Overview

Dataset statistics

Number of variables30
Number of observations52
Missing cells474
Missing cells (%)30.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory256.5 B

Variable types

Numeric6
Categorical7
DateTime4
Unsupported6
Text7

Dataset

Description23년07월_6270000_대구광역시_09_28_03_P_계량기제조업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000099416&dataSetDetailId=DDI_0000099474&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
인허가취소일자 has 52 (100.0%) missing valuesMissing
폐업일자 has 47 (90.4%) missing valuesMissing
휴업시작일자 has 52 (100.0%) missing valuesMissing
휴업종료일자 has 52 (100.0%) missing valuesMissing
재개업일자 has 52 (100.0%) missing valuesMissing
소재지전화 has 7 (13.5%) missing valuesMissing
소재지면적 has 52 (100.0%) missing valuesMissing
소재지우편번호 has 17 (32.7%) missing valuesMissing
소재지전체주소 has 3 (5.8%) missing valuesMissing
도로명전체주소 has 13 (25.0%) missing valuesMissing
도로명우편번호 has 26 (50.0%) missing valuesMissing
업태구분명 has 52 (100.0%) missing valuesMissing
좌표정보(X) has 12 (23.1%) missing valuesMissing
좌표정보(Y) has 12 (23.1%) missing valuesMissing
사무소전화번호 has 7 (13.5%) missing valuesMissing
사업장전화번호 has 18 (34.6%) 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
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

Reproduction

Analysis started2023-08-19 13:05:23.666970
Analysis finished2023-08-19 13:05:25.102153
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:25.396343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-08-19T22:05:25.936208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
계량기제조업
52 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계량기제조업 52
100.0%

Length

2023-08-19T22:05:26.438008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:26.689495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기제조업 52
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
09_28_03_P
52 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_03_P
2nd row09_28_03_P
3rd row09_28_03_P
4th row09_28_03_P
5th row09_28_03_P

Common Values

ValueCountFrequency (%)
09_28_03_P 52
100.0%

Length

2023-08-19T22:05:26.994153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:27.197523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_03_p 52
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4865000
Minimum3420000
Maximum6270000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:27.478996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3425500
Q13467500
median4875000
Q36270000
95-th percentile6270000
Maximum6270000
Range2850000
Interquartile range (IQR)2802500

Descriptive statistics

Standard deviation1418774
Coefficient of variation (CV)0.29162877
Kurtosis-2.081215
Mean4865000
Median Absolute Deviation (MAD)1395000
Skewness-0.00029008654
Sum2.5298 × 108
Variance2.0129196 × 1012
MonotonicityIncreasing
2023-08-19T22:05:27.827376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
6270000 26
50.0%
3480000 7
 
13.5%
3470000 6
 
11.5%
3450000 5
 
9.6%
3460000 4
 
7.7%
3420000 3
 
5.8%
3430000 1
 
1.9%
ValueCountFrequency (%)
3420000 3
 
5.8%
3430000 1
 
1.9%
3450000 5
 
9.6%
3460000 4
 
7.7%
3470000 6
 
11.5%
3480000 7
 
13.5%
6270000 26
50.0%
ValueCountFrequency (%)
6270000 26
50.0%
3480000 7
 
13.5%
3470000 6
 
11.5%
3460000 4
 
7.7%
3450000 5
 
9.6%
3430000 1
 
1.9%
3420000 3
 
5.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1063774 × 1018
Minimum1.967627 × 1017
Maximum2.022345 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:28.143941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.967627 × 1017
5-th percentile1.986627 × 1017
Q12.004377 × 1017
median1.0987549 × 1018
Q32.0128478 × 1018
95-th percentile2.021348 × 1018
Maximum2.022345 × 1018
Range1.8255823 × 1018
Interquartile range (IQR)1.8124101 × 1018

Descriptive statistics

Standard deviation9.1521144 × 1017
Coefficient of variation (CV)0.82721449
Kurtosis-2.081483
Mean1.1063774 × 1018
Median Absolute Deviation (MAD)9.0174215 × 1017
Skewness0.0001004995
Sum2.1913943 × 1018
Variance8.3761199 × 1035
MonotonicityNot monotonic
2023-08-19T22:05:28.743393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2017342013506500002 1
 
