Overview

Dataset statistics

Number of variables30
Number of observations75
Missing cells574
Missing cells (%)25.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.1 KiB
Average record size in memory260.8 B

Variable types

Numeric10
Categorical9
Unsupported6
Text5

Dataset

Description6270000_대구광역시_09_28_04_P_계량기증명업_3월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000084749&dataSetDetailId=DDI_0000084815&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
데이터갱신구분 is highly imbalanced (82.3%)Imbalance
데이터갱신일자 is highly imbalanced (82.5%)Imbalance
사업장전화번호 is highly imbalanced (87.1%)Imbalance
인허가취소일자 has 75 (100.0%) missing valuesMissing
폐업일자 has 52 (69.3%) missing valuesMissing
휴업시작일자 has 75 (100.0%) missing valuesMissing
휴업종료일자 has 75 (100.0%) missing valuesMissing
재개업일자 has 75 (100.0%) missing valuesMissing
소재지전화 has 4 (5.3%) missing valuesMissing
소재지면적 has 75 (100.0%) missing valuesMissing
소재지우편번호 has 35 (46.7%) missing valuesMissing
소재지전체주소 has 7 (9.3%) missing valuesMissing
도로명전체주소 has 4 (5.3%) missing valuesMissing
도로명우편번호 has 14 (18.7%) missing valuesMissing
업태구분명 has 75 (100.0%) missing valuesMissing
좌표정보(X) has 4 (5.3%) missing valuesMissing
좌표정보(Y) has 4 (5.3%) 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 18:21:27.591166
Analysis finished2023-12-10 18:21:28.232016
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38
Minimum1
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:28.335358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.7
Q119.5
median38
Q356.5
95-th percentile71.3
Maximum75
Range74
Interquartile range (IQR)37

Descriptive statistics

Standard deviation21.794495
Coefficient of variation (CV)0.57353933
Kurtosis-1.2
Mean38
Median Absolute Deviation (MAD)19
Skewness0
Sum2850
Variance475
MonotonicityStrictly increasing
2023-12-11T03:21:28.572765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
49 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
50 1
 
1.3%
48 1
 
1.3%
Other values (65) 65
86.7%
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 (%)
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%
67 1
1.3%
66 1
1.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
계량기증명업
75 

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 75
100.0%

Length

2023-12-11T03:21:28.812057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:28.968307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기증명업 75
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size732.0 B
09_28_04_P
75 

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 75
100.0%

Length

2023-12-11T03:21:29.143247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:29.318455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_04_p 75
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3465200
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:29.472619image/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 deviation18036
Coefficient of variation (CV)0.0052048944
Kurtosis0.024522129
Mean3465200
Median Absolute Deviation (MAD)10000
Skewness-1.0484728
Sum2.5989 × 108
Variance3.252973 × 108
MonotonicityIncreasing
2023-12-11T03:21:29.653193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3480000 34
45.3%
3450000 17
22.7%
3470000 15
20.0%
3430000 5
 
6.7%
3420000 3
 
4.0%
3460000 1
 
1.3%
ValueCountFrequency (%)
3420000 3
 
4.0%
3430000 5
 
6.7%
3450000 17
22.7%
3460000 1
 
1.3%
3470000 15
20.0%
3480000 34
45.3%
ValueCountFrequency (%)
3480000 34
45.3%
3470000 15
20.0%
3460000 1
 
1.3%
3450000 17
22.7%
3430000 5
 
6.7%
3420000 3
 
4.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0019732 × 1018
Minimum1.981345 × 1018
Maximum2.019348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:29.891161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.981345 × 1018
5-th percentile1.9837465 × 1018
Q11.995847 × 1018
median2.000348 × 1018
Q32.011845 × 1018
95-th percentile2.017648 × 1018
Maximum2.019348 × 1018
Range3.8003035 × 1016
Interquartile range (IQR)1.5998007 × 1016

Descriptive statistics

Standard deviation1.052579 × 1016
Coefficient of variation (CV)0.0052577078
Kurtosis-0.85046614
Mean2.0019732 × 1018
Median Absolute Deviation (MAD)1.0000029 × 1016
Skewness-0.16726066
Sum2.5740372 × 1018
Variance1.1079226 × 1032
MonotonicityNot monotonic
2023-12-11T03:21:30.173371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1990342005806500008 1
 
1.3%
2006348009506500001 1
 
1.3%
1998348000006500008 1
 
1.3%
2000348000006500003 1
 
1.3%
2000348000006500004 1
 
1.3%
2001348000506500001 1
 
1.3%
2002348006906500001 1
 
1.3%
2015348032606500004 1
 
1.3%
2017348035806500001 1
 
1.3%
2008348028906500002 1
 
1.3%
Other values (65) 65
86.7%
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 (%)
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%
2015348032606500002 1
1.3%
2015348032606500001 1
1.3%

인허가일자
Real number (ℝ)

Distinct67
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20007503
Minimum19810701
Maximum20191111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:30.467249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19810701
5-th percentile19835113
Q119930820
median19990406
Q320115668
95-th percentile20173816
Maximum20191111
Range380410
Interquartile range (IQR)184848

