Overview

Dataset statistics

Number of variables30
Number of observations77
Missing cells591
Missing cells (%)25.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory260.7 B

Variable types

Numeric10
Categorical8
Unsupported6
Text5
DateTime1

Dataset

Description22년06월_6270000_대구광역시_09_28_04_P_계량기증명업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000093851&dataSetDetailId=DDI_0000093874&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
데이터갱신구분 is highly imbalanced (51.9%)Imbalance
사업장전화번호 is highly imbalanced (87.4%)Imbalance
인허가취소일자 has 77 (100.0%) missing valuesMissing
폐업일자 has 52 (67.5%) missing valuesMissing
휴업시작일자 has 77 (100.0%) missing valuesMissing
휴업종료일자 has 77 (100.0%) missing valuesMissing
재개업일자 has 77 (100.0%) missing valuesMissing
소재지전화 has 4 (5.2%) missing valuesMissing
소재지면적 has 77 (100.0%) missing valuesMissing
소재지우편번호 has 37 (48.1%) missing valuesMissing
소재지전체주소 has 7 (9.1%) missing valuesMissing
도로명전체주소 has 4 (5.2%) missing valuesMissing
도로명우편번호 has 14 (18.2%) missing valuesMissing
업태구분명 has 77 (100.0%) missing valuesMissing
좌표정보(X) has 4 (5.2%) missing valuesMissing
좌표정보(Y) has 4 (5.2%) missing valuesMissing
사무소전화번호 has 3 (3.9%) 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 started2024-04-21 09:40:10.674377
Analysis finished2024-04-21 09:40:11.363304
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:11.495335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median39
Q358
95-th percentile73.2
Maximum77
Range76
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.371857
Coefficient of variation (CV)0.57363737
Kurtosis-1.2
Mean39
Median Absolute Deviation (MAD)19
Skewness0
Sum3003
Variance500.5
MonotonicityStrictly increasing
2024-04-21T18:40:11.756120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 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%
51 1
 
1.3%
49 1
 
1.3%
Other values (67) 67
87.0%
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 (%)
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%
69 1
1.3%
68 1
1.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size744.0 B
계량기증명업
77 

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 77
100.0%

Length

2024-04-21T18:40:11.990053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:12.149608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기증명업 77
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size744.0 B
09_28_04_P
77 

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 77
100.0%

Length

2024-04-21T18:40:12.323361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:12.483111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_04_p 77
100.0%

개방자치단체코드
Real number (ℝ)

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3464935.1
Minimum3420000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:12.627777image/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 deviation18326.238
Coefficient of variation (CV)0.0052890566
Kurtosis-0.11429864
Mean3464935.1
Median Absolute Deviation (MAD)10000
Skewness-1.0165297
Sum2.668 × 108
Variance3.3585099 × 108
MonotonicityIncreasing
2024-04-21T18:40:12.812505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3480000 35
45.5%
3450000 17
22.1%
3470000 15
19.5%
3430000 6
 
7.8%
3420000 3
 
3.9%
3460000 1
 
1.3%
ValueCountFrequency (%)
3420000 3
 
3.9%
3430000 6
 
7.8%
3450000 17
22.1%
3460000 1
 
1.3%
3470000 15
19.5%
3480000 35
45.5%
ValueCountFrequency (%)
3480000 35
45.5%
3470000 15
19.5%
3460000 1
 
1.3%
3450000 17
22.1%
3430000 6
 
7.8%
3420000 3
 
3.9%

관리번호
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0024634 × 1018
Minimum1.981345 × 1018
Maximum2.021348 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:13.054039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.981345 × 1018
5-th percentile1.983947 × 1018
Q11.996346 × 1018
median2.001347 × 1018
Q32.012345 × 1018
95-th percentile2.0185478 × 1018
Maximum2.021348 × 1018
Range4.0003035 × 1016
Interquartile range (IQR)1.5999004 × 1016

Descriptive statistics

Standard deviation1.0817237 × 1016
Coefficient of variation (CV)0.0054019651
Kurtosis-0.86093687
Mean2.0024634 × 1018
Median Absolute Deviation (MAD)9.0019988 × 1015
Skewness-0.14583009
Sum6.6157282 × 1018
Variance1.1701263 × 1032
MonotonicityNot monotonic
2024-04-21T18:40:13.519110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1990342005806500008 1
 
