Overview

Dataset statistics

Number of variables30
Number of observations79
Missing cells611
Missing cells (%)25.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.7 KiB
Average record size in memory255.7 B

Variable types

Numeric5
Categorical9
DateTime3
Unsupported6
Text7

Dataset

Description23년06월_6270000_대구광역시_09_28_04_P_계량기증명업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000098696&dataSetDetailId=DDI_0000098749&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
데이터갱신일자 is highly imbalanced (62.4%)Imbalance
사업장전화번호 is highly imbalanced (85.3%)Imbalance
인허가취소일자 has 79 (100.0%) missing valuesMissing
폐업일자 has 54 (68.4%) missing valuesMissing
휴업시작일자 has 79 (100.0%) missing valuesMissing
휴업종료일자 has 79 (100.0%) missing valuesMissing
재개업일자 has 79 (100.0%) missing valuesMissing
소재지전화 has 5 (6.3%) missing valuesMissing
소재지면적 has 79 (100.0%) missing valuesMissing
소재지우편번호 has 38 (48.1%) missing valuesMissing
소재지전체주소 has 6 (7.6%) missing valuesMissing
도로명전체주소 has 4 (5.1%) missing valuesMissing
도로명우편번호 has 14 (17.7%) missing valuesMissing
업태구분명 has 79 (100.0%) missing valuesMissing
좌표정보(X) has 6 (7.6%) missing valuesMissing
좌표정보(Y) has 6 (7.6%) missing valuesMissing
사무소전화번호 has 4 (5.1%) 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 started2023-12-10 20:52:09.483868
Analysis finished2023-12-10 20:52:10.221032
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40
Minimum1
Maximum79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T05:52:10.368849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.9
Q120.5
median40
Q359.5
95-th percentile75.1
Maximum79
Range78
Interquartile range (IQR)39

Descriptive statistics

Standard deviation22.949219
Coefficient of variation (CV)0.57373048
Kurtosis-1.2
Mean40
Median Absolute Deviation (MAD)20
Skewness0
Sum3160
Variance526.66667
MonotonicityStrictly increasing
2023-12-11T05:52:10.656890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
2 1
 
1.3%
59 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
79 1
1.3%
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
계량기증명업
79 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계량기증명업 79
100.0%

Length

2023-12-11T05:52:10.919858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:11.085755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기증명업 79
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
09_28_04_P
79 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_04_P
2nd row09_28_04_P
3rd row09_28_04_P
4th row09_28_04_P
5th row09_28_04_P

Common Values

ValueCountFrequency (%)
09_28_04_P 79
100.0%

Length

2023-12-11T05:52:11.266809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:11.432036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_04_p 79
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3464303.8
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T05:52:11.568525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3420000
5-th percentile3430000
Q13450000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range60000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation18583.391
Coefficient of variation (CV)0.0053642498
Kurtosis-0.31575063
Mean3464303.8
Median Absolute Deviation (MAD)10000
Skewness-0.93889257
Sum2.7368 × 108
Variance3.4534242 × 108
MonotonicityIncreasing
2023-12-11T05:52:11.743196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3480000 35
44.3%
3450000 18
22.8%
3470000 15
19.0%
3430000 7
 
8.9%
3420000 3
 
3.8%
3460000 1
 
1.3%
ValueCountFrequency (%)
3420000 3
 
3.8%
3430000 7
 
8.9%
3450000 18
22.8%
3460000 1
 
1.3%
3470000 15
19.0%
3480000 35
44.3%
ValueCountFrequency (%)
3480000 35
44.3%
3470000 15
19.0%
3460000 1
 
1.3%
3450000 18
22.8%
3430000 7
 
8.9%
3420000 3
 
3.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0026792 × 1018
Minimum1.981345 × 1018
Maximum2.021348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T05:52:11.961580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.981345 × 1018
5-th percentile1.9841475 × 1018
Q11.996347 × 1018
median2.001347 × 1018
Q32.0123465 × 1018
95-th percentile2.0184479 × 1018
Maximum2.021348 × 1018
Range4.0003035 × 1016
Interquartile range (IQR)1.5999518 × 1016

Descriptive statistics

Standard deviation1.0784939 × 1016
Coefficient of variation (CV)0.0053852552
Kurtosis-0.85249989
Mean2.0026792 × 1018
Median Absolute Deviation (MAD)9.0020105 × 1015
Skewness-0.18171587
Sum-7.8090384 × 1018
Variance1.163149 × 1032
MonotonicityNot monotonic
2023-12-11T05:52:12.188867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1990342005806500008 1
 