Descriptive statistics

Standard deviation109928
Coefficient of variation (CV)0.0054943388
Kurtosis-1.1326625
Mean20007503
Median Absolute Deviation (MAD)109177
Skewness0.019433936
Sum1.5005627 × 109
Variance1.2084166 × 1010
MonotonicityNot monotonic
2023-12-11T03:21:30.765744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19810701 3
 
4.0%
19980527 2
 
2.7%
19880628 2
 
2.7%
19960202 2
 
2.7%
19881229 2
 
2.7%
20010219 2
 
2.7%
19950127 2
 
2.7%
20180803 1
 
1.3%
20181017 1
 
1.3%
20120320 1
 
1.3%
Other values (57) 57
76.0%
ValueCountFrequency (%)
19810701 3
4.0%
19821104 1
 
1.3%
19841117 1
 
1.3%
19860805 1
 
1.3%
19871119 1
 
1.3%
19871230 1
 
1.3%
19880402 1
 
1.3%
19880429 1
 
1.3%
19880628 2
2.7%
19881213 1
 
1.3%
ValueCountFrequency (%)
20191111 1
1.3%
20190701 1
1.3%
20181017 1
1.3%
20180803 1
1.3%
20170822 1
1.3%
20170612 1
1.3%
20151123 1
1.3%
20151111 1
1.3%
20150819 1
1.3%
20150624 1
1.3%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
1
44 
3
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 44
58.7%
3 31
41.3%

Length

2023-12-11T03:21:30.988158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:31.150863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 44
58.7%
3 31
41.3%

영업상태명
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
영업/정상
44 
폐업
31 

Length

Max length5
Median length5
Mean length3.76
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 44
58.7%
폐업 31
41.3%

Length

2023-12-11T03:21:31.356319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:31.549057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 44
58.7%
폐업 31
41.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
1
44 
3
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 44
58.7%
3 31
41.3%

Length

2023-12-11T03:21:31.740213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:31.927347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 44
58.7%
3 31
41.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
영업중
44 
폐업
31 

Length

Max length3
Median length3
Mean length2.5866667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 44
58.7%
폐업 31
41.3%

Length

2023-12-11T03:21:32.114671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:32.293347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 44
58.7%
폐업 31
41.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)87.0%
Missing52
Missing (%)69.3%
Infinite0
Infinite (%)0.0%
Mean20097164
Minimum19980105
Maximum20180509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:32.479083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980105
5-th percentile19991651
Q120075722
median20110802
Q320135470
95-th percentile20170090
Maximum20180509
Range200404
Interquartile range (IQR)59747

Descriptive statistics

Standard deviation56108.796
Coefficient of variation (CV)0.0027918763
Kurtosis-0.14019014
Mean20097164
Median Absolute Deviation (MAD)29579
Skewness-0.72527351
Sum4.6223477 × 108
Variance3.148197 × 109
MonotonicityNot monotonic
2023-12-11T03:21:32.725759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20090622 2
 
2.7%
20110802 2
 
2.7%
20081223 2
 
2.7%
20060320 1
 
1.3%
19980105 1
 
1.3%
20150128 1
 
1.3%
20110630 1
 
1.3%
20140114 1
 
1.3%
20160927 1
 
1.3%
20171108 1
 
1.3%
Other values (10) 10
 
13.3%
(Missing) 52
69.3%
ValueCountFrequency (%)
19980105 1
1.3%
19990601 1
1.3%
20001104 1
1.3%
20021005 1
1.3%
20060320 1
1.3%
20070222 1
1.3%
20081223 2
2.7%
20090622 2
2.7%
20110630 1
1.3%
20110802 2
2.7%
ValueCountFrequency (%)
20180509 1
1.3%
20171108 1
1.3%
20160927 1
1.3%
20150128 1
1.3%
20140114 1
1.3%
20140113 1
1.3%
20130826 1
1.3%
20130325 1
1.3%
20120611 1
1.3%
20110830 1
1.3%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

소재지전화
Text

MISSING 

Distinct68
Distinct (%)95.8%
Missing4
Missing (%)5.3%
Memory size732.0 B
2023-12-11T03:21:33.156069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.112676
Min length7

Characters and Unicode

Total characters789
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

Unique65 ?
Unique (%)91.5%

Sample

1st row053 962 8989
2nd row053 963 0689
3rd row053 981 6767
4th row053 3583917
5th row053 567 4770
ValueCountFrequency (%)
053 42
25.8%
053585 6
 
3.7%
615 4
 
2.5%
053615 3
 
1.8%
581 3
 
1.8%
357 3
 
1.8%
582 2
 
1.2%
3777 2
 
1.2%
585 2
 
1.2%
5052 2
 
1.2%
Other values (91) 94
57.7%
2023-12-11T03:21:33.818114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 157
19.9%
3 121
15.3%
0 115
14.6%
95
12.0%
8 54
 
6.8%
1 48
 
6.1%
6 47
 
6.0%
2 44
 
5.6%
7 38
 
4.8%
9 37
 
4.7%
Other values (2) 33
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 690
87.5%
Space Separator 95
 
12.0%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 157
22.8%
3 121
17.5%
0 115
16.7%
8 54
 