1.9%
199162700009100001 1
 
1.9%
198662700009100001 1
 
1.9%
199562700009100001 1
 
1.9%
199862700009100001 1
 
1.9%
200262700009100001 1
 
1.9%
200362700009100002 1
 
1.9%
200462700009100002 1
 
1.9%
200562700009100001 1
 
1.9%
200562700009100002 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
196762700009100001 1
1.9%
197262700009100001 1
1.9%
198662700009100001 1
1.9%
198662700009100002 1
1.9%
199162700009100001 1
1.9%
199562700009100001 1
1.9%
199662700009100001 1
1.9%
199862700009100001 1
1.9%
200062700009100001 1
1.9%
200162700009100001 1
1.9%
ValueCountFrequency (%)
2022345016006500002 1
1.9%
2022345016006500001 1
1.9%
2021348036506500003 1
1.9%
2021348036506500001 1
1.9%
2020348036506500001 1
1.9%
2019348036506500003 1
1.9%
2019348036506500001 1
1.9%
2019347018106500002 1
1.9%
2018346014006500003 1
1.9%
2018346014006500001 1
1.9%

인허가일자
Date

Distinct44
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum1967-04-28 00:00:00
Maximum2022-06-08 00:00:00
2023-08-19T22:05:29.363446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-19T22:05:30.310743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
1
39 
3
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 39
75.0%
3 13
 
25.0%

Length

2023-08-19T22:05:30.680620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:30.972914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
75.0%
3 13
 
25.0%

영업상태명
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
영업/정상
39 
폐업
13 

Length

Max length5
Median length5
Mean length4.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 39
75.0%
폐업 13
 
25.0%

Length

2023-08-19T22:05:31.336240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:31.790941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 39
75.0%
폐업 13
 
25.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
1
39 
3
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 39
75.0%
3 13
 
25.0%

Length

2023-08-19T22:05:32.157151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:32.432505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 39
75.0%
3 13
 
25.0%

상세영업상태명
Categorical

Distinct3
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
영업중
20 
등록
19 
폐업
13 

Length

Max length3
Median length2
Mean length2.3846154
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업중
2nd row영업중
3rd row영업중
4th row폐업
5th row영업중

Common Values

ValueCountFrequency (%)
영업중 20
38.5%
등록 19
36.5%
폐업 13
25.0%

Length

2023-08-19T22:05:32.830462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:33.179173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 20
38.5%
등록 19
36.5%
폐업 13
25.0%

폐업일자
Date

MISSING 

Distinct5
Distinct (%)100.0%
Missing47
Missing (%)90.4%
Memory size548.0 B
Minimum2012-02-29 00:00:00
Maximum2023-03-31 00:00:00
2023-08-19T22:05:33.425129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-19T22:05:33.660955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

소재지전화
Text

MISSING 

Distinct38
Distinct (%)84.4%
Missing7
Missing (%)13.5%
Memory size548.0 B
2023-08-19T22:05:34.244732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.511111
Min length7

Characters and Unicode

Total characters473
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

Unique31 ?
Unique (%)68.9%

Sample

1st row031 883 5400
2nd row0539536303
3rd row053 383 7181
4th row0539438359
5th row053 742 3398
ValueCountFrequency (%)
053 12
 
16.9%
0535861800 2
 
2.8%
0536322225 2
 
2.8%
0533246154 2
 
2.8%
4600 2
 
2.8%
238 2
 
2.8%
0535923771 2
 
2.8%
0533811740 2
 
2.8%
0539536303 2
 
2.8%
0539438359 2
 
2.8%
Other values (41) 41
57.7%
2023-08-19T22:05:35.366070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 447
94.5%
Space Separator 26
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
20.1%
3 84
18.8%
5 80
17.9%
1 44
9.8%
8 28
 
6.3%
2 27
 
6.0%
9 26
 
5.8%
7 24
 
5.4%
4 23
 
5.1%
6 21
 
4.7%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

소재지우편번호
Text

MISSING 

Distinct26
Distinct (%)74.3%
Missing17
Missing (%)32.7%
Memory size548.0 B
2023-08-19T22:05:35.814656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters245
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

Unique19 ?
Unique (%)54.3%

Sample

1st row703-828
2nd row702-862
3rd row702-120
4th row702-010
5th row706-140
ValueCountFrequency (%)
702-815 3
 
8.6%
702-835 3
 
8.6%
702-120 2
 
5.7%
706-140 2
 
5.7%
702-862 2
 
5.7%
703-828 2
 
5.7%
704-240 2
 
5.7%
704-828 1
 
2.9%
711-842 1
 
2.9%
702-873 1
 
2.9%
Other values (16) 16
45.7%
2023-08-19T22:05:36.635975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
20.4%
7 36
14.7%
- 35
14.3%
2 28
11.4%
8 26
10.6%
1 22
9.0%
4 15
 
6.1%
5 13
 
5.3%
3 8
 
3.3%
6 6
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
85.7%
Dash Punctuation 35
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
23.8%
7 36
17.1%
2 28
13.3%
8 26
12.4%
1 22
10.5%
4 15
 
