Overview

Dataset statistics

Number of variables32
Number of observations65
Missing cells537
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.6 KiB
Average record size in memory278.0 B

Variable types

Numeric11
Categorical11
Unsupported6
Text3
DateTime1

Dataset

Description6270000_대구광역시_09_28_12_P_전력기술감리업체_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085949&dataSetDetailId=DDI_0000086008&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
개방자치단체코드 has constant value ""Constant
업종구분명 has constant value ""Constant
인허가취소일자 has 65 (100.0%) missing valuesMissing
폐업일자 has 54 (83.1%) missing valuesMissing
휴업시작일자 has 65 (100.0%) missing valuesMissing
휴업종료일자 has 65 (100.0%) missing valuesMissing
재개업일자 has 65 (100.0%) missing valuesMissing
소재지전화 has 2 (3.1%) missing valuesMissing
소재지면적 has 65 (100.0%) missing valuesMissing
소재지우편번호 has 11 (16.9%) missing valuesMissing
소재지전체주소 has 9 (13.8%) missing valuesMissing
도로명전체주소 has 26 (40.0%) missing valuesMissing
도로명우편번호 has 26 (40.0%) missing valuesMissing
업태구분명 has 65 (100.0%) missing valuesMissing
좌표정보(X) has 9 (13.8%) missing valuesMissing
좌표정보(Y) has 9 (13.8%) missing valuesMissing
실질자본금 has 1 (1.5%) 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
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
실질자본금 has 30 (46.2%) zerosZeros

Reproduction

Analysis started2024-04-17 14:57:24.616461
Analysis finished2024-04-17 14:57:24.958842
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:25.011042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q117
median33
Q349
95-th percentile61.8
Maximum65
Range64
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.90767
Coefficient of variation (CV)0.57295971
Kurtosis-1.2
Mean33
Median Absolute Deviation (MAD)16
Skewness0
Sum2145
Variance357.5
MonotonicityStrictly increasing
2024-04-17T23:57:25.114885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
50 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%
56 1
1.5%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
전력기술감리업체
65 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전력기술감리업체 65
100.0%

Length

2024-04-17T23:57:25.221030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:25.290353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전력기술감리업체 65
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
09_28_12_P
65 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_12_P
2nd row09_28_12_P
3rd row09_28_12_P
4th row09_28_12_P
5th row09_28_12_P

Common Values

ValueCountFrequency (%)
09_28_12_P 65
100.0%

Length

2024-04-17T23:57:25.369197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:25.442226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_12_p 65
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
6270000
65 

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 65
100.0%

Length

2024-04-17T23:57:25.515872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:25.587760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 65
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0093193 × 1017
Minimum1.997627 × 1017
Maximum2.020627 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:25.672813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.997627 × 1017
5-th percentile1.997627 × 1017
Q12.005627 × 1017
median2.008627 × 1017
Q32.013627 × 1017
95-th percentile2.019627 × 1017
Maximum2.020627 × 1017
Range2.3 × 1015
Interquartile range (IQR)8 × 1014

Descriptive statistics

Standard deviation6.8827753 × 1014
Coefficient of variation (CV)0.0034254264
Kurtosis-0.86934313
Mean2.0093193 × 1017
Median Absolute Deviation (MAD)4 × 1014
Skewness-0.009368365
Sum-5.3861686 × 1018
Variance4.7372596 × 1029
MonotonicityNot monotonic
2024-04-17T23:57:25.782491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201962700008600005 1
 
1.5%
201762700008600005 1
 
1.5%
201262700008600001 1
 
1.5%
201262700008600002 1
 
1.5%
201262700008600003 1
 
1.5%
201262700008600004 1
 
1.5%
201262700008600005 1
 
1.5%
201262700008600006 1
 
1.5%
201362700008600001 1
 
1.5%
199762700008600006 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
199762700008600001 1
1.5%
199762700008600002 1
1.5%
199762700008600003 1
1.5%
199762700008600004 1
1.5%
199762700008600005 1
1.5%
199762700008600006 1
1.5%
199862700008600001 1
1.5%
200062700008600001 1
1.5%
200062700008600002 1
1.5%
200062700008600003 1
1.5%
ValueCountFrequency (%)
202062700008600003 1
1.5%
202062700008600002 1
1.5%
202062700008600001 1
1.5%
201962700008600005 1
1.5%
201962700008600004 1
1.5%
201962700008600003 1
1.5%
201962700008600002 1
1.5%
201962700008600001 1
1.5%
201862700008600003 1
1.5%
201862700008600002 1
1.5%

인허가일자
Real number (ℝ)

Distinct62
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20087242
Minimum19970214
Maximum20200311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:25.904687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970214
5-th percentile19970412
Q120050719
median20081030
Q320130619
95-th percentile20190911
Maximum20200311
Range230097
Interquartile range (IQR)79900