7.8%
1 48
 
7.0%
6 47
 
6.8%
2 44
 
6.4%
7 38
 
5.5%
9 37
 
5.4%
4 29
 
4.2%
Space Separator
ValueCountFrequency (%)
95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 789
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 157
19.9%
3 121
15.3%
0 115
14.6%
95
12.0%
8 54
 
6.8%
1 48
 
6.1%
6 47
 
6.0%
2 44
 
5.6%
7 38
 
4.8%
9 37
 
4.7%
Other values (2) 33
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 157
19.9%
3 121
15.3%
0 115
14.6%
95
12.0%
8 54
 
6.8%
1 48
 
6.1%
6 47
 
6.0%
2 44
 
5.6%
7 38
 
4.8%
9 37
 
4.7%
Other values (2) 33
 
4.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)77.5%
Missing35
Missing (%)46.7%
Infinite0
Infinite (%)0.0%
Mean706382.5
Minimum702011
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:34.078967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum702011
5-th percentile702030
Q1702815.75
median704280
Q3711815.75
95-th percentile711872
Maximum711892
Range9881
Interquartile range (IQR)9000

Descriptive statistics

Standard deviation4149.7433
Coefficient of variation (CV)0.0058746406
Kurtosis-1.6601052
Mean706382.5
Median Absolute Deviation (MAD)1553.5
Skewness0.52124411
Sum28255300
Variance17220369
MonotonicityNot monotonic
2023-12-11T03:21:34.340036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
711813 3
 
4.0%
711823 3
 
4.0%
702030 2
 
2.7%
704320 2
 
2.7%
704330 2
 
2.7%
702815 2
 
2.7%
702814 2
 
2.7%
711851 1
 
1.3%
711857 1
 
1.3%
711891 1
 
1.3%
Other values (21) 21
28.0%
(Missing) 35
46.7%
ValueCountFrequency (%)
702011 1
1.3%
702030 2
2.7%
702083 1
1.3%
702650 1
1.3%
702803 1
1.3%
702814 2
2.7%
702815 2
2.7%
702816 1
1.3%
702851 1
1.3%
702865 1
1.3%
ValueCountFrequency (%)
711892 1
 
1.3%
711891 1
 
1.3%
711871 1
 
1.3%
711857 1
 
1.3%
711852 1
 
1.3%
711851 1
 
1.3%
711823 3
4.0%
711821 1
 
1.3%
711814 1
 
1.3%
711813 3
4.0%

소재지전체주소
Text

MISSING 

Distinct63
Distinct (%)92.6%
Missing7
Missing (%)9.3%
Memory size732.0 B
2023-12-11T03:21:34.898857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length22.867647
Min length16

Characters and Unicode

Total characters1555
Distinct characters85
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

Unique58 ?
Unique (%)85.3%

Sample

1st row대구광역시 동구 신서동 139번지 1호
2nd row대구광역시 동구 동호동 207번지 1 호
3rd row대구광역시 동구 검사동 960번지 25 호
4th row대구광역시 서구 비산동 1678번지
5th row대구광역시 서구 중리동 1051-5
ValueCountFrequency (%)
대구광역시 68
 
20.0%
달성군 30
 
8.8%
북구 15
 
4.4%
달서구 14
 
4.1%
다사읍 9
 
2.6%
하빈면 7
 
2.1%
노원동3가 7
 
2.1%
논공읍 7
 
2.1%
서재리 7
 
2.1%
서구 5
 
1.5%
Other values (127) 171
50.3%
2023-12-11T03:21:35.731856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
17.7%
구 109
 
7.0%
대 72
 
4.6%
역 69
 
4.4%
지 69
 
4.4%
광 68
 
4.4%
시 68
 
4.4%
번 66
 
4.2%
1 57
 
3.7%
달 44
 
2.8%
Other values (75) 658
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 982
63.2%
Decimal Number 286
 
18.4%
Space Separator 275
 
17.7%
Dash Punctuation 10
 
0.6%
Other Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 109
 
11.1%
대 72
 
7.3%
역 69
 
7.0%
지 69
 
7.0%
광 68
 
6.9%
시 68
 
6.9%
번 66
 
6.7%
달 44
 
4.5%
동 42
 
4.3%
호 35
 
3.6%
Other values (61) 340
34.6%
Decimal Number
ValueCountFrequency (%)
1 57
19.9%
3 36
12.6%
2 35
12.2%
8 28
9.8%
6 26
9.1%
5 26
9.1%
4 22
 
7.7%
0 22
 
7.7%
7 20
 
7.0%
9 14
 
4.9%
Space Separator
ValueCountFrequency (%)
275
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 983
63.2%
Common 572
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 109
 
11.1%
대 72
 
7.3%
역 69
 
7.0%
지 69
 
7.0%
광 68
 
6.9%
시 68
 
6.9%
번 66
 
6.7%
달 44
 
4.5%
동 42
 
4.3%
호 35
 
3.6%
Other values (62) 341
34.7%
Common
ValueCountFrequency (%)
275
48.1%
1 57
 
10.0%
3 36
 
6.3%
2 35
 
6.1%
8 28
 
4.9%
6 26
 
4.5%
5 26
 
4.5%
4 22
 
3.8%
0 22
 
3.8%
7 20
 
3.5%
Other values (3) 25
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 982
63.2%
ASCII 572
36.8%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
48.1%
1 57
 
