Overview

Dataset statistics

Number of variables32
Number of observations82
Missing cells651
Missing cells (%)24.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.8 KiB
Average record size in memory271.6 B

Variable types

Numeric6
Categorical11
DateTime5
Unsupported5
Text5

Dataset

Description23년10월_6270000_대구광역시_09_28_12_P_전력기술감리업체
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000101129&dataSetDetailId=DDI_0000101197&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
개방자치단체코드 has constant value ""Constant
재개업일자 has constant value ""Constant
업종구분명 has constant value ""Constant
인허가취소일자 has 82 (100.0%) missing valuesMissing
폐업일자 has 67 (81.7%) missing valuesMissing
휴업시작일자 has 82 (100.0%) missing valuesMissing
휴업종료일자 has 82 (100.0%) missing valuesMissing
재개업일자 has 81 (98.8%) missing valuesMissing
소재지전화 has 3 (3.7%) missing valuesMissing
소재지면적 has 82 (100.0%) missing valuesMissing
소재지우편번호 has 12 (14.6%) missing valuesMissing
소재지전체주소 has 10 (12.2%) missing valuesMissing
도로명전체주소 has 22 (26.8%) missing valuesMissing
도로명우편번호 has 22 (26.8%) missing valuesMissing
업태구분명 has 82 (100.0%) missing valuesMissing
좌표정보(X) has 12 (14.6%) missing valuesMissing
좌표정보(Y) has 12 (14.6%) 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
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 38 (46.3%) zerosZeros

Reproduction

Analysis started2023-11-11 14:11:53.729336
Analysis finished2023-11-11 14:11:54.838377
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5
Minimum1
Maximum82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:11:54.989406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.05
Q121.25
median41.5
Q361.75
95-th percentile77.95
Maximum82
Range81
Interquartile range (IQR)40.5

Descriptive statistics

Standard deviation23.815261
Coefficient of variation (CV)0.57386172
Kurtosis-1.2
Mean41.5
Median Absolute Deviation (MAD)20.5
Skewness0
Sum3403
Variance567.16667
MonotonicityStrictly increasing
2023-11-11T23:11:55.240472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
63 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
전력기술감리업체
82 

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 82
100.0%

Length

2023-11-11T23:11:55.524405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:55.703620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전력기술감리업체 82
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
09_28_12_P
82 

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 82
100.0%

Length

2023-11-11T23:11:55.878107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:56.055413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_12_p 82
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
6270000
82 

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 82
100.0%

Length

2023-11-11T23:11:56.239513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:56.401220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 82
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0117614 × 1017
Minimum1.997627 × 1017
Maximum2.023627 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:11:56.567933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.997627 × 1017
5-th percentile1.997627 × 1017
Q12.006627 × 1017
median2.010627 × 1017
Q32.019627 × 1017
95-th percentile2.022577 × 1017
Maximum2.023627 × 1017
Range2.6 × 1015
Interquartile range (IQR)1.3 × 1015

Descriptive statistics

Standard deviation7.8283116 × 1014
Coefficient of variation (CV)0.0038912724
Kurtosis-1.1050702
Mean2.0117614 × 1017
Median Absolute Deviation (MAD)7 × 1014
Skewness-0.20858366
Sum-1.9503007 × 1018
Variance6.1282462 × 1029
MonotonicityNot monotonic
2023-11-11T23:11:56.844657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201962700008600001 1
 
1.2%
201862700008600003 1
 
1.2%
202162700008600002 1
 
1.2%
202162700008600001 1
 
1.2%
202262700008600004 1
 
1.2%
202062700008600004 1
 
1.2%
202162700008600004 1
 
1.2%
202162700008600007 1
 
1.2%
202162700008600005 1
 
1.2%
201762700008600005 1
 
1.2%
Other values (72) 72
87.8%
ValueCountFrequency (%)
199762700008600001 1
1.2%
199762700008600002 1
1.2%
199762700008600003 1
1.2%
199762700008600004 1
1.2%
199762700008600005 1
1.2%
199762700008600006 1
1.2%
199862700008600001 1
1.2%
200062700008600001 1
1.2%
200062700008600002 1
1.2%
200062700008600003 1
1.2%
ValueCountFrequency (%)
202362700008600001 1
1.2%
202262700008600004 1
1.2%
202262700008600003 1
1.2%
202262700008600002 1
1.2%
202262700008600001 1
1.2%
202162700008600007 1
1.2%
202162700008600006 1
1.2%
202162700008600005 1
1.2%
202162700008600004 1
1.2%
202162700008600003 1
1.2%

인허가일자
Date

Distinct77
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum1997-02-14 00:00:00
Maximum2023-02-01 00:00:00
2023-11-11T23:11:57.036850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-11T23:11:57.235992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
1
65 
3
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 65
79.3%
3 17
 