1.3%
2000348000006500003 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%
1998348000006500008 1
 
1.3%
Other values (67) 67
87.0%
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
Real number (ℝ)

Distinct69
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20012658
Minimum19810701
Maximum20210903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:13.794736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19810701
5-th percentile19837114
Q119940825
median20010219
Q320120320
95-th percentile20182954
Maximum20210903
Range400202
Interquartile range (IQR)179495

Descriptive statistics

Standard deviation113032.33
Coefficient of variation (CV)0.0056480421
Kurtosis-1.1363294
Mean20012658
Median Absolute Deviation (MAD)109708
Skewness0.02333304
Sum1.5409747 × 109
Variance1.2776308 × 1010
MonotonicityNot monotonic
2024-04-21T18:40:14.067429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19810701 3
 
3.9%
19960202 2
 
2.6%
19980527 2
 
2.6%
20010219 2
 
2.6%
19881229 2
 
2.6%
19950127 2
 
2.6%
19880628 2
 
2.6%
20151123 1
 
1.3%
20020627 1
 
1.3%
20011221 1
 
1.3%
Other values (59) 59
76.6%
ValueCountFrequency (%)
19810701 3
3.9%
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
2.6%
19881213 1
 
1.3%
ValueCountFrequency (%)
20210903 1
1.3%
20201012 1
1.3%
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%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size744.0 B
1
44 
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 44
57.1%
3 33
42.9%

Length

2024-04-21T18:40:14.308942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:14.478517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 44
57.1%
3 33
42.9%

영업상태명
Categorical

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size744.0 B
영업/정상
44 
폐업
33 

Length

Max length5
Median length5
Mean length3.7142857
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 44
57.1%
폐업 33
42.9%

Length

2024-04-21T18:40:14.662687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:14.843270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 44
57.1%
폐업 33
42.9%

상세영업상태코드
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size744.0 B
1
43 
3
33 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 43
55.8%
3 33
42.9%
5 1
 
1.3%

Length

2024-04-21T18:40:15.016635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:15.190713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 43
55.8%
3 33
42.9%
5 1
 
1.3%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size744.0 B
영업중
43 
폐업
33 
<NA>
 
1

Length

Max length4
Median length3
Mean length2.5844156
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 43
55.8%
폐업 33
42.9%
<NA> 1
 
1.3%

Length

2024-04-21T18:40:15.392943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:15.588354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 43
55.8%
폐업 33
42.9%
na 1
 
1.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)88.0%
Missing52
Missing (%)67.5%
Infinite0
Infinite (%)0.0%
Mean20105472
Minimum19980105
Maximum20201123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:15.771175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980105
5-th percentile19992702
Q120081223
median20110802
Q320140114
95-th percentile20196823
Maximum20201123
Range221018
Interquartile range (IQR)58891

Descriptive statistics

Standard deviation60931.607
Coefficient of variation (CV)0.0030305982
Kurtosis-0.18718102
Mean20105472
Median Absolute Deviation (MAD)29579
Skewness-0.51424805
Sum5.026368 × 108
Variance3.7126607 × 109
MonotonicityNot monotonic
2024-04-21T18:40:15.976479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20090622 2
 
2.6%
20110802 2
 
2.6%
20081223 2
 
2.6%
20060320 1
 
1.3%
19980105 1
 
1.3%
20160927 1
 
1.3%
20140114 1
 
1.3%
20110630 1
 
1.3%
20201123 1
 
1.3%
20130826 1
 
1.3%
Other values (12) 12
 
15.6%
(Missing) 52
67.5%
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
2.6%
20090622 2
2.6%
20110630 1
1.3%
20110802 2
2.6%
ValueCountFrequency (%)
20201123 1
1.3%
20200902 1
1.3%
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%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

소재지전화
Text

MISSING 

Distinct70
Distinct (%)95.9%
Missing4
Missing (%)5.2%
Memory size744.0 B
2024-04-21T18:40:16.752970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.205479
Min length7

Characters and Unicode

Total characters818
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 (%)91.8%

Sample

1st row053 962 8989
2nd row053 963 0689
3rd row053 981 6767
4th row0533593996
5th row053 3583917
ValueCountFrequency (%)
053 45
26.3%
053585 6
 