1.3%
1997342005806500001 1
 
1.3%
2008348028906500002 1
 
1.3%
2006348009506500001 1
 
1.3%
2017348035806500001 1
 
1.3%
2015348032606500004 1
 
1.3%
2002348006906500001 1
 
1.3%
2001348000506500001 1
 
1.3%
2000348000006500004 1
 
1.3%
2000348000006500003 1
 
1.3%
Other values (69) 69
87.3%
ValueCountFrequency (%)
1981345001206500004 1
1.3%
1981345001206500005 1
1.3%
1981345001206500007 1
1.3%
1982343001006500005 1
1.3%
1984348000006500001 1
1.3%
1986343001006500014 1
1.3%
1987345001206500005 1
1.3%
1988343001006500015 1
1.3%
1988345001206500009 1
1.3%
1988348000006500002 1
1.3%
ValueCountFrequency (%)
2021348036506500002 1
1.3%
2020343009506500001 1
1.3%
2019348036506500002 1
1.3%
2019347018106500001 1
1.3%
2018348036506500002 1
1.3%
2018348036506500001 1
1.3%
2017348035806500001 1
1.3%
2017345014906500001 1
1.3%
2015348032606500004 1
1.3%
2015348032606500003 1
1.3%

인허가일자
Date

Distinct71
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum1981-07-01 00:00:00
Maximum2021-09-03 00:00:00
2023-12-11T05:52:12.411622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:52:12.617070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
1
46 
3
33 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 46
58.2%
3 33
41.8%

Length

2023-12-11T05:52:12.814617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:12.972422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 46
58.2%
3 33
41.8%

영업상태명
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
영업/정상
46 
폐업
33 

Length

Max length5
Median length5
Mean length3.7468354
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 46
58.2%
폐업 33
41.8%

Length

2023-12-11T05:52:13.185842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:13.376140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 46
58.2%
폐업 33
41.8%

상세영업상태코드
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
1
44 
3
33 
5
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 44
55.7%
3 33
41.8%
5 2
 
2.5%

Length

2023-12-11T05:52:13.554636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:13.729960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 44
55.7%
3 33
41.8%
5 2
 
2.5%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size764.0 B
영업중
44 
폐업
33 
<NA>
 
2

Length

Max length4
Median length3
Mean length2.6075949
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 44
55.7%
폐업 33
41.8%
<NA> 2
 
2.5%

Length

2023-12-11T05:52:13.933036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:14.202915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 44
55.7%
폐업 33
41.8%
na 2
 
2.5%

폐업일자
Date

MISSING 

Distinct22
Distinct (%)88.0%
Missing54
Missing (%)68.4%
Memory size764.0 B
Minimum1998-01-05 00:00:00
Maximum2020-11-23 00:00:00
2023-12-11T05:52:14.348483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:52:14.552168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

소재지전화
Text

MISSING 

Distinct70
Distinct (%)94.6%
Missing5
Missing (%)6.3%
Memory size764.0 B
2023-12-11T05:52:14.939064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.189189
Min length7

Characters and Unicode

Total characters828
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)89.2%

Sample

1st row053 962 8989
2nd row053 981 6767
3rd row053 963 0689
4th row0535920602
5th row0533593996
ValueCountFrequency (%)
053 45
26.2%
053585 6
 
3.5%
615 4
 
2.3%
357 3
 
1.7%
053615 3
 
1.7%
581 3
 
1.7%
591 3
 
1.7%
582 2
 
1.2%
585 2
 
1.2%
592 2
 
1.2%
Other values (94) 99
57.6%
2023-12-11T05:52:15.650839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 164
19.8%
3 128
15.5%
0 122
14.7%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
5.0%
7 37
 
4.5%
Other values (2) 32
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 723
87.3%
Space Separator 101
 
12.2%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 164
22.7%
3 128
17.7%
0 122
16.9%
8 55
 
7.6%
1 52
 
7.2%
6 49
 
6.8%
2 47
 
6.5%
9 41
 
5.7%
7 37
 
5.1%
4 28
 
3.9%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 164
19.8%
3 128
15.5%
0 122
14.7%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
5.0%
7 37
 
4.5%
Other values (2) 32
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 164
19.8%
3 128
15.5%
0 122
14.7%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
5.0%
7 37
 
4.5%
Other values (2) 32
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

소재지우편번호
Text

MISSING 

Distinct32
Distinct (%)78.0%
Missing38
Missing (%)48.1%
Memory size764.0 B
2023-12-11T05:52:15.949874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters287
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

Unique25 ?
Unique (%)61.0%

Sample

1st row703-834
2nd row702-800
3rd row702-030
4th row702-872
5th row702-865
ValueCountFrequency (%)
711-813 3
 
7.3%
711-823 3
 
7.3%
702-814 2
 
4.9%
704-330 2
 
4.9%
702-815 2
 
4.9%
704-320 2
 
4.9%
702-030 2
 
4.9%
702-800 1
 
2.4%
702-872 1
 
2.4%
711-857 1
 
2.4%
Other values (22) 22
53.7%
2023-12-11T05:52:16.417461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 50
17.4%
1 46
16.0%
7 44
15.3%
- 41
14.3%
8 27
9.4%
2 27
9.4%
3 20
 