20.7%

Length

2023-11-11T23:11:57.410318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:57.551260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
79.3%
3 17
 
20.7%

영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
영업/정상
65 
폐업
17 

Length

Max length5
Median length5
Mean length4.3780488
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 65
79.3%
폐업 17
 
20.7%

Length

2023-11-11T23:11:57.702526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:57.881934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 65
79.3%
폐업 17
 
20.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
1
65 
3
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 65
79.3%
3 17
 
20.7%

Length

2023-11-11T23:11:58.258506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:58.422130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 65
79.3%
3 17
 
20.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
인허가
65 
폐업
17 

Length

Max length3
Median length3
Mean length2.7926829
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인허가 65
79.3%
폐업 17
 
20.7%

Length

2023-11-11T23:11:58.745551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:11:58.986958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인허가 65
79.3%
폐업 17
 
20.7%

폐업일자
Date

MISSING 

Distinct14
Distinct (%)93.3%
Missing67
Missing (%)81.7%
Memory size788.0 B
Minimum2007-01-29 00:00:00
Maximum2023-10-10 00:00:00
2023-11-11T23:11:59.172081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-11T23:11:59.381444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

재개업일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing81
Missing (%)98.8%
Memory size788.0 B
Minimum2022-01-15 00:00:00
Maximum2022-01-15 00:00:00
2023-11-11T23:11:59.564638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-11T23:11:59.733923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

소재지전화
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)78.5%
Missing3
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean7.0151952 × 108
Minimum5.3 × 108
Maximum7.0752517 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:11:59.929754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.3 × 108
5-th percentile5.3215135 × 108
Q15.3451645 × 108
median5.366587 × 108
Q35.3754095 × 108
95-th percentile5.4047741 × 108
Maximum7.0752517 × 109
Range6.5452517 × 109
Interquartile range (IQR)3024496.5

Descriptive statistics

Standard deviation1.0314666 × 109
Coefficient of variation (CV)1.470332
Kurtosis36.895187
Mean7.0151952 × 108
Median Absolute Deviation (MAD)906877
Skewness6.1612406
Sum5.5420042 × 1010
Variance1.0639234 × 1018
MonotonicityNot monotonic
2023-11-11T23:12:00.153748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
536287200 4
 
4.9%
539392448 3
 
3.7%
537410109 3
 
3.7%
536254119 2
 
2.4%
536244868 2
 
2.4%
537190306 2
 
2.4%
537565577 2
 
2.4%
535938550 2
 
2.4%
537542172 2
 
2.4%
537511888 2
 
2.4%
Other values (52) 55
67.1%
(Missing) 3
 
3.7%
ValueCountFrequency (%)
530000000 1
1.2%
531111111 2
2.4%
532144343 1
1.2%
532152130 1
1.2%
532161110 1
1.2%
532161966 1
1.2%
532163119 1
1.2%
532410233 1
1.2%
532534412 1
1.2%
532541720 1
1.2%
ValueCountFrequency (%)
7075251673 1
 
1.2%
7046590335 1
 
1.2%
549732400 1
 
1.2%
549732004 1
 
1.2%
539449118 1
 
1.2%
539414916 1
 
1.2%
539392448 3
3.7%
539391901 1
 
1.2%
538150386 1
 
1.2%
537836701 1
 
1.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

소재지우편번호
Text

MISSING 

Distinct55
Distinct (%)78.6%
Missing12
Missing (%)14.6%
Memory size788.0 B
2023-11-11T23:12:00.608657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.8857143
Min length5

Characters and Unicode

Total characters412
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)62.9%

Sample

1st row41401
2nd row42474
3rd row41487
4th row41946
5th row39033
ValueCountFrequency (%)
701-829 4
 
5.7%
701-824 3
 
4.3%
41408 3
 
4.3%
41474 2
 
2.9%
700-421 2
 
2.9%
42812 2
 
2.9%
41401 2
 
2.9%
41487 2
 
2.9%
41263 2
 
2.9%
42251 2
 
2.9%
Other values (45) 46
65.7%
2023-11-11T23:12:01.227620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 79
19.2%
0 65
15.8%
1 50
12.1%
2 50
12.1%
7 45
10.9%
8 33
8.0%
- 31
 
7.5%
6 21
 
5.1%
5 15
 
3.6%
9 14
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 381
92.5%
Dash Punctuation 31
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 79
20.7%
0 65
17.1%
1 50
13.1%
2 50
13.1%
7 45
11.8%
8 33
8.7%
6 21
 
5.5%
5 15
 
3.9%
9 14
 
3.7%
3 9
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 412
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 79
19.2%
0 65
15.8%
1 50
12.1%
2 50
12.1%
7 45
10.9%
8 33
8.0%
- 31
 
