Overview

Dataset statistics

Number of variables44
Number of observations3531
Missing cells35366
Missing cells (%)22.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory379.0 B

Variable types

Numeric16
Categorical15
Text7
Unsupported4
DateTime1
Boolean1

Dataset

Description22년11월_6270000_대구광역시_06_20_01_P_세탁업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000097053&dataSetDetailId=DDI_0000097067&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (87.3%)Imbalance
위생업태명 is highly imbalanced (87.3%)Imbalance
사용시작지하층 is highly imbalanced (58.3%)Imbalance
사용끝지하층 is highly imbalanced (58.1%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3531 (100.0%) missing valuesMissing
폐업일자 has 1132 (32.1%) missing valuesMissing
휴업시작일자 has 3531 (100.0%) missing valuesMissing
휴업종료일자 has 3531 (100.0%) missing valuesMissing
재개업일자 has 3531 (100.0%) missing valuesMissing
소재지전화 has 234 (6.6%) missing valuesMissing
소재지면적 has 88 (2.5%) missing valuesMissing
도로명전체주소 has 1344 (38.1%) missing valuesMissing
도로명우편번호 has 1364 (38.6%) missing valuesMissing
좌표정보(X) has 200 (5.7%) missing valuesMissing
좌표정보(Y) has 200 (5.7%) missing valuesMissing
건물지상층수 has 824 (23.3%) missing valuesMissing
건물지하층수 has 1372 (38.9%) missing valuesMissing
사용끝지상층 has 1189 (33.7%) missing valuesMissing
조건부허가신고사유 has 3529 (99.9%) missing valuesMissing
세탁기수 has 1718 (48.7%) missing valuesMissing
여성종사자수 has 3149 (89.2%) missing valuesMissing
남성종사자수 has 3062 (86.7%) missing valuesMissing
회수건조기수 has 1818 (51.5%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -20.73692912)Skewed
번호 has unique valuesUnique
관리번호 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
건물지상층수 has 886 (25.1%) zerosZeros
건물지하층수 has 1692 (47.9%) zerosZeros
사용끝지상층 has 506 (14.3%) zerosZeros
세탁기수 has 585 (16.6%) zerosZeros
여성종사자수 has 247 (7.0%) zerosZeros
남성종사자수 has 225 (6.4%) zerosZeros
회수건조기수 has 952 (27.0%) zerosZeros

Reproduction

Analysis started2024-04-18 09:32:05.511573
Analysis finished2024-04-18 09:32:06.747053
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3531
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1766
Minimum1
Maximum3531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:06.824541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile177.5
Q1883.5
median1766
Q32648.5
95-th percentile3354.5
Maximum3531
Range3530
Interquartile range (IQR)1765

Descriptive statistics

Standard deviation1019.4562
Coefficient of variation (CV)0.57726853
Kurtosis-1.2
Mean1766
Median Absolute Deviation (MAD)883
Skewness0
Sum6235746
Variance1039291
MonotonicityStrictly increasing
2024-04-18T18:32:06.965482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2360 1
 
< 0.1%
2349 1
 
< 0.1%
2350 1
 
< 0.1%
2351 1
 
< 0.1%
2352 1
 
< 0.1%
2353 1
 
< 0.1%
2354 1
 
< 0.1%
2355 1
 
< 0.1%
2356 1
 
< 0.1%
Other values (3521) 3521
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3531 1
< 0.1%
3530 1
< 0.1%
3529 1
< 0.1%
3528 1
< 0.1%
3527 1
< 0.1%
3526 1
< 0.1%
3525 1
< 0.1%
3524 1
< 0.1%
3523 1
< 0.1%
3522 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
세탁업
3531 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
세탁업 3531
100.0%

Length

2024-04-18T18:32:07.095838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:07.194373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
세탁업 3531
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
06_20_01_P
3531 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row06_20_01_P
2nd row06_20_01_P
3rd row06_20_01_P
4th row06_20_01_P
5th row06_20_01_P

Common Values

ValueCountFrequency (%)
06_20_01_P 3531
100.0%

Length

2024-04-18T18:32:07.305786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:07.395144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
06_20_01_p 3531
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3448354.6
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:07.477877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13430000
median3450000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation20332.506
Coefficient of variation (CV)0.005896292
Kurtosis-1.1487433
Mean3448354.6
Median Absolute Deviation (MAD)20000
Skewness-0.27851949
Sum1.217614 × 1010
Variance4.1341079 × 108
MonotonicityIncreasing
2024-04-18T18:32:07.623123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 743
21.0%
3460000 639
18.1%
3420000 516
14.6%
3450000 510
14.4%
3430000 400
11.3%
3440000 350
9.9%
3480000 212
 
6.0%
3410000 161
 
4.6%
ValueCountFrequency (%)
3410000 161
 
4.6%
3420000 516
14.6%
3430000 400
11.3%
3440000 350
9.9%
3450000 510
14.4%
3460000 639
18.1%
3470000 743
21.0%
3480000 212
 
6.0%
ValueCountFrequency (%)
3480000 212
 
6.0%
3470000 743
21.0%
3460000 639
18.1%
3450000 510
14.4%
3440000 350
9.9%
3430000 400
11.3%
3420000 516
14.6%
3410000 161
 
4.6%

관리번호
Text

UNIQUE 

Distinct3531
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
2024-04-18T18:32:07.807205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters77682
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

Unique3531 ?
Unique (%)100.0%

Sample

1st row3410000-205-2003-00002
2nd row3410000-205-2008-00002
3rd row3410000-205-2003-00017
4th row3410000-205-1987-00026
5th row3410000-205-1999-00003
ValueCountFrequency (%)
3410000-205-2003-00002 1
 
< 0.1%
3460000-205-1989-00024 1
 
< 0.1%
3460000-205-1995-00003 1
 
< 0.1%
3460000-205-1999-00005 1
 
< 0.1%
3460000-205-1993-00001 1
 
< 0.1%
3460000-205-2001-00006 1
 
< 0.1%
3460000-205-2020-00004 1
 
< 0.1%
3460000-205-1990-00012 1
 
< 0.1%
3460000-205-1987-00007 1
 
< 0.1%
3460000-205-1987-00009 1
 
< 0.1%
Other values (3521) 3521
99.7%
2024-04-18T18:32:08.129896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33893
43.6%
- 10593
 
13.6%
2 7257
 
9.3%
3 5254
 
6.8%
5 4778
 
6.2%
4 4668
 
6.0%
1 3786
 
4.9%
9 3238
 
4.2%
7 1592
 
2.0%
6 1357
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67089
86.4%
Dash Punctuation 10593
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33893
50.5%
2 7257
 
10.8%
3 5254
 
7.8%
5 4778
 
7.1%
4 4668
 
7.0%
1 3786
 
5.6%
9 3238
 
4.8%
7 1592
 
2.4%
6 1357
 
2.0%
8 1266
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 10593
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77682
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33893
43.6%
- 10593
 
13.6%
2 7257
 
9.3%
3 5254
 
6.8%
5 4778
 
6.2%
4 4668
 
6.0%
1 3786
 
4.9%
9 3238
 
4.2%
7 1592
 
2.0%
6 1357
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33893
43.6%
- 10593
 
13.6%
2 7257
 
9.3%
3 5254
 
6.8%
5 4778
 
6.2%
4 4668
 
6.0%
1 3786
 
4.9%
9 3238
 
4.2%
7 1592
 
2.0%
6 1357
 
1.7%

인허가일자
Real number (ℝ)