7.0%
4 17
 
5.9%
5 8
 
2.8%
6 4
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 246
85.7%
Dash Punctuation 41
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
20.3%
1 46
18.7%
7 44
17.9%
8 27
11.0%
2 27
11.0%
3 20
 
8.1%
4 17
 
6.9%
5 8
 
3.3%
6 4
 
1.6%
9 3
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 287
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 50
17.4%
1 46
16.0%
7 44
15.3%
- 41
14.3%
8 27
9.4%
2 27
9.4%
3 20
 
7.0%
4 17
 
5.9%
5 8
 
2.8%
6 4
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 287
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 50
17.4%
1 46
16.0%
7 44
15.3%
- 41
14.3%
8 27
9.4%
2 27
9.4%
3 20
 
7.0%
4 17
 
5.9%
5 8
 
2.8%
6 4
 
1.4%

소재지전체주소
Text

MISSING 

Distinct67
Distinct (%)91.8%
Missing6
Missing (%)7.6%
Memory size764.0 B
2023-12-11T05:52:16.907389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length27
Mean length22.972603
Min length16

Characters and Unicode

Total characters1677
Distinct characters89
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)83.6%

Sample

1st row대구광역시 동구 신서동 139번지 1호
2nd row대구광역시 동구 검사동 960번지 25 호
3rd row대구광역시 동구 동호동 207번지 1 호
4th row대구광역시 서구 이현동 268번지 3호
5th row대구광역시 서구 평리동 595-23
ValueCountFrequency (%)
대구광역시 73
 
19.9%
달성군 31
 
8.5%
북구 17
 
4.6%
달서구 14
 
3.8%
다사읍 9
 
2.5%
논공읍 8
 
2.2%
서재리 7
 
1.9%
서구 7
 
1.9%
노원동3가 7
 
1.9%
하빈면 7
 
1.9%
Other values (136) 186
50.8%
2023-12-11T05:52:17.996733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
297
17.7%
구 118
 
7.0%
대 77
 
4.6%
역 74
 
4.4%
광 73
 
4.4%
시 73
 
4.4%
지 71
 
4.2%
번 68
 
4.1%
1 60
 
3.6%
동 47
 
2.8%
Other values (79) 719
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1050
62.6%
Decimal Number 315
 
18.8%
Space Separator 297
 
17.7%
Dash Punctuation 13
 
0.8%
Other Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 118
 
11.2%
대 77
 
7.3%
역 74
 
7.0%
광 73
 
7.0%
시 73
 
7.0%
지 71
 
6.8%
번 68
 
6.5%
동 47
 
4.5%
달 45
 
4.3%
리 39
 
3.7%
Other values (65) 365
34.8%
Decimal Number
ValueCountFrequency (%)
1 60
19.0%
2 41
13.0%
3 39
12.4%
8 31
9.8%
5 30
9.5%
6 28
8.9%
0 24
 
7.6%
7 23
 
7.3%
4 23
 
7.3%
9 16
 
5.1%
Space Separator
ValueCountFrequency (%)
297
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1051
62.7%
Common 626
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 118
 
11.2%
대 77
 
7.3%
역 74
 
7.0%
광 73
 
6.9%
시 73
 
6.9%
지 71
 
6.8%
번 68
 
6.5%
동 47
 
4.5%
달 45
 
4.3%
리 39
 
3.7%
Other values (66) 366
34.8%
Common
ValueCountFrequency (%)
297
47.4%
1 60
 
9.6%
2 41
 
6.5%
3 39
 
6.2%
8 31
 
5.0%
5 30
 
4.8%
6 28
 
4.5%
0 24
 
3.8%
7 23
 
3.7%
4 23
 
3.7%
Other values (3) 30
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1050
62.6%
ASCII 626
37.3%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
297
47.4%
1 60
 
9.6%
2 41
 
6.5%
3 39
 
6.2%
8 31
 
5.0%
5 30
 
4.8%
6 28
 
4.5%
0 24
 
3.8%
7 23
 
3.7%
4 23
 
3.7%
Other values (3) 30
 
4.8%
Hangul
ValueCountFrequency (%)
구 118
 
11.2%
대 77
 
7.3%
역 74
 
7.0%
광 73
 
7.0%
시 73
 
7.0%
지 71
 
6.8%
번 68
 
6.5%
동 47
 
4.5%
달 45
 
4.3%
리 39
 
3.7%
Other values (65) 365
34.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명전체주소
Text

MISSING 

Distinct68
Distinct (%)90.7%
Missing4
Missing (%)5.1%
Memory size764.0 B
2023-12-11T05:52:18.490936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length30
Mean length24.146667
Min length20