7.1%
5 13
 
6.2%
3 8
 
3.8%
6 6
 
2.9%
9 6
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 245
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
20.4%
7 36
14.7%
- 35
14.3%
2 28
11.4%
8 26
10.6%
1 22
9.0%
4 15
 
6.1%
5 13
 
5.3%
3 8
 
3.3%
6 6
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
20.4%
7 36
14.7%
- 35
14.3%
2 28
11.4%
8 26
10.6%
1 22
9.0%
4 15
 
6.1%
5 13
 
5.3%
3 8
 
3.3%
6 6
 
2.4%

소재지전체주소
Text

MISSING 

Distinct48
Distinct (%)98.0%
Missing3
Missing (%)5.8%
Memory size548.0 B
2023-08-19T22:05:37.240316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length25.163265
Min length19

Characters and Unicode

Total characters1233
Distinct characters106
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st row대구광역시 북구 서변동 1724번지 31통 3반 서변그린타운 103동 806호
2nd row경상북도 포항시 남구 대잠동 986번지 5호
3rd row대구광역시 서구 원대동3가 990번지 7호
4th row경상북도 김천시 감문면 문무리 978
5th row대구광역시 북구 침산1동 1025번지 6호
ValueCountFrequency (%)
대구광역시 47
 
19.1%
북구 17
 
6.9%
달서구 10
 
4.1%
달성군 9
 
3.7%
수성구 6
 
2.4%
노원3가 4
 
1.6%
1호 4
 
1.6%
응암리 3
 
1.2%
2호 3
 
1.2%
구지면 3
 
1.2%
Other values (114) 140
56.9%
2023-08-19T22:05:38.247691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
278
22.5%
구 89
 
7.2%
대 55
 
4.5%
1 50
 
4.1%
시 49
 
4.0%
지 48
 
3.9%
역 47
 
3.8%
광 47
 
3.8%
번 44
 
3.6%
동 40
 
3.2%
Other values (96) 486
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 702
56.9%
Space Separator 278
 
22.5%
Decimal Number 238
 
19.3%
Dash Punctuation 13
 
1.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 89
 
12.7%
대 55
 
7.8%
시 49
 
7.0%
지 48
 
6.8%
역 47
 
6.7%
광 47
 
6.7%
번 44
 
6.3%
동 40
 
5.7%
호 30
 
4.3%
달 20
 
2.8%
Other values (82) 233
33.2%
Decimal Number
ValueCountFrequency (%)
1 50
21.0%
2 34
14.3%
3 29
12.2%
0 23
9.7%
7 22
9.2%
6 21
8.8%
9 19
 
8.0%
5 16
 
6.7%
8 14
 
5.9%
4 10
 
4.2%
Space Separator
ValueCountFrequency (%)
278
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 702
56.9%
Common 531
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 89
 
12.7%
대 55
 
7.8%
시 49
 
7.0%
지 48
 
6.8%
역 47
 
6.7%
광 47
 
6.7%
번 44
 
6.3%
동 40
 
5.7%
호 30
 
4.3%
달 20
 
2.8%
Other values (82) 233
33.2%
Common
ValueCountFrequency (%)
278
52.4%
1 50
 
9.4%
2 34
 
6.4%
3 29
 
5.5%
0 23
 
4.3%
7 22
 
4.1%
6 21
 
4.0%
9 19
 
3.6%
5 16
 
3.0%
8 14
 
2.6%
Other values (4) 25
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 702
56.9%
ASCII 531
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
278
52.4%
1 50
 
9.4%
2 34
 
6.4%
3 29
 
5.5%
0 23
 
4.3%
7 22
 
4.1%
6 21
 
4.0%
9 19
 
3.6%
5 16
 
3.0%
8 14
 
2.6%
Other values (4) 25
 
4.7%
Hangul
ValueCountFrequency (%)
구 89
 
12.7%
대 55
 
7.8%
시 49
 
7.0%
지 48
 
6.8%
역 47
 
6.7%
광 47
 
6.7%
번 44
 
6.3%
동 40
 
5.7%
호 30
 
4.3%
달 20
 
2.8%
Other values (82) 233
33.2%

도로명전체주소
Text

MISSING 

Distinct32
Distinct (%)82.1%
Missing13
Missing (%)25.0%
Memory size548.0 B
2023-08-19T22:05:38.976192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length28
Mean length25.692308
Min length20

Characters and Unicode

Total characters1002
Distinct characters115
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

Unique25 ?
Unique (%)64.1%

Sample

1st row대구광역시 동구 신평로 84, 2층 (신평동)
2nd row대구광역시 동구 동촌로 425 (용계동)
3rd row경상북도 포항시 남구 대이로67번길 5 (대잠동)
4th row대구광역시 서구 옥산로 8 (원대동3가)
5th row경상북도 김천시 감문면 문화로 429-19
ValueCountFrequency (%)
대구광역시 37
 