SKEWED 

Distinct2345
Distinct (%)66.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19960791
Minimum199005
Maximum20221116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:08.272652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199005
5-th percentile19870821
Q119950116
median20011231
Q320050819
95-th percentile20150622
Maximum20221116
Range20022111
Interquartile range (IQR)100702.5

Descriptive statistics

Standard deviation935113.3
Coefficient of variation (CV)0.046847508
Kurtosis431.896
Mean19960791
Median Absolute Deviation (MAD)50812
Skewness-20.736929
Sum7.0481551 × 1010
Variance8.7443688 × 1011
MonotonicityNot monotonic
2024-04-18T18:32:08.415812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030716 218
 
6.2%
20030227 71
 
2.0%
19870720 27
 
0.8%
20030728 24
 
0.7%
20030908 17
 
0.5%
19870821 17
 
0.5%
19870608 12
 
0.3%
19870703 12
 
0.3%
19870701 11
 
0.3%
19870713 10
 
0.3%
Other values (2335) 3112
88.1%
ValueCountFrequency (%)
199005 1
< 0.1%
199105 1
< 0.1%
199112 1
< 0.1%
199204 1
< 0.1%
199605 2
0.1%
199809 1
< 0.1%
1987115 1
< 0.1%
19710301 1
< 0.1%
19791231 1
< 0.1%
19810601 1
< 0.1%
ValueCountFrequency (%)
20221116 1
< 0.1%
20221004 1
< 0.1%
20220920 1
< 0.1%
20220826 1
< 0.1%
20220818 2
0.1%
20220714 1
< 0.1%
20220629 1
< 0.1%
20220429 1
< 0.1%
20220405 1
< 0.1%
20220318 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3531
Missing (%)100.0%
Memory size31.2 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
3
2399 
1
1132 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2399
67.9%
1 1132
32.1%

Length

2024-04-18T18:32:08.555733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:08.652446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2399
67.9%
1 1132
32.1%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
폐업
2399 
영업/정상
1132 

Length

Max length5
Median length2
Mean length2.9617672
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2399
67.9%
영업/정상 1132
32.1%

Length

2024-04-18T18:32:08.746380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:08.856416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2399
67.9%
영업/정상 1132
32.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
2
2399 
1
1132 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2399
67.9%
1 1132
32.1%

Length

2024-04-18T18:32:08.971346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:09.080356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2399
67.9%
1 1132
32.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
폐업
2399 
영업
1132 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2399
67.9%
영업 1132
32.1%

Length

2024-04-18T18:32:09.175182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:09.274861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2399
67.9%
영업 1132
32.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct1624
Distinct (%)67.7%
Missing1132
Missing (%)32.1%
Infinite0
Infinite (%)0.0%
Mean20110444
Minimum19970110
Maximum20221128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:09.421888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970110
5-th percentile20031124
Q120060131
median20100910
Q320160620
95-th percentile20210521
Maximum20221128
Range251018
Interquartile range (IQR)100489.5

Descriptive statistics

Standard deviation58656.321
Coefficient of variation (CV)0.0029167094
Kurtosis-1.2060409
Mean20110444
Median Absolute Deviation (MAD)49980
Skewness0.25281354
Sum4.8244955 × 1010
Variance3.440564 × 109
MonotonicityNot monotonic
2024-04-18T18:32:09.560929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031128 47
 
1.3%
20050930 44
 
1.2%
20030924 31
 
0.9%
20031230 28
 
0.8%
20031229 25
 
0.7%
20041229 12
 
0.3%
20041230 10
 
0.3%
20090119 9
 
0.3%
20031222 9
 
0.3%
20031226 9
 
0.3%
Other values (1614) 2175
61.6%
(Missing) 1132
32.1%
ValueCountFrequency (%)
19970110 1
< 0.1%
20000110 1
< 0.1%
20000310 1
< 0.1%
20011102 1
< 0.1%
20011112 1
< 0.1%
20011116 1
< 0.1%
20020305 1
< 0.1%
20020306 1
< 0.1%
20020313 1
< 0.1%
20020417 1
< 0.1%
ValueCountFrequency (%)
20221128 2
0.1%
20221125 1
< 0.1%
20221124 2
0.1%
20221122 1
< 0.1%
20221121 1
< 0.1%
20221018 1
< 0.1%
20221012 1
< 0.1%
20221011 1
< 0.1%
20221004 2
0.1%
20220930 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3531
Missing (%)100.0%
Memory size31.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3531
Missing (%)100.0%
Memory size31.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3531
Missing (%)100.0%
Memory size31.2 KiB

소재지전화
Text

MISSING 

Distinct3115
Distinct (%)94.5%
Missing234
Missing (%)6.6%
Memory size27.7 KiB
2024-04-18T18:32:09.849520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.227176
Min length3

Characters and Unicode

Total characters37016
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

Unique2941 ?
Unique (%)89.2%

Sample

1st row053 4214559
2nd row053 423 2033
3rd row053 2540763
4th row053 4259032
5th row053 4243594
ValueCountFrequency (%)
053 3033
42.2%
764 28
 
0.4%
791 25
 
0.3%
763 21
 
0.3%
762 19
 
0.3%
754 19
 
0.3%
792 18
 
0.3%
781 17
 
0.2%
765 17
 
0.2%
752 15
 
0.2%
Other values (3212) 3971
55.3%
2024-04-18T18:32:10.226072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6643
17.9%
3 5611
15.2%
0 5063
13.7%
3922
10.6%
6 2797
7.6%
2 2659
7.2%
7 2432
 
6.6%
4 2145
 
5.8%
1 1961
 
5.3%
8 1920
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33094
89.4%
Space Separator 3922
 
10.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6643
20.1%
3 5611
17.0%
0 5063
15.3%
6 2797
8.5%
2 2659
8.0%
7 2432
 
7.3%
4 2145
 
6.5%
1 1961
 
5.9%
8 1920
 
5.8%
9 1863
 
5.6%
Space Separator
ValueCountFrequency (%)
3922
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37016
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6643
17.9%
3 5611
15.2%
0 5063
13.7%
3922
10.6%
6 2797
7.6%
2 2659
7.2%
7 2432
 
6.6%
4 2145
 
5.8%
1 1961
 
5.3%
8 1920
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6643
17.9%
3 5611
15.2%
0 5063
13.7%
3922
10.6%
6 2797
7.6%
2 2659
7.2%
7 2432
 
6.6%
4 2145
 
5.8%
1 1961
 
5.3%
8 1920
 
5.2%

소재지면적
Text

MISSING 

Distinct1281
Distinct (%)37.2%
Missing88
Missing (%)2.5%
Memory size27.7 KiB
2024-04-18T18:32:10.538784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6305547
Min length3

Characters and Unicode

Total characters15943
Distinct characters12
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

Unique930 ?
Unique (%)27.0%

Sample

1st row.00
2nd row33.00
3rd row26.64
4th row.00
5th row23.40
ValueCountFrequency (%)
00 689
 
20.0%
33.00 84
 
2.4%
30.00 59
 
1.7%
26.40 49
 
1.4%
16.50 44
 
1.3%
20.00 43
 
1.2%
19.80 41
 
1.2%
36.00 38
 
1.1%
23.10 37
 
1.1%
24.00 35
 
1.0%
Other values (1271) 2324
67.5%
2024-04-18T18:32:10.978164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4299
27.0%
. 3443
21.6%
2 1472
 
9.2%
3 1311
 
8.2%
1 1023
 
6.4%
4 961
 
6.0%
5 885
 
5.6%
6 792
 
5.0%
8 665
 
4.2%
9 554
 
3.5%
Other values (2) 538
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12499
78.4%
Other Punctuation 3444
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4299
34.4%
2 1472
 