Characters and Unicode

Total characters1811
Distinct characters113
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)81.3%

Sample

1st row대구광역시 동구 해동로 237 (검사동)
2nd row대구광역시 동구 안심로 267 (동호동)
3rd row대구광역시 서구 북비산로13길 1 (이현동)
4th row대구광역시 서구 북비산로 121 (평리동)
5th row대구광역시 서구 염색공단천로1길 37 (비산동)
ValueCountFrequency (%)
대구광역시 75
 
19.7%
달성군 34
 
8.9%
북구 16
 
4.2%
달서구 15
 
3.9%
하빈면 10
 
2.6%
논공읍 9
 
2.4%
다사읍 9
 
2.4%
서구 7
 
1.8%
노원동3가 6
 
1.6%
하빈남로 4
 
1.1%
Other values (153) 195
51.3%
2023-12-11T05:52:19.127059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
306
 
16.9%
구 122
 
6.7%
대 81
 
4.5%
역 76
 
4.2%
광 75
 
4.1%
시 75
 
4.1%
1 69
 
3.8%
로 67
 
3.7%
달 54
 
3.0%
동 51
 
2.8%
Other values (103) 835
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1139
62.9%
Space Separator 306
 
16.9%
Decimal Number 269
 
14.9%
Open Punctuation 41
 
2.3%
Close Punctuation 41
 
2.3%
Dash Punctuation 10
 
0.6%
Other Punctuation 4
 
0.2%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 122
 
10.7%
대 81
 
7.1%
역 76
 
6.7%
광 75
 
6.6%
시 75
 
6.6%
로 67
 
5.9%
달 54
 
4.7%
동 51
 
4.5%
성 48
 
4.2%
서 40
 
3.5%
Other values (87) 450
39.5%
Decimal Number
ValueCountFrequency (%)
1 69
25.7%
2 48
17.8%
3 31
11.5%
6 22
 
8.2%
4 18
 
6.7%
5 18
 
6.7%
7 17
 
6.3%
8 17
 
6.3%
0 16
 
5.9%
9 13
 
4.8%
Space Separator
ValueCountFrequency (%)
306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1140
62.9%
Common 671
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 122
 
10.7%
대 81
 
7.1%
역 76
 
6.7%
광 75
 
6.6%
시 75
 
6.6%
로 67
 
5.9%
달 54
 
4.7%
동 51
 
4.5%
성 48
 
4.2%
서 40
 
3.5%
Other values (88) 451
39.6%
Common
ValueCountFrequency (%)
306
45.6%
1 69
 
10.3%
2 48
 
7.2%
( 41
 
6.1%
) 41
 
6.1%
3 31
 
4.6%
6 22
 
3.3%
4 18
 
2.7%
5 18
 
2.7%
7 17
 
2.5%
Other values (5) 60
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1139
62.9%
ASCII 671
37.1%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306
45.6%
1 69
 
10.3%
2 48
 
7.2%
( 41
 
6.1%
) 41
 
6.1%
3 31
 
4.6%
6 22
 
3.3%
4 18
 
2.7%
5 18
 
2.7%
7 17
 
2.5%
Other values (5) 60
 
8.9%
Hangul
ValueCountFrequency (%)
구 122
 
10.7%
대 81
 
7.1%
역 76
 
6.7%
광 75
 
6.6%
시 75
 
6.6%
로 67
 
5.9%
달 54
 
4.7%
동 51
 
4.5%
성 48
 
4.2%
서 40
 
3.5%
Other values (87) 450
39.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct39
Distinct (%)60.0%
Missing14
Missing (%)17.7%
Memory size764.0 B
2023-12-11T05:52:19.432210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.6
Min length5

Characters and Unicode

Total characters429
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

Unique25 ?
Unique (%)38.5%

Sample

1st row41748
2nd row41748
3rd row703-833
4th row41748
5th row703-834
ValueCountFrequency (%)
711-813 7
 
10.8%
711-854 4
 
6.2%
711-823 4
 
6.2%
42905 3
 
4.6%
41748 3
 
4.6%
704-401 3
 
4.6%
711-820 2
 
3.1%
702-083 2
 
3.1%
711-814 2
 
3.1%
711-851 2
 
3.1%
Other values (29) 33
50.8%
2023-12-11T05:52:19.958738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 76
17.7%
0 69
16.1%
7 59
13.8%
- 52
12.1%
8 42
9.8%
4 42
9.8%
2 31
7.2%
3 29
 
6.8%
5 15
 
3.5%
9 9
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 377
87.9%
Dash Punctuation 52
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 76
20.2%
0 69
18.3%
7 59
15.6%
8 42
11.1%
4 42
11.1%
2 31
8.2%
3 29
 