Descriptive statistics

Standard deviation68399.604
Coefficient of variation (CV)0.0034051267
Kurtosis-0.86255586
Mean20087242
Median Absolute Deviation (MAD)40603
Skewness-0.024578549
Sum1.3056707 × 109
Variance4.6785059 × 109
MonotonicityNot monotonic
2024-04-17T23:57:26.017795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070207 3
 
4.6%
20160414 2
 
3.1%
20191010 1
 
1.5%
20091110 1
 
1.5%
20100503 1
 
1.5%
20120120 1
 
1.5%
20120223 1
 
1.5%
20120222 1
 
1.5%
20120306 1
 
1.5%
20121004 1
 
1.5%
Other values (52) 52
80.0%
ValueCountFrequency (%)
19970214 1
1.5%
19970228 1
1.5%
19970403 1
1.5%
19970411 1
1.5%
19970418 1
1.5%
19970625 1
1.5%
19980902 1
1.5%
20000410 1
1.5%
20000623 1
1.5%
20001020 1
1.5%
ValueCountFrequency (%)
20200311 1
1.5%
20200204 1
1.5%
20200103 1
1.5%
20191010 1
1.5%
20190513 1
1.5%
20190312 1
1.5%
20190117 1
1.5%
20181005 1
1.5%
20180806 1
1.5%
20171220 1
1.5%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
1
52 
3
13 

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 (%)
1 52
80.0%
3 13
 
20.0%

Length

2024-04-17T23:57:26.114084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:26.187555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 52
80.0%
3 13
 
20.0%

영업상태명
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
영업/정상
52 
폐업
13 

Length

Max length5
Median length5
Mean length4.4
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 (%)
영업/정상 52
80.0%
폐업 13
 
20.0%

Length

2024-04-17T23:57:26.281206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:26.370182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 52
80.0%
폐업 13
 
20.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
1
52 
3
13 

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 (%)
1 52
80.0%
3 13
 
20.0%

Length

2024-04-17T23:57:26.473074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:26.560223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 52
80.0%
3 13
 
20.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
인허가
52 
폐업
13 

Length

Max length3
Median length3
Mean length2.8
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인허가 52
80.0%
폐업 13
 
20.0%

Length

2024-04-17T23:57:26.638823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:26.712899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인허가 52
80.0%
폐업 13
 
20.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)90.9%
Missing54
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean20100489
Minimum20070129
Maximum20180620
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:26.788199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20070129
5-th percentile20070168
Q120070218
median20091110
Q320115222
95-th percentile20165510
Maximum20180620
Range110491
Interquartile range (IQR)45004

Descriptive statistics

Standard deviation37435.323
Coefficient of variation (CV)0.0018624085
Kurtosis0.66037624
Mean20100489
Median Absolute Deviation (MAD)20903
Skewness1.1891656
Sum2.2110538 × 108
Variance1.4014034 × 109
MonotonicityNot monotonic
2024-04-17T23:57:26.872194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20070207 2
 
3.1%
20070129 1
 
1.5%
20091110 1
 
1.5%
20180620 1
 
1.5%
20100809 1
 
1.5%
20070228 1
 
1.5%
20150401 1
 
1.5%
20071226 1
 
1.5%
20110127 1
 
1.5%
20120316 1
 
1.5%
(Missing) 54
83.1%
ValueCountFrequency (%)
20070129 1
1.5%
20070207 2
3.1%
20070228 1
1.5%
20071226 1
1.5%
20091110 1
1.5%
20100809 1
1.5%
20110127 1
1.5%
20120316 1
1.5%
20150401 1
1.5%
20180620 1
1.5%
ValueCountFrequency (%)
20180620 1
1.5%
20150401 1
1.5%
20120316 1
1.5%
20110127 1
1.5%
20100809 1
1.5%
20091110 1
1.5%
20071226 1
1.5%
20070228 1
1.5%
20070207 2
3.1%
20070129 1
1.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

소재지전화
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)79.4%
Missing2
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean5.3596926 × 108
Minimum5.3111111 × 108
Maximum5.3944912 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:26.974057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.3111111 × 108
5-th percentile5.3215311 × 108
Q15.342658 × 108
median5.3638271 × 108
Q35.3746348 × 108
95-th percentile5.3793204 × 108
Maximum5.3944912 × 108
Range8338007
Interquartile range (IQR)3197673.5

Descriptive statistics

Standard deviation2116000.7
Coefficient of variation (CV)0.003947989
Kurtosis-0.42278339
Mean5.3596926 × 108
Median Absolute Deviation (MAD)1129177
Skewness-0.74242344
Sum3.3766063 × 1010
Variance4.4774592 × 1012
MonotonicityNot monotonic
2024-04-17T23:57:27.088096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536287200 4
 