11.8%
3 1311
 
10.5%
1 1023
 
8.2%
4 961
 
7.7%
5 885
 
7.1%
6 792
 
6.3%
8 665
 
5.3%
9 554
 
4.4%
7 537
 
4.3%
Other Punctuation
ValueCountFrequency (%)
. 3443
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15943
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4299
27.0%
. 3443
21.6%
2 1472
 
9.2%
3 1311
 
8.2%
1 1023
 
6.4%
4 961
 
6.0%
5 885
 
5.6%
6 792
 
5.0%
8 665
 
4.2%
9 554
 
3.5%
Other values (2) 538
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4299
27.0%
. 3443
21.6%
2 1472
 
9.2%
3 1311
 
8.2%
1 1023
 
6.4%
4 961
 
6.0%
5 885
 
5.6%
6 792
 
5.0%
8 665
 
4.2%
9 554
 
3.5%
Other values (2) 538
 
3.4%

소재지우편번호
Real number (ℝ)

Distinct565
Distinct (%)16.1%
Missing19
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean704579.81
Minimum700020
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:11.128668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700020
5-th percentile701170
Q1702831.75
median704803
Q3705833.25
95-th percentile711812
Maximum711891
Range11871
Interquartile range (IQR)3001.5

Descriptive statistics

Standard deviation2520.291
Coefficient of variation (CV)0.0035770128
Kurtosis1.4442743
Mean704579.81
Median Absolute Deviation (MAD)1941
Skewness0.99582675
Sum2.4744843 × 109
Variance6351866.8
MonotonicityNot monotonic
2024-04-18T18:32:11.284488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 49
 
1.4%
702040 40
 
1.1%
706170 36
 
1.0%
701804 32
 
0.9%
704060 30
 
0.8%
704932 23
 
0.7%
706838 23
 
0.7%
711812 22
 
0.6%
706831 22
 
0.6%
711852 20
 
0.6%
Other values (555) 3215
91.1%
ValueCountFrequency (%)
700020 3
0.1%
700081 1
 
< 0.1%
700092 2
0.1%
700093 1
 
< 0.1%
700100 1
 
< 0.1%
700113 1
 
< 0.1%
700120 1
 
< 0.1%
700150 1
 
< 0.1%
700160 3
0.1%
700180 1
 
< 0.1%
ValueCountFrequency (%)
711891 7
 
0.2%
711874 4
 
0.1%
711873 2
 
0.1%
711872 6
 
0.2%
711864 9
0.3%
711861 4
 
0.1%
711852 20
0.6%
711851 2
 
0.1%
711845 7
 
0.2%
711843 4
 
0.1%
Distinct3376
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
2024-04-18T18:32:11.611493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length51
Mean length25.260833
Min length16

Characters and Unicode

Total characters89196
Distinct characters353
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3229 ?
Unique (%)91.4%

Sample

1st row대구광역시 중구 삼덕동3가 300-0001번지
2nd row대구광역시 중구 동인동1가 0233-0001번지
3rd row대구광역시 중구 북내동 0031-0001번지
4th row대구광역시 중구 대봉동 10-1번지
5th row대구광역시 중구 화전동 28번지
ValueCountFrequency (%)
대구광역시 3531
 
21.2%
달서구 743
 
4.5%
수성구 639
 
3.8%
동구 516
 
3.1%
북구 510
 
3.1%
서구 400
 
2.4%
남구 350
 
2.1%
대명동 231
 
1.4%
달성군 212
 
1.3%
중구 161
 
1.0%
Other values (4151) 9336
56.1%
2024-04-18T18:32:12.160887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16111
18.1%
6933
 
7.8%
1 4719
 
5.3%
4509
 
5.1%
3938
 
4.4%
3602
 
4.0%
3544
 
4.0%
3542
 
4.0%
3420
 
3.8%
3033
 
3.4%
Other values (343) 35845
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50349
56.4%
Decimal Number 19434
 
21.8%
Space Separator 16111
 
18.1%
Dash Punctuation 2827
 
3.2%
Close Punctuation 180
 
0.2%
Open Punctuation 180
 
0.2%
Uppercase Letter 69
 
0.1%
Other Punctuation 37
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6933
13.8%
4509
 
9.0%
3938
 
7.8%
3602
 
7.2%
3544
 
7.0%
3542
 
7.0%
3420
 
6.8%
3033
 
6.0%
1274
 
2.5%
1207
 
2.4%
Other values (312) 15347
30.5%
Uppercase Letter
ValueCountFrequency (%)
A 22
31.9%
B 17
24.6%
P 10
14.5%
T 10
14.5%
K 2
 
2.9%
S 2
 
2.9%
L 2
 
2.9%
C 1
 
1.4%
D 1
 
1.4%
H 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 4719
24.3%
0 2443
12.6%
2 2406
12.4%
3 1881
 
9.7%
4 1586
 
8.2%
5 1488
 
7.7%
6 1341
 
6.9%
7 1248
 
6.4%
9 1170
 
6.0%
8 1152
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 24
64.9%
. 8
 
21.6%
/ 4
 
10.8%
@ 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
e 8
88.9%
s 1
 
11.1%
Space Separator
ValueCountFrequency (%)
16111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2827
100.0%
Close Punctuation
ValueCountFrequency (%)
) 180
100.0%
Open Punctuation
ValueCountFrequency (%)
( 180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50349
56.4%
Common 38769
43.5%
Latin 78
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6933
13.8%
4509
 
9.0%
3938
 
7.8%
3602
 
7.2%
3544
 
7.0%
3542
 
7.0%
3420
 
6.8%
3033
 
6.0%
1274
 
2.5%
1207
 
2.4%
Other values (312) 15347
30.5%
Common
ValueCountFrequency (%)
16111
41.6%
1 4719
 
12.2%
- 2827
 
7.3%
0 2443
 
6.3%
2 2406
 
6.2%
3 1881
 
4.9%
4 1586
 
4.1%
5 1488
 
3.8%
6 1341
 
3.5%
7 1248
 
3.2%
Other values (8) 2719
 
7.0%
Latin
ValueCountFrequency (%)
A 22
28.2%
B 17
21.8%
P 10
12.8%
T 10
12.8%
e 8
 
10.3%
K 2
 
2.6%
S 2
 
2.6%
L 2
 
2.6%
C 1
 
1.3%
D 1
 
1.3%
Other values (3) 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50349
56.4%
ASCII 38847
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16111
41.5%
1 4719
 
12.1%
- 2827
 
7.3%
0 2443
 
6.3%
2 2406
 
6.2%
3 1881
 
4.8%
4 1586
 
4.1%
5 1488
 
3.8%
6 1341
 
3.5%
7 1248
 
3.2%
Other values (21) 2797
 
7.2%
Hangul
ValueCountFrequency (%)
6933
13.8%
4509
 
9.0%
3938
 
7.8%
3602
 
7.2%
3544
 
7.0%
3542
 
7.0%
3420
 
6.8%
3033
 
6.0%
1274
 
2.5%
1207
 
2.4%
Other values (312) 15347
30.5%

도로명전체주소
Text

MISSING 

Distinct2157
Distinct (%)98.6%
Missing1344
Missing (%)38.1%
Memory size27.7 KiB
2024-04-18T18:32:12.517687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length52
Mean length30.532236
Min length15

Characters and Unicode

Total characters66774
Distinct characters371
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2127 ?
Unique (%)97.3%