7.7%
5 15
 
4.0%
9 9
 
2.4%
6 5
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 429
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 76
17.7%
0 69
16.1%
7 59
13.8%
- 52
12.1%
8 42
9.8%
4 42
9.8%
2 31
7.2%
3 29
 
6.8%
5 15
 
3.5%
9 9
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 429
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 76
17.7%
0 69
16.1%
7 59
13.8%
- 52
12.1%
8 42
9.8%
4 42
9.8%
2 31
7.2%
3 29
 
6.8%
5 15
 
3.5%
9 9
 
2.1%

사업장명
Text

Distinct69
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size764.0 B
2023-12-11T05:52:20.281375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.5443038
Min length2

Characters and Unicode

Total characters596
Distinct characters113
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)77.2%

Sample

1st row우성계량증명업소
2nd row원호계량증명업소
3rd row성림계량사
4th row(주)경원스틸
5th row(주)와이케이철강
ValueCountFrequency (%)
달성계량증명업소 3
 
3.6%
공단계량증명업소 3
 
3.6%
대지상사 2
 
2.4%
우진계량증명업소 2
 
2.4%
주)경원스틸 2
 
2.4%
공단산업계량증명업소 2
 
2.4%
쌍용계량증명업소 2
 
2.4%
서재계량증명업소 2
 
2.4%
솔례 1
 
1.2%
달서계량증명업소 1
 
1.2%
Other values (63) 63
75.9%
2023-12-11T05:52:20.857934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 51
 
8.6%
량 51
 
8.6%
업 47
 
7.9%
소 47
 
7.9%
증 43
 
7.2%
명 43
 
7.2%
대 18
 
3.0%
주 17
 
2.9%
( 15
 
2.5%
) 15
 
2.5%
Other values (103) 249
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 560
94.0%
Open Punctuation 15
 
2.5%
Close Punctuation 15
 
2.5%
Space Separator 4
 
0.7%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 51
 
9.1%
량 51
 
9.1%
업 47
 
8.4%
소 47
 
8.4%
증 43
 
7.7%
명 43
 
7.7%
대 18
 
3.2%
주 17
 
3.0%
성 14
 
2.5%
공 14
 
2.5%
Other values (98) 215
38.4%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
94.0%
Common 36
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 51
 
9.1%
량 51
 
9.1%
업 47
 
8.4%
소 47
 
8.4%
증 43
 
7.7%
명 43
 
7.7%
대 18
 
3.2%
주 17
 
3.0%
성 14
 
2.5%
공 14
 
2.5%
Other values (98) 215
38.4%
Common
ValueCountFrequency (%)
( 15
41.7%
) 15
41.7%
4
 
11.1%
5 1
 
2.8%
2 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 560
94.0%
ASCII 36
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 51
 
9.1%
량 51
 
9.1%
업 47
 
8.4%
소 47
 
8.4%
증 43
 
7.7%
명 43
 
7.7%
대 18
 
3.2%
주 17
 
3.0%
성 14
 
2.5%
공 14
 
2.5%
Other values (98) 215
38.4%
ASCII
ValueCountFrequency (%)
( 15
41.7%
) 15
41.7%
4
 
11.1%
5 1
 
2.8%
2 1
 
2.8%

최종수정시점
Date

UNIQUE 

Distinct79
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size764.0 B
Minimum2008-08-27 17:57:34
Maximum2023-06-28 16:19:10
2023-12-11T05:52:21.090307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:52:21.359253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
I
69 
U
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 69
87.3%
U 10
 
12.7%

Length

2023-12-11T05:52:21.590123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:21.732146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 69
87.3%
u 10
 
12.7%

데이터갱신일자
Categorical

IMBALANCE 

Distinct17
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size764.0 B
2018-08-31 23:59:59
63 
2023-04-09 00:20:21
 
1
2020-10-14 00:23:10
 
1
2023-06-01 00:19:36
 
1
2023-06-02 02:40:00
 
1
Other values (12)
12 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique16 ?
Unique (%)20.3%

Sample

1st row2018-08-31 23:59:59
2nd row2018-08-31 23:59:59
3rd row2018-08-31 23:59:59
4th row2023-04-09 00:20:21
5th row2020-10-14 00:23:10

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59 63
79.7%
2023-04-09 00:20:21 1
 
1.3%
2020-10-14 00:23:10 1
 
1.3%
2023-06-01 00:19:36 1
 
1.3%
2023-06-02 02:40:00 1
 
1.3%
2023-06-30 02:40:00 1
 
1.3%
2020-09-04 02:40:00 1
 
1.3%
2020-08-30 02:40:00 1
 
1.3%
2019-07-04 02:21:28 1
 
1.3%
2020-04-22 02:40:00 1
 
1.3%
Other values (7) 7
 
8.9%

Length

2023-12-11T05:52:21.882686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 63
39.9%
23:59:59 63
39.9%
02:40:00 10
 