10.0%
3 36
 
6.3%
2 35
 
6.1%
8 28
 
4.9%
6 26
 
4.5%
5 26
 
4.5%
4 22
 
3.8%
0 22
 
3.8%
7 20
 
3.5%
Other values (3) 25
 
4.4%
Hangul
ValueCountFrequency (%)
구 109
 
11.1%
대 72
 
7.3%
역 69
 
7.0%
지 69
 
7.0%
광 68
 
6.9%
시 68
 
6.9%
번 66
 
6.7%
달 44
 
4.5%
동 42
 
4.3%
호 35
 
3.6%
Other values (61) 340
34.6%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명전체주소
Text

MISSING 

Distinct65
Distinct (%)91.5%
Missing4
Missing (%)5.3%
Memory size732.0 B
2023-12-11T03:21:36.380090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.71831
Min length20

Characters and Unicode

Total characters1684
Distinct characters104
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

Unique59 ?
Unique (%)83.1%

Sample

1st row대구광역시 동구 안심로 267 (동호동)
2nd row대구광역시 동구 해동로 237 (검사동)
3rd row대구광역시 서구 염색공단천로1길 37 (비산동)
4th row대구광역시 서구 와룡로 355 (중리동)
5th row대구광역시 서구 북비산로 115 (평리동)
ValueCountFrequency (%)
대구광역시 71
 
19.9%
달성군 33
 
9.3%
북구 15
 
4.2%
달서구 15
 
4.2%
하빈면 10
 
2.8%
다사읍 9
 
2.5%
논공읍 8
 
2.2%
노원동3가 6
 
1.7%
서구 5
 
1.4%
검단북로11길 4
 
1.1%
Other values (143) 180
50.6%
2023-12-11T03:21:37.277578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
286
 
17.0%
구 115
 
6.8%
대 76
 
4.5%
역 72
 
4.3%
광 71
 
4.2%
시 71
 
4.2%
로 63
 
3.7%
1 59
 
3.5%
달 52
 
3.1%
성 48
 
2.9%
Other values (94) 771
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1067
63.4%
Space Separator 286
 
17.0%
Decimal Number 244
 
14.5%
Open Punctuation 38
 
2.3%
Close Punctuation 38
 
2.3%
Dash Punctuation 9
 
0.5%
Other Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 115
 
10.8%
대 76
 
7.1%
역 72
 
6.7%
광 71
 
6.7%
시 71
 
6.7%
로 63
 
5.9%
달 52
 
4.9%
성 48
 
4.5%
동 47
 
4.4%
서 38
 
3.6%
Other values (78) 414
38.8%
Decimal Number
ValueCountFrequency (%)
1 59
24.2%
2 44
18.0%
3 29
11.9%
6 20
 
8.2%
7 17
 
7.0%
0 16
 
6.6%
8 16
 
6.6%
5 15
 
6.1%
4 15
 
6.1%
9 13
 
5.3%
Space Separator
ValueCountFrequency (%)
286
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1068
63.4%
Common 616
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 115
 
10.8%
대 76
 
7.1%
역 72
 
6.7%
광 71
 
6.6%
시 71
 
6.6%
로 63
 
5.9%
달 52
 
4.9%
성 48
 
4.5%
동 47
 
4.4%
서 38
 
3.6%
Other values (79) 415
38.9%
Common
ValueCountFrequency (%)
286
46.4%
1 59
 
9.6%
2 44
 
7.1%
( 38
 
6.2%
) 38
 
6.2%
3 29
 
4.7%
6 20
 
3.2%
7 17
 
2.8%
0 16
 
2.6%
8 16
 
2.6%
Other values (5) 53
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1067
63.4%
ASCII 616
36.6%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
286
46.4%
1 59
 
9.6%
2 44
 
7.1%
( 38
 
6.2%
) 38
 
6.2%
3 29
 
4.7%
6 20
 
3.2%
7 17
 
2.8%
0 16
 
2.6%
8 16
 
2.6%
Other values (5) 53
 
8.6%
Hangul
ValueCountFrequency (%)
구 115
 
10.8%
대 76
 
7.1%
역 72
 
6.7%
광 71
 
6.7%
시 71
 
6.7%
로 63
 
5.9%
달 52
 
4.9%
성 48
 
4.5%
동 47
 
4.4%
서 38
 
3.6%
Other values (78) 414
38.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)62.3%
Missing14
Missing (%)18.7%
Infinite0
Infinite (%)0.0%
Mean598625.92
Minimum41507
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:37.664845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41507
5-th percentile42725
Q1702260
median704400
Q3711820
95-th percentile711854
Maximum711891
Range670384
Interquartile range (IQR)9560

Descriptive statistics

Standard deviation248271.46
Coefficient of variation (CV)0.41473556
Kurtosis1.5122164
Mean598625.92
Median Absolute Deviation (MAD)7413
Skewness-1.8606035
Sum36516181
Variance6.1638717 × 1010
MonotonicityNot monotonic
2023-12-11T03:21:37.912552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
711813 7
 