Sample

1st row대구광역시 중구 서성로16길 28 (북내동)
2nd row대구광역시 중구 중앙대로66길 44 (남산동)
3rd row대구광역시 중구 국채보상로131길 55 (동인동1가, 시티타운상가 15호)
4th row대구광역시 중구 관덕정길 56 (남산동)
5th row대구광역시 중구 국채보상로93길 25 (대신동)
ValueCountFrequency (%)
대구광역시 2187
 
16.8%
달서구 450
 
3.5%
수성구 400
 
3.1%
북구 363
 
2.8%
1층 321
 
2.5%
동구 280
 
2.2%
서구 226
 
1.7%
남구 222
 
1.7%
달성군 158
 
1.2%
대명동 148
 
1.1%
Other values (2780) 8249
63.4%
2024-04-18T18:32:13.283223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10822
 
16.2%
4469
 
6.7%
3224
 
4.8%
1 3022
 
4.5%
2787
 
4.2%
2274
 
3.4%
2211
 
3.3%
2193
 
3.3%
( 2167
 
3.2%
) 2167
 
3.2%
Other values (361) 31438
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38424
57.5%
Decimal Number 11187
 
16.8%
Space Separator 10822
 
16.2%
Open Punctuation 2167
 
3.2%
Close Punctuation 2167
 
3.2%
Other Punctuation 1533
 
2.3%
Dash Punctuation 392
 
0.6%
Uppercase Letter 74
 
0.1%
Lowercase Letter 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4469
 
11.6%
3224
 
8.4%
2787
 
7.3%
2274
 
5.9%
2211
 
5.8%
2193
 
5.7%
2072
 
5.4%
1457
 
3.8%
958
 
2.5%
945
 
2.5%
Other values (330) 15834
41.2%
Uppercase Letter
ValueCountFrequency (%)
A 27
36.5%
B 12
16.2%
T 11
14.9%
P 11
14.9%
D 3
 
4.1%
K 3
 
4.1%
S 2
 
2.7%
C 2
 
2.7%
H 1
 
1.4%
L 1
 
1.4%
Decimal Number
ValueCountFrequency (%)
1 3022
27.0%
2 1575
14.1%
0 1293
11.6%
3 1195
 
10.7%
4 900
 
8.0%
5 858
 
7.7%
6 711
 
6.4%
7 636
 
5.7%
8 531
 
4.7%
9 466
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 1517
99.0%
@ 10
 
0.7%
. 4
 
0.3%
/ 2
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
e 7
87.5%
s 1
 
12.5%
Space Separator
ValueCountFrequency (%)
10822
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2167
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 392
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38424
57.5%
Common 28268
42.3%
Latin 82
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4469
 
11.6%
3224
 
8.4%
2787
 
7.3%
2274
 
5.9%
2211
 
5.8%
2193
 
5.7%
2072
 
5.4%
1457
 
3.8%
958
 
2.5%
945
 
2.5%
Other values (330) 15834
41.2%
Common
ValueCountFrequency (%)
10822
38.3%
1 3022
 
10.7%
( 2167
 
7.7%
) 2167
 
7.7%
2 1575
 
5.6%
, 1517
 
5.4%
0 1293
 
4.6%
3 1195
 
4.2%
4 900
 
3.2%
5 858
 
3.0%
Other values (8) 2752
 
9.7%
Latin
ValueCountFrequency (%)
A 27
32.9%
B 12
14.6%
T 11
13.4%
P 11
13.4%
e 7
 
8.5%
D 3
 
3.7%
K 3
 
3.7%
S 2
 
2.4%
C 2
 
2.4%
H 1
 
1.2%
Other values (3) 3
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38424
57.5%
ASCII 28350
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10822
38.2%
1 3022
 
10.7%
( 2167
 
7.6%
) 2167
 
7.6%
2 1575
 
5.6%
, 1517
 
5.4%
0 1293
 
4.6%
3 1195
 
4.2%
4 900
 
3.2%
5 858
 
3.0%
Other values (21) 2834
 
10.0%
Hangul
ValueCountFrequency (%)
4469
 
11.6%
3224
 
8.4%
2787
 
7.3%
2274
 
5.9%
2211
 
5.8%
2193
 
5.7%
2072
 
5.4%
1457
 
3.8%
958
 
2.5%
945
 
2.5%
Other values (330) 15834
41.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1004
Distinct (%)46.3%
Missing1364
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean42077.049
Minimum41002
Maximum43022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:13.425663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41002
5-th percentile41136
Q141551
median42129
Q342626.5
95-th percentile42928.7
Maximum43022
Range2020
Interquartile range (IQR)1075.5

Descriptive statistics

Standard deviation576.2679
Coefficient of variation (CV)0.01369554
Kurtosis-1.1962589
Mean42077.049
Median Absolute Deviation (MAD)535
Skewness-0.14006424
Sum91180966
Variance332084.7
MonotonicityNot monotonic
2024-04-18T18:32:13.569072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41569 9
 
0.3%
42679 7
 
0.2%
42644 7
 
0.2%
41534 7
 
0.2%
42970 7
 
0.2%
42819 7
 
0.2%
41450 7
 
0.2%
42915 7
 
0.2%
42452 7
 
0.2%
42446 7
 
0.2%
Other values (994) 2095
59.3%
(Missing) 1364
38.6%
ValueCountFrequency (%)
41002 3
0.1%
41005 3
0.1%
41020 1
 
< 0.1%
41022 2
 
0.1%
41024 1
 
< 0.1%
41025 1
 
< 0.1%
41026 5
0.1%
41029 1
 
< 0.1%
41033 1
 
< 0.1%
41034 2
 
0.1%
ValueCountFrequency (%)
43022 1
 
< 0.1%
43018 1
 
< 0.1%
43014 2
0.1%
43010 2
0.1%
43009 1
 
< 0.1%
43008 3
0.1%
43005 2
0.1%
43003 2
0.1%
43002 1
 
< 0.1%
43000 1
 
< 0.1%
Distinct2270
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
2024-04-18T18:32:13.815527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length5.1625602
Min length2

Characters and Unicode

Total characters18229
Distinct characters492
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1748 ?
Unique (%)49.5%

Sample

1st row진아
2nd row(주) 유니코
3rd row성주사
4th row백광
5th row백구세탁소
ValueCountFrequency (%)
현대세탁소 28
 
0.8%
세탁소 27
 
0.7%
제일세탁소 26
 
0.7%
보성세탁소 21
 
0.6%
우방세탁소 20
 
0.5%
백광세탁소 19
 
0.5%
백설세탁소 18
 
0.5%
명성세탁소 16
 
0.4%
삼성세탁소 16
 
0.4%
대성세탁소 16
 
0.4%
Other values (2271) 3431
94.3%
2024-04-18T18:32:14.214044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2535
 
13.9%
2495
 
13.7%
1655
 
9.1%
503
 
2.8%
480
 
2.6%
404
 
2.2%
388
 
2.1%
279
 
1.5%
248
 
1.4%
246
 
1.3%
Other values (482) 8996
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17893
98.2%
Space Separator 109
 
0.6%
Uppercase Letter 64
 
0.4%
Decimal Number 59
 
0.3%
Close Punctuation 35
 
0.2%
Open Punctuation 35
 
0.2%
Other Punctuation 15
 
0.1%
Lowercase Letter 14
 
0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2535
 
14.2%
2495
 
13.9%
1655
 
9.2%
503
 
2.8%
480
 
2.7%
404
 
2.3%
388
 
2.2%
279
 
1.6%
248
 
1.4%
246
 
1.4%
Other values (443) 8660
48.4%
Uppercase Letter
ValueCountFrequency (%)
A 7
10.9%
C 7
10.9%
K 6
 
