Space Separator 13
 
1.0%
Uppercase Letter 10
 
0.8%
Other Symbol 2
 
0.2%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 136
 
13.5%
이 51
 
5.1%
엔 51
 
5.1%
경 42
 
4.2%
환 38
 
3.8%
지 33
 
3.3%
에 32
 
3.2%
스 29
 
2.9%
텍 24
 
2.4%
플 17
 
1.7%
Other values (111) 553
55.0%
Uppercase Letter
ValueCountFrequency (%)
N 2
20.0%
E 2
20.0%
G 2
20.0%
D 1
10.0%
S 1
10.0%
V 1
10.0%
I 1
10.0%
Open Punctuation
ValueCountFrequency (%)
( 128
100.0%
Close Punctuation
ValueCountFrequency (%)
) 128
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1008
78.2%
Common 271
 
21.0%
Latin 10
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 136
 
13.5%
이 51
 
5.1%
엔 51
 
5.1%
경 42
 
4.2%
환 38
 
3.8%
지 33
 
3.3%
에 32
 
3.2%
스 29
 
2.9%
텍 24
 
2.4%
플 17
 
1.7%
Other values (112) 555
55.1%
Latin
ValueCountFrequency (%)
N 2
20.0%
E 2
20.0%
G 2
20.0%
D 1
10.0%
S 1
10.0%
V 1
10.0%
I 1
10.0%
Common
ValueCountFrequency (%)
( 128
47.2%
) 128
47.2%
13
 
4.8%
& 1
 
0.4%
- 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1006
78.0%
ASCII 281
 
21.8%
None 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 136
 
13.5%
이 51
 
5.1%
엔 51
 
5.1%
경 42
 
4.2%
환 38
 
3.8%
지 33
 
3.3%
에 32
 
3.2%
스 29
 
2.9%
텍 24
 
2.4%
플 17
 
1.7%
Other values (111) 553
55.0%
ASCII
ValueCountFrequency (%)
( 128
45.6%
) 128
45.6%
13
 
4.6%
N 2
 
0.7%
E 2
 
0.7%
G 2
 
0.7%
D 1
 
0.4%
S 1
 
0.4%
& 1
 
0.4%
- 1
 
0.4%
Other values (2) 2
 
0.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct156
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0164018 × 1013
Minimum2.0061127 × 1013
Maximum2.0221006 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:53.003250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0061127 × 1013
5-th percentile2.0080665 × 1013
Q12.0120771 × 1013
median2.0170662 × 1013
Q32.021044 × 1013
95-th percentile2.0220727 × 1013
Maximum2.0221006 × 1013
Range1.5987896 × 1011
Interquartile range (IQR)8.9669025 × 1010

Descriptive statistics

Standard deviation4.9020684 × 1010
Coefficient of variation (CV)0.002431097
Kurtosis-1.1325892
Mean2.0164018 × 1013
Median Absolute Deviation (MAD)4.0097 × 1010
Skewness-0.41827742
Sum3.1455869 × 1015
Variance2.4030275 × 1021
MonotonicityNot monotonic
2024-04-18T14:40:54.216748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190514133401 1
 
0.6%
20151026103326 1
 
0.6%
20170404131703 1
 
0.6%
20110308131323 1
 
0.6%
20151026102630 1
 
0.6%
20180720174127 1
 
0.6%
20141205133106 1
 
0.6%
20170803132436 1
 
0.6%
20160824193418 1
 
0.6%
20130305171040 1
 
0.6%
Other values (146) 146
93.6%
ValueCountFrequency (%)
20061127172753 1
0.6%
20061127173223 1
0.6%
20070920153422 1
0.6%
20070921164240 1
0.6%
20080409123330 1
0.6%
20080409131733 1
0.6%
20080423222652 1
0.6%
20080514094300 1
0.6%
20080715105435 1
0.6%
20080827194413 1
0.6%
ValueCountFrequency (%)
20221006132459 1
0.6%
20220921142559 1
0.6%
20220914120037 1
0.6%
20220829171505 1
0.6%
20220829094835 1
0.6%
20220822130625 1
0.6%
20220822130528 1
0.6%
20220729175035 1
0.6%
20220726104221 1
0.6%
20220721155919 1
0.6%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
89 
U
67 