18.3%
북구 11
 
5.4%
달서구 9
 
4.5%
달성군 7
 
3.5%
수성구 6
 
3.0%
산격동 4
 
2.0%
구지면 3
 
1.5%
동구 3
 
1.5%
신당동 3
 
1.5%
5 2
 
1.0%
Other values (89) 117
57.9%
2023-08-19T22:05:40.083522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
163
 
16.3%
구 72
 
7.2%
대 51
 
5.1%
동 44
 
4.4%
시 41
 
4.1%
로 39
 
3.9%
광 37
 
3.7%
역 37
 
3.7%
) 32
 
3.2%
( 32
 
3.2%
Other values (105) 454
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 620
61.9%
Space Separator 163
 
16.3%
Decimal Number 145
 
14.5%
Close Punctuation 32
 
3.2%
Open Punctuation 32
 
3.2%
Other Punctuation 5
 
0.5%
Dash Punctuation 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 72
 
11.6%
대 51
 
8.2%
동 44
 
7.1%
시 41
 
6.6%
로 39
 
6.3%
광 37
 
6.0%
역 37
 
6.0%
길 24
 
3.9%
달 18
 
2.9%
성 18
 
2.9%
Other values (90) 239
38.5%
Decimal Number
ValueCountFrequency (%)
1 25
17.2%
2 25
17.2%
5 20
13.8%
4 15
10.3%
7 13
9.0%
3 13
9.0%
6 12
8.3%
8 9
 
6.2%
9 8
 
5.5%
0 5
 
3.4%
Space Separator
ValueCountFrequency (%)
163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 620
61.9%
Common 382
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 72
 
11.6%
대 51
 
8.2%
동 44
 
7.1%
시 41
 
6.6%
로 39
 
6.3%
광 37
 
6.0%
역 37
 
6.0%
길 24
 
3.9%
달 18
 
2.9%
성 18
 
2.9%
Other values (90) 239
38.5%
Common
ValueCountFrequency (%)
163
42.7%
) 32
 
8.4%
( 32
 
8.4%
1 25
 
6.5%
2 25
 
6.5%
5 20
 
5.2%
4 15
 
3.9%
7 13
 
3.4%
3 13
 
3.4%
6 12
 
3.1%
Other values (5) 32
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 620
61.9%
ASCII 382
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
42.7%
) 32
 
8.4%
( 32
 
8.4%
1 25
 
6.5%
2 25
 
6.5%
5 20
 
5.2%
4 15
 
3.9%
7 13
 
3.4%
3 13
 
3.4%
6 12
 
3.1%
Other values (5) 32
 
8.4%
Hangul
ValueCountFrequency (%)
구 72
 
11.6%
대 51
 
8.2%
동 44
 
7.1%
시 41
 
6.6%
로 39
 
6.3%
광 37
 
6.0%
역 37
 
6.0%
길 24
 
3.9%
달 18
 
2.9%
성 18
 
2.9%
Other values (90) 239
38.5%

도로명우편번호
Text

MISSING 

Distinct21
Distinct (%)80.8%
Missing26
Missing (%)50.0%
Memory size548.0 B
2023-08-19T22:05:40.568350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6
Min length5

Characters and Unicode

Total characters156
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

Unique17 ?
Unique (%)65.4%

Sample

1st row41133
2nd row701-835
3rd row37684
4th row703-828
5th row39507
ValueCountFrequency (%)
43008 3
 
11.5%
42725 2
 
7.7%
704-240 2
 
7.7%
43023 2
 
7.7%
706-140 1
 
3.8%
41133 1
 
3.8%
701-835 1
 
3.8%
704-919 1
 
3.8%
704-900 1
 
3.8%
704-920 1
 
3.8%
Other values (11) 11
42.3%
2023-08-19T22:05:41.485548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34
21.8%
4 23
14.7%
2 19
12.2%
7 18
11.5%
3 13
 
8.3%
- 13
 
8.3%
1 11
 
7.1%
8 10
 
6.4%
5 6
 
3.8%
9 6
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 143
91.7%
Dash Punctuation 13
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34
23.8%
4 23
16.1%
2 19
13.3%
7 18
12.6%
3 13
 
9.1%
1 11
 
7.7%
8 10
 
7.0%
5 6
 
4.2%
9 6
 
4.2%
6 3
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34
21.8%
4 23
14.7%
2 19
12.2%
7 18
11.5%
3 13
 