9.4%
O 6
 
9.4%
E 4
 
6.2%
D 4
 
6.2%
G 4
 
6.2%
I 4
 
6.2%
L 4
 
6.2%
P 3
 
4.7%
Other values (8) 15
23.4%
Decimal Number
ValueCountFrequency (%)
1 17
28.8%
2 17
28.8%
3 9
15.3%
4 6
 
10.2%
9 3
 
5.1%
5 3
 
5.1%
8 2
 
3.4%
6 2
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 8
57.1%
r 2
 
14.3%
k 2
 
14.3%
a 1
 
7.1%
p 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 11
73.3%
, 2
 
13.3%
& 1
 
6.7%
/ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17893
98.2%
Common 258
 
1.4%
Latin 78
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2535
 
14.2%
2495
 
13.9%
1655
 
9.2%
503
 
2.8%
480
 
2.7%
404
 
2.3%
388
 
2.2%
279
 
1.6%
248
 
1.4%
246
 
1.4%
Other values (443) 8660
48.4%
Latin
ValueCountFrequency (%)
e 8
 
10.3%
A 7
 
9.0%
C 7
 
9.0%
K 6
 
7.7%
O 6
 
7.7%
E 4
 
5.1%
D 4
 
5.1%
G 4
 
5.1%
I 4
 
5.1%
L 4
 
5.1%
Other values (13) 24
30.8%
Common
ValueCountFrequency (%)
109
42.2%
) 35
 
13.6%
( 35
 
13.6%
1 17
 
6.6%
2 17
 
6.6%
. 11
 
4.3%
3 9
 
3.5%
4 6
 
2.3%
- 5
 
1.9%
9 3
 
1.2%
Other values (6) 11
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17893
98.2%
ASCII 336
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2535
 
14.2%
2495
 
13.9%
1655
 
9.2%
503
 
2.8%
480
 
2.7%
404
 
2.3%
388
 
2.2%
279
 
1.6%
248
 
1.4%
246
 
1.4%
Other values (443) 8660
48.4%
ASCII
ValueCountFrequency (%)
109
32.4%
) 35
 
10.4%
( 35
 
10.4%
1 17
 
5.1%
2 17
 
5.1%
. 11
 
3.3%
3 9
 
2.7%
e 8
 
2.4%
A 7
 
2.1%
C 7
 
2.1%
Other values (29) 81
24.1%

최종수정시점
Real number (ℝ)

Distinct2663
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0109192 × 1013
Minimum2.001091 × 1013
Maximum2.0221128 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:14.347417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001091 × 1013
5-th percentile2.002083 × 1013
Q12.0040602 × 1013
median2.0100831 × 1013
Q32.0180514 × 1013
95-th percentile2.0220214 × 1013
Maximum2.0221128 × 1013
Range2.1021816 × 1011
Interquartile range (IQR)1.3991161 × 1011

Descriptive statistics

Standard deviation6.7827066 × 1010
Coefficient of variation (CV)0.0033729384
Kurtosis-1.3617146
Mean2.0109192 × 1013
Median Absolute Deviation (MAD)6.9676948 × 1010
Skewness0.2402842
Sum7.1005557 × 1016
Variance4.6005109 × 1021
MonotonicityNot monotonic
2024-04-18T18:32:14.474849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20041126000000 78
 
2.2%
20020410000000 48
 
1.4%
20031202000000 47
 
1.3%
20030724000000 29
 
0.8%
20030603000000 26
 
0.7%
20020411000000 24
 
0.7%
20030325000000 24
 
0.7%
20030721000000 23
 
0.7%
20030122000000 22
 
0.6%
20030121000000 22
 
0.6%
Other values (2653) 3188
90.3%
ValueCountFrequency (%)
20010910000000 1
 
< 0.1%
20011005000000 4
 
0.1%
20011006000000 2
 
0.1%
20011011000000 2
 
0.1%
20020326000000 1
 
< 0.1%
20020409000000 9
 
0.3%
20020410000000 48
1.4%
20020411000000 24
0.7%
20020418000000 1
 
< 0.1%
20020423000000 1
 
< 0.1%
ValueCountFrequency (%)
20221128162817 1
< 0.1%
20221128153430 1
< 0.1%
20221128103556 1
< 0.1%
20221125134300 1
< 0.1%
20221125123256 1
< 0.1%
20221124131026 1
< 0.1%
20221124093251 1
< 0.1%
20221123173410 1
< 0.1%
20221122172312 1
< 0.1%
20221122172024 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
I
2726 
U
805 

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 2726
77.2%
U 805
 
22.8%

Length

2024-04-18T18:32:14.591133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:14.679198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2726
77.2%
u 805
 
22.8%
Distinct461
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
Minimum2018-08-31 23:59:59
Maximum2022-11-30 02:40:00
2024-04-18T18:32:14.782825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T18:32:14.912930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
일반세탁업
3410 
운동화전문세탁업
 
86
세탁업 기타
 
23
빨래방업
 
12

Length

Max length8
Median length5
Mean length5.0761824
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3410
96.6%
운동화전문세탁업 86
 
2.4%
세탁업 기타 23
 
0.7%
빨래방업 12
 
0.3%

Length

2024-04-18T18:32:15.040424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:15.141235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3410
95.9%
운동화전문세탁업 86
 
2.4%
세탁업 23
 
0.6%
기타 23
 
0.6%
빨래방업 12
 
0.3%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2869
Distinct (%)86.1%
Missing200
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean343033.89
Minimum327557.24
Maximum358060.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:15.243356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327557.24
5-th percentile334975.61
Q1339746.43
median342481
Q3346380.33
95-th percentile353138.48
Maximum358060.65
Range30503.408
Interquartile range (IQR)6633.8993

Descriptive statistics

Standard deviation5079.3049
Coefficient of variation (CV)0.014807006
Kurtosis0.22657226
Mean343033.89
Median Absolute Deviation (MAD)3270.161
Skewness0.098776659
Sum1.1426459 × 109
Variance25799338
MonotonicityNot monotonic
2024-04-18T18:32:15.386040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
338962.151491269 5
 
0.1%
347296.208543798 5
 
0.1%
338692.161634264 5
 
0.1%
338969.480757299 5
 
0.1%
341420.593871095 4
 
0.1%
340630.056274461 4
 
0.1%
354088.785458472 4
 
0.1%
345399.462012806 4
 
0.1%
339324.389142051 4
 
0.1%
347412.422846559 4
 
0.1%
Other values (2859) 3287
93.1%
(Missing) 200
 
5.7%
ValueCountFrequency (%)
327557.239553708 1
< 0.1%
327770.336985265 1
< 0.1%
327811.761116979 1
< 0.1%
327853.173808645 1
< 0.1%
328223.184090209 1
< 0.1%
328342.10797327 1
< 0.1%
328420.408085296 1
< 0.1%
328446.299883876 1
< 0.1%
328896.964041988 1
< 0.1%
329116.875999959 1
< 0.1%
ValueCountFrequency (%)
358060.647418873 1
 
< 0.1%
356610.086476575 1
 
< 0.1%
356468.087524666 1
 
< 0.1%
356388.525061719 1
 
< 0.1%
356353.404987598 1
 
< 0.1%
356310.91765893 3
0.1%
356270.185688667 1
 
< 0.1%
356267.166058634 1
 
< 0.1%
356258.185380378 1
 
< 0.1%
356175.418160422 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2869
Distinct (%)86.1%
Missing200
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean263255.52
Minimum240358.72
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:15.524875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240358.72
5-th percentile257482.92
Q1261145.49
median263197.3
Q3265480.94
95-th percentile270738.16
Maximum278091.65
Range37732.931
Interquartile range (IQR)4335.4487