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 89
57.1%
U 67
42.9%

Length

2024-04-18T14:40:54.356647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:54.452096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 89
57.1%
u 67
42.9%

데이터갱신일자
Date

Distinct60
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-11-14 02:37:29
Maximum2022-10-08 02:40:00
2024-04-18T14:40:54.555102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T14:40:54.687037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)78.5%
Missing21
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean339668.48
Minimum326780
Maximum355576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:54.833925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326780
5-th percentile332940.83
Q1335193.7
median339060.54
Q3344224.82
95-th percentile347972.25
Maximum355576
Range28796
Interquartile range (IQR)9031.1215

Descriptive statistics

Standard deviation5154.4024
Coefficient of variation (CV)0.015174804
Kurtosis-0.06333553
Mean339668.48
Median Absolute Deviation (MAD)4058.2935
Skewness0.38466373
Sum45855245
Variance26567865
MonotonicityNot monotonic
2024-04-18T14:40:54.978654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
334621.225167 8
 
5.1%
344912.358902 3
 
1.9%
335199.688361 3
 
1.9%
336839.695095 3
 
1.9%
339654.246784 3
 
1.9%
344255.865358 2
 
1.3%
339755.076237 2
 
1.3%
339777.0 2
 
1.3%
352954.301946 2
 
1.3%
340022.118911 2
 
1.3%
Other values (96) 105
67.3%
(Missing) 21
 
13.5%
ValueCountFrequency (%)
326780.0 1
0.6%
329454.216845 1
0.6%
330363.440564 1
0.6%
331535.063936 1
0.6%
332153.420375 1
0.6%
332610.0 1
0.6%
332777.25472 1
0.6%
333010.938174 1
0.6%
333204.185268 2
1.3%
333346.979452 1
0.6%
ValueCountFrequency (%)
355576.0 1
0.6%
352954.301946 2
1.3%
348879.46041 1
0.6%
348378.873769 1
0.6%
348002.0 2
1.3%
347959.493733 1
0.6%
346986.540457 1
0.6%
346621.319605 1
0.6%
346576.337771 1
0.6%
346361.653327 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct106
Distinct (%)78.5%
Missing21
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean263520.65
Minimum243302
Maximum272987.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:55.110923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243302
5-th percentile257474
Q1261322.78
median262427.43
Q3266506.45
95-th percentile270240.73
Maximum272987.62
Range29685.62
Interquartile range (IQR)5183.6711

Descriptive statistics

Standard deviation4665.9861
Coefficient of variation (CV)0.01770634
Kurtosis4.092132
Mean263520.65
Median Absolute Deviation (MAD)2255.6838
Skewness-1.0102542
Sum35575287
Variance21771426
MonotonicityNot monotonic
2024-04-18T14:40:55.237369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262044.332358 8
 
5.1%
268253.830253 3
 
1.9%
259343.910784 3
 
1.9%
262065.487156 3
 
1.9%
269791.354544 3
 
1.9%
270243.37448 2
 
1.3%
262368.397824 2
 
1.3%
257474.0 2
 
1.3%
264243.167646 2
 
1.3%
272987.619729 2
 
1.3%
Other values (96) 105
67.3%
(Missing) 21
 
13.5%
ValueCountFrequency (%)
243302.0 1
0.6%
243957.688389 1
0.6%
249180.711679 1
0.6%
253850.09474 1
0.6%
257280.684298 1
0.6%
257380.142481 1
0.6%
257474.0 2
1.3%
257850.291372 1
0.6%
258719.392567 1
0.6%
258751.186976 1
0.6%
ValueCountFrequency (%)
272987.619729 2
1.3%
272436.922125 1
 
0.6%
272405.875051 1
 
0.6%
271184.176036 1
 
0.6%
270243.37448 2
1.3%
270239.59999 1
 
0.6%
270209.50299 1
 
0.6%
270010.0 2
1.3%
270000.062466 1
 
0.6%
269791.354544 3
1.9%

실험실면적
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
117 
0
39 

Length

Max length4
Median length4
Mean length3.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 117
75.0%
0 39
 