8.3%
- 13
 
8.3%
1 11
 
7.1%
8 10
 
6.4%
5 6
 
3.8%
9 6
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34
21.8%
4 23
14.7%
2 19
12.2%
7 18
11.5%
3 13
 
8.3%
- 13
 
8.3%
1 11
 
7.1%
8 10
 
6.4%
5 6
 
3.8%
9 6
 
3.8%

사업장명
Text

Distinct37
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-08-19T22:05:41.987455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.6730769
Min length4

Characters and Unicode

Total characters399
Distinct characters100
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)48.1%

Sample

1st row옴니시스템(주) 대구지점
2nd row신라계기제작소
3rd row(주)우리기술
4th row대성계기제작소
5th row주식회사 태성콘텍
ValueCountFrequency (%)
대경계량시스템 3
 
5.4%
한국유체기술(주 3
 
5.4%
파워플러스콤(주 3
 
5.4%
신라계기제작소 2
 
3.6%
주)한국센서 2
 
3.6%
주)카라 2
 
3.6%
주)지텍산업 2
 
3.6%
주)아이디알시스템 2
 
3.6%
카스대구점 2
 
3.6%
에이앤디판매(주 2
 
3.6%
Other values (31) 33
58.9%
2023-08-19T22:05:42.976557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 34
 
8.5%
( 32
 
8.0%
) 32
 
8.0%
스 16
 
4.0%
기 14
 
3.5%
대 13
 
3.3%
계 12
 
3.0%
이 11
 
2.8%
시 8
 
2.0%
템 8
 
2.0%
Other values (90) 219
54.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 331
83.0%
Open Punctuation 32
 
8.0%
Close Punctuation 32
 
8.0%
Space Separator 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
10.3%
스 16
 
4.8%
기 14
 
4.2%
대 13
 
3.9%
계 12
 
3.6%
이 11
 
3.3%
시 8
 
2.4%
템 8
 
2.4%
량 7
 
2.1%
업 7
 
2.1%
Other values (87) 201
60.7%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 331
83.0%
Common 68
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
10.3%
스 16
 
4.8%
기 14
 
4.2%
대 13
 
3.9%
계 12
 
3.6%
이 11
 
3.3%
시 8
 
2.4%
템 8
 
2.4%
량 7
 
2.1%
업 7
 
2.1%
Other values (87) 201
60.7%
Common
ValueCountFrequency (%)
( 32
47.1%
) 32
47.1%
4
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 331
83.0%
ASCII 68
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 34
 
10.3%
스 16
 
4.8%
기 14
 
4.2%
대 13
 
3.9%
계 12
 
3.6%
이 11
 
3.3%
시 8
 
2.4%
템 8
 
2.4%
량 7
 
2.1%
업 7
 
2.1%
Other values (87) 201
60.7%
ASCII
ValueCountFrequency (%)
( 32
47.1%
) 32
47.1%
4
 
5.9%

최종수정시점
Date

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum2006-09-06 16:44:13
Maximum2023-06-26 14:46:06
2023-08-19T22:05:43.350989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-19T22:05:43.713417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
I
45 
U
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 45
86.5%
U 7
 
13.5%

Length

2023-08-19T22:05:44.108210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-19T22:05:44.343846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 45
86.5%
u 7
 
13.5%

데이터갱신일자
Date

Distinct16
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
Minimum2018-08-31 23:59:59
Maximum2023-06-28 02:40:00
2023-08-19T22:05:44.535395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-19T22:05:44.860764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing52
Missing (%)100.0%
Memory size600.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)87.5%
Missing12
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean341059.6
Minimum301083.04
Maximum410879.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:45.331506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum301083.04
5-th percentile328574
Q1334363.42
median340754.8
Q3344484.2
95-th percentile353836.75
Maximum410879.2
Range109796.16
Interquartile range (IQR)10120.777

Descriptive statistics

Standard deviation14830.34
Coefficient of variation (CV)0.043483132
Kurtosis13.173891
Mean341059.6
Median Absolute Deviation (MAD)6191.7431
Skewness2.2607106
Sum13642384
Variance2.1993897 × 108
MonotonicityNot monotonic
2023-08-19T22:05:45.726006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
353836.746083025 2
 
