Overview

Dataset statistics

Number of variables50
Number of observations814
Missing cells9459
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory343.5 KiB
Average record size in memory432.2 B

Variable types

Numeric16
Categorical18
Text7
Unsupported6
DateTime1
Boolean2

Dataset

Description6270000_대구광역시_11_44_01_P_목욕장업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000090791&dataSetDetailId=DDI_0000090789&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (72.3%)Imbalance
위생업태명 is highly imbalanced (72.3%)Imbalance
의자수 is highly imbalanced (55.0%)Imbalance
다중이용업소여부 is highly imbalanced (84.0%)Imbalance
인허가취소일자 has 814 (100.0%) missing valuesMissing
폐업일자 has 279 (34.3%) missing valuesMissing
휴업시작일자 has 814 (100.0%) missing valuesMissing
휴업종료일자 has 814 (100.0%) missing valuesMissing
재개업일자 has 814 (100.0%) missing valuesMissing
소재지전화 has 29 (3.6%) missing valuesMissing
도로명전체주소 has 330 (40.5%) missing valuesMissing
도로명우편번호 has 340 (41.8%) missing valuesMissing
좌표정보(X) has 47 (5.8%) missing valuesMissing
좌표정보(Y) has 47 (5.8%) missing valuesMissing
건물지상층수 has 176 (21.6%) missing valuesMissing
건물지하층수 has 237 (29.1%) missing valuesMissing
사용시작지상층 has 224 (27.5%) missing valuesMissing
사용끝지상층 has 285 (35.0%) missing valuesMissing
욕실수 has 241 (29.6%) missing valuesMissing
조건부허가신고사유 has 813 (99.9%) missing valuesMissing
조건부허가시작일자 has 814 (100.0%) missing valuesMissing
조건부허가종료일자 has 814 (100.0%) missing valuesMissing
여성종사자수 has 761 (93.5%) missing valuesMissing
남성종사자수 has 759 (93.2%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -22.9754012)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
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 128 (15.7%) zerosZeros
건물지하층수 has 170 (20.9%) zerosZeros
사용시작지상층 has 148 (18.2%) zerosZeros
사용끝지상층 has 88 (10.8%) zerosZeros
욕실수 has 186 (22.9%) zerosZeros
여성종사자수 has 35 (4.3%) zerosZeros
남성종사자수 has 35 (4.3%) zerosZeros

Reproduction

Analysis started2023-12-10 19:29:49.293574
Analysis finished2023-12-10 19:29:50.847955
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct814
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean407.5
Minimum1
Maximum814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:50.969771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile41.65
Q1204.25
median407.5
Q3610.75
95-th percentile773.35
Maximum814
Range813
Interquartile range (IQR)406.5

Descriptive statistics

Standard deviation235.12585
Coefficient of variation (CV)0.57699596
Kurtosis-1.2
Mean407.5
Median Absolute Deviation (MAD)203.5
Skewness0
Sum331705
Variance55284.167
MonotonicityStrictly increasing
2023-12-11T04:29:51.247365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
548 1
 
0.1%
538 1
 
0.1%
539 1
 
0.1%
540 1
 
0.1%
541 1
 
0.1%
542 1
 
0.1%
543 1
 
0.1%
544 1
 
0.1%
545 1
 
0.1%
Other values (804) 804
98.8%
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 (%)
814 1
0.1%
813 1
0.1%
812 1
0.1%
811 1
0.1%
810 1
0.1%
809 1
0.1%
808 1
0.1%
807 1
0.1%
806 1
0.1%
805 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
목욕장업
814 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목욕장업 814
100.0%

Length

2023-12-11T04:29:51.498765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:51.646344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 814
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
11_44_01_P
814 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_44_01_P
2nd row11_44_01_P
3rd row11_44_01_P
4th row11_44_01_P
5th row11_44_01_P

Common Values

ValueCountFrequency (%)
11_44_01_P 814
100.0%

Length

2023-12-11T04:29:51.792079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:51.930917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 814
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3444926.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:52.069546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13422500
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)37500

Descriptive statistics

Standard deviation21047.173
Coefficient of variation (CV)0.0061096149
Kurtosis-1.2307107
Mean3444926.3
Median Absolute Deviation (MAD)20000
Skewness-0.13209957
Sum2.80417 × 109
Variance4.4298349 × 108
MonotonicityIncreasing
2023-12-11T04:29:52.253727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 141
17.3%
3420000 134
16.5%
3450000 130
16.0%
3460000 130
16.0%
3430000 90
11.1%
3440000 80
9.8%
3410000 70
8.6%
3480000 39
 
4.8%
ValueCountFrequency (%)
3410000 70
8.6%
3420000 134
16.5%
3430000 90
11.1%
3440000 80
9.8%
3450000 130
16.0%
3460000 130
16.0%
3470000 141
17.3%
3480000 39
 