3.5%
615 4
 
2.3%
591 3
 
1.8%
357 3
 
1.8%
053615 3
 
1.8%
581 3
 
1.8%
592 2
 
1.2%
3777 2
 
1.2%
585 2
 
1.2%
Other values (94) 98
57.3%
2024-04-21T18:40:17.767258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 119
14.5%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 713
87.2%
Space Separator 101
 
12.3%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 163
22.9%
3 127
17.8%
0 119
16.7%
8 55
 
7.7%
1 49
 
6.9%
6 48
 
6.7%
2 46
 
6.5%
9 40
 
5.6%
7 38
 
5.3%
4 28
 
3.9%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 818
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 119
14.5%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 119
14.5%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)77.5%
Missing37
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean706382.5
Minimum702011
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:17.997864image/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
2024-04-21T18:40:18.226189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
711823 3
 
3.9%
711813 3
 
3.9%
702815 2
 
2.6%
704330 2
 
2.6%
704320 2
 
2.6%
702030 2
 
2.6%
702814 2
 
2.6%
711857 1
 
1.3%
711851 1
 
1.3%
711852 1
 
1.3%
Other values (21) 21
27.3%
(Missing) 37
48.1%
ValueCountFrequency (%)
702011 1
1.3%
702030 2
2.6%
702083 1
1.3%
702650 1
1.3%
702803 1
1.3%
702814 2
2.6%
702815 2
2.6%
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
3.9%
711821 1
 
1.3%
711814 1
 
1.3%
711813 3
3.9%

소재지전체주소
Text

MISSING 

Distinct65
Distinct (%)92.9%
Missing7
Missing (%)9.1%
Memory size744.0 B
2024-04-21T18:40:19.319312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length22.8
Min length16

Characters and Unicode

Total characters1596
Distinct characters86
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

Unique60 ?
Unique (%)85.7%

Sample

1st row대구광역시 동구 신서동 139번지 1호
2nd row대구광역시 동구 동호동 207번지 1 호
3rd row대구광역시 동구 검사동 960번지 25 호
4th row대구광역시 서구 평리동 595-23
5th row대구광역시 서구 비산동 1678번지
ValueCountFrequency (%)
대구광역시 70
 
20.1%
달성군 31
 
8.9%
북구 15
 
4.3%
달서구 14
 
4.0%
다사읍 9
 
2.6%
논공읍 8
 
2.3%
서재리 7
 
2.0%
하빈면 7
 
2.0%
노원동3가 7
 
2.0%
서구 6
 
1.7%
Other values (131) 175
50.1%
2024-04-21T18:40:20.656591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
282
17.7%
구 112
 
7.0%
대 74
 
4.6%
역 71
 
4.4%
광 70
 
4.4%
시 70
 
4.4%
지 69
 
4.3%
번 66
 
4.1%
1 57
 
3.6%
달 45
 
2.8%
Other values (76) 680
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1005
63.0%
Decimal Number 295
 
18.5%
Space Separator 282
 
17.7%
Dash Punctuation 12
 
0.8%
Other Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 112
 
11.1%
대 74
 
7.4%
역 71
 
7.1%
광 70
 
7.0%
시 70
 
7.0%
지 69
 
6.9%
번 66
 
6.6%
달 45
 
4.5%
동 43
 
4.3%
리 37
 
3.7%
Other values (62) 348
34.6%
Decimal Number
ValueCountFrequency (%)
1 57
19.3%
2 37
12.5%
3 37
12.5%
8 28
9.5%
5 28
9.5%
6 26
8.8%
4 23
7.8%
7 22
 
7.5%
0 22
 
7.5%
9 15
 
5.1%
Space Separator
ValueCountFrequency (%)
282
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1006
63.0%
Common 590
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 112
 
11.1%
대 74
 
7.4%
역 71
 
7.1%
광 70
 
7.0%
시 70
 
7.0%
지 69
 
6.9%
번 66
 
6.6%
달 45
 
4.5%
동 43
 
4.3%
리 37
 
3.7%
Other values (63) 349
34.7%
Common
ValueCountFrequency (%)
282
47.8%
1 57
 
9.7%
2 37
 
6.3%
3 37
 
6.3%
8 28
 
4.7%
5 28
 
4.7%
6 26
 
4.4%
4 23
 
3.9%
7 22
 
3.7%
0 22
 
3.7%
Other values (3) 28
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1005
63.0%
ASCII 590
37.0%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
282
47.8%
1 57
 