6.2%
537410109 3
 
4.6%
536254119 2
 
3.1%
535938550 2
 
3.1%
537542172 2
 
3.1%
533212004 2
 
3.1%
537511888 2
 
3.1%
531111111 2
 
3.1%
537190306 2
 
3.1%
533118415 2
 
3.1%
Other values (40) 40
61.5%
(Missing) 2
 
3.1%
ValueCountFrequency (%)
531111111 2
3.1%
532144343 1
1.5%
532152130 1
1.5%
532161966 1
1.5%
532410233 1
1.5%
532534412 1
1.5%
532541720 1
1.5%
533118415 2
3.1%
533212004 2
3.1%
533812220 1
1.5%
ValueCountFrequency (%)
539449118 1
1.5%
539414916 1
1.5%
539392448 1
1.5%
537942635 1
1.5%
537836701 1
1.5%
537809000 1
1.5%
537687097 1
1.5%
537598881 1
1.5%
537565577 1
1.5%
537542172 2
3.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct47
Distinct (%)87.0%
Missing11
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean471065.87
Minimum41242
Maximum706852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:27.185911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41242
5-th percentile41405.55
Q142462
median701826.5
Q3705807
95-th percentile706822.55
Maximum706852
Range665610
Interquartile range (IQR)663345

Descriptive statistics

Standard deviation319119.99
Coefficient of variation (CV)0.6774424
Kurtosis-1.6552645
Mean471065.87
Median Absolute Deviation (MAD)4194.5
Skewness-0.63822053
Sum25437557
Variance1.0183757 × 1011
MonotonicityNot monotonic
2024-04-17T23:57:27.291668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
701829 4
 
6.2%
701824 3
 
4.6%
705809 2
 
3.1%
700421 2
 
3.1%
42812 1
 
1.5%
706844 1
 
1.5%
705801 1
 
1.5%
702717 1
 
1.5%
42013 1
 
1.5%
705825 1
 
1.5%
Other values (37) 37
56.9%
(Missing) 11
 
16.9%
ValueCountFrequency (%)
41242 1
1.5%
41260 1
1.5%
41401 1
1.5%
41408 1
1.5%
41474 1
1.5%
41476 1
1.5%
41487 1
1.5%
41586 1
1.5%
41904 1
1.5%
41946 1
1.5%
ValueCountFrequency (%)
706852 1
1.5%
706846 1
1.5%
706844 1
1.5%
706811 1
1.5%
706806 1
1.5%
706805 1
1.5%
706040 1
1.5%
706032 1
1.5%
706010 1
1.5%
705837 1
1.5%

소재지전체주소
Text

MISSING 

Distinct53
Distinct (%)94.6%
Missing9
Missing (%)13.8%
Memory size652.0 B
2024-04-17T23:57:27.543069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length24.821429
Min length18

Characters and Unicode

Total characters1390
Distinct characters107
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)91.1%

Sample

1st row대구광역시 북구 칠성동2가 127번지 ,107동106호(성광우방타운)
2nd row대구광역시 동구 신천동 292-6 유성푸르나임 520호
3rd row대구광역시 중구 동인동4가 386-7 강남빌딩,6층
4th row대구광역시 북구 읍내동 397-10
5th row대구광역시 남구 대명동 1641-13
ValueCountFrequency (%)
대구광역시 47
 
17.1%
수성구 13
 
4.7%
동구 12
 
4.4%
북구 10
 
3.6%
남구 9
 
3.3%
대구 9
 
3.3%
2호 6
 
2.2%
달서구 6
 
2.2%
중구 5
 
1.8%
신천동 5
 
1.8%
Other values (125) 153
55.6%
2024-04-17T23:57:28.099742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
22.2%
구 111
 
8.0%
동 73
 
5.3%
대 64
 
4.6%
1 54
 
3.9%
2 51
 
3.7%
광 48
 
3.5%
역 47
 
3.4%
시 47
 
3.4%
3 41
 
2.9%
Other values (97) 545
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 753
54.2%
Space Separator 309
22.2%
Decimal Number 303
21.8%
Dash Punctuation 19
 
1.4%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 111
14.7%
동 73
 
9.7%
대 64
 
8.5%
광 48
 
6.4%
역 47
 
6.2%
시 47
 
6.2%
지 41
 
5.4%
번 39
 
5.2%
호 31
 
4.1%
성 22
 
2.9%
Other values (82) 230
30.5%
Decimal Number
ValueCountFrequency (%)
1 54
17.8%
2 51
16.8%
3 41
13.5%
7 31
10.2%
6 24
7.9%
0 23
7.6%
8 23
7.6%
4 23
7.6%
5 20
 
6.6%
9 13
 
4.3%
Space Separator
ValueCountFrequency (%)
309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
54.2%
Common 637
45.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 111
14.7%
동 73
 
9.7%
대 64
 
8.5%
광 48
 
6.4%
역 47
 
6.2%
시 47
 
6.2%
지 41
 
5.4%
번 39
 
5.2%
호 31
 
4.1%
성 22
 
2.9%
Other values (82) 230
30.5%
Common
ValueCountFrequency (%)
309
48.5%
1 54
 
8.5%
2 51
 
8.0%
3 41
 
6.4%
7 31
 
4.9%
6 24
 
3.8%
0 23
 
3.6%
8 23
 
3.6%
4 23
 
3.6%
5 20
 
3.1%
Other values (5) 38
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 753
54.2%
ASCII 637
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
48.5%
1 54
 