7.5%
6 21
 
5.1%
5 15
 
3.6%
9 14
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 79
19.2%
0 65
15.8%
1 50
12.1%
2 50
12.1%
7 45
10.9%
8 33
8.0%
- 31
 
7.5%
6 21
 
5.1%
5 15
 
3.6%
9 14
 
3.4%

소재지전체주소
Text

MISSING 

Distinct66
Distinct (%)91.7%
Missing10
Missing (%)12.2%
Memory size788.0 B
2023-11-11T23:12:01.931076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length24.375
Min length18

Characters and Unicode

Total characters1755
Distinct characters130
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

Unique62 ?
Unique (%)86.1%

Sample

1st row대구광역시 북구 읍내동 397-10
2nd row대구광역시 남구 대명동 1641-13
3rd row대구광역시 북구 매천동 714번지 1층
4th row대구광역시 중구 동인동4가 386-7 강남빌딩,6층
5th row대구광역시 군위군 효령면 장군리 61-2
ValueCountFrequency (%)
대구광역시 63
 
17.7%
동구 15
 
4.2%
북구 15
 
4.2%
수성구 14
 
3.9%
남구 11
 
3.1%
달서구 10
 
2.8%
대구 9
 
2.5%
신천동 7
 
2.0%
2호 5
 
1.4%
대명동 5
 
1.4%
Other values (153) 202
56.7%
2023-11-11T23:12:02.886257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
362
20.6%
구 143
 
8.1%
동 92
 
5.2%
대 84
 
4.8%
1 68
 
3.9%
광 64
 
3.6%
역 64
 
3.6%
시 64
 
3.6%
2 59
 
3.4%
3 48
 
2.7%
Other values (120) 707
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 969
55.2%
Decimal Number 388
22.1%
Space Separator 362
 
20.6%
Dash Punctuation 31
 
1.8%
Other Punctuation 3
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 143
14.8%
동 92
 
9.5%
대 84
 
8.7%
광 64
 
6.6%
역 64
 
6.6%
시 64
 
6.6%
지 46
 
4.7%
번 43
 
4.4%
호 36
 
3.7%
성 24
 
2.5%
Other values (105) 309
31.9%
Decimal Number
ValueCountFrequency (%)
1 68
17.5%
2 59
15.2%
3 48
12.4%
7 40
10.3%
4 35
9.0%
5 31
8.0%
8 30
7.7%
0 29
7.5%
6 27
 
7.0%
9 21
 
5.4%
Space Separator
ValueCountFrequency (%)
362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 969
55.2%
Common 786
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 143
14.8%
동 92
 
9.5%
대 84
 
8.7%
광 64
 
6.6%
역 64
 
6.6%
시 64
 
6.6%
지 46
 
4.7%
번 43
 
4.4%
호 36
 
3.7%
성 24
 
2.5%
Other values (105) 309
31.9%
Common
ValueCountFrequency (%)
362
46.1%
1 68
 
8.7%
2 59
 
7.5%
3 48
 
6.1%
7 40
 
5.1%
4 35
 
4.5%
- 31
 
3.9%
5 31
 
3.9%
8 30
 
3.8%
0 29
 
3.7%
Other values (5) 53
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 969
55.2%
ASCII 786
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
362
46.1%
1 68
 
8.7%
2 59
 
7.5%
3 48
 
6.1%
7 40
 
5.1%
4 35
 
4.5%
- 31
 
3.9%
5 31
 
3.9%
8 30
 
3.8%
0 29
 
3.7%
Other values (5) 53
 
6.7%
Hangul
ValueCountFrequency (%)
구 143
14.8%
동 92
 
9.5%
대 84
 
8.7%
광 64
 
6.6%
역 64
 
6.6%
시 64
 
6.6%
지 46
 
4.7%
번 43
 
4.4%
호 36
 
3.7%
성 24
 
2.5%
Other values (105) 309
31.9%

도로명전체주소
Text

MISSING 

Distinct55
Distinct (%)91.7%
Missing22
Missing (%)26.8%
Memory size788.0 B
2023-11-11T23:12:03.512263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length28.116667
Min length21

Characters and Unicode

Total characters1687
Distinct characters145
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

Unique50 ?
Unique (%)83.3%

Sample

1st row대구광역시 북구 칠곡중앙대로128길 9 (읍내동)
2nd row대구광역시 남구 두류공원로5길 16-61 (대명동)
3rd row대구광역시 북구 매전로4길 20-30, 1층 (매천동)
4th row대구광역시 중구 국채보상로 726, 강남빌딩 6층 (동인동4가)
5th row대구광역시 군위군 효령면 경북대로 2220, 2층
ValueCountFrequency (%)
대구광역시 60
 