Descriptive statistics

Standard deviation4134.6796
Coefficient of variation (CV)0.015705956
Kurtosis4.196211
Mean263255.52
Median Absolute Deviation (MAD)2158.4719
Skewness-0.74101626
Sum8.7690413 × 108
Variance17095576
MonotonicityNot monotonic
2024-04-18T18:32:15.696861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
262515.182501563 5
 
0.1%
261275.08308428 5
 
0.1%
259135.243156101 5
 
0.1%
257548.491948507 5
 
0.1%
272763.955160132 4
 
0.1%
272309.461235988 4
 
0.1%
260467.894846029 4
 
0.1%
263307.377365399 4
 
0.1%
259405.796433635 4
 
0.1%
259469.387426454 4
 
0.1%
Other values (2859) 3287
93.1%
(Missing) 200
 
5.7%
ValueCountFrequency (%)
240358.722944009 1
< 0.1%
240622.56148125 1
< 0.1%
240649.764741954 1
< 0.1%
240755.21422067 1
< 0.1%
240854.426297061 1
< 0.1%
240894.621331233 1
< 0.1%
240899.421415258 1
< 0.1%
242471.306039654 1
< 0.1%
242492.351659569 1
< 0.1%
244642.33521458 1
< 0.1%
ValueCountFrequency (%)
278091.653532319 1
 
< 0.1%
273737.606850141 1
 
< 0.1%
273712.08248913 1
 
< 0.1%
273593.092834991 1
 
< 0.1%
273581.899446227 1
 
< 0.1%
273524.079238797 1
 
< 0.1%
273441.249972922 2
0.1%
273288.390299726 1
 
< 0.1%
273237.600006005 1
 
< 0.1%
273228.659245823 3
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
일반세탁업
3410 
운동화전문세탁업
 
86
세탁업 기타
 
23
빨래방업
 
12

Length

Max length8
Median length5
Mean length5.0761824
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반세탁업 3410
96.6%
운동화전문세탁업 86
 
2.4%
세탁업 기타 23
 
0.7%
빨래방업 12
 
0.3%

Length

2024-04-18T18:32:15.854846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:15.965326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반세탁업 3410
95.9%
운동화전문세탁업 86
 
2.4%
세탁업 23
 
0.6%
기타 23
 
0.6%
빨래방업 12
 
0.3%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.8%
Missing824
Missing (%)23.3%
Infinite0
Infinite (%)0.0%
Mean1.6889546
Minimum0
Maximum57
Zeros886
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:16.071362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum57
Range57
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3005912
Coefficient of variation (CV)1.3621392
Kurtosis188.88763
Mean1.6889546
Median Absolute Deviation (MAD)1
Skewness10.247424
Sum4572
Variance5.2927198
MonotonicityNot monotonic
2024-04-18T18:32:16.182809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 886
25.1%
2 717
20.3%
3 528
15.0%
1 369
10.5%
4 143
 
4.0%
5 36
 
1.0%
6 7
 
0.2%
11 3
 
0.1%
20 3
 
0.1%
7 2
 
0.1%
Other values (11) 13
 
0.4%
(Missing) 824
23.3%
ValueCountFrequency (%)
0 886
25.1%
1 369
10.5%
2 717
20.3%
3 528
15.0%
4 143
 
4.0%
5 36
 
1.0%
6 7
 
0.2%
7 2
 
0.1%
8 1
 
< 0.1%
9 2
 
0.1%
ValueCountFrequency (%)
57 1
 
< 0.1%
40 1
 
< 0.1%
36 1
 
< 0.1%
32 1
 
< 0.1%
24 1
 
< 0.1%
20 3
0.1%
17 1
 
< 0.1%
15 2
0.1%
12 1
 
< 0.1%
11 3
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.4%
Missing1372
Missing (%)38.9%
Infinite0
Infinite (%)0.0%
Mean0.23668365
Minimum0
Maximum7
Zeros1692
Zeros (%)47.9%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:16.304852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.51215741
Coefficient of variation (CV)2.1638901
Kurtosis29.533934
Mean0.23668365
Median Absolute Deviation (MAD)0
Skewness3.7786375
Sum511
Variance0.26230522
MonotonicityNot monotonic
2024-04-18T18:32:16.401574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1692
47.9%
1 445
 
12.6%
2 12
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1372
38.9%
ValueCountFrequency (%)
0 1692
47.9%
1 445
 
12.6%
2 12
 
0.3%
3 4
 
0.1%
4 3
 
0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
0.1%
3 4
 
0.1%
2 12
 
0.3%
1 445
 
12.6%
0 1692
47.9%
Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
1
1730 
<NA>
1004 
0
740 
2
 
51
3
 
5

Length

Max length4
Median length1
Mean length1.8530161
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 1730
49.0%
<NA> 1004
28.4%
0 740
21.0%
2 51
 
1.4%
3 5
 
0.1%
4 1
 
< 0.1%

Length

2024-04-18T18:32:16.523577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:16.627115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1730
49.0%
na 1004
28.4%
0 740
21.0%
2 51
 
1.4%
3 5
 
0.1%
4 1
 
< 0.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing1189
Missing (%)33.7%
Infinite0
Infinite (%)0.0%
Mean0.82707088
Minimum0
Maximum10
Zeros506
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:16.728034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58126955
Coefficient of variation (CV)0.702805
Kurtosis81.523039
Mean0.82707088
Median Absolute Deviation (MAD)0
Skewness5.1319215
Sum1937
Variance0.33787429
MonotonicityNot monotonic
2024-04-18T18:32:16.822273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 1771
50.2%
0 506
 
14.3%
2 54
 
1.5%
3 6
 
0.2%
10 3
 
0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 1189
33.7%
ValueCountFrequency (%)
0 506
 
14.3%
1 1771
50.2%
2 54
 
1.5%
3 6
 
0.2%
4 1
 
< 0.1%
6 1
 
< 0.1%
10 3
 
0.1%
ValueCountFrequency (%)
10 3
 
0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
3 6
 
0.2%
2 54
 
1.5%
1 1771
50.2%
0 506
 
14.3%

사용시작지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
0
1912 
<NA>
1580 
1
 
34
4
 
2
2
 
2

Length

Max length4
Median length1
Mean length2.3423959
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1912
54.1%
<NA> 1580
44.7%
1 34
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2024-04-18T18:32:16.928334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:17.033486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1912
54.1%
na 1580
44.7%
1 34
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
<NA>
1860 
0
1631 
1
 
35
4
 
2
2
 
2

Length

Max length4
Median length4
Mean length2.5802889
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1860
52.7%
0 1631
46.2%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%

Length

2024-04-18T18:32:17.144863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:17.264270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1860
52.7%
0 1631
46.2%
1 35
 
1.0%
4 2
 
0.1%
2 2
 
0.1%
6 1
 
< 0.1%
Distinct2
Distinct (%)100.0%
Missing3529
Missing (%)99.9%
Memory size27.7 KiB
2024-04-18T18:32:17.429461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length70
Mean length70
Min length58

Characters and Unicode

Total characters140
Distinct characters75
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

Unique2 ?
Unique (%)100.0%

Sample

1st row폐업,지위승계등 금지(과태료50만원체납),'05,'07년 위생교육미필 2007.05.07현재행정처분진행중
2nd row가설건축물 존치기간(2007.11.30까지)만료시 존치기간 연장, 이전 또는 자진폐업을 하여야 하며 이를 이행하지 않을시 영업신고의 효력이 소멸됨.
ValueCountFrequency (%)
폐업,지위승계등 1
 