9.7%
2 37
 
6.3%
3 37
 
6.3%
8 28
 
4.7%
5 28
 
4.7%
6 26
 
4.4%
4 23
 
3.9%
7 22
 
3.7%
0 22
 
3.7%
Other values (3) 28
 
4.7%
Hangul
ValueCountFrequency (%)
구 112
 
11.1%
대 74
 
7.4%
역 71
 
7.1%
광 70
 
7.0%
시 70
 
7.0%
지 69
 
6.9%
번 66
 
6.6%
달 45
 
4.5%
동 43
 
4.3%
리 37
 
3.7%
Other values (62) 348
34.6%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명전체주소
Text

MISSING 

Distinct67
Distinct (%)91.8%
Missing4
Missing (%)5.2%
Memory size744.0 B
2024-04-21T18:40:21.864790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.808219
Min length20

Characters and Unicode

Total characters1738
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

Unique61 ?
Unique (%)83.6%

Sample

1st row대구광역시 동구 안심로 267 (동호동)
2nd row대구광역시 동구 해동로 237 (검사동)
3rd row대구광역시 서구 북비산로 121 (평리동)
4th row대구광역시 서구 염색공단천로1길 37 (비산동)
5th row대구광역시 서구 와룡로 346 (중리동)
ValueCountFrequency (%)
대구광역시 73
 
19.9%
달성군 34
 
9.3%
달서구 15
 
4.1%
북구 15
 
4.1%
하빈면 10
 
2.7%
논공읍 9
 
2.5%
다사읍 9
 
2.5%
노원동3가 6
 
1.6%
서구 6
 
1.6%
검단동 4
 
1.1%
Other values (145) 185
50.5%
2024-04-21T18:40:23.514476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
294
 
16.9%
구 118
 
6.8%
대 79
 
4.5%
역 74
 
4.3%
광 73
 
4.2%
시 73
 
4.2%
1 65
 
3.7%
로 65
 
3.7%
달 54
 
3.1%
성 48
 
2.8%
Other values (94) 795
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1097
63.1%
Space Separator 294
 
16.9%
Decimal Number 257
 
14.8%
Close Punctuation 39
 
2.2%
Open Punctuation 39
 
2.2%
Dash Punctuation 10
 
0.6%
Other Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 118
 
10.8%
대 79
 
7.2%
역 74
 
6.7%
광 73
 
6.7%
시 73
 
6.7%
로 65
 
5.9%
달 54
 
4.9%
성 48
 
4.4%
동 47
 
4.3%
서 39
 
3.6%
Other values (78) 427
38.9%
Decimal Number
ValueCountFrequency (%)
1 65
25.3%
2 46
17.9%
3 29
11.3%
6 22
 
8.6%
4 17
 
6.6%
8 17
 
6.6%
7 17
 
6.6%
5 16
 
6.2%
0 15
 
5.8%
9 13
 
5.1%
Space Separator
ValueCountFrequency (%)
294
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1098
63.2%
Common 640
36.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 118
 
10.7%
대 79
 
7.2%
역 74
 
6.7%
광 73
 
6.6%
시 73
 
6.6%
로 65
 
5.9%
달 54
 
4.9%
성 48
 
4.4%
동 47
 
4.3%
서 39
 
3.6%
Other values (79) 428
39.0%
Common
ValueCountFrequency (%)
294
45.9%
1 65
 
10.2%
2 46
 
7.2%
) 39
 
6.1%
( 39
 
6.1%
3 29
 
4.5%
6 22
 
3.4%
4 17
 
2.7%
8 17
 
2.7%
7 17
 
2.7%
Other values (5) 55
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1097
63.1%
ASCII 640
36.8%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
294
45.9%
1 65
 
10.2%
2 46
 
7.2%
) 39
 
6.1%
( 39
 
6.1%
3 29
 
4.5%
6 22
 
3.4%
4 17
 
2.7%
8 17
 
2.7%
7 17
 
2.7%
Other values (5) 55
 
8.6%
Hangul
ValueCountFrequency (%)
구 118
 
10.8%
대 79
 
7.2%
역 74
 
6.7%
광 73
 
6.7%
시 73
 
6.7%
로 65
 
5.9%
달 54
 
4.9%
성 48
 
4.4%
동 47
 
4.3%
서 39
 
3.6%
Other values (78) 427
38.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)61.9%
Missing14
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean580966.65
Minimum41507
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:23.894551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41507
5-th percentile42706.4
Q1702083
median704360
Q3711817
95-th percentile711854
Maximum711891
Range670384
Interquartile range (IQR)9734