9.3%
711854 4
 
5.3%
711823 4
 
5.3%
704401 3
 
4.0%
42905 3
 
4.0%
711851 2
 
2.7%
711814 2
 
2.7%
711820 2
 
2.7%
704190 2
 
2.7%
703833 2
 
2.7%
Other values (28) 30
40.0%
(Missing) 14
18.7%
ValueCountFrequency (%)
41507 1
 
1.3%
41748 1
 
1.3%
42705 1
 
1.3%
42725 1
 
1.3%
42900 1
 
1.3%
42905 3
4.0%
43008 1
 
1.3%
43013 1
 
1.3%
702030 2
2.7%
702050 1
 
1.3%
ValueCountFrequency (%)
711891 1
 
1.3%
711857 1
 
1.3%
711854 4
5.3%
711852 1
 
1.3%
711851 2
 
2.7%
711845 1
 
1.3%
711823 4
5.3%
711820 2
 
2.7%
711814 2
 
2.7%
711813 7
9.3%

사업장명
Text

Distinct66
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-11T03:21:38.299996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.6266667
Min length4

Characters and Unicode

Total characters572
Distinct characters108
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

Unique59 ?
Unique (%)78.7%

Sample

1st row우성계량증명업소
2nd row성림계량사
3rd row원호계량증명업소
4th row북부계량증명업소
5th row신광계량증명업소
ValueCountFrequency (%)
달성계량증명업소 3
 
3.8%
공단계량증명업소 3
 
3.8%
공단산업계량증명업소 2
 
2.6%
서재계량증명업소 2
 
2.6%
쌍용계량증명업소 2
 
2.6%
우진계량증명업소 2
 
2.6%
대지상사 2
 
2.6%
현풍증명계량소 1
 
1.3%
주)부성리싸이클링 1
 
1.3%
파워플러스콤(주 1
 
1.3%
Other values (59) 59
75.6%
2023-12-11T03:21:38.965004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 52
 
9.1%
량 52
 
9.1%
소 48
 
8.4%
업 46
 
8.0%
증 44
 
7.7%
명 44
 
7.7%
대 18
 
3.1%
성 14
 
2.4%
공 13
 
2.3%
주 13
 
2.3%
Other values (98) 228
39.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 544
95.1%
Close Punctuation 11
 
1.9%
Open Punctuation 11
 
1.9%
Space Separator 3
 
0.5%
Decimal Number 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 52
 
9.6%
량 52
 
9.6%
소 48
 
8.8%
업 46
 
8.5%
증 44
 
8.1%
명 44
 
8.1%
대 18
 
3.3%
성 14
 
2.6%
공 13
 
2.4%
주 13
 
2.4%
Other values (92) 200
36.8%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 544
95.1%
Common 28
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 52
 
9.6%
량 52
 
9.6%
소 48
 
8.8%
업 46
 
8.5%
증 44
 
8.1%
명 44
 
8.1%
대 18
 
3.3%
성 14
 
2.6%
공 13
 
2.4%
주 13
 
2.4%
Other values (92) 200
36.8%
Common
ValueCountFrequency (%)
) 11
39.3%
( 11
39.3%
3
 
10.7%
5 1
 
3.6%
& 1
 
3.6%
2 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 544
95.1%
ASCII 28
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 52
 
9.6%
량 52
 
9.6%
소 48
 
8.8%
업 46
 
8.5%
증 44
 
8.1%
명 44
 
8.1%
대 18
 
3.3%
성 14
 
2.6%
공 13
 
2.4%
주 13
 
2.4%
Other values (92) 200
36.8%
ASCII
ValueCountFrequency (%)
) 11
39.3%
( 11
39.3%
3
 
10.7%
5 1
 
3.6%
& 1
 
3.6%
2 1
 
3.6%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct75
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0136058 × 1013
Minimum2.0080827 × 1013
Maximum2.0191121 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:39.243882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0080827 × 1013
5-th percentile2.0090622 × 1013
Q12.0111031 × 1013
median2.0130325 × 1013
Q32.0170718 × 1013
95-th percentile2.0180867 × 1013
Maximum2.0191121 × 1013
Range1.1029394 × 1011
Interquartile range (IQR)5.9686952 × 1010

Descriptive statistics

Standard deviation3.1896658 × 1010
Coefficient of variation (CV)0.0015840567
Kurtosis-1.1848949
Mean2.0136058 × 1013
Median Absolute Deviation (MAD)1.9295028 × 1010
Skewness0.30063306
Sum1.5102044 × 1015
Variance1.0173968 × 1021
MonotonicityNot monotonic
2023-12-11T03:21:39.519313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090204084225 1
 
1.3%
20111031140048 1
 
1.3%
20121115145932 1
 
1.3%
20180703132725 1
 
1.3%
20191106114136 1
 
1.3%
20130325170531 1
 
1.3%
20111031140406 1
 
1.3%
20170327161027 1
 
1.3%
20170612101851 1
 
1.3%
20180703132657 1
 
1.3%
Other values (65) 65
86.7%
ValueCountFrequency (%)
20080827175734 1
1.3%
20081223172915 1
1.3%
20090204084225 1
1.3%
20090622150752 1
1.3%
20090622152425 1
1.3%
20090622173242 1
1.3%
20090622182248 1
1.3%
20100813103043 1
1.3%
20100813103127 1
1.3%
20111030141633 1
1.3%
ValueCountFrequency (%)
20191121111608 1
1.3%
20191106114136 1
1.3%
20190702145324 1
1.3%
20181017102120 1
1.3%
20180803151521 1
1.3%
20180704090455 1
1.3%
20180703132725 1
1.3%
20180703132657 1
1.3%
20180703132627 1
1.3%
20180703132601 1
1.3%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
I
73 
U
 