25.0%

Length

2024-04-18T14:40:55.374316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:55.501867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 117
75.0%
0 39
 
25.0%

사업장구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
환경전문공사업
156 

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 156
100.0%

Length

2024-04-18T14:40:55.604760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:55.705260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 156
100.0%

영업소면적
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)24.4%
Missing111
Missing (%)71.2%
Infinite0
Infinite (%)0.0%
Mean136.77556
Minimum0
Maximum4390
Zeros35
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:55.788549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile304.68
Maximum4390
Range4390
Interquartile range (IQR)0

Descriptive statistics

Standard deviation655.02872
Coefficient of variation (CV)4.7890774
Kurtosis43.091837
Mean136.77556
Median Absolute Deviation (MAD)0
Skewness6.5055918
Sum6154.9
Variance429062.63
MonotonicityNot monotonic
2024-04-18T14:40:55.891102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 35
 
22.4%
115.0 1
 
0.6%
364.0 1
 
0.6%
76.15 1
 
0.6%
153.0 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%
(Missing) 111
71.2%
ValueCountFrequency (%)
0.0 35
22.4%
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 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

실험실지역코드
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)66.7%
Missing141
Missing (%)90.4%
Infinite0
Infinite (%)0.0%
Mean2.725213 × 109
Minimum2.7140111 × 109
Maximum2.771038 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:56.034264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.7140111 × 109
5-th percentile2.7140111 × 109
Q12.7170104 × 109
median2.7230126 × 109
Q32.7290108 × 109
95-th percentile2.7416195 × 109
Maximum2.771038 × 109
Range57026922
Interquartile range (IQR)12000350

Descriptive statistics

Standard deviation13869028
Coefficient of variation (CV)0.0050891538
Kurtosis9.4782069
Mean2.725213 × 109
Median Absolute Deviation (MAD)5999000
Skewness2.8237183
Sum4.0878195 × 1010
Variance1.9234994 × 1014
MonotonicityNot monotonic
2024-04-18T14:40:56.158403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2717010600 2
 
1.3%
2717010300 2
 
1.3%
2729011600 2
 
1.3%
2714011100 2
 
1.3%
2723012600 2
 
1.3%
2723011200 1
 
0.6%
2771038022 1
 
0.6%
2729010700 1
 
0.6%
2726011300 1
 
0.6%
2729010900 1
 
0.6%
(Missing) 141
90.4%
ValueCountFrequency (%)
2714011100 2
1.3%
2717010300 2
1.3%
2717010600 2
1.3%
2723011200 1
0.6%
2723012600 2
1.3%
2726011300 1
0.6%
2729010700 1
0.6%
2729010900 1
0.6%
2729011600 2
1.3%
2771038022 1
0.6%
ValueCountFrequency (%)
2771038022 1
0.6%
2729011600 2
1.3%
2729010900 1
0.6%
2729010700 1
0.6%
2726011300 1
0.6%
2723012600 2
1.3%
2723011200 1
0.6%
2717010600 2
1.3%
2717010300 2
1.3%
2714011100 2
1.3%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)73.3%
Missing141
Missing (%)90.4%
Infinite0
Infinite (%)0.0%
Mean483188.47
Minimum41749
Maximum706813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:56.261795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41749
5-th percentile42421
Q142926
median702828
Q3703830
95-th percentile704976.9
Maximum706813
Range665064
Interquartile range (IQR)660904

Descriptive statistics

Standard deviation322458.12
Coefficient of variation (CV)0.66735475
Kurtosis-1.6153753
Mean483188.47
Median Absolute Deviation (MAD)1024
Skewness-0.7881836
Sum7247827
Variance1.0397924 × 1011
MonotonicityNot monotonic
2024-04-18T14:40:56.356221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
703830 2
 