6.3%
02:21:28 1
 
0.6%
2020-11-28 1
 
0.6%
02:37:38 1
 
0.6%
2018-10-19 1
 
0.6%
00:22:49 1
 
0.6%
2021-09-05 1
 
0.6%
2021-02-27 1
 
0.6%
Other values (15) 15
 
9.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing79
Missing (%)100.0%
Memory size843.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)89.0%
Missing6
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean335639.79
Minimum326192.2
Maximum354741.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T05:52:22.057884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326192.2
5-th percentile326550.63
Q1330684.95
median334984.95
Q3339585.28
95-th percentile345984.35
Maximum354741.9
Range28549.703
Interquartile range (IQR)8900.3297

Descriptive statistics

Standard deviation6370.0841
Coefficient of variation (CV)0.01897893
Kurtosis-0.13346501
Mean335639.79
Median Absolute Deviation (MAD)4600.3315
Skewness0.44658914
Sum24501705
Variance40577972
MonotonicityNot monotonic
2023-12-11T05:52:22.295308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330899.370928245 2
 
2.5%
339081.538017673 2
 
2.5%
331770.735791307 2
 
2.5%
334902.493029553 2
 
2.5%
335126.439534623 2
 
2.5%
326987.047868799 2
 
2.5%
334282.929798618 2
 
2.5%
334984.946983459 2
 
2.5%
327205.850311946 1
 
1.3%
329396.040634373 1
 
1.3%
Other values (55) 55
69.6%
(Missing) 6
 
7.6%
ValueCountFrequency (%)
326192.201539851 1
1.3%
326246.351761417 1
1.3%
326320.135400382 1
1.3%
326341.93301276 1
1.3%
326689.760538056 1
1.3%
326773.449629962 1
1.3%
326987.047868799 2
2.5%
327205.850311946 1
1.3%
327554.749825424 1
1.3%
328137.029305625 1
1.3%
ValueCountFrequency (%)
354741.904563206 1
1.3%
349314.087253478 1
1.3%
346234.566096387 1
1.3%
346052.168115926 1
1.3%
345939.142242153 1
1.3%
345665.162766102 1
1.3%
345582.9741724 1
1.3%
344144.597124313 1
1.3%
343011.774837308 1
1.3%
342937.580405421 1
1.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)89.0%
Missing6
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean261040.33
Minimum238774.71
Maximum271647.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size843.0 B
2023-12-11T05:52:22.524216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238774.71
5-th percentile241668.21
Q1260298.54
median264106.22
Q3265862.77
95-th percentile268920.67
Maximum271647.09
Range32872.386
Interquartile range (IQR)5564.228

Descriptive statistics

Standard deviation7920.4846
Coefficient of variation (CV)0.030341996
Kurtosis1.4600867
Mean261040.33
Median Absolute Deviation (MAD)3060.8102
Skewness-1.470464
Sum19055944
Variance62734076
MonotonicityNot monotonic
2023-12-11T05:52:22.740566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
248772.305647284 2
 
2.5%
265466.000238272 2
 
2.5%
255218.275232768 2
 
2.5%
264106.215422125 2
 
2.5%
264967.82183764 2
 
2.5%
263346.437143099 2
 
2.5%
264796.577876753 2
 
2.5%
260340.178400042 2
 
2.5%
265862.767001177 1
 
1.3%
253584.756458479 1
 
1.3%
Other values (55) 55
69.6%
(Missing) 6
 
7.6%
ValueCountFrequency (%)
238774.707824281 1
1.3%
238818.550604093 1
1.3%
239224.138323023 1
1.3%
241657.908856086 1
1.3%
241675.077662344 1
1.3%
248302.414416179 1
1.3%
248517.038826751 1
1.3%
248586.503507737 1
1.3%
248772.305647284 2
2.5%
250680.643647057 1
1.3%
ValueCountFrequency (%)
271647.094222276 1
1.3%
269620.252518927 1
1.3%
269598.747901672 1
1.3%
269040.161615502 1
1.3%
268841.001354367 1
1.3%
268692.111156641 1
1.3%
268116.208501133 1
1.3%
267902.207813641 1
1.3%
267761.787840802 1
1.3%
267599.197678964 1
1.3%

사무소전화번호
Text

MISSING 

Distinct71
Distinct (%)94.7%
Missing4
Missing (%)5.1%
Memory size764.0 B
2023-12-11T05:52:23.098348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.053333
Min length1

Characters and Unicode

Total characters829
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)89.3%

Sample

1st row053 962 8989
2nd row053 981 6767
3rd row053 963 0689
4th row0535920602
5th row0533593996
ValueCountFrequency (%)
053 45
26.0%
053585 6
 