8.5%
2 51
 
8.0%
3 41
 
6.4%
7 31
 
4.9%
6 24
 
3.8%
0 23
 
3.6%
8 23
 
3.6%
4 23
 
3.6%
5 20
 
3.1%
Other values (5) 38
 
6.0%
Hangul
ValueCountFrequency (%)
구 111
14.7%
동 73
 
9.7%
대 64
 
8.5%
광 48
 
6.4%
역 47
 
6.2%
시 47
 
6.2%
지 41
 
5.4%
번 39
 
5.2%
호 31
 
4.1%
성 22
 
2.9%
Other values (82) 230
30.5%

도로명전체주소
Text

MISSING 

Distinct36
Distinct (%)92.3%
Missing26
Missing (%)40.0%
Memory size652.0 B
2024-04-17T23:57:28.342502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length27.282051
Min length21

Characters and Unicode

Total characters1064
Distinct characters112
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)84.6%

Sample

1st row대구광역시 북구 호암로 20, 107동 106호 (칠성동2가, 성광우방타운)
2nd row대구광역시 동구 동부로22길 48, 유성푸르나임 520호 (신천동)
3rd row대구광역시 중구 국채보상로 726, 강남빌딩 6층 (동인동4가)
4th row대구광역시 북구 칠곡중앙대로128길 9 (읍내동)
5th row대구광역시 남구 두류공원로5길 16-61 (대명동)
ValueCountFrequency (%)
대구광역시 39
 
18.0%
북구 12
 
5.5%
수성구 8
 
3.7%
동구 5
 
2.3%
신천동 5
 
2.3%
달서구 4
 
1.8%
중구 4
 
1.8%
남구 4
 
1.8%
읍내동 4
 
1.8%
대명동 4
 
1.8%
Other values (107) 128
59.0%
2024-04-17T23:57:28.699258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
16.7%
구 79
 
7.4%
동 54
 
5.1%
대 53
 
5.0%
광 40
 
3.8%
역 39
 
3.7%
시 39
 
3.7%
) 37
 
3.5%
( 37
 
3.5%
로 37
 
3.5%
Other values (102) 471
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 624
58.6%
Space Separator 178
 
16.7%
Decimal Number 165
 
15.5%
Close Punctuation 37
 
3.5%
Open Punctuation 37
 
3.5%
Other Punctuation 15
 
1.4%
Dash Punctuation 8
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 79
 
12.7%
동 54
 
8.7%
대 53
 
8.5%
광 40
 
6.4%
역 39
 
6.2%
시 39
 
6.2%
로 37
 
5.9%
길 23
 
3.7%
성 18
 
2.9%
북 14
 
2.2%
Other values (87) 228
36.5%
Decimal Number
ValueCountFrequency (%)
1 28
17.0%
2 26
15.8%
3 21
12.7%
5 18
10.9%
6 15
9.1%
4 14
8.5%
7 13
7.9%
8 12
7.3%
0 12
7.3%
9 6
 
3.6%
Space Separator
ValueCountFrequency (%)
178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 624
58.6%
Common 440
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 79
 
12.7%
동 54
 
8.7%
대 53
 
8.5%
광 40
 
6.4%
역 39
 
6.2%
시 39
 
6.2%
로 37
 
5.9%
길 23
 
3.7%
성 18
 
2.9%
북 14
 
2.2%
Other values (87) 228
36.5%
Common
ValueCountFrequency (%)
178
40.5%
) 37
 
8.4%
( 37
 
8.4%
1 28
 
6.4%
2 26
 
5.9%
3 21
 
4.8%
5 18
 
4.1%
6 15
 
3.4%
, 15
 
3.4%
4 14
 
3.2%
Other values (5) 51
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 624
58.6%
ASCII 440
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
40.5%
) 37
 
8.4%
( 37
 
8.4%
1 28
 
6.4%
2 26
 
5.9%
3 21
 
4.8%
5 18
 
4.1%
6 15
 
3.4%
, 15
 
3.4%
4 14
 
3.2%
Other values (5) 51
 
11.6%
Hangul
ValueCountFrequency (%)
구 79
 
12.7%
동 54
 
8.7%
대 53
 
8.5%
광 40
 
6.4%
역 39
 
6.2%
시 39
 
6.2%
로 37
 
5.9%
길 23
 
3.7%
성 18
 
2.9%
북 14
 
2.2%
Other values (87) 228
36.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)94.9%
Missing26
Missing (%)40.0%
Infinite0
Infinite (%)0.0%
Mean296813.05
Minimum41242
Maximum711851
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:28.802014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41242
5-th percentile41259.2
Q141536.5
median42474
Q3702845.5
95-th percentile706810.7
Maximum711851
Range670609
Interquartile range (IQR)661309