18.2%
북구 19
 
5.8%
수성구 10
 
3.0%
달서구 8
 
2.4%
동구 8
 
2.4%
남구 8
 
2.4%
신천동 6
 
1.8%
읍내동 5
 
1.5%
3층 5
 
1.5%
중구 4
 
1.2%
Other values (156) 197
59.7%
2023-11-11T23:12:04.512821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
 
16.0%
구 122
 
7.2%
대 85
 
5.0%
동 80
 
4.7%
시 63
 
3.7%
역 61
 
3.6%
광 61
 
3.6%
) 57
 
3.4%
( 57
 
3.4%
로 56
 
3.3%
Other values (135) 775
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
58.2%
Decimal Number 271
 
16.1%
Space Separator 270
 
16.0%
Close Punctuation 57
 
3.4%
Open Punctuation 57
 
3.4%
Other Punctuation 31
 
1.8%
Dash Punctuation 19
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 122
 
12.4%
대 85
 
8.7%
동 80
 
8.1%
시 63
 
6.4%
역 61
 
6.2%
광 61
 
6.2%
로 56
 
5.7%
길 34
 
3.5%
북 23
 
2.3%
성 22
 
2.2%
Other values (120) 375
38.2%
Decimal Number
ValueCountFrequency (%)
2 48
17.7%
1 41
15.1%
3 37
13.7%
5 31
11.4%
4 28
10.3%
0 22
8.1%
7 20
7.4%
6 18
 
6.6%
9 13
 
4.8%
8 13
 
4.8%
Space Separator
ValueCountFrequency (%)
270
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 982
58.2%
Common 705
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 122
 
12.4%
대 85
 
8.7%
동 80
 
8.1%
시 63
 
6.4%
역 61
 
6.2%
광 61
 
6.2%
로 56
 
5.7%
길 34
 
3.5%
북 23
 
2.3%
성 22
 
2.2%
Other values (120) 375
38.2%
Common
ValueCountFrequency (%)
270
38.3%
) 57
 
8.1%
( 57
 
8.1%
2 48
 
6.8%
1 41
 
5.8%
3 37
 
5.2%
5 31
 
4.4%
, 31
 
4.4%
4 28
 
4.0%
0 22
 
3.1%
Other values (5) 83
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 982
58.2%
ASCII 705
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
38.3%
) 57
 
8.1%
( 57
 
8.1%
2 48
 
6.8%
1 41
 
5.8%
3 37
 
5.2%
5 31
 
4.4%
, 31
 
4.4%
4 28
 
4.0%
0 22
 
3.1%
Other values (5) 83
 
11.8%
Hangul
ValueCountFrequency (%)
구 122
 
12.4%
대 85
 
8.7%
동 80
 
8.1%
시 63
 
6.4%
역 61
 
6.2%
광 61
 
6.2%
로 56
 
5.7%
길 34
 
3.5%
북 23
 
2.3%
성 22
 
2.2%
Other values (120) 375
38.2%

도로명우편번호
Text

MISSING 

Distinct49
Distinct (%)81.7%
Missing22
Missing (%)26.8%
Memory size788.0 B
2023-11-11T23:12:04.922781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4666667
Min length5

Characters and Unicode

Total characters328
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)66.7%

Sample

1st row41401
2nd row42474
3rd row41487
4th row41946
5th row39033
ValueCountFrequency (%)
41467 3
 
5.0%
41408 3
 
5.0%
42251 2
 
3.3%
41487 2
 
3.3%
41263 2
 
3.3%
41401 2
 
3.3%
41474 2
 
3.3%
42812 2
 
3.3%
41904 2
 
3.3%
42410 1
 
1.7%
Other values (39) 39
65.0%
2023-11-11T23:12:05.588478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 85
25.9%
2 44
13.4%
0 41
12.5%
1 40
12.2%
7 31
 
9.5%
8 26
 
7.9%
6 18
 
5.5%
- 14
 
4.3%
5 12
 
3.7%
3 9
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 314
95.7%
Dash Punctuation 14
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 85
27.1%
2 44
14.0%
0 41
13.1%
1 40
12.7%
7 31
 
9.9%
8 26
 
8.3%
6 18
 
5.7%
5 12
 
3.8%
3 9
 
2.9%
9 8
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 328
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 85
25.9%
2 44
13.4%
0 41
12.5%
1 40
12.2%
7 31
 
9.5%
8 26
 
7.9%
6 18
 
5.5%
- 14
 
4.3%
5 12
 
3.7%
3 9
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 85
25.9%
2 44
13.4%
0 41
12.5%
1 40
12.2%
7 31
 