2

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 73
97.3%
U 2
 
2.7%

Length

2023-12-11T03:21:39.767787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:39.964036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 73
97.3%
u 2
 
2.7%

데이터갱신일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size732.0 B
2018-08-31 23:59:59.0
71 
2019-07-04 02:21:28.0
 
1
2018-10-19 02:37:38.0
 
1
2019-11-08 02:40:00.0
 
1
2019-11-23 02:40:00.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique4 ?
Unique (%)5.3%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 71
94.7%
2019-07-04 02:21:28.0 1
 
1.3%
2018-10-19 02:37:38.0 1
 
1.3%
2019-11-08 02:40:00.0 1
 
1.3%
2019-11-23 02:40:00.0 1
 
1.3%

Length

2023-12-11T03:21:40.155919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:40.359014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 71
47.3%
23:59:59.0 71
47.3%
02:40:00.0 2
 
1.3%
2019-07-04 1
 
0.7%
02:21:28.0 1
 
0.7%
2018-10-19 1
 
0.7%
02:37:38.0 1
 
0.7%
2019-11-08 1
 
0.7%
2019-11-23 1
 
0.7%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing75
Missing (%)100.0%
Memory size807.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)88.7%
Missing4
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean335699.09
Minimum326192.2
Maximum354741.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:41.017336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326192.2
5-th percentile326515.85
Q1330792.16
median334984.95
Q3339658.75
95-th percentile345995.66
Maximum354741.9
Range28549.703
Interquartile range (IQR)8866.5882

Descriptive statistics

Standard deviation6392.6352
Coefficient of variation (CV)0.019042754
Kurtosis-0.10108524
Mean335699.09
Median Absolute Deviation (MAD)4600.3315
Skewness0.47490236
Sum23834635
Variance40865785
MonotonicityNot monotonic
2023-12-11T03:21:41.277768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
334902.493029 2
 
2.7%
334984.946983 2
 
2.7%
326987.047869 2
 
2.7%
331765.493298 2
 
2.7%
334282.929799 2
 
2.7%
345665.162766 2
 
2.7%
330899.370928 2
 
2.7%
335126.439535 2
 
2.7%
329081.561467 1
 
1.3%
326320.1354 1
 
1.3%
Other values (53) 53
70.7%
(Missing) 4
 
5.3%
ValueCountFrequency (%)
326192.20154 1
1.3%
326246.351761 1
1.3%
326320.1354 1
1.3%
326341.933013 1
1.3%
326689.760538 1
1.3%
326773.44963 1
1.3%
326987.047869 2
2.7%
327152.0 1
1.3%
328137.029306 1
1.3%
328348.10847 1
1.3%
ValueCountFrequency (%)
354741.904563 1
1.3%
349314.087253 1
1.3%
346326.181585 1
1.3%
346052.168116 1
1.3%
345939.142242 1
1.3%
345665.162766 2
2.7%
345582.974172 1
1.3%
343011.774837 1
1.3%
342937.580405 1
1.3%
342444.386416 1
1.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)88.7%
Missing4
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean261061.82
Minimum238774.71
Maximum271647.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size807.0 B
2023-12-11T03:21:41.530728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238774.71
5-th percentile241657.95
Q1259834.93
median263779.3
Q3265896.1
95-th percentile269609.5
Maximum271647.09
Range32872.386
Interquartile range (IQR)6061.164

Descriptive statistics

Standard deviation7939.5881
Coefficient of variation (CV)0.030412675
Kurtosis1.5426243
Mean261061.82
Median Absolute Deviation (MAD)3317.1396
Skewness-1.4715486
Sum18535389
Variance63037060
MonotonicityNot monotonic
2023-12-11T03:21:41.780564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
264106.215422 2
 
2.7%
260340.1784 2
 
2.7%
263346.437143 2
 
2.7%
255196.387595 2
 
2.7%
264796.577877 2
 
2.7%
269620.252519 2
 
2.7%
248772.305647 2
 
2.7%
264967.821838 2
 
2.7%
252942.606123 1
 
1.3%
264212.934923 1
 
1.3%
Other values (53) 53
70.7%
(Missing) 4
 
5.3%
ValueCountFrequency (%)
238774.707824 1
1.3%
238818.550604 1
1.3%
239224.138323 1
1.3%
241657.908856 1
1.3%
241658.0 1
1.3%
248302.414416 1
1.3%
248517.038827 1
1.3%
248586.503508 1
1.3%
248772.305647 2
2.7%
252942.606123 1
1.3%
ValueCountFrequency (%)
271647.094222 1
1.3%
269818.769625 1
1.3%
269620.252519 2
2.7%
269598.747902 1
1.3%
268841.001354 1
1.3%
268692.111157 1
1.3%
267902.207814 1
1.3%
267761.787841 1
1.3%
267599.197679 1
1.3%
267364.664497 1
1.3%