Descriptive statistics

Standard deviation326644.02
Coefficient of variation (CV)1.1005042
Kurtosis-1.8541101
Mean296813.05
Median Absolute Deviation (MAD)1066
Skewness0.49361933
Sum11575709
Variance1.0669632 × 1011
MonotonicityNot monotonic
2024-04-17T23:57:28.898350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
41467 2
 
3.1%
41904 2
 
3.1%
42013 1
 
1.5%
701824 1
 
1.5%
706807 1
 
1.5%
702828 1
 
1.5%
702847 1
 
1.5%
42250 1
 
1.5%
42812 1
 
1.5%
41242 1
 
1.5%
Other values (27) 27
41.5%
(Missing) 26
40.0%
ValueCountFrequency (%)
41242 1
1.5%
41252 1
1.5%
41260 1
1.5%
41401 1
1.5%
41408 1
1.5%
41467 2
3.1%
41474 1
1.5%
41476 1
1.5%
41487 1
1.5%
41586 1
1.5%
ValueCountFrequency (%)
711851 1
1.5%
706844 1
1.5%
706807 1
1.5%
706806 1
1.5%
706032 1
1.5%
705802 1
1.5%
705801 1
1.5%
704800 1
1.5%
702847 1
1.5%
702846 1
1.5%

사업장명
Text

Distinct59
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
2024-04-17T23:57:29.085973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.9846154
Min length5

Characters and Unicode

Total characters584
Distinct characters97
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)83.1%

Sample

1st row(주)주원이엔즈
2nd row주식회사 이엠시
3rd row주식회사 청이엔지
4th row경원기업 주식회사
5th row주식회사 공인기술단
ValueCountFrequency (%)
주식회사 12
 
15.2%
주)기성이앤씨 3
 
3.8%
주)우전엔지니어링 2
 
2.5%
우성설계감리(주 2
 
2.5%
주)경도기술단 2
 
2.5%
덕원기술단 2
 
2.5%
대진엔지니어링 1
 
1.3%
주)덕원기술사 1
 
1.3%
주)새빛엔지니어링 1
 
1.3%
주)세명전기 1
 
1.3%
Other values (52) 52
65.8%
2024-04-17T23:57:29.382661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 58
 
9.9%
( 45
 
7.7%
) 45
 
7.7%
이 24
 
4.1%
엔 24
 
4.1%
사 24
 
4.1%
기 22
 
3.8%
지 19
 
3.3%
14
 
2.4%
어 12
 
2.1%
Other values (87) 297
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 474
81.2%
Open Punctuation 45
 
7.7%
Close Punctuation 45
 
7.7%
Space Separator 14
 
2.4%
Uppercase Letter 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 58
 
12.2%
이 24
 
5.1%
엔 24
 
5.1%
사 24
 
5.1%
기 22
 
4.6%
지 19
 
4.0%
어 12
 
2.5%
링 12
 
2.5%
회 12
 
2.5%
식 12
 
2.5%
Other values (80) 255
53.8%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
C 2
33.3%
N 1
16.7%
M 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 474
81.2%
Common 104
 
17.8%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 58
 
12.2%
이 24
 
5.1%
엔 24
 
5.1%
사 24
 
5.1%
기 22
 
4.6%
지 19
 
4.0%
어 12
 
2.5%
링 12
 
2.5%
회 12
 
2.5%
식 12
 
2.5%
Other values (80) 255
53.8%
Latin
ValueCountFrequency (%)
E 2
33.3%
C 2
33.3%
N 1
16.7%
M 1
16.7%
Common
ValueCountFrequency (%)
( 45
43.3%
) 45
43.3%
14
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 474
81.2%
ASCII 110
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 58
 
12.2%
이 24
 
5.1%
엔 24
 
5.1%
사 24
 
5.1%
기 22
 
4.6%
지 19
 
4.0%
어 12
 
2.5%
링 12
 
2.5%
회 12
 
2.5%
식 12
 
2.5%
Other values (80) 255
53.8%
ASCII
ValueCountFrequency (%)
( 45
40.9%
) 45
40.9%
14
 
12.7%
E 2
 
1.8%
C 2
 
1.8%
N 1
 
0.9%
M 1
 
0.9%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0144994 × 1013
Minimum2.0070207 × 1013
Maximum2.0200831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:29.499845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070207 × 1013
5-th percentile2.0070573 × 1013
Q12.0120427 × 1013
median2.0131119 × 1013
Q32.0190105 × 1013
95-th percentile2.0198307 × 1013
Maximum2.0200831 × 1013
Range1.3062398 × 1011
Interquartile range (IQR)6.9678069 × 1010

Descriptive statistics

Standard deviation3.9424316 × 1010
Coefficient of variation (CV)0.0019570279
Kurtosis-0.9716837
Mean2.0144994 × 1013
Median Absolute Deviation (MAD)2.990503 × 1010
Skewness-0.24084649
Sum1.3094246 × 1015
Variance1.5542767 × 1021
MonotonicityNot monotonic
2024-04-17T23:57:29.613866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191011153113 1
 