3.8%
336351.45503398 2
 
3.8%
342579.662250074 2
 
3.8%
333939.000275872 2
 
3.8%
344336.220920186 2
 
3.8%
332368.902860736 1
 
1.9%
328584.22585351 1
 
1.9%
329321.218502168 1
 
1.9%
335002.250163565 1
 
1.9%
341407.038519116 1
 
1.9%
Other values (25) 25
48.1%
(Missing) 12
23.1%
ValueCountFrequency (%)
301083.036950272 1
1.9%
328379.724398425 1
1.9%
328584.22585351 1
1.9%
328852.216440499 1
1.9%
329012.9782257 1
1.9%
329321.218502168 1
1.9%
332177.438962239 1
1.9%
332368.902860736 1
1.9%
333939.000275872 2
3.8%
334504.894957113 1
1.9%
ValueCountFrequency (%)
410879.20095392 1
1.9%
353836.746083025 2
3.8%
352149.518987501 1
1.9%
351885.808116793 1
1.9%
351544.53617974 1
1.9%
348761.524894409 1
1.9%
347993.559843973 1
1.9%
347017.917990507 1
1.9%
344756.123528245 1
1.9%
344393.556429503 1
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct35
Distinct (%)87.5%
Missing12
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean262693.51
Minimum239248.53
Maximum302974.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:46.160651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239248.53
5-th percentile239901.59
Q1260206.32
median262569.19
Q3267756.01
95-th percentile272703.41
Maximum302974.74
Range63726.209
Interquartile range (IQR)7549.6825

Descriptive statistics

Standard deviation11507.355
Coefficient of variation (CV)0.043805253
Kurtosis3.5122142
Mean262693.51
Median Absolute Deviation (MAD)5033.9078
Skewness0.41780918
Sum10507740
Variance1.3241923 × 108
MonotonicityNot monotonic
2023-08-19T22:05:46.598934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
261866.995362251 2
 
3.8%
259291.199101002 2
 
3.8%
267680.129055063 2
 
3.8%
260767.276685538 2
 
3.8%
268235.518219507 2
 
3.8%
243207.754695381 1
 
1.9%
251098.043305421 1
 
1.9%
254362.898509079 1
 
1.9%
260935.23124577 1
 
1.9%
267642.754527813 1
 
1.9%
Other values (25) 25
48.1%
(Missing) 12
23.1%
ValueCountFrequency (%)
239248.529887081 1
1.9%
239889.968036153 1
1.9%
239902.205989972 1
1.9%
243207.754695381 1
1.9%
243503.685707022 1
1.9%
251098.043305421 1
1.9%
254362.898509079 1
1.9%
259291.199101002 2
3.8%
259405.796433635 1
1.9%
260473.166164767 1
1.9%
ValueCountFrequency (%)
302974.738672273 1
1.9%
282589.461631921 1
1.9%
272183.092133128 1
1.9%
270947.744860696 1
1.9%
270704.837614874 1
1.9%
270372.281141347 1
1.9%
268235.518219507 2
3.8%
268048.514857183 1
1.9%
267983.637751997 1
1.9%
267680.129055063 2
3.8%

사무소전화번호
Text

MISSING 

Distinct38
Distinct (%)84.4%
Missing7
Missing (%)13.5%
Memory size548.0 B
2023-08-19T22:05:47.165381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.511111
Min length7

Characters and Unicode

Total characters473
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

Unique31 ?
Unique (%)68.9%

Sample

1st row031 883 5400
2nd row0539536303
3rd row053 383 7181
4th row0539438359
5th row053 742 3398
ValueCountFrequency (%)
053 12
 
16.9%
0535861800 2
 
2.8%
0536322225 2
 
2.8%
0533246154 2
 
2.8%
4600 2
 
2.8%
238 2
 
2.8%
0535923771 2
 
2.8%
0533811740 2
 
2.8%
0539536303 2
 
2.8%
0539438359 2
 
2.8%
Other values (41) 41
57.7%
2023-08-19T22:05:47.945130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 447
94.5%
Space Separator 26
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
20.1%
3 84
18.8%
5 80
17.9%
1 44
9.8%
8 28
 
6.3%
2 27
 
6.0%
9 26
 
5.8%
7 24
 
5.4%
4 23
 
5.1%
6 21
 
4.7%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 473
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 473
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
19.0%
3 84
17.8%
5 80
16.9%
1 44
9.3%
8 28
 
5.9%
2 27
 
5.7%
9 26
 
5.5%
26
 
5.5%
7 24
 
5.1%
4 23
 
4.9%

사업장전화번호
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)67.6%
Missing18
Missing (%)34.6%
Infinite0
Infinite (%)0.0%
Mean5.3528638 × 108
Minimum5.32552 × 108
Maximum5.3983694 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-08-19T22:05:48.347765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.32552 × 108
5-th percentile5.3291687 × 108
Q15.3357298 × 108
median5.3585434 × 108
Q35.360935 × 108
95-th percentile5.3953692 × 108
Maximum5.3983694 × 108
Range7284939
Interquartile range (IQR)2520514.2