3.5%
615 4
 
2.3%
591 3
 
1.7%
053615 3
 
1.7%
581 3
 
1.7%
357 3
 
1.7%
0535920602 2
 
1.2%
3777 2
 
1.2%
592 2
 
1.2%
Other values (95) 100
57.8%
2023-12-11T05:52:23.586259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 164
19.8%
3 128
15.4%
0 123
14.8%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
4.9%
7 37
 
4.5%
Other values (2) 32
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 724
87.3%
Space Separator 101
 
12.2%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 164
22.7%
3 128
17.7%
0 123
17.0%
8 55
 
7.6%
1 52
 
7.2%
6 49
 
6.8%
2 47
 
6.5%
9 41
 
5.7%
7 37
 
5.1%
4 28
 
3.9%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 829
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 164
19.8%
3 128
15.4%
0 123
14.8%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
4.9%
7 37
 
4.5%
Other values (2) 32
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 829
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 164
19.8%
3 128
15.4%
0 123
14.8%
101
12.2%
8 55
 
6.6%
1 52
 
6.3%
6 49
 
5.9%
2 47
 
5.7%
9 41
 
4.9%
7 37
 
4.5%
Other values (2) 32
 
3.9%

사업장전화번호
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size764.0 B
<NA>
76 
533814115
 
1
533593382
 
1
535923771
 
1

Length

Max length9
Median length4
Mean length4.1898734
Min length4

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 76
96.2%
533814115 1
 
1.3%
533593382 1
 
1.3%
535923771 1
 
1.3%

Length

2023-12-11T05:52:23.785372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:52:23.933646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 76
96.2%
533814115 1
 