1.5%
20200831164342 1
 
1.5%
20181127114523 1
 
1.5%
20130307144515 1
 
1.5%
20131119180706 1
 
1.5%
20130111140945 1
 
1.5%
20121004182306 1
 
1.5%
20171020152125 1
 
1.5%
20130620104724 1
 
1.5%
20120508110334 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
20070207180440 1
1.5%
20070207180454 1
1.5%
20070228163732 1
1.5%
20070409134931 1
1.5%
20071226145247 1
1.5%
20080414220520 1
1.5%
20091111150349 1
1.5%
20091230093506 1
1.5%
20100810134437 1
1.5%
20101214150220 1
1.5%
ValueCountFrequency (%)
20200831164342 1
1.5%
20200311174611 1
1.5%
20200204145926 1
1.5%
20200103162651 1
1.5%
20191121092440 1
1.5%
20191011153113 1
1.5%
20191010182649 1
1.5%
20191010182547 1
1.5%
20191010182523 1
1.5%
20190429180524 1
1.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
I
50 
U
15 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 50
76.9%
U 15
 
23.1%

Length

2024-04-17T23:57:29.714384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:29.786940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 50
76.9%
u 15
 
23.1%

데이터갱신일자
Date

Distinct18
Distinct (%)27.7%
Missing0
Missing (%)0.0%
Memory size652.0 B
Minimum2018-08-31 23:59:59
Maximum2020-09-02 02:40:00
2024-04-17T23:57:29.854507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T23:57:29.939771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing65
Missing (%)100.0%
Memory size717.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)80.4%
Missing9
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean344044.55
Minimum328989.66
Maximum350775.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:30.053463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum328989.66
5-th percentile337159.24
Q1342147.9
median344960.22
Q3346938.59
95-th percentile348627.08
Maximum350775.26
Range21785.603
Interquartile range (IQR)4790.6916

Descriptive statistics

Standard deviation3948.831
Coefficient of variation (CV)0.011477674
Kurtosis2.8328176
Mean344044.55
Median Absolute Deviation (MAD)2199.1658
Skewness-1.3401323
Sum19266495
Variance15593266
MonotonicityNot monotonic
2024-04-17T23:57:30.155177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
346973.195338 4
 
6.2%
346621.939233 3
 
4.6%
342429.117454 2
 
3.1%
339715.275892 2
 
3.1%
342550.434136 2
 
3.1%
341097.35783 2
 
3.1%
340224.842223 2
 
3.1%
342147.895939 2
 
3.1%
348585.347528 1
 
1.5%
349147.612849 1
 
1.5%
Other values (35) 35
53.8%
(Missing) 9
 
13.8%
ValueCountFrequency (%)
328989.656877 1
1.5%
334521.362697 1
1.5%
336818.179374 1
1.5%
337272.9286 1
1.5%
339155.347017 1
1.5%
339672.705294 1
1.5%
339715.275892 2
3.1%
340224.842223 2
3.1%
341097.35783 2
3.1%
341995.073056 1
1.5%
ValueCountFrequency (%)
350775.260289 1
1.5%
349147.612849 1
1.5%
348752.270317 1
1.5%
348585.347528 1
1.5%
348383.677966 1
1.5%
347664.620884 1
1.5%
347293.090917 1
1.5%
347099.834795 1
1.5%
347071.550988 1
1.5%
347019.893434 1
1.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct45
Distinct (%)80.4%
Missing9
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean264509.72
Minimum253616.88
Maximum273683.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:30.252980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum253616.88
5-th percentile258982.41
Q1262027.36
median264572.22
Q3265889.51
95-th percentile273548.12
Maximum273683.92
Range20067.034
Interquartile range (IQR)3862.1564

Descriptive statistics

Standard deviation4101.2555
Coefficient of variation (CV)0.015505122
Kurtosis0.60640674
Mean264509.72
Median Absolute Deviation (MAD)2431.8254
Skewness0.37516522
Sum14812544
Variance16820297
MonotonicityNot monotonic
2024-04-17T23:57:30.366899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
264995.374262 4
 
6.2%
265048.328601 3
 
4.6%
261115.730073 2
 
3.1%
269601.909686 2
 
3.1%
273683.918029 2
 
3.1%
261484.477732 2
 
3.1%
273548.124057 2
 
3.1%
262200.395899 2
 
3.1%
264011.729006 1
 
1.5%
262560.2074 1
 
1.5%
Other values (35) 35
53.8%
(Missing) 9
 
13.8%
ValueCountFrequency (%)
253616.883535 1
1.5%
258200.600036 1
1.5%
258392.178871 1
1.5%
259179.153082 1
1.5%
259248.897035 1
1.5%
259274.066034 1
1.5%
260803.261834 1
1.5%
261103.127608 1
1.5%
261115.730073 2
3.1%
261359.11856 1
1.5%
ValueCountFrequency (%)
273683.918029 2
3.1%
273548.124057 2
3.1%
270781.562229 1
1.5%
270065.788689 1
1.5%
269601.909686 2
3.1%
268535.276449 1
1.5%
268408.951404 1
1.5%
268253.789362 1
1.5%
267778.536355 1
1.5%
267142.757949 1
1.5%