9.5%
8 26
 
7.9%
6 18
 
5.5%
- 14
 
4.3%
5 12
 
3.7%
3 9
 
2.7%

사업장명
Text

Distinct77
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-11-11T23:12:06.016271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.7195122
Min length4

Characters and Unicode

Total characters715
Distinct characters108
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

Unique73 ?
Unique (%)89.0%

Sample

1st row경원기업 주식회사
2nd row주식회사 공인기술단
3rd row(주)넥스트이엔지
4th row주식회사 청이엔지
5th row주식회사 나무전기
ValueCountFrequency (%)
주식회사 16
 
16.2%
주)기성이앤씨 3
 
3.0%
우성설계감리(주 2
 
2.0%
나우전기 2
 
2.0%
주)우전엔지니어링 2
 
2.0%
덕원기술단 2
 
2.0%
주)위너엔지니어링 1
 
1.0%
주)유성이앤씨 1
 
1.0%
한국안전기술(주 1
 
1.0%
세이프소방방재 1
 
1.0%
Other values (68) 68
68.7%
2023-11-11T23:12:06.667757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 68
 
9.5%
( 49
 
6.9%
) 49
 
6.9%
이 33
 
4.6%
엔 31
 
4.3%
사 30
 
4.2%
기 28
 
3.9%
지 25
 
3.5%
회 18
 
2.5%
식 18
 
2.5%
Other values (98) 366
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 591
82.7%
Open Punctuation 49
 
6.9%
Close Punctuation 49
 
6.9%
Space Separator 17
 
2.4%
Uppercase Letter 9
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 68
 
11.5%
이 33
 
5.6%
엔 31
 
5.2%
사 30
 
5.1%
기 28
 
4.7%
지 25
 
4.2%
회 18
 
3.0%
식 18
 
3.0%
씨 16
 
2.7%
니 15
 
2.5%
Other values (90) 309
52.3%
Uppercase Letter
ValueCountFrequency (%)
E 3
33.3%
N 2
22.2%
C 2
22.2%
M 1
 
11.1%
G 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 591
82.7%
Common 115
 
16.1%
Latin 9
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 68
 
11.5%
이 33
 
5.6%
엔 31
 
5.2%
사 30
 
5.1%
기 28
 
4.7%
지 25
 
4.2%
회 18
 
3.0%
식 18
 
3.0%
씨 16
 
2.7%
니 15
 
2.5%
Other values (90) 309
52.3%
Latin
ValueCountFrequency (%)
E 3
33.3%
N 2
22.2%
C 2
22.2%
M 1
 
11.1%
G 1
 
11.1%
Common
ValueCountFrequency (%)
( 49
42.6%
) 49
42.6%
17
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 591
82.7%
ASCII 124
 
17.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 68
 
11.5%
이 33
 
5.6%
엔 31
 
5.2%
사 30
 
5.1%
기 28
 
4.7%
지 25
 
4.2%
회 18
 
3.0%
식 18
 
3.0%
씨 16
 
2.7%
니 15
 
2.5%
Other values (90) 309
52.3%
ASCII
ValueCountFrequency (%)
( 49
39.5%
) 49
39.5%
17
 
13.7%
E 3
 
2.4%
N 2
 
1.6%
C 2
 
1.6%
M 1
 
0.8%
G 1
 
0.8%

최종수정시점
Date

UNIQUE 

Distinct82
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2007-02-07 18:04:40
Maximum2023-10-26 14:08:47
2023-11-11T23:12:06.972574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-11T23:12:07.225255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
I
44 
U
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 44
53.7%
U 38
46.3%

Length

2023-11-11T23:12:07.466185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:12:07.730187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 44
53.7%
u 38
46.3%

데이터갱신일자
Date

Distinct35
Distinct (%)42.7%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2018-08-31 23:59:59
Maximum2023-10-28 02:40:00
2023-11-11T23:12:07.934750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-11-11T23:12:08.158959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82
Missing (%)100.0%
Memory size870.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)78.6%
Missing12
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean344171.58
Minimum336818.18
Maximum353928.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:12:08.476240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum336818.18
5-th percentile339028.25
Q1341097.36
median344195.36
Q3346895.56
95-th percentile350042.82
Maximum353928.88
Range17110.704
Interquartile range (IQR)5798.2071

Descriptive statistics

Standard deviation3755.7789
Coefficient of variation (CV)0.010912519
Kurtosis-0.2046544
Mean344171.58
Median Absolute Deviation (MAD)2762.5866
Skewness0.25704252
Sum24092010
Variance14105875
MonotonicityNot monotonic
2023-11-11T23:12:08.688721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
342550.434135631 3
 