Descriptive statistics

Standard deviation2033960.1
Coefficient of variation (CV)0.0037997605
Kurtosis0.21160921
Mean5.3528638 × 108
Median Absolute Deviation (MAD)2023995.5
Skewness0.84228721
Sum1.8199737 × 1010
Variance4.1369936 × 1012
MonotonicityNot monotonic
2023-08-19T22:05:49.019639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
535920373 2
 
3.8%
533521727 2
 
3.8%
533829120 2
 
3.8%
536150072 2
 
3.8%
535923771 2
 
3.8%
539536303 2
 
3.8%
535861800 2
 
3.8%
533831561 2
 
3.8%
536163693 2
 
3.8%
533516008 2
 
3.8%
Other values (13) 14
26.9%
(Missing) 18
34.6%
ValueCountFrequency (%)
532552004 1
1.9%
532552503 1
1.9%
533113060 1
1.9%
533143800 1
1.9%
533516008 2
3.8%
533521727 2
3.8%
533571117 1
1.9%
533578579 1
1.9%
533593382 1
1.9%
533829120 2
3.8%
ValueCountFrequency (%)
539836943 1
1.9%
539538075 1
1.9%
539536303 2
3.8%
536276500 1
1.9%
536163693 2
3.8%
536150072 2
3.8%
535923771 2
3.8%
535920373 2
3.8%
535911119 1
1.9%
535861800 2
3.8%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
01계량기제조업09_28_03_P342000020173420135065000022017-04-11<NA>1영업/정상1영업중<NA><NA><NA><NA>031 883 5400<NA><NA><NA>대구광역시 동구 신평로 84, 2층 (신평동)41133옴니시스템(주) 대구지점2017-04-12 14:28:33I2018-10-11 15:46:28<NA>351544.53618265604.874007031 883 5400<NA>
12계량기제조업09_28_03_P342000020063420000065000022012-01-20<NA>1영업/정상1영업중<NA><NA><NA><NA>0539536303<NA><NA>대구광역시 북구 서변동 1724번지 31통 3반 서변그린타운 103동 806호대구광역시 동구 동촌로 425 (용계동)701-835신라계기제작소2012-01-20 12:35:40I2018-10-11 15:46:28<NA>344029.924271270947.7448610539536303539536303
23계량기제조업09_28_03_P342000020153420135065000032015-09-15<NA>1영업/정상1영업중<NA><NA><NA><NA>053 383 7181<NA><NA>경상북도 포항시 남구 대잠동 986번지 5호경상북도 포항시 남구 대이로67번길 5 (대잠동)37684(주)우리기술2022-03-15 09:26:05U2022-03-17 02:40:00<NA>410879.200954282589.461632053 383 7181<NA>
34계량기제조업09_28_03_P343000020063430000065000042012-01-31<NA>3폐업3폐업2016-08-24<NA><NA><NA>0539438359<NA>703-828대구광역시 서구 원대동3가 990번지 7호대구광역시 서구 옥산로 8 (원대동3가)703-828대성계기제작소2016-08-24 17:47:47I2018-10-11 15:46:28<NA>342312.897137266350.3592380539438359533521727
45계량기제조업09_28_03_P345000020223450160065000012022-03-07<NA>1영업/정상1영업중<NA><NA><NA><NA><NA><NA><NA>경상북도 김천시 감문면 문무리 978경상북도 김천시 감문면 문화로 429-1939507주식회사 태성콘텍2022-03-08 14:59:55I2022-03-10 13:22:36<NA>301083.03695302974.738672<NA><NA>
56계량기제조업09_28_03_P345000020033450000065000022003-08-20<NA>1영업/정상1영업중<NA><NA><NA><NA>053 742 3398<NA>702-862대구광역시 북구 침산1동 1025번지 6호대구광역시 북구 노원로 182 (침산동)702-050에이앤디판매(주)2018-06-20 09:49:22I2018-10-11 15:46:28<NA>342579.66225267680.129055053 742 3398533516008
67계량기제조업09_28_03_P345000020053450000065000012005-01-18<NA>1영업/정상1영업중<NA><NA><NA><NA>053 954 4600<NA>702-120대구광역시 북구 동변동 200번지 2호대구광역시 북구 동변로24길 58-1 (동변동)702-120한국유체기술(주)2020-01-21 09:06:48U2020-01-23 02:40:00<NA>344393.55643270704.837615053 954 4600536163693
78계량기제조업09_28_03_P345000020053450000065000022005-08-01<NA>1영업/정상1영업중<NA><NA><NA><NA>0533811740<NA>702-010대구광역시 북구 산격동 646번지 20호대구광역시 북구 동북로 43 (산격동)702-010카스대구점2023-06-26 14:46:06U2023-06-28 02:40:00<NA>344244.890305268048.5148570533811740533831561