5.3%
자진폐업을 1
 
5.3%
효력이 1
 
5.3%
영업신고의 1
 
5.3%
않을시 1
 
5.3%
이행하지 1
 
5.3%
이를 1
 
5.3%
하며 1
 
5.3%
하여야 1
 
5.3%
또는 1
 
5.3%
Other values (9) 9
47.4%
2024-04-18T18:32:17.742561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
12.1%
0 10
 
7.1%
. 5
 
3.6%
7 4
 
2.9%
, 4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.1%
3
 
2.1%
3
 
2.1%
Other values (65) 83
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
61.4%
Decimal Number 22
 
15.7%
Space Separator 17
 
12.1%
Other Punctuation 11
 
7.9%
Close Punctuation 2
 
1.4%
Open Punctuation 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Decimal Number
ValueCountFrequency (%)
0 10
45.5%
7 4
 
18.2%
5 3
 
13.6%
2 2
 
9.1%
1 2
 
9.1%
3 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 5
45.5%
, 4
36.4%
' 2
 
18.2%
Space Separator
ValueCountFrequency (%)
17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
61.4%
Common 54
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%
Common
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
61.4%
ASCII 54
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17
31.5%
0 10
18.5%
. 5
 
9.3%
7 4
 
7.4%
, 4
 
7.4%
5 3
 
5.6%
2 2
 
3.7%
' 2
 
3.7%
1 2
 
3.7%
) 2
 
3.7%
Other values (2) 3
 
5.6%
Hangul
ValueCountFrequency (%)
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
2
 
2.3%
Other values (53) 59
68.6%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
<NA>
3530 
20070213
 
1

Length

Max length8
Median length4
Mean length4.0011328
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3530
> 99.9%
20070213 1
 
< 0.1%

Length

2024-04-18T18:32:17.875122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:17.996085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3530
> 99.9%
20070213 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
<NA>
3530 
20071130
 
1

Length

Max length8
Median length4
Mean length4.0011328
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3530
> 99.9%
20071130 1
 
< 0.1%

Length

2024-04-18T18:32:18.101500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:18.216164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3530
> 99.9%
20071130 1
 
< 0.1%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size27.7 KiB
<NA>
1848 
임대
1423 
자가
260 

Length

Max length4
Median length4
Mean length3.046729
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1848
52.3%
임대 1423
40.3%
자가 260
 
7.4%

Length

2024-04-18T18:32:18.320837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T18:32:18.443411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1848
52.3%
임대 1423
40.3%
자가 260
 
7.4%

세탁기수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.6%
Missing1718
Missing (%)48.7%
Infinite0
Infinite (%)0.0%
Mean1.2614451
Minimum0
Maximum20
Zeros585
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:18.535957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2157164
Coefficient of variation (CV)0.96374894
Kurtosis32.152962
Mean1.2614451
Median Absolute Deviation (MAD)1
Skewness2.7627835
Sum2287
Variance1.4779663
MonotonicityNot monotonic
2024-04-18T18:32:18.646849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 586
 
16.6%
0 585
 
16.6%
1 457
 
12.9%
3 127
 
3.6%
4 42
 
1.2%
5 7
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
20 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 1718
48.7%
ValueCountFrequency (%)
0 585
16.6%
1 457
12.9%
2 586
16.6%
3 127
 
3.6%
4 42
 
1.2%
5 7
 
0.2%
6 4
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
9 1
 
< 0.1%
7 3
 
0.1%
6 4
 
0.1%
5 7
 
0.2%
4 42
 
1.2%
3 127
 
3.6%
2 586
16.6%
1 457
12.9%
0 585
16.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.4%
Missing3149
Missing (%)89.2%
Infinite0
Infinite (%)0.0%
Mean0.4973822
Minimum0
Maximum20
Zeros247
Zeros (%)7.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:18.755113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum20
Range20
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3646237
Coefficient of variation (CV)2.7436119
Kurtosis118.34192
Mean0.4973822
Median Absolute Deviation (MAD)0
Skewness9.4217211
Sum190
Variance1.8621979
MonotonicityNot monotonic
2024-04-18T18:32:18.858513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 247
 
7.0%
1 124
 
3.5%
2 3
 
0.1%
3 2
 
0.1%
5 2
 
0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 3149
89.2%
ValueCountFrequency (%)
0 247
7.0%
1 124
3.5%
2 3
 
0.1%
3 2
 
0.1%
5 2
 
0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
20 1
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
5 2
 
0.1%
3 2
 
0.1%
2 3
 
0.1%
1 124
3.5%
0 247
7.0%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.5%
Missing3062
Missing (%)86.7%
Infinite0
Infinite (%)0.0%
Mean0.60341151
Minimum0
Maximum9
Zeros225
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:18.970642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.79291001
Coefficient of variation (CV)1.3140452
Kurtosis35.828312
Mean0.60341151
Median Absolute Deviation (MAD)1
Skewness4.1898273
Sum283
Variance0.62870629
MonotonicityNot monotonic
2024-04-18T18:32:19.060234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 225
 
6.4%
1 224
 
6.3%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 3062
86.7%
ValueCountFrequency (%)
0 225
6.4%
1 224
6.3%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 1
 
< 0.1%
4 2
 
0.1%
3 3
 
0.1%
2 13
 
0.4%
1 224
6.3%
0 225
6.4%

회수건조기수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.5%
Missing1818
Missing (%)51.5%
Infinite0
Infinite (%)0.0%
Mean0.47810858
Minimum0
Maximum10
Zeros952
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size31.2 KiB
2024-04-18T18:32:19.159807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.63089698
Coefficient of variation (CV)1.3195684
Kurtosis38.487148
Mean0.47810858
Median Absolute Deviation (MAD)0
Skewness3.4708011
Sum819
Variance0.398031
MonotonicityNot monotonic
2024-04-18T18:32:19.290277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 952
27.0%
1 729
20.6%
2 21
 
0.6%
3 6
 
0.2%
4 2
 
0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1818
51.5%
ValueCountFrequency (%)
0 952
27.0%
1 729
20.6%
2 21
 
0.6%
3 6
 
0.2%
4 2
 
0.1%
5 1
 
< 0.1%
7 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%
4 2
 
0.1%
3 6
 
0.2%
2 21
 
0.6%
1 729
20.6%
0 952
27.0%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
False
3530 
True
 