3.7%
339715.275891533 3
 
3.7%
346621.939233257 3
 
3.7%
346973.195337702 3
 
3.7%
340224.842223043 3
 
3.7%
345896.977353176 2
 
2.4%
339155.347016679 2
 
2.4%
339692.068631494 2
 
2.4%
342429.117453876 2
 
2.4%
341097.357830197 2
 
2.4%
Other values (45) 45
54.9%
(Missing) 12
 
14.6%
ValueCountFrequency (%)
336818.179374162 1
 
1.2%
337272.928599609 1
 
1.2%
338146.048222367 1
 
1.2%
338924.266944344 1
 
1.2%
339155.347016679 2
2.4%
339666.89805761 1
 
1.2%
339692.068631494 2
2.4%
339715.275891533 3
3.7%
339922.644222408 1
 
1.2%
340224.842223043 3
3.7%
ValueCountFrequency (%)
353928.883617217 1
1.2%
352904.676227722 1
1.2%
352508.861736613 1
1.2%
350775.260288725 1
1.2%
349147.61284899 1
1.2%
348877.264262122 1
1.2%
348585.347528119 1
1.2%
348383.677965782 1
1.2%
347664.620883796 1
1.2%
347470.257305061 1
1.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct55
Distinct (%)78.6%
Missing12
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean265177.69
Minimum256156.01
Maximum292256.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:12:08.914885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum256156.01
5-th percentile258746.32
Q1261484.48
median264819.5
Q3268134.72
95-th percentile273622.81
Maximum292256.97
Range36100.967
Interquartile range (IQR)6650.2399

Descriptive statistics

Standard deviation5393.6258
Coefficient of variation (CV)0.020339666
Kurtosis7.9791971
Mean265177.69
Median Absolute Deviation (MAD)3379.1171
Skewness1.984442
Sum18562439
Variance29091200
MonotonicityNot monotonic
2023-11-11T23:12:09.162760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
273683.918029084 3
 
3.7%
269601.909686209 3
 
3.7%
265048.32860083 3
 
3.7%
264995.374262301 3
 
3.7%
273548.124057049 3
 
3.7%
265140.936598727 2
 
2.4%
268535.276448655 2
 
2.4%
258178.917239669 2
 
2.4%
261115.730073153 2
 
2.4%
261484.477731744 2
 
2.4%
Other values (45) 45
54.9%
(Missing) 12
 
14.6%
ValueCountFrequency (%)
256156.006261751 1
1.2%
258178.917239669 2
2.4%
258392.178871232 1
1.2%
259179.153081779 1
1.2%
259248.897035138 1
1.2%
259274.066034488 1
1.2%
259798.975468906 1
1.2%
259811.193991935 1
1.2%
260645.517099214 1
1.2%
260803.261833604 1
1.2%
ValueCountFrequency (%)
292256.972974569 1
 
1.2%
273683.918029084 3
3.7%
273548.124057049 3
3.7%
270911.45465356 1
 
1.2%
270781.562229066 1
 
1.2%
270065.788688571 1
 
1.2%
269601.909686209 3
3.7%
268870.659507124 1
 
1.2%
268535.276448655 2
2.4%
268408.951404422 1
 
1.2%

업종구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
감리업
82 

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 82
100.0%

Length

2023-11-11T23:12:09.486129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:12:09.661900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
감리업 82
100.0%

설계감리업종류명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
전문감리업
47 
종합감리업
35 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전문감리업 47
57.3%
종합감리업 35
42.7%

Length

2023-11-11T23:12:09.844885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:12:10.045925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전문감리업 47
57.3%
종합감리업 35
42.7%

소속국가명
Categorical

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
<NA>
49 
대한민국
33 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 49
59.8%
대한민국 33
40.2%

Length

2023-11-11T23:12:10.237104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-11-11T23:12:10.432230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 49
59.8%
대한민국 33
40.2%

실질자본금
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62066618
Minimum0
Maximum5 × 108
Zeros38
Zeros (%)46.3%
Negative0
Negative (%)0.0%
Memory size870.0 B
2023-11-11T23:12:10.620026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50000000
Q358450590
95-th percentile2.57595 × 108
Maximum5 × 108
Range5 × 108
Interquartile range (IQR)58450590

Descriptive statistics

Standard deviation1.0392576 × 108
Coefficient of variation (CV)1.6744228
Kurtosis8.4725614
Mean62066618
Median Absolute Deviation (MAD)50000000
Skewness2.8085745
Sum5.0894626 × 109
Variance1.0800564 × 1016
MonotonicityNot monotonic
2023-11-11T23:12:10.855536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 38
46.3%
50000000 17
20.7%
100000000 4
 