업종구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
감리업
65 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
감리업 65
100.0%

Length

2024-04-17T23:57:30.475403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:30.546827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감리업 65
100.0%

설계감리업종류명
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
전문감리업
35 
종합감리업
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전문감리업
2nd row전문감리업
3rd row전문감리업
4th row전문감리업
5th row종합감리업

Common Values

ValueCountFrequency (%)
전문감리업 35
53.8%
종합감리업 30
46.2%

Length

2024-04-17T23:57:30.634765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:30.711459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문감리업 35
53.8%
종합감리업 30
46.2%

소속국가명
Categorical

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
대한민국
33 
<NA>
32 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대한민국 33
50.8%
<NA> 32
49.2%

Length

2024-04-17T23:57:30.790919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:57:30.865177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대한민국 33
50.8%
na 32
49.2%

실질자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)31.2%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean68021502
Minimum0
Maximum5 × 108
Zeros30
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-04-17T23:57:30.941555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50000000
Q382636236
95-th percentile3.1683055 × 108
Maximum5 × 108
Range5 × 108
Interquartile range (IQR)82636236

Descriptive statistics

Standard deviation1.1278175 × 108
Coefficient of variation (CV)1.6580309
Kurtosis7.0370007
Mean68021502
Median Absolute Deviation (MAD)50000000
Skewness2.6150434
Sum4.3533761 × 109
Variance1.2719724 × 1016
MonotonicityNot monotonic
2024-04-17T23:57:31.066334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 30
46.2%
50000000 10
 