사무소전화번호
Text

Distinct72
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
2023-12-11T03:21:42.262618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.146667
Min length7

Characters and Unicode

Total characters836
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

Unique69 ?
Unique (%)92.0%

Sample

1st row053 962 8989
2nd row053 963 0689
3rd row053 981 6767
4th row053 3583917
5th row053 567 4770
ValueCountFrequency (%)
053 42
24.7%
053585 6
 
3.5%
615 4
 
2.4%
581 3
 
1.8%
357 3
 
1.8%
053615 3
 
1.8%
5052 2
 
1.2%
585 2
 
1.2%
591 2
 
1.2%
3777 2
 
1.2%
Other values (98) 101
59.4%
2023-12-11T03:21:42.963192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 158
18.9%
0 129
15.4%
3 123
14.7%
98
11.7%
8 56
 
6.7%
1 55
 
6.6%
6 54
 
6.5%
2 45
 
5.4%
7 41
 
4.9%
9 41
 
4.9%
Other values (2) 36
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 734
87.8%
Space Separator 98
 
11.7%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 158
21.5%
0 129
17.6%
3 123
16.8%
8 56
 
7.6%
1 55
 
7.5%
6 54
 
7.4%
2 45
 
6.1%
7 41
 
5.6%
9 41
 
5.6%
4 32
 
4.4%
Space Separator
ValueCountFrequency (%)
98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 158
18.9%
0 129
15.4%
3 123
14.7%
98
11.7%
8 56
 
6.7%
1 55
 
6.6%
6 54
 
6.5%
2 45
 
5.4%
7 41
 
4.9%
9 41
 
4.9%
Other values (2) 36
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 158
18.9%
0 129
15.4%
3 123
14.7%
98
11.7%
8 56
 
6.7%
1 55
 
6.6%
6 54
 
6.5%
2 45
 
5.4%
7 41
 
4.9%
9 41
 
4.9%
Other values (2) 36
 
4.3%

사업장전화번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size732.0 B
<NA>
73 
533593382
 
1
535923771
 
1

Length

Max length9
Median length4
Mean length4.1333333
Min length4

Unique

Unique2 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 73
97.3%
533593382 1
 
1.3%
535923771 1
 
1.3%

Length

2023-12-11T03:21:43.244443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:21:43.437369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 73
97.3%
533593382 1
 