4.9%
500000000 2
 
2.4%
210000000 2
 
2.4%
60075000 2
 
2.4%
51937772 1
 
1.2%
110080000 1
 
1.2%
50878576 1
 
1.2%
52603240 1
 
1.2%
Other values (13) 13
 
15.9%
ValueCountFrequency (%)
0 38
46.3%
50000000 17
20.7%
50086440 1
 
1.2%
50501944 1
 
1.2%
50878576 1
 
1.2%
51937772 1
 
1.2%
52603240 1
 
1.2%
53577360 1
 
1.2%
60075000 2
 
2.4%
72409136 1
 
1.2%
ValueCountFrequency (%)
500000000 2
2.4%
433000000 1
1.2%
335683008 1
1.2%
260100000 1
1.2%
210000000 2
2.4%
197395104 1
1.2%
164955616 1
1.2%
141785456 1
1.2%
110080000 1
1.2%
103774040 1
1.2%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명설계감리업종류명소속국가명실질자본금
01전력기술감리업체09_28_12_P62700002019627000086000012019-01-17<NA>1영업/정상1인허가<NA><NA><NA><NA>533118415<NA>41401대구광역시 북구 읍내동 397-10대구광역시 북구 칠곡중앙대로128길 9 (읍내동)41401경원기업 주식회사2019-10-10 18:26:49U2019-10-12 02:40:00<NA>340224.842223273548.124057감리업전문감리업대한민국50000000
12전력기술감리업체09_28_12_P62700002019627000086000022017-12-20<NA>1영업/정상1인허가<NA><NA><NA><NA>532161966<NA>42474대구광역시 남구 대명동 1641-13대구광역시 남구 두류공원로5길 16-61 (대명동)42474주식회사 공인기술단2019-11-21 09:24:40U2019-11-23 02:40:00<NA>342006.931839261205.185758감리업종합감리업<NA>197395104
23전력기술감리업체09_28_12_P62700002019627000086000032019-03-12<NA>1영업/정상1인허가<NA><NA><NA><NA>539392448<NA>41487대구광역시 북구 매천동 714번지 1층대구광역시 북구 매전로4길 20-30, 1층 (매천동)41487(주)넥스트이엔지2022-09-24 15:05:05U2022-09-26 02:40:00<NA>339155.347017268535.276449감리업전문감리업<NA>50501944
34전력기술감리업체09_28_12_P62700002019627000086000042019-05-13<NA>1영업/정상1인허가<NA><NA><NA><NA>532541720<NA>41946대구광역시 중구 동인동4가 386-7 강남빌딩,6층대구광역시 중구 국채보상로 726, 강남빌딩 6층 (동인동4가)41946주식회사 청이엔지2019-10-10 18:25:23U2019-10-12 02:40:00<NA>345323.318065264335.308575감리업전문감리업<NA>90544944
45전력기술감리업체09_28_12_P62700002020647000086000022020-02-04<NA>1영업/정상1인허가<NA><NA><NA><NA><NA><NA>39033대구광역시 군위군 효령면 장군리 61-2대구광역시 군위군 효령면 경북대로 2220, 2층39033주식회사 나무전기2023-04-03 15:24:27I2023-07-01 16:42:10<NA>341829.990652292256.972975감리업전문감리업<NA>0
56전력기술감리업체09_28_12_P62700002022627000086000012022-03-28<NA>1영업/정상1인허가<NA><NA><NA><NA>530000000<NA>41059대구광역시 동구 상매동 505-10 중앙빌딩 501호대구광역시 동구 이노밸리로 3, 중앙빌딩 4층 501호(상매동)41059나래이엔지2022-08-16 18:54:38U2022-08-18 02:40:00<NA>353928.883617266641.633672감리업전문감리업<NA>50000000
67전력기술감리업체09_28_12_P62700002020627000086000032020-03-11<NA>1영업/정상1인허가<NA><NA><NA><NA>532144343<NA>41474대구광역시 북구 서변동 1729-5대구광역시 북구 호국로57길 31-12, 3층 302호 (서변동)41474주식회사 성민이엔지2021-04-06 09:25:23U2021-04-08 02:40:00<NA>343990.953377270781.562229감리업전문감리업<NA>50000000
78전력기술감리업체09_28_12_P62700002020627000086000022020-02-04<NA>1영업/정상1인허가<NA><NA><NA><NA>536220944<NA>42458대구광역시 남구 대명동 3020-43대구광역시 남구 대경6길 1 (대명동)42458(주)나무전기2020-02-04 14:59:26I2020-02-06 00:23:24<NA>342147.895939262200.395899감리업전문감리업<NA>50000000
89전력기술감리업체09_28_12_P62700002023627000086000012023-02-01<NA>1영업/정상1인허가<NA><NA><NA><NA>549732400<NA>41408대구광역시 북구 국우동 671번지대구광역시 북구 도남길 45-4(국우동)41408주식회사 태화엔지니어링2023-02-24 10:59:47U2023-05-26 08:48:36<NA>342550.434136273683.918029감리업전문감리업<NA>0