89계량기제조업09_28_03_P345000020223450160065000022022-06-08<NA>1영업/정상1영업중<NA><NA><NA><NA>0539540100<NA><NA>대구광역시 수성구 대흥동 857-5대구광역시 수성구 알파시티1로31길 17(대흥동)42250(주)한맥아이피에스2022-06-09 15:09:13I2022-06-11 00:22:30<NA>351885.808117260647.8973050539540100<NA>
910계량기제조업09_28_03_P346000020183460140065000012018-12-07<NA>1영업/정상1영업중<NA><NA><NA><NA>070 77880136<NA><NA>대구광역시 수성구 지산동 1019-12대구광역시 수성구 무학로35길 76 (지산동)42184(주)엔케이 어드벤스2020-09-17 12:00:33U2020-09-19 02:40:00<NA>347017.917991260473.166165070 77880136<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
4243계량기제조업09_28_03_P62700002001627000091000012001-11-06<NA>1영업/정상1등록<NA><NA><NA><NA>0535923771<NA>704-828대구광역시 달서구 월성2동 86-1번지 월성아파트형공장 5층 503호<NA><NA>파워플러스콤(주)2010-07-07 17:48:54I2018-08-31 23:59:59<NA><NA><NA>0535923771535923771
4344계량기제조업09_28_03_P62700002006627000091000022006-01-12<NA>1영업/정상1등록<NA><NA><NA><NA>0539536303<NA>701-835대구광역시 동구 용계동 936번지대구광역시 동구 동촌로 425 (용계동)<NA>신라계기제작소2006-09-06 16:47:15I2018-08-31 23:59:59<NA>352149.518988265228.7058130539536303539536303
4445계량기제조업09_28_03_P62700002006627000091000042006-12-21<NA>1영업/정상1등록<NA><NA><NA><NA>0539438359<NA>703-828대구광역시 서구 원대3가 990-7번지<NA><NA>대성계기제작소2009-10-08 13:13:00I2018-08-31 23:59:59<NA><NA><NA>0539438359533521727
4546계량기제조업09_28_03_P62700001972627000091000011972-11-08<NA>3폐업3폐업<NA><NA><NA><NA>0533578579<NA>702-815대구광역시 북구 노원3가 305번지대구광역시 북구 노원로9길 17 (노원동3가)<NA>대원도량형기제작소2009-12-21 15:50:50I2018-08-31 23:59:59<NA>341345.717029267095.178630533578579533578579
4647계량기제조업09_28_03_P62700002000627000091000012000-01-28<NA>3폐업3폐업<NA><NA><NA><NA>0532552503<NA>702-815대구광역시 북구 노원3가 239-8번지<NA><NA>서진종합상사2009-12-21 15:50:09I2018-08-31 23:59:59<NA><NA><NA>0532552503532552503
4748계량기제조업09_28_03_P62700002006627000091000032006-08-17<NA>3폐업3폐업<NA><NA><NA><NA>0533246154<NA>702-835대구광역시 북구 산격2동 671번지대구광역시 북구 연암로42길 37 (산격동)<NA>대경계량시스템2007-05-14 13:29:04I2018-08-31 23:59:59<NA>344336.22092268235.518220533246154533829120
4849계량기제조업09_28_03_P62700001986627000091000021986-02-12<NA>3폐업3폐업<NA><NA><NA><NA><NA><NA>705-805대구광역시 남구 대명9동 882-4번지<NA><NA>화성설비계량공사2007-05-14 13:26:06I2018-08-31 23:59:59<NA><NA><NA><NA>536276500
4950계량기제조업09_28_03_P62700001967627000091000011967-04-28<NA>3폐업3폐업<NA><NA><NA><NA><NA><NA>702-873대구광역시 북구 산격1동 517번지대구광역시 북구 동북로 92 (산격동)<NA>상수도사업본부 시설관리소2007-05-14 13:26:30I2018-08-31 23:59:59<NA>344756.123528267983.637752<NA>539538075
5051계량기제조업09_28_03_P62700002004627000091000012004-07-20<NA>3폐업3폐업<NA><NA><NA><NA>0536322225<NA>711-842대구광역시 달성군 옥포면 강림리 474-6번지<NA><NA>태성산업2009-12-21 15:51:29I2018-08-31 23:59:59<NA><NA><NA>0536322225536150072
5152계량기제조업09_28_03_P62700002003627000091000012003-05-06<NA>3폐업3폐업<NA><NA><NA><NA>0533113060<NA>702-864대구광역시 북구 태전동 229번지대구광역시 북구 칠곡중앙대로63길 5 (태전동)<NA>신성계량시스템2007-05-14 13:28:02I2018-08-31 23:59:59<NA>339468.954369270372.2811410533113060533113060