1.3%
42839 2
 
1.3%
701804 2
 
1.3%
702865 2
 
1.3%
703849 1
 
0.6%
702828 1
 
0.6%
43013 1
 
0.6%
42709 1
 
0.6%
706813 1
 
0.6%
704190 1
 
0.6%
(Missing) 141
90.4%
ValueCountFrequency (%)
41749 1
0.6%
42709 1
0.6%
42839 2
1.3%
43013 1
0.6%
701804 2
1.3%
702828 1
0.6%
702865 2
1.3%
703830 2
1.3%
703849 1
0.6%
704190 1
0.6%
ValueCountFrequency (%)
706813 1
0.6%
704190 1
0.6%
703849 1
0.6%
703830 2
1.3%
702865 2
1.3%
702828 1
0.6%
701804 2
1.3%
43013 1
0.6%
42839 2
1.3%
42709 1
0.6%

실험실산
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
141 
1
 
10
0
 
5

Length

Max length4
Median length4
Mean length3.7115385
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> 141
90.4%
1 10
 
6.4%
0 5
 
3.2%

Length

2024-04-18T14:40:56.478553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:56.575674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 141
90.4%
1 10
 
6.4%
0 5
 
3.2%

실험실번지
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)80.0%
Missing141
Missing (%)90.4%
Infinite0
Infinite (%)0.0%
Mean737.86667
Minimum42
Maximum1492
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:56.659876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42
5-th percentile42
Q1439.5
median573
Q31172.5
95-th percentile1350.6
Maximum1492
Range1450
Interquartile range (IQR)733

Descriptive statistics

Standard deviation473.21693
Coefficient of variation (CV)0.64133123
Kurtosis-1.2777521
Mean737.86667
Median Absolute Deviation (MAD)511
Skewness0.12246715
Sum11068
Variance223934.27
MonotonicityNot monotonic
2024-04-18T14:40:56.764960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
42 2
 
1.3%
1084 2
 
1.3%
539 2
 
1.3%
1492 1
 
0.6%
340 1
 
0.6%
597 1
 
0.6%
1290 1
 
0.6%
1261 1
 
0.6%
1287 1
 
0.6%
333 1
 
0.6%
Other values (2) 2
 
1.3%
(Missing) 141
90.4%
ValueCountFrequency (%)
42 2
1.3%
333 1
0.6%
340 1
0.6%
539 2
1.3%
565 1
0.6%
573 1
0.6%
597 1
0.6%
1084 2
1.3%
1261 1
0.6%
1287 1
0.6%
ValueCountFrequency (%)
1492 1
0.6%
1290 1
0.6%
1287 1
0.6%
1261 1
0.6%
1084 2
1.3%
597 1
0.6%
573 1
0.6%
565 1
0.6%
539 2
1.3%
340 1
0.6%

실험실호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)80.0%
Missing141
Missing (%)90.4%
Infinite0
Infinite (%)0.0%
Mean156.8
Minimum0
Maximum697
Zeros1
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:56.868379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.7
Q11.5
median11
Q3220
95-th percentile697
Maximum697
Range697
Interquartile range (IQR)218.5

Descriptive statistics

Standard deviation263.57086
Coefficient of variation (CV)1.6809366
Kurtosis0.48768789
Mean156.8
Median Absolute Deviation (MAD)10
Skewness1.4404308
Sum2352
Variance69469.6
MonotonicityNot monotonic
2024-04-18T14:40:57.006927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 3
 
1.9%
697 2
 
1.3%
450 1
 
0.6%
34 1
 
0.6%
30 1
 
0.6%
2 1
 
0.6%
14 1
 
0.6%
0 1
 
0.6%
406 1
 
0.6%
11 1
 
0.6%
Other values (2) 2
 
1.3%
(Missing) 141
90.4%
ValueCountFrequency (%)
0 1
 
0.6%
1 3
1.9%
2 1
 
0.6%
3 1
 
0.6%
5 1
 
0.6%
11 1
 
0.6%
14 1
 
0.6%
30 1
 
0.6%
34 1
 
0.6%
406 1
 
0.6%
ValueCountFrequency (%)
697 2
1.3%
450 1
0.6%
406 1
0.6%
34 1
0.6%
30 1
0.6%
14 1
0.6%
11 1
0.6%
5 1
0.6%
3 1
0.6%
2 1
0.6%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