1
ValueCountFrequency (%)
False 3530
> 99.9%
True 1
 
< 0.1%
2024-04-18T18:32:19.406044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조기수다중이용업소여부
01세탁업06_20_01_P34100003410000-205-2003-0000219921014<NA>3폐업2폐업20090121<NA><NA><NA>053 4214559<NA>700413대구광역시 중구 삼덕동3가 300-0001번지<NA><NA>진아20070910103800I2018-08-31 23:59:59.0일반세탁업344952.904168263899.71513일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
12세탁업06_20_01_P34100003410000-205-2008-0000220080807<NA>3폐업2폐업20080820<NA><NA><NA>053 423 2033.00700421대구광역시 중구 동인동1가 0233-0001번지<NA><NA>(주) 유니코20080807111117I2018-08-31 23:59:59.0일반세탁업344637.632881264667.618454일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
23세탁업06_20_01_P34100003410000-205-2003-0001720030908<NA>3폐업2폐업20160322<NA><NA><NA>053 254076333.00700340대구광역시 중구 북내동 0031-0001번지대구광역시 중구 서성로16길 28 (북내동)41919성주사20120223143632I2018-08-31 23:59:59.0일반세탁업343440.170776264831.180532일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
34세탁업06_20_01_P34100003410000-205-1987-0002619871127<NA>3폐업2폐업20060526<NA><NA><NA>053 425903226.64700809대구광역시 중구 대봉동 10-1번지<NA><NA>백광20040214000000I2018-08-31 23:59:59.0일반세탁업344983.552432263576.591255일반세탁업1<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
45세탁업06_20_01_P34100003410000-205-1999-0000319990827<NA>3폐업2폐업20081212<NA><NA><NA>053 4243594.00700100대구광역시 중구 화전동 28번지<NA><NA>백구세탁소20070828133813I2018-08-31 23:59:59.0일반세탁업343995.332261264874.973286일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
56세탁업06_20_01_P34100003410000-205-1987-0001319870819<NA>3폐업2폐업20090108<NA><NA><NA>053 257190023.40700360대구광역시 중구 도원동 3번지<NA><NA>고속사20070828103854I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
67세탁업06_20_01_P34100003410000-205-1987-0001419870819<NA>3폐업2폐업20060125<NA><NA><NA>053 254069024.60700252대구광역시 중구 서문로2가 38-3번지<NA><NA>은성20040213000000I2018-08-31 23:59:59.0일반세탁업343110.028589264537.556467일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
78세탁업06_20_01_P34100003410000-205-1988-0001119880620<NA>3폐업2폐업20090119<NA><NA><NA>053 255055823.62700330대구광역시 중구 서야동 28번지<NA><NA>제일사20070828104205I2018-08-31 23:59:59.0일반세탁업343055.831616264767.125282일반세탁업2<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
89세탁업06_20_01_P34100003410000-205-1987-0001519870819<NA>3폐업2폐업20090108<NA><NA><NA>053 257347622.57700819대구광역시 중구 대신동 1082번지<NA><NA>재건20090205170430I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
910세탁업06_20_01_P34100003410000-205-1987-0001819870819<NA>3폐업2폐업20090120<NA><NA><NA>0530423312010.42700803대구광역시 중구 남산동 659-9번지<NA><NA>광명20040216000000I2018-08-31 23:59:59.0일반세탁업<NA><NA>일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조기수다중이용업소여부
35213522세탁업06_20_01_P34800003480000-205-2004-0000520040914<NA>1영업/정상1영업<NA><NA><NA><NA>053 588801129.92711815대구광역시 달성군 다사읍 죽곡리 129-1 강창하이츠 104호대구광역시 달성군 다사읍 달구벌대로 812, 104호 (강창하이츠)42915강창하이츠세탁소20200916131305U2020-09-18 02:40:00.0일반세탁업331916.550581263290.230568일반세탁업<NA><NA>11<NA><NA><NA><NA><NA>임대<NA><NA><NA>1N
35223523세탁업06_20_01_P34800003480000-205-2001-0000220010626<NA>1영업/정상1영업<NA><NA><NA><NA>053 644122229.25711832대구광역시 달성군 화원읍 명곡리 133 명곡 미래빌 3단지 상가 201호대구광역시 달성군 화원읍 명곡로 26 (명곡 미래빌 3단지 상가 201호)42959미래빌세탁20211209193653U2021-12-11 02:40:00.0일반세탁업335210.886707256282.434898일반세탁업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
35233524세탁업06_20_01_P34800003480000-205-1999-0000419990118<NA>1영업/정상1영업<NA><NA><NA><NA>053 586641733.00711812대구광역시 달성군 다사읍 매곡리 719-3 강창한서꼼빠니아타운 203/204대구광역시 달성군 다사읍 달구벌대로 802-1, 203동 204호 (강창한서꼼빠니아타운)42915한서세탁소20211209201917U2021-12-11 02:40:00.0일반세탁업331781.789518263289.821736일반세탁업2<NA>11<NA><NA><NA><NA><NA>자가<NA><NA><NA><NA>N
35243525세탁업06_20_01_P34800003480000-205-2001-0001020011212<NA>1영업/정상1영업<NA><NA><NA><NA>053 644466625.00711832대구광역시 달성군 화원읍 명곡리 220 명곡미래빌 5단지 상가동 103호대구광역시 달성군 화원읍 명천로 243, 상가동 103호 (명곡미래빌 5단지)429605단지세탁20211209192358U2021-12-11 02:40:00.0일반세탁업334873.400609256334.726827일반세탁업2<NA>11<NA><NA><NA><NA><NA>임대<NA><NA><NA><NA>N
35253526세탁업06_20_01_P34800003480000-205-1999-0000919990208<NA>1영업/정상1영업<NA><NA><NA><NA>053 611877043.77711872대구광역시 달성군 현풍면 부리 448-2번지대구광역시 달성군 현풍면 현풍중앙로16길 942999한일세탁소20180921144405U2018-09-21 23:59:59.0일반세탁업330533.782763245084.899689일반세탁업1<NA>11<NA><NA><NA><NA><NA>임대<NA><NA><NA><NA>N
35263527세탁업06_20_01_P34800003480000-205-1998-0000319980430<NA>1영업/정상1영업<NA><NA><NA><NA>053 614798156.10711891대구광역시 달성군 구지면 창리 446-3대구광역시 달성군 구지면 창리로11길 58-643010경성세탁소20211209192543U2021-12-11 02:40:00.0일반세탁업327811.761117240899.421415일반세탁업4<NA>11<NA><NA><NA><NA><NA>임대<NA><NA><NA><NA>N
35273528세탁업06_20_01_P34800003480000-205-1987-0000619870604<NA>1영업/정상1영업<NA><NA><NA><NA>053 767503023.10711864대구광역시 달성군 가창면 용계리 69-4번지대구광역시 달성군 가창면 가창로 1097, 1층42933아모레세탁소20170411100417I2018-08-31 23:59:59.0일반세탁업346564.465283256962.407489일반세탁업000000<NA><NA><NA><NA>1<NA><NA>0N
35283529세탁업06_20_01_P34800003480000-205-2007-0000220070404<NA>1영업/정상1영업<NA><NA><NA><NA>053 611124477.01<NA>대구광역시 달성군 현풍읍 중리 237 외 1필지대구광역시 달성군 현풍읍 현풍중앙로10길 57 (외 1필지)42996기분좋은크리닝20211209193044U2021-12-11 02:40:00.0일반세탁업330894.544268244883.054949일반세탁업3<NA>11<NA><NA><NA><NA><NA>임대3<NA><NA>1N
35293530세탁업06_20_01_P34800003480000-205-2000-0000220001113<NA>1영업/정상1영업<NA><NA><NA><NA>053 591235426.88711815대구광역시 달성군 다사읍 죽곡리 373번지 e-편한세상 301/103대구광역시 달성군 다사읍 죽곡1길 42 (e-편한세상 301/103)42918이편한세탁소20110812112027I2018-08-31 23:59:59.0일반세탁업332102.190328262589.09627일반세탁업311100<NA><NA><NA>임대0<NA><NA>1N
35303531세탁업06_20_01_P34800003480000-205-2000-0000120000529<NA>1영업/정상1영업<NA><NA><NA><NA>053 644487119.80711832대구광역시 달성군 화원읍 명곡리 139번지 명곡 미래빌 4동 101호대구광역시 달성군 화원읍 화암로 120, 4동 101호 (명곡 미래빌)42959주공세탁소20050728000000I2018-08-31 23:59:59.0일반세탁업335510.581294256371.924899일반세탁업2<NA>11<NA><NA><NA><NA><NA>자가<NA><NA><NA><NA>N