Descriptive statistics

Standard deviation263277.82
Coefficient of variation (CV)0.453172
Kurtosis0.62653551
Mean580966.65
Median Absolute Deviation (MAD)7453
Skewness-1.6143856
Sum36600899
Variance6.9315209 × 1010
MonotonicityNot monotonic
2024-04-21T18:40:24.298496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
711813 7
 
9.1%
711854 4
 
5.2%
711823 4
 
5.2%
42905 3
 
3.9%
704401 3
 
3.9%
704190 2
 
2.6%
711820 2
 
2.6%
711814 2
 
2.6%
711851 2
 
2.6%
703833 2
 
2.6%
Other values (29) 32
41.6%
(Missing) 14
18.2%
ValueCountFrequency (%)
41507 1
 
1.3%
41748 2
2.6%
42705 1
 
1.3%
42719 1
 
1.3%
42900 1
 
1.3%
42905 3
3.9%
42976 1
 
1.3%
43008 1
 
1.3%
43013 1
 
1.3%
702030 2
2.6%
ValueCountFrequency (%)
711891 1
 
1.3%
711857 1
 
1.3%
711854 4
5.2%
711852 1
 
1.3%
711851 2
 
2.6%
711845 1
 
1.3%
711823 4
5.2%
711820 2
 
2.6%
711814 2
 
2.6%
711813 7
9.1%

사업장명
Text

Distinct68
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size744.0 B
2024-04-21T18:40:25.045696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.5454545
Min length2

Characters and Unicode

Total characters581
Distinct characters114
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

Unique61 ?
Unique (%)79.2%

Sample

1st row우성계량증명업소
2nd row성림계량사
3rd row원호계량증명업소
4th row(주)와이케이철강
5th row북부계량증명업소
ValueCountFrequency (%)
공단계량증명업소 3
 
3.8%
달성계량증명업소 3
 
3.8%
서재계량증명업소 2
 
2.5%
우진계량증명업소 2
 
2.5%
공단산업계량증명업소 2
 
2.5%
대지상사 2
 
2.5%
쌍용계량증명업소 2
 
2.5%
화원계량증명업소 1
 
1.2%
주)비엔에이코리아 1
 
1.2%
계량증명업소 1
 
1.2%
Other values (61) 61
76.2%
2024-04-21T18:40:26.233634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 51
 
8.8%
량 51
 
8.8%
업 47
 
8.1%
소 47
 
8.1%
증 43
 
7.4%
명 43
 
7.4%
대 18
 
3.1%
주 15
 
2.6%
성 14
 
2.4%
공 13
 
2.2%
Other values (104) 239
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 549
94.5%
Open Punctuation 13
 
2.2%
Close Punctuation 13
 
2.2%
Space Separator 3
 
0.5%
Decimal Number 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 51
 
9.3%
량 51
 
9.3%
업 47
 
8.6%
소 47
 
8.6%
증 43
 
7.8%
명 43
 
7.8%
대 18
 
3.3%
주 15
 
2.7%
성 14
 
2.6%
공 13
 
2.4%
Other values (98) 207
37.7%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 549
94.5%
Common 32
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 51
 
9.3%
량 51
 
9.3%
업 47
 
8.6%
소 47
 
8.6%
증 43
 
7.8%
명 43
 
7.8%
대 18
 
3.3%
주 15
 
2.7%
성 14
 
2.6%
공 13
 
2.4%
Other values (98) 207
37.7%
Common
ValueCountFrequency (%)
( 13
40.6%
) 13
40.6%
3
 
9.4%
5 1
 
3.1%
& 1
 
3.1%
2 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 549
94.5%
ASCII 32
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 51
 
9.3%
량 51
 
9.3%
업 47
 
8.6%
소 47
 
8.6%
증 43
 
7.8%
명 43
 
7.8%
대 18
 
3.3%
주 15
 
2.7%
성 14
 
2.6%
공 13
 
2.4%
Other values (98) 207
37.7%
ASCII
ValueCountFrequency (%)
( 13
40.6%
) 13
40.6%
3
 