4.8%
ValueCountFrequency (%)
3480000 39
 
4.8%
3470000 141
17.3%
3460000 130
16.0%
3450000 130
16.0%
3440000 80
9.8%
3430000 90
11.1%
3420000 134
16.5%
3410000 70
8.6%

관리번호
Text

UNIQUE 

Distinct814
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T04:29:52.575665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters17908
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

Unique814 ?
Unique (%)100.0%

Sample

1st row3410000-202-1976-00001
2nd row3410000-202-1968-00001
3rd row3410000-202-1996-00001
4th row3410000-202-1970-00002
5th row3410000-202-1993-00001
ValueCountFrequency (%)
3410000-202-1976-00001 1
 
0.1%
3460000-202-1998-00008 1
 
0.1%
3460000-202-2002-00003 1
 
0.1%
3460000-202-2003-00003 1
 
0.1%
3460000-202-1997-00028 1
 
0.1%
3460000-202-1997-00027 1
 
0.1%
3460000-202-1997-00019 1
 
0.1%
3460000-202-2002-00002 1
 
0.1%
3460000-202-1997-00037 1
 
0.1%
3460000-202-2007-00001 1
 
0.1%
Other values (804) 804
98.8%
2023-12-11T04:29:53.013116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7956
44.4%
- 2442
 
13.6%
2 2430
 
13.6%
3 1190
 
6.6%
4 1068
 
6.0%
1 925
 
5.2%
9 764
 
4.3%
7 403
 
2.3%
5 260
 
1.5%
6 256
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15466
86.4%
Dash Punctuation 2442
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7956
51.4%
2 2430
 
15.7%
3 1190
 
7.7%
4 1068
 
6.9%
1 925
 
6.0%
9 764
 
4.9%
7 403
 
2.6%
5 260
 
1.7%
6 256
 
1.7%
8 214
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2442
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17908
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7956
44.4%
- 2442
 
13.6%
2 2430
 
13.6%
3 1190
 
6.6%
4 1068
 
6.0%
1 925
 
5.2%
9 764
 
4.3%
7 403
 
2.3%
5 260
 
1.5%
6 256
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17908
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7956
44.4%
- 2442
 
13.6%
2 2430
 
13.6%
3 1190
 
6.6%
4 1068
 
6.0%
1 925
 
5.2%
9 764
 
4.3%
7 403
 
2.3%
5 260
 
1.5%
6 256
 
1.4%

인허가일자
Real number (ℝ)

Distinct656
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19974411
Minimum19601125
Maximum20210618
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:53.242709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19601125
5-th percentile19741223
Q119950212
median19990118
Q320030720
95-th percentile20140583
Maximum20210618
Range609493
Interquartile range (IQR)80508

Descriptive statistics

Standard deviation104306.75
Coefficient of variation (CV)0.0052220186
Kurtosis0.88316666
Mean19974411
Median Absolute Deviation (MAD)40599.5
Skewness-0.74784835
Sum1.6259171 × 1010
Variance1.0879897 × 1010
MonotonicityNot monotonic
2023-12-11T04:29:53.468304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030718 31
 
3.8%
19970513 27
 
3.3%
19970220 21
 
2.6%
19970721 12
 
1.5%
19970701 10
 
1.2%
19970221 8
 
1.0%
20031128 6
 
0.7%
19970619 5
 
0.6%
19970723 4
 
0.5%
19970120 3
 
0.4%
Other values (646) 687
84.4%
ValueCountFrequency (%)
19601125 1
0.1%
19640303 1
0.1%
19661019 1
0.1%
19671116 1
0.1%
19671130 1
0.1%
19680803 1
0.1%
19690208 1
0.1%
19690901 1
0.1%
19700824 1
0.1%
19700827 1
0.1%
ValueCountFrequency (%)
20210618 1
0.1%
20210119 1
0.1%
20201211 1
0.1%
20200116 1
0.1%
20191203 1
0.1%
20190911 1
0.1%
20190902 2
0.2%
20190703 1
0.1%
20190215 1
0.1%
20190117 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3
535 
1
279 

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 (%)
3 535
65.7%
1 279
34.3%

Length

2023-12-11T04:29:53.647746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:53.795922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 535
65.7%
1 279
34.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
535 
영업/정상
279 

Length

Max length5
Median length2
Mean length3.0282555
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 535
65.7%
영업/정상 279
34.3%

Length

2023-12-11T04:29:53.932260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:54.069446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 535
65.7%
영업/정상 279
34.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2
535 
1
279 

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 (%)
2 535
65.7%
1 279
34.3%

Length

2023-12-11T04:29:54.192002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:54.295841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 535
65.7%
1 279
34.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
535 
영업
279 

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 535
65.7%
영업 279
34.3%

Length

2023-12-11T04:29:54.399086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:29:54.488997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 535
65.7%
영업 279
34.3%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct478
Distinct (%)89.3%
Missing279
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean20064568
Minimum200201
Maximum20210622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:54.663937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200201
5-th percentile20030406
Q120050769
median20090119
Q320150716
95-th percentile20200649
Maximum20210622
Range20010421
Interquartile range (IQR)99947.5