1.3%
535923771 1
 
1.3%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
01계량기증명업09_28_04_P3420000199034200580650000819900511<NA>3폐업3폐업20081223<NA><NA><NA>053 962 8989<NA><NA>대구광역시 동구 신서동 139번지 1호<NA><NA>우성계량증명업소20090204084225I2018-08-31 23:59:59.0<NA><NA><NA>053 962 8989<NA>
12계량기증명업09_28_04_P3420000199534200580650000119951028<NA>3폐업3폐업<NA><NA><NA><NA>053 963 0689<NA><NA>대구광역시 동구 동호동 207번지 1 호대구광역시 동구 안심로 267 (동호동)<NA>성림계량사20100813103127I2018-08-31 23:59:59.0<NA>354741.904563264283.362303053 963 0689<NA>
23계량기증명업09_28_04_P3420000199734200580650000119970612<NA>3폐업3폐업<NA><NA><NA><NA>053 981 6767<NA><NA>대구광역시 동구 검사동 960번지 25 호대구광역시 동구 해동로 237 (검사동)<NA>원호계량증명업소20100813103043I2018-08-31 23:59:59.0<NA>349314.087253266191.555896053 981 6767<NA>
34계량기증명업09_28_04_P3430000198234300100650000519821104<NA>1영업/정상1영업중<NA><NA><NA><NA>053 3583917<NA><NA>대구광역시 서구 비산동 1678번지대구광역시 서구 염색공단천로1길 37 (비산동)<NA>북부계량증명업소20180620155936I2018-08-31 23:59:59.0<NA>340310.091298266545.42264053 3583917<NA>
45계량기증명업09_28_04_P3430000199734300100650001619970322<NA>3폐업3폐업20130826<NA><NA><NA>053 567 4770<NA><NA>대구광역시 서구 중리동 1051-5대구광역시 서구 와룡로 355 (중리동)703833신광계량증명업소20130826175504I2018-08-31 23:59:59.0<NA>338776.058115263779.298649053 567 4770<NA>
56계량기증명업09_28_04_P3430000198834300100650001519881213<NA>3폐업3폐업20150128<NA><NA><NA>053 553 1199<NA>703834대구광역시 서구 평리6동 595번지 9호대구광역시 서구 북비산로 115 (평리동)703834대기계량증명업소20150128174601I2018-08-31 23:59:59.0<NA>339508.143637265406.821275053 553 1199<NA>
67계량기증명업09_28_04_P3430000198634300100650001419860805<NA>1영업/정상1영업중<NA><NA><NA><NA>053 565 0222<NA><NA>대구광역시 서구 중리동 1120-1번지대구광역시 서구 와룡로 346 (중리동)703833화성계량증명업소20180620155902I2018-08-31 23:59:59.0<NA>338844.987977263632.895918053 565 0222<NA>
78계량기증명업09_28_04_P3430000201534300950650000120151111<NA>1영업/정상1영업중<NA><NA><NA><NA>0535920602<NA><NA>대구광역시 서구 이현동 268번지 3호대구광역시 서구 북비산로13길 1 (이현동)41748(주)경원스틸20180619133204I2018-08-31 23:59:59.0<NA>339060.968259265432.3503360535920602<NA>
89계량기증명업09_28_04_P3450000201134500990650000120110823<NA>1영업/정상1영업중<NA><NA><NA><NA>053 353 8369<NA>702030대구광역시 북구 검단동 1393번지 67호대구광역시 북구 검단북로11길 21 (검단동)702030황형원부동산20111030145133I2018-08-31 23:59:59.0<NA>345582.974172269598.747902053 353 8369<NA>
910계량기증명업09_28_04_P3450000201234500990650000220121008<NA>1영업/정상1영업중<NA><NA><NA><NA>053 744 2555<NA>702011대구광역시 북구 산격동 1806번지대구광역시 북구 유통단지로8길 120-1 (산격동)702838한국 에이엔디(주) 대구지사20140107111955I2018-08-31 23:59:59.0<NA>345939.142242268692.111157053 744 2555<NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
6566계량기증명업09_28_04_P3480000201034802910650000320101118<NA>3폐업3폐업20140114<NA><NA><NA>005305830391<NA>711821대구광역시 달성군 하빈면 묘리 1023번지 3호대구광역시 달성군 하빈면 묘동1길 48711820(주)비엔에이코리아20160428133142I2018-08-31 23:59:59.0<NA>328137.029306266712.314053005305830391<NA>
6667계량기증명업09_28_04_P3480000200734802890652006120060110<NA>3폐업3폐업<NA><NA><NA><NA>0535845933<NA>711823대구광역시 달성군 하빈면 봉촌리 54번지대구광역시 달성군 하빈면 하빈남로 268711823대지상사20111031135943I2018-08-31 23:59:59.0<NA>326987.047869263346.4371430535845933<NA>
6768계량기증명업09_28_04_P3480000200234800690650000220021109<NA>3폐업3폐업<NA><NA><NA><NA>053585 7207<NA><NA>대구광역시 달성군 다사읍 세천리 184번지대구광역시 달성군 다사읍 세천북로10길 19-1711814대구재생계량사20111031140222I2018-08-31 23:59:59.0<NA>333294.078519265412.710122053585 7207<NA>
6869계량기증명업09_28_04_P3480000200034800000650000819980527<NA>3폐업3폐업20110630<NA><NA><NA>053585 8544<NA>711813대구광역시 달성군 다사읍 서재리 743번지대구광역시 달성군 다사읍 서재본길 94711813형제계량증명업소20180704090455I2018-08-31 23:59:59.0<NA>334282.929799264796.577877053585 8544<NA>
6970계량기증명업09_28_04_P3480000200034800000650000619960202<NA>3폐업3폐업<NA><NA><NA><NA>053585 2527<NA><NA>대구광역시 달성군 다사읍 서재리 181번지대구광역시 달성군 다사읍 서재로12길 26711813우진계량증명업소20111031141851I2018-08-31 23:59:59.0<NA>334902.493029264106.215422053585 2527<NA>
7071계량기증명업09_28_04_P3480000200034800000650000519950127<NA>3폐업3폐업20110802<NA><NA><NA>053585 1212<NA><NA>대구광역시 달성군 다사읍 서재리 91번지대구광역시 달성군 다사읍 서재로 137711813서재계량증명업소20111031142021I2018-08-31 23:59:59.0<NA>335126.439535264967.821838053585 1212<NA>
7172계량기증명업09_28_04_P3480000198834800000650000419881229<NA>3폐업3폐업<NA><NA><NA><NA>053614 5196<NA><NA>대구광역시 달성군 옥포면 본리리 2214-1번지대구광역시 달성군 논공읍 비슬로 2165711854옥포계량증명업소20111031144222I2018-08-31 23:59:59.0<NA>331765.493298255196.387595053614 5196<NA>
7273계량기증명업09_28_04_P3480000198834800000650000319880628<NA>3폐업3폐업<NA><NA><NA><NA>053615 3777<NA><NA>대구광역시 달성군 논공읍 북리 803-245번지대구광역시 달성군 논공읍 논공로 724711854공단산업계량증명업소20111031144331I2018-08-31 23:59:59.0<NA>330899.370928248772.305647053615 3777<NA>
7374계량기증명업09_28_04_P3480000198834800000650000219880402<NA>3폐업3폐업<NA><NA><NA><NA>053615 5052<NA><NA>대구광역시 달성군 논공읍 북리 803-282번지대구광역시 달성군 논공읍 논공로 782711854논공공단계량업소20111031144439I2018-08-31 23:59:59.0<NA>330348.399402248586.503508053615 5052<NA>
7475계량기증명업09_28_04_P3480000199534800000650000519950127<NA>3폐업3폐업20110802<NA><NA><NA>053585 1212<NA><NA>대구광역시 달성군 다사읍 서재리 91번지대구광역시 달성군 다사읍 서재로 137711813서재계량증명업소20111031144031I2018-08-31 23:59:59.0<NA>335126.439535264967.821838053585 1212<NA>