실험실특수주소
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing152
Missing (%)97.4%
Memory size1.3 KiB
2024-04-18T14:40:57.134368image/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%
2024-04-18T14:40:57.394396image/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 

Missing156
Missing (%)100.0%
Memory size1.5 KiB

실험실특수주소호
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
155 
801
 
1

Length

Max length4
Median length4
Mean length3.9935897
Min length3

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> 155
99.4%
801 1
 
0.6%

Length

2024-04-18T14:40:57.522748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:57.634854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 155
99.4%
801 1
 
0.6%

실험실도로명주소시군구코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
27290
 
3
27170
 
2
27710
 
1

Length

Max length5
Median length4
Mean length4.0384615
Min length4

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> 150
96.2%
27290 3
 
1.9%
27170 2
 
1.3%
27710 1
 
0.6%

Length

2024-04-18T14:40:57.735423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:57.839091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
96.2%
27290 3
 
1.9%
27170 2
 
1.3%
27710 1
 
0.6%

실험실도로명주소읍면동코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
2717010300
 
2
2729011600
 
2
2771038022
 
1
2729010700
 
1

Length

Max length10
Median length4
Mean length4.2307692
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
96.2%
2717010300 2
 
1.3%
2729011600 2
 
1.3%
2771038022 1
 
0.6%
2729010700 1
 
0.6%

Length

2024-04-18T14:40:57.950812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:58.063276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
96.2%
2717010300 2
 
1.3%
2729011600 2
 
1.3%
2771038022 1
 
0.6%
2729010700 1
 
0.6%

실험실도로명주소읍면동구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
1
 
5
0
 
1

Length

Max length4
Median length4
Mean length3.8846154
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> 150
96.2%
1 5
 
3.2%
0 1
 
0.6%

Length

2024-04-18T14:40:58.186867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:58.287095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
96.2%
1 5
 
3.2%
0 1
 
0.6%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing150
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean3263457.8
Minimum2147001
Maximum4854691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:58.374259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2147001
5-th percentile2396002
Q13143005.2
median3144510.5
Q33146775.5
95-th percentile4427775.5
Maximum4854691
Range2707690
Interquartile range (IQR)3770.25

Descriptive statistics

Standard deviation875769.93
Coefficient of variation (CV)0.26835644
Kurtosis3.2289112
Mean3263457.8
Median Absolute Deviation (MAD)2012
Skewness1.1749625
Sum19580747
Variance7.6697297 × 1011
MonotonicityNot monotonic
2024-04-18T14:40:58.469049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3143006 1
 
0.6%
3147029 1
 
0.6%
4854691 1
 
0.6%
2147001 1
 
0.6%
3146015 1
 
0.6%
3143005 1
 
0.6%
(Missing) 150
96.2%
ValueCountFrequency (%)
2147001 1
0.6%
3143005 1
0.6%
3143006 1
0.6%
3146015 1
0.6%
3147029 1
0.6%
4854691 1
0.6%
ValueCountFrequency (%)
4854691 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%
Missing155
Missing (%)99.4%
Memory size1.3 KiB
2024-04-18T14:40:58.589224image/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%
2024-04-18T14:40:58.841532image/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 (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
148 
0
 
8

Length

Max length4
Median length4
Mean length3.8461538
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> 148
94.9%
0 8
 
5.1%

Length

2024-04-18T14:40:58.969464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:59.080051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
94.9%
0 8
 
5.1%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing150
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean224.83333
Minimum45
Maximum555
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-18T14:40:59.159306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile59
Q1116.5
median174
Q3271.25
95-th percentile491.25
Maximum555
Range510
Interquartile range (IQR)154.75

Descriptive statistics

Standard deviation183.16377
Coefficient of variation (CV)0.81466466
Kurtosis1.9676987
Mean224.83333
Median Absolute Deviation (MAD)99.5
Skewness1.3865908
Sum1349
Variance33548.967
MonotonicityNot monotonic
2024-04-18T14:40:59.250338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
185 1
 