15.4%
100000000 4
 
6.2%
60075000 2
 
3.1%
500000000 2
 
3.1%
210000000 2
 
3.1%
51937773 1
 
1.5%
50501942 1
 
1.5%
110080000 1
 
1.5%
335683000 1
 
1.5%
Other values (10) 10
 
15.4%
ValueCountFrequency (%)
0 30
46.2%
50000000 10
 
15.4%
50086440 1
 
1.5%
50501942 1
 
1.5%
50878575 1
 
1.5%
51937773 1
 
1.5%
52603240 1
 
1.5%
60075000 2
 
3.1%
80000000 1
 
1.5%
90544944 1
 
1.5%
ValueCountFrequency (%)
500000000 2
3.1%
433000000 1
 
1.5%
335683000 1
 
1.5%
210000000 2
3.1%
197395109 1
 
1.5%
164955610 1
 
1.5%
141785455 1
 
1.5%
110080000 1
 
1.5%
103774041 1
 
1.5%
100000000 4
6.2%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명설계감리업종류명소속국가명실질자본금
01전력기술감리업체09_28_12_P627000020196270000860000520191010<NA>1영업/정상1인허가<NA><NA><NA><NA><NA><NA>41586대구광역시 북구 칠성동2가 127번지 ,107동106호(성광우방타운)대구광역시 북구 호암로 20, 107동 106호 (칠성동2가, 성광우방타운)41586(주)주원이엔즈20191011153113I2019-10-13 00:22:48.0<NA>343728.419265773.314268감리업전문감리업<NA>50000000
12전력기술감리업체09_28_12_P627000020206270000860000120200103<NA>1영업/정상1인허가<NA><NA><NA><NA>532410233<NA>41242대구광역시 동구 신천동 292-6 유성푸르나임 520호대구광역시 동구 동부로22길 48, 유성푸르나임 520호 (신천동)41242주식회사 이엠시20200103162651I2020-01-05 00:23:25.0<NA>346801.104968264796.170378감리업전문감리업<NA>100000000
23전력기술감리업체09_28_12_P627000020196270000860000420190513<NA>1영업/정상1인허가<NA><NA><NA><NA>532541720<NA>41946대구광역시 중구 동인동4가 386-7 강남빌딩,6층대구광역시 중구 국채보상로 726, 강남빌딩 6층 (동인동4가)41946주식회사 청이엔지20191010182523U2019-10-12 02:40:00.0<NA>345323.318065264335.308575감리업전문감리업<NA>90544944
34전력기술감리업체09_28_12_P627000020196270000860000120190117<NA>1영업/정상1인허가<NA><NA><NA><NA>533118415<NA>41401대구광역시 북구 읍내동 397-10대구광역시 북구 칠곡중앙대로128길 9 (읍내동)41401경원기업 주식회사20191010182649U2019-10-12 02:40:00.0<NA>340224.842223273548.124057감리업전문감리업대한민국50000000
45전력기술감리업체09_28_12_P627000020196270000860000220171220<NA>1영업/정상1인허가<NA><NA><NA><NA>532161966<NA>42474대구광역시 남구 대명동 1641-13대구광역시 남구 두류공원로5길 16-61 (대명동)42474주식회사 공인기술단20191121092440U2019-11-23 02:40:00.0<NA>342147.895939262200.395899감리업종합감리업<NA>197395109
56전력기술감리업체09_28_12_P627000020196270000860000320190312<NA>1영업/정상1인허가<NA><NA><NA><NA>539392448<NA>41487대구광역시 북구 매천동 714번지 1층대구광역시 북구 매전로4길 20-30, 1층 (매천동)41487(주)넥스트이엔지20191010182547U2019-10-12 02:40:00.0<NA>339155.347017268535.276449감리업전문감리업<NA>50501942
67전력기술감리업체09_28_12_P627000020186270000860000320181005<NA>1영업/정상1인허가<NA><NA><NA><NA>539414916<NA>41476대구광역시 북구 서변동 1787-2대구광역시 북구 호국로 209, 7층 (서변동)41476주식회사 대림엔지니어링20181005180806I2018-10-07 02:37:39.0<NA>344255.087791270065.788689감리업전문감리업<NA>50000000
78전력기술감리업체09_28_12_P627000020106270000860000420100716<NA>1영업/정상1인허가<NA><NA><NA><NA>537456112<NA>706806대구광역시 수성구 만촌동 989번지 9호대구광역시 수성구 충의로 39 (만촌동)706806우진엔지니어링20181016104816U2018-10-18 02:36:29.0<NA>348585.347528264011.729006감리업전문감리업<NA>51937773
89전력기술감리업체09_28_12_P627000019986270000860000119980902<NA>1영업/정상1인허가<NA><NA><NA><NA>534240278<NA><NA><NA>대구광역시 중구 동덕로 36 (대봉동)700809(주)뉴한국설계감리20150622093623I2018-08-31 23:59:59.0<NA>344952.242897263180.500999감리업전문감리업대한민국0
910전력기술감리업체09_28_12_P627000019976270000860000419970214<NA>1영업/정상1인허가<NA><NA><NA><NA>534242113<NA>700421대구 중구 동인동1가 234-5번지<NA><NA>(주)한신엔지니어링20150202132739I2018-08-31 23:59:59.0<NA><NA><NA>감리업종합감리업대한민국0
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명설계감리업종류명소속국가명실질자본금
5556전력기술감리업체09_28_12_P627000020036270000860000120030304<NA>3폐업3폐업20070207<NA><NA><NA><NA><NA>701829대구 동구 신천4동 332-8<NA><NA>(주)우전엔지니어링20070207180454I2018-08-31 23:59:59.0<NA><NA><NA>감리업전문감리업대한민국<NA>
5657전력기술감리업체09_28_12_P627000020056270000860000320050719<NA>3폐업3폐업<NA><NA><NA><NA>535938550<NA><NA><NA>대구광역시 달성군 논공읍 달성군청로6길 17711851(주)광명설비연구소20130118100144I2018-08-31 23:59:59.0<NA>328989.656877253616.883535감리업전문감리업대한민국0
5758전력기술감리업체09_28_12_P627000020036270000860000320031111<NA>3폐업3폐업20100809<NA><NA><NA>534761671<NA>705020대구 남구 봉덕동 687-7 3층<NA><NA>(주)동원테크20100810134437I2018-08-31 23:59:59.0<NA><NA><NA>감리업전문감리업대한민국0
5859전력기술감리업체09_28_12_P627000020066270000860000220060817<NA>3폐업3폐업20070207<NA><NA><NA>536287200<NA>705809대구광역시 남구 대명1동 792번지 27호<NA><NA>(주)기성이앤씨20070207180440I2018-08-31 23:59:59.0<NA>342429.117454261115.730073감리업전문감리업<NA>52603240
5960전력기술감리업체09_28_12_P627000020076270000860000420070207<NA>3폐업3폐업<NA><NA><NA><NA>536287200<NA>705809대구광역시 남구 대명1동 792번지 27호<NA><NA>(주)기성이앤씨20091230093506I2018-08-31 23:59:59.0<NA>342429.117454261115.730073감리업종합감리업<NA>0
6061전력기술감리업체09_28_12_P627000020076270000860000320070207<NA>3폐업3폐업20070228<NA><NA><NA>532152130<NA>706846대구광역시 수성구 지산2동 1272번지 3호<NA><NA>그린전기감리20070228163732I2018-08-31 23:59:59.0<NA>347664.620884259179.153082감리업전문감리업<NA>0
6162전력기술감리업체09_28_12_P627000020086270000860000120080508<NA>3폐업3폐업20150401<NA><NA><NA>535811977<NA>704929대구광역시 달서구 이곡1동 1000번지 210호 (203호)<NA><NA>주식회사 북극20150421173125I2018-08-31 23:59:59.0<NA>336818.179374262138.815756감리업전문감리업대한민국50000000
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