910전력기술감리업체09_28_12_P62700002010627000086000042010-07-16<NA>1영업/정상1인허가<NA><NA><NA><NA>537456112<NA>706-806대구광역시 수성구 만촌동 989번지 9호대구광역시 수성구 충의로 39 (만촌동)706-806우진엔지니어링2018-10-16 10:48:16U2018-10-18 02:36:29<NA>348585.347528264011.729006감리업전문감리업<NA>51937772
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명설계감리업종류명소속국가명실질자본금
7273전력기술감리업체09_28_12_P62700002003627000086000032003-11-11<NA>3폐업3폐업2010-08-09<NA><NA><NA>534761671<NA>705-020대구 남구 봉덕동 687-7 3층<NA><NA>(주)동원테크2010-08-10 13:44:37I2018-08-31 23:59:59<NA><NA><NA>감리업전문감리업대한민국0
7374전력기술감리업체09_28_12_P62700002006627000086000022006-08-17<NA>3폐업3폐업2007-02-07<NA><NA><NA>536287200<NA>705-809대구광역시 남구 대명1동 792번지 27호<NA><NA>(주)기성이앤씨2007-02-07 18:04:40I2018-08-31 23:59:59<NA>342429.117454261115.730073감리업전문감리업<NA>52603240
7475전력기술감리업체09_28_12_P62700002007627000086000042007-02-07<NA>3폐업3폐업<NA><NA><NA><NA>536287200<NA>705-809대구광역시 남구 대명1동 792번지 27호<NA><NA>(주)기성이앤씨2009-12-30 09:35:06I2018-08-31 23:59:59<NA>342429.117454261115.730073감리업종합감리업<NA>0
7576전력기술감리업체09_28_12_P62700002007627000086000032007-02-07<NA>3폐업3폐업2007-02-28<NA><NA><NA>532152130<NA>706-846대구광역시 수성구 지산2동 1272번지 3호<NA><NA>그린전기감리2007-02-28 16:37:32I2018-08-31 23:59:59<NA>347664.620884259179.153082감리업전문감리업<NA>0
7677전력기술감리업체09_28_12_P62700002008627000086000012008-05-08<NA>3폐업3폐업2015-04-01<NA><NA><NA>535811977<NA>704-929대구광역시 달서구 이곡1동 1000번지 210호 (203호)<NA><NA>주식회사 북극2015-04-21 17:31:25I2018-08-31 23:59:59<NA>336818.179374262138.815756감리업전문감리업대한민국50000000
7778전력기술감리업체09_28_12_P62700002007627000086000062007-11-15<NA>3폐업3폐업2007-12-26<NA><NA><NA>537410109<NA>701-824대구광역시 동구 신천3동 83번지 2호<NA><NA>덕원기술단2007-12-26 14:52:47I2018-08-31 23:59:59<NA>346621.939233265048.328601감리업전문감리업<NA>0
7879전력기술감리업체09_28_12_P62700002010627000086000032010-05-06<NA>3폐업3폐업2011-01-27<NA><NA><NA>537542172<NA>701-829대구광역시 동구 신천4동 332번지 8호<NA><NA>부강이엔씨(주)2011-01-28 18:10:51I2018-08-31 23:59:59<NA>346973.195338264995.374262감리업전문감리업대한민국60075000
7980전력기술감리업체09_28_12_P62700002010627000086000052010-08-02<NA>3폐업3폐업2012-03-16<NA><NA><NA>534289495<NA>706-032대구광역시 수성구 수성동2가 184번지 1호대구광역시 수성구 수성로64길 35-1 (수성동2가)706-032태하기술단2012-03-19 14:06:02I2018-08-31 23:59:59<NA>345866.54634262682.961583감리업전문감리업<NA>50878576
8081전력기술감리업체09_28_12_P62700002017627000086000022017-05-24<NA>3폐업3폐업2017-05-30<NA><NA><NA>536244868<NA><NA>대구광역시 남구 봉덕동 547번지 28호대구광역시 남구 봉덕로9길 47 (봉덕동)42430나우전기2020-12-28 14:14:13U2020-12-30 02:40:00<NA>344106.911763261947.962294감리업전문감리업<NA>0
8182전력기술감리업체09_28_12_P62700002021627000086000062021-07-22<NA>3폐업3폐업2023-10-10<NA><NA><NA>537565577<NA>41263대구광역시 동구 신천동 1368번지대구광역시 동구 동부로5길 41-3(신천동)41263(주)대천이엔지2023-10-26 14:08:47U2023-10-28 02:40:00<NA>345896.977353265140.936599감리업전문감리업<NA>0