1.3%
533593382 1
 
1.3%
535923771 1
 
1.3%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
01계량기증명업09_28_04_P342000019903420058065000081990-05-11<NA>3폐업3폐업2008-12-23<NA><NA><NA>053 962 8989<NA><NA>대구광역시 동구 신서동 139번지 1호<NA><NA>우성계량증명업소2009-02-04 08:42:25I2018-08-31 23:59:59<NA><NA><NA>053 962 8989<NA>
12계량기증명업09_28_04_P342000019973420058065000011997-06-12<NA>3폐업3폐업<NA><NA><NA><NA>053 981 6767<NA><NA>대구광역시 동구 검사동 960번지 25 호대구광역시 동구 해동로 237 (검사동)<NA>원호계량증명업소2010-08-13 10:30:43I2018-08-31 23:59:59<NA>349314.087253266191.555896053 981 6767<NA>
23계량기증명업09_28_04_P342000019953420058065000011995-10-28<NA>3폐업3폐업<NA><NA><NA><NA>053 963 0689<NA><NA>대구광역시 동구 동호동 207번지 1 호대구광역시 동구 안심로 267 (동호동)<NA>성림계량사2010-08-13 10:31:27I2018-08-31 23:59:59<NA>354741.904563264283.362303053 963 0689<NA>
34계량기증명업09_28_04_P343000020153430095065000022015-11-12<NA>1영업/정상1영업중<NA><NA><NA><NA>0535920602<NA><NA>대구광역시 서구 이현동 268번지 3호대구광역시 서구 북비산로13길 1 (이현동)41748(주)경원스틸2023-04-07 10:04:00I2023-04-09 00:20:21<NA>339081.538018265466.0002380535920602<NA>
45계량기증명업09_28_04_P343000020203430095065000012020-10-12<NA>1영업/정상1영업중<NA><NA><NA><NA>0533593996<NA><NA>대구광역시 서구 평리동 595-23대구광역시 서구 북비산로 121 (평리동)41748(주)와이케이철강2020-10-12 16:10:13I2020-10-14 00:23:10<NA>339553.416133265409.317990533593996<NA>
56계량기증명업09_28_04_P343000019823430010065000051982-11-04<NA>1영업/정상1영업중<NA><NA><NA><NA>053 3583917<NA><NA>대구광역시 서구 비산동 1678번지대구광역시 서구 염색공단천로1길 37 (비산동)<NA>북부계량증명업소2018-06-20 15:59:36I2018-08-31 23:59:59<NA>340310.091298266545.42264053 3583917<NA>
67계량기증명업09_28_04_P343000019863430010065000141986-08-05<NA>1영업/정상1영업중<NA><NA><NA><NA>053 565 0222<NA><NA>대구광역시 서구 중리동 1120-1번지대구광역시 서구 와룡로 346 (중리동)703-833화성계량증명업소2018-06-20 15:59:02I2018-08-31 23:59:59<NA>338844.987977263632.895918053 565 0222<NA>
78계량기증명업09_28_04_P343000020153430095065000012015-11-11<NA>1영업/정상1영업중<NA><NA><NA><NA>0535920602<NA><NA>대구광역시 서구 이현동 268번지 3호대구광역시 서구 북비산로13길 1 (이현동)41748(주)경원스틸2018-06-19 13:32:04I2018-08-31 23:59:59<NA>339081.538018265466.0002380535920602<NA>
89계량기증명업09_28_04_P343000019883430010065000151988-12-13<NA>3폐업3폐업2015-01-28<NA><NA><NA>053 553 1199<NA>703-834대구광역시 서구 평리6동 595번지 9호대구광역시 서구 북비산로 115 (평리동)703-834대기계량증명업소2015-01-28 17:46:01I2018-08-31 23:59:59<NA>339508.148441265406.81051053 553 1199<NA>
910계량기증명업09_28_04_P343000019973430010065000161997-03-22<NA>3폐업3폐업2013-08-26<NA><NA><NA>053 567 4770<NA><NA>대구광역시 서구 중리동 1051-5대구광역시 서구 와룡로 355 (중리동)703-833신광계량증명업소2013-08-26 17:55:04I2018-08-31 23:59:59<NA>338776.058115263779.298649053 567 4770<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
6970계량기증명업09_28_04_P348000019883480000065000031988-06-28<NA>3폐업3폐업<NA><NA><NA><NA>053615 3777<NA><NA>대구광역시 달성군 논공읍 북리 803-245번지대구광역시 달성군 논공읍 논공로 724711-854공단산업계량증명업소2011-10-31 14:43:31I2018-08-31 23:59:59<NA>330899.370928248772.305647053615 3777<NA>
7071계량기증명업09_28_04_P348000019883480000065000041988-12-29<NA>3폐업3폐업<NA><NA><NA><NA>053614 5196<NA><NA>대구광역시 달성군 옥포면 본리리 2214-1번지대구광역시 달성군 논공읍 비슬로 2165711-854옥포계량증명업소2011-10-31 14:42:22I2018-08-31 23:59:59<NA>331770.735791255218.275233053614 5196<NA>
7172계량기증명업09_28_04_P348000020153480326065000022015-06-24<NA>3폐업3폐업2020-11-23<NA><NA><NA><NA><NA>711-823대구광역시 달성군 하빈면 봉촌리 652번지대구광역시 달성군 하빈면 하빈남로 305711-823현대공인계량증명업소2020-11-26 16:00:34U2020-11-28 02:40:00<NA>326689.760538263137.319532<NA><NA>
7273계량기증명업09_28_04_P348000020003480000065000051995-01-27<NA>3폐업3폐업2011-08-02<NA><NA><NA>053585 1212<NA><NA>대구광역시 달성군 다사읍 서재리 91번지대구광역시 달성군 다사읍 서재로 137711-813서재계량증명업소2011-10-31 14:20:21I2018-08-31 23:59:59<NA>335126.439535264967.821838053585 1212<NA>
7374계량기증명업09_28_04_P348000020003480000065000061996-02-02<NA>3폐업3폐업<NA><NA><NA><NA>053585 2527<NA><NA>대구광역시 달성군 다사읍 서재리 181번지대구광역시 달성군 다사읍 서재로12길 26711-813우진계량증명업소2011-10-31 14:18:51I2018-08-31 23:59:59<NA>334902.49303264106.215422053585 2527<NA>
7475계량기증명업09_28_04_P348000020003480000065000081998-05-27<NA>3폐업3폐업2011-06-30<NA><NA><NA>053585 8544<NA>711-813대구광역시 달성군 다사읍 서재리 743번지대구광역시 달성군 다사읍 서재본길 94711-813형제계량증명업소2018-07-04 09:04:55I2018-08-31 23:59:59<NA>334282.929799264796.577877053585 8544<NA>
7576계량기증명업09_28_04_P348000020023480069065000022002-11-09<NA>3폐업3폐업<NA><NA><NA><NA>053585 7207<NA><NA>대구광역시 달성군 다사읍 세천리 184번지대구광역시 달성군 다사읍 세천북로10길 19-1711-814대구재생계량사2011-10-31 14:02:22I2018-08-31 23:59:59<NA>333299.052085265405.862217053585 7207<NA>
7677계량기증명업09_28_04_P348000020073480289065200612006-01-10<NA>3폐업3폐업<NA><NA><NA><NA>0535845933<NA>711-823대구광역시 달성군 하빈면 봉촌리 54번지대구광역시 달성군 하빈면 하빈남로 268711-823대지상사2011-10-31 13:59:43I2018-08-31 23:59:59<NA>326987.047869263346.4371430535845933<NA>
7778계량기증명업09_28_04_P348000020103480291065000032010-11-18<NA>3폐업3폐업2014-01-14<NA><NA><NA>005305830391<NA>711-821대구광역시 달성군 하빈면 묘리 1023번지 3호대구광역시 달성군 하빈면 묘동1길 48711-820(주)비엔에이코리아2016-04-28 13:31:42I2018-08-31 23:59:59<NA>328137.029306266712.314053005305830391<NA>
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