0.6%
101 1
 
0.6%
45 1
 
0.6%
555 1
 
0.6%
300 1
 
0.6%
163 1
 
0.6%
(Missing) 150
96.2%
ValueCountFrequency (%)
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%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
151 
0
 
4
23
 
1

Length

Max length4
Median length4
Mean length3.9102564
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> 151
96.8%
0 4
 
2.6%
23 1
 
0.6%

Length

2024-04-18T14:40:59.364193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:59.466990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 151
96.8%
0 4
 
2.6%
23 1
 
0.6%

실험실도로명주소우편번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
42839
 
2
703849
 
1
43013
 
1
42709
 
1

Length

Max length6
Median length4
Mean length4.0448718
Min length4

Unique

Unique4 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
96.2%
42839 2
 
1.3%
703849 1
 
0.6%
43013 1
 
0.6%
42709 1
 
0.6%
41749 1
 
0.6%

Length

2024-04-18T14:40:59.592275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T14:40:59.721399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
96.2%
42839 2
 
1.3%
703849 1
 
0.6%
43013 1
 
0.6%
42709 1
 
0.6%
41749 1
 
0.6%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
01환경전문공사업09_30_16_P627000062700000920060003020190514<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704944대구 달서구 장기동 173번지 23호대구광역시 달서구 성서동로 315 (장기동)<NA>(주)동덕이엔비20190514133401U2019-05-16 02:40:00.0<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_P627000062700000920150000220210526<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달서구 성서로76길 11 (이곡동)704929(주)에스엘테크20210526172533U2021-05-28 02:40:00.0<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_P627000062700000920060002620220914<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703833대구광역시 서구 중리동 1119번지 7호대구광역시 서구 와룡로72길 8 (중리동)703833(주)청수20220914120037U2022-09-16 02:40:00.0<NA>338894.926928263825.3908150환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34환경전문공사업09_30_16_P627000062700000920060002920200316<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>702710대구광역시 북구 산격2동 1629번지 유통단지산업용재관 18동 224호대구광역시 북구 구암로65길 2-1, 2층 (구암동)41424유림환경개발(주)20201029133209U2020-10-31 02:40:00.0<NA>344912.358902268253.830253<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45환경전문공사업09_30_16_P627000062700000920060003420220308<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703830대구광역시 서구 이현동 42번지 450호대구광역시 서구 와룡로87길 24 (이현동)703830(주)신라엔텍20220308142211U2022-03-10 02:40:00.0<NA>338615.297418264600.1978950환경전문공사업0.0<NA>2717010600703830142450<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56환경전문공사업09_30_16_P627000062700000920060004820191031<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704919대구광역시 달서구 신당동 1320번지 2호대구광역시 달서구 달서대로 559, 이앤씨동 (신당동,이노비즈타워609호)704919(주)대일환경기술20191031100721U2019-11-02 02:40:00.0<NA>334621.225167262044.332358<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_P627000062700000920060000120210414<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>706853대구광역시 수성구 황금2동 847번지 2호대구광역시 수성구 동대구로 111 (황금동)706853화성산업(주)20210414144321U2021-04-16 02:40:00.0<NA>346621.319605261243.121518<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
78환경전문공사업09_30_16_P627000062700000920060000220191107<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>703849대구광역시 서구 평리5동 1492번지 34호대구광역시 서구 서대구로 185 (평리동)703849(주)대산엔지니어링20220721155919U2022-07-23 02:40:00.0<NA>340320.175876264946.0182470환경전문공사업0.0<NA>27170103007038491149234<NA><NA><NA><NA><NA>27170271701030013143006<NA>0185<NA>703849