9.4%
5 1
 
3.1%
& 1
 
3.1%
2 1
 
3.1%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0142796 × 1013
Minimum2.0080827 × 1013
Maximum2.0210903 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:26.480012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0080827 × 1013
5-th percentile2.0090622 × 1013
Q12.0111031 × 1013
median2.0131106 × 1013
Q32.018062 × 1013
95-th percentile2.0201035 × 1013
Maximum2.0210903 × 1013
Range1.3007597 × 1011
Interquartile range (IQR)6.9589012 × 1010

Descriptive statistics

Standard deviation3.787018 × 1010
Coefficient of variation (CV)0.0018800856
Kurtosis-1.2972972
Mean2.0142796 × 1013
Median Absolute Deviation (MAD)2.9321962 × 1010
Skewness0.28086903
Sum1.5509953 × 1015
Variance1.4341505 × 1021
MonotonicityNot monotonic
2024-04-21T18:40:26.750962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090204084225 1
 
1.3%
20180703132725 1
 
1.3%
20180703132657 1
 
1.3%
20111031140048 1
 
1.3%
20170612101851 1
 
1.3%
20170327161027 1
 
1.3%
20111031140406 1
 
1.3%
20200410101012 1
 
1.3%
20191106114136 1
 
1.3%
20121115145932 1
 
1.3%
Other values (67) 67
87.0%
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 (%)
20210903140900 1
1.3%
20210426111431 1
1.3%
20210225151007 1
1.3%
20201126160034 1
1.3%
20201012161013 1
1.3%
20200902161335 1
1.3%
20200828182636 1
1.3%
20200420125949 1
1.3%
20200410101012 1
1.3%
20191106114136 1
1.3%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size744.0 B
I
69 
U
8 

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
89.6%
U 8
 
10.4%

Length

2024-04-21T18:40:26.976286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:27.144352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 69
89.6%
u 8
 
10.4%

데이터갱신일자
Date

Distinct13
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size744.0 B
Minimum2018-08-31 23:59:59
Maximum2021-09-05 00:22:49
2024-04-21T18:40:27.299814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T18:40:27.483473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing77
Missing (%)100.0%
Memory size821.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)89.0%
Missing4
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean335640.32
Minimum326192.2
Maximum354741.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:27.690842image/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 deviation6391.7687
Coefficient of variation (CV)0.019043507
Kurtosis-0.12764978
Mean335640.32
Median Absolute Deviation (MAD)4600.3315
Skewness0.4634818
Sum24501743
Variance40854708
MonotonicityNot monotonic
2024-04-21T18:40:27.933243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
345665.162766 2
 
2.6%
335126.439535 2
 
2.6%
326987.047869 2
 
2.6%
331765.493298 2
 
2.6%
330899.370928 2
 
2.6%
334282.929799 2
 
2.6%
334902.493029 2
 
2.6%
334984.946983 2
 
2.6%
343011.774837 1
 
1.3%
326773.44963 1
 
1.3%
Other values (55) 55
71.4%
(Missing) 4
 
5.2%
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
2.6%
327152.0 1
1.3%
327554.749825 1
1.3%
328137.029306 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
2.6%
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 

Distinct65
Distinct (%)89.0%
Missing4
Missing (%)5.2%
Infinite0
Infinite (%)0.0%
Mean260979.16
Minimum238774.71
Maximum271647.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size821.0 B
2024-04-21T18:40:28.386795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238774.71
5-th percentile241657.96
Q1259371.33
median263779.3
Q3265822
95-th percentile269607.35
Maximum271647.09
Range32872.386
Interquartile range (IQR)6450.6699

Descriptive statistics

Standard deviation7939.6727
Coefficient of variation (CV)0.030422631
Kurtosis1.3875097
Mean260979.16
Median Absolute Deviation (MAD)3317.1396
Skewness-1.4269556
Sum19051479
Variance63038403
MonotonicityNot monotonic
2024-04-21T18:40:28.636741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
269620.252519 2
 