89환경전문공사업09_30_16_P627000062700000920060000420170710<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>702828대구광역시 북구 복현2동 340번지 30호대구광역시 북구 동북로 287 (복현동)<NA>금오환경개발(주)20170710105041I2019-03-23 02:20:03.0<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_P627000062700000920060001020220303<NA>1영업/정상N신규<NA><NA><NA><NA><NA><NA>704919대구광역시 달서구 신당동 1320번지 2호 이앤씨 이노비즈타워 1206호대구광역시 달서구 달서대로 559 (신당동,이앤씨 이노비즈타워 1206호)<NA>(주)신세계엔텍20220303115914U2022-03-05 02:40:00.0<NA>334621.225167262044.3323580환경전문공사업0.0<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
146147환경전문공사업09_30_16_P627000062700000920200000820201113<NA>3폐업Q폐업20220207<NA><NA><NA><NA><NA>41752대구광역시 서구 이현동 42-406대구광역시 서구 문화로7길 28-4 (이현동)41752(주)동방환경플랜트20220207173503U2022-02-09 02:40:00.0<NA>338726.810069265131.8864180환경전문공사업0.0<NA>27170103004174905653<NA><NA><NA><NA><NA>27170271701030013143005<NA>0163041749
147148환경전문공사업09_30_16_P627000062700000920210000320211228<NA>3폐업Q폐업20220211<NA><NA><NA><NA><NA>42704대구광역시 달서구 갈산동 971-2대구광역시 달서구 성서공단로 217, 510호 (갈산동)42704(주)청림환경20220211083744U2022-02-13 02:40:00.0<NA>336058.627858260608.8121810환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
148149환경전문공사업09_30_16_P627000062700000920110000520181025<NA>3폐업Q폐업20200205<NA><NA><NA><NA><NA>702866대구광역시 북구 태전동 995번지 4호 (2충)대구광역시 북구 연암로 151-43 (산격동)702846동방이엠아이(주)20200205131217U2020-02-07 02:40:00.0<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>
149150환경전문공사업09_30_16_P627000062700000920170000620181015<NA>3폐업Q폐업20190808<NA><NA><NA><NA><NA><NA><NA>대구시 달성군 유가면 테크노순환로8길9<NA>(주)아이지에스피20190808090159U2019-08-10 02:40:00.0<NA><NA><NA><NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
150151환경전문공사업09_30_16_P627000062700000920080000820170913<NA>3폐업Q폐업20181112<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 칠곡중앙대로 250-1 (태전동,4층)<NA>(주)세종플랜트20181112095931I2018-11-14 02:37:29.0<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>
151152환경전문공사업09_30_16_P627000062700000920060002320210811<NA>3폐업Q폐업20220216<NA><NA><NA><NA><NA>43008대구광역시 달성군 구지면 응암리 1278-10대구광역시 달성군 구지면 국가산단대로46길 6343008(주)지이테크20220218083338U2022-02-20 02:40:00.0<NA><NA><NA>0환경전문공사업0.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
152153환경전문공사업09_30_16_P627000062700000920060001320200908<NA>3폐업Q폐업20201217<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 호국로 227 (서변동,5층)<NA>(주)수성이앤씨20201228152012U2020-12-30 02:40:00.0<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>
153154환경전문공사업09_30_16_P627000062700000920080000520161114<NA>3폐업Q폐업20180710<NA><NA><NA><NA><NA>711834대구광역시 달성군 화원읍 천내리 107번지 3호대구광역시 달성군 화원읍 성천로 122<NA>(주)금창엔지니어링20181130151033I2018-12-02 02:20:04.0<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>
154155환경전문공사업09_30_16_P627000062700000920110000820191230<NA>3폐업Q폐업20210129<NA><NA><NA><NA><NA>42709대구광역시 달서구 신당동 1320-2 이앤씨이노비즈타워 503호대구광역시 달서구 달서대로 559, 이앤씨이노비즈타워 503호 (신당동)42709엔테크원(주)20210129093258U2021-01-31 02:40:00.0<NA>334621.225167262044.332358<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
155156환경전문공사업09_30_16_P627000062700000920180000220180729<NA>3폐업Q폐업20181231<NA><NA><NA><NA><NA><NA>대구광역시 동구 율하동 1447번지 율하동우체국대구광역시 동구 안심로16길 49 (율하동)<NA>주식회사 지엔비20181231151144I2019-01-02 02:20:35.0<NA><NA><NA><NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>