2.6%
264967.821838 2
 
2.6%
263346.437143 2
 
2.6%
255196.387595 2
 
2.6%
248772.305647 2
 
2.6%
264796.577877 2
 
2.6%
264106.215422 2
 
2.6%
260340.1784 2
 
2.6%
267902.207814 1
 
1.3%
265478.266025 1
 
1.3%
Other values (55) 55
71.4%
(Missing) 4
 
5.2%
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
2.6%
250680.643647 1
1.3%
ValueCountFrequency (%)
271647.094222 1
1.3%
269818.769625 1
1.3%
269620.252519 2
2.6%
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

MISSING 

Distinct71
Distinct (%)95.9%
Missing3
Missing (%)3.9%
Memory size744.0 B
2024-04-21T18:40:29.469705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.067568
Min length1

Characters and Unicode

Total characters819
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

Unique68 ?
Unique (%)91.9%

Sample

1st row053 962 8989
2nd row053 963 0689
3rd row053 981 6767
4th row0533593996
5th row053 3583917
ValueCountFrequency (%)
053 45
26.2%
053585 6
 
3.5%
615 4
 
2.3%
053615 3
 
1.7%
591 3
 
1.7%
357 3
 
1.7%
581 3
 
1.7%
592 2
 
1.2%
585 2
 
1.2%
582 2
 
1.2%
Other values (95) 99
57.6%
2024-04-21T18:40:30.489841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 120
14.7%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 714
87.2%
Space Separator 101
 
12.3%
Dash Punctuation 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 163
22.8%
3 127
17.8%
0 120
16.8%
8 55
 
7.7%
1 49
 
6.9%
6 48
 
6.7%
2 46
 
6.4%
9 40
 
5.6%
7 38
 
5.3%
4 28
 
3.9%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 819
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 120
14.7%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 819
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 163
19.9%
3 127
15.5%
0 120
14.7%
101
12.3%
8 55
 
6.7%
1 49
 
6.0%
6 48
 
5.9%
2 46
 
5.6%
9 40
 
4.9%
7 38
 
4.6%
Other values (2) 32
 
3.9%

사업장전화번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size744.0 B
<NA>
75 
533593382
 
1
535923771
 
1

Length

Max length9
Median length4
Mean length4.1298701
Min length4

Unique

Unique2 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 75
97.4%
533593382 1
 
1.3%
535923771 1
 
1.3%

Length

2024-04-21T18:40:30.725099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T18:40:30.906394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 75
97.4%
533593382 1
 
1.3%
535923771 1
 
1.3%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(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_P3430000202034300950650000120201012<NA>1영업/정상1영업중<NA><NA><NA><NA>0533593996<NA><NA>대구광역시 서구 평리동 595-23대구광역시 서구 북비산로 121 (평리동)41748(주)와이케이철강20201012161013I2020-10-14 00:23:10.0<NA>339553.416132265409.317990533593996<NA>
45계량기증명업09_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>
56계량기증명업09_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>
67계량기증명업09_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>
78계량기증명업09_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>
89계량기증명업09_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>
910계량기증명업09_28_04_P3450000198934500120650000619891027<NA>1영업/정상1영업중<NA><NA><NA><NA>053 356 6764<NA>702815대구광역시 북구 노원동3가 232번지대구광역시 북구 노원로9길 24 (노원동3가)702083제일계량증명업소20131227155925I2018-08-31 23:59:59.0<NA>341375.359269267166.95839053 356 6764<NA>
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무소전화번호사업장전화번호
6768계량기증명업09_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>
6869계량기증명업09_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>
6970계량기증명업09_28_04_P3480000201534803260650000220150624<NA>3폐업3폐업20201123<NA><NA><NA><NA><NA>711823대구광역시 달성군 하빈면 봉촌리 652번지대구광역시 달성군 하빈면 하빈남로 305711823현대공인계량증명업소20201126160034U2020-11-28 02:40:00.0<NA>326689.760538263137.319532<NA><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_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>
7273계량기증명업09_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>
7374계량기증명업09_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>
7475계량기증명업09_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>
7576계량기증명업09_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>
7677계량기증명업09_28_04_P3480000201334803120650000120130506<NA>3폐업3폐업20160927<NA><NA><NA>0535252750<NA>711813대구광역시 달성군 다사읍 서재리 523번지대구광역시 달성군 다사읍 서재본길 49711813오성기업(주)20160927160555I2018-08-31 23:59:59.0<NA>334672.532301264618.5832190535252750<NA>