Descriptive statistics

Standard deviation862337.7
Coefficient of variation (CV)0.042978135
Kurtosis530.22953
Mean20064568
Median Absolute Deviation (MAD)49696
Skewness-22.975401
Sum1.0734544 × 1010
Variance7.4362631 × 1011
MonotonicityNot monotonic
2023-12-11T04:29:54.839130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030718 9
 
1.1%
20090119 6
 
0.7%
20031112 4
 
0.5%
20190701 3
 
0.4%
20031229 3
 
0.4%
20120111 3
 
0.4%
20041103 3
 
0.4%
20060419 3
 
0.4%
20050117 3
 
0.4%
20090108 3
 
0.4%
Other values (468) 495
60.8%
(Missing) 279
34.3%
ValueCountFrequency (%)
200201 1
0.1%
20010321 1
0.1%
20010404 1
0.1%
20010418 1
0.1%
20010502 1
0.1%
20010620 1
0.1%
20011022 1
0.1%
20020304 1
0.1%
20020326 1
0.1%
20020410 1
0.1%
ValueCountFrequency (%)
20210622 1
0.1%
20210604 1
0.1%
20210602 1
0.1%
20210527 1
0.1%
20210510 1
0.1%
20210503 1
0.1%
20210406 1
0.1%
20210322 1
0.1%
20210305 1
0.1%
20210303 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

소재지전화
Text

MISSING 

Distinct757
Distinct (%)96.4%
Missing29
Missing (%)3.6%
Memory size6.5 KiB
2023-12-11T04:29:55.110368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.747771
Min length7

Characters and Unicode

Total characters8437
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

Unique729 ?
Unique (%)92.9%

Sample

1st row053 4240045
2nd row053 5548141
3rd row053 2524466
4th row053 4296062
5th row053 4239984
ValueCountFrequency (%)
053 647
40.4%
767 8
 
0.5%
781 6
 
0.4%
753 6
 
0.4%
743 6
 
0.4%
752 5
 
0.3%
765 5
 
0.3%
323 4
 
0.2%
792 4
 
0.2%
763 4
 
0.2%
Other values (832) 908
56.6%
2023-12-11T04:29:55.566175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1498
17.8%
0 1278
15.1%
3 1257
14.9%
825
9.8%
6 601
7.1%
2 594
 
7.0%
7 542
 
6.4%
1 489
 
5.8%
4 469
 
5.6%
8 450
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7612
90.2%
Space Separator 825
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1498
19.7%
0 1278
16.8%
3 1257
16.5%
6 601
7.9%
2 594
 
7.8%
7 542
 
7.1%
1 489
 
6.4%
4 469
 
6.2%
8 450
 
5.9%
9 434
 
5.7%
Space Separator
ValueCountFrequency (%)
825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8437
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1498
17.8%
0 1278
15.1%
3 1257
14.9%
825
9.8%
6 601
7.1%
2 594
 
7.0%
7 542
 
6.4%
1 489
 
5.8%
4 469
 
5.6%
8 450
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1498
17.8%
0 1278
15.1%
3 1257
14.9%
825
9.8%
6 601
7.1%
2 594
 
7.0%
7 542
 
6.4%
1 489
 
5.8%
4 469
 
5.6%
8 450
 
5.3%

소재지면적
Text

Distinct755
Distinct (%)92.9%
Missing1
Missing (%)0.1%
Memory size6.5 KiB
2023-12-11T04:29:55.935199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2829028
Min length3

Characters and Unicode

Total characters5108
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

Unique717 ?
Unique (%)88.2%

Sample

1st row198.00
2nd row.00
3rd row328.88
4th row131.25
5th row574.70
ValueCountFrequency (%)
00 16
 
2.0%
660.00 5
 
0.6%
450.00 3
 
0.4%
492.00 3
 
0.4%
165.00 3
 
0.4%
360.00 2
 
0.2%
289.80 2
 
0.2%
650.00 2
 
0.2%
458.00 2
 
0.2%
144.00 2
 
0.2%
Other values (745) 773
95.1%
2023-12-11T04:29:56.537652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 865
16.9%
. 813
15.9%
1 411
8.0%
4 409
8.0%
5 402
7.9%
2 389
7.6%
3 386
7.6%
6 361
7.1%
8 339
 
6.6%
7 312
 
6.1%
Other values (2) 421
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4152
81.3%
Other Punctuation 956
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 865
20.8%
1 411
9.9%
4 409
9.9%
5 402
9.7%
2 389
9.4%
3 386
9.3%
6 361
8.7%
8 339
 
8.2%
7 312
 
7.5%
9 278
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 813
85.0%
, 143
 
15.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5108
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 865
16.9%
. 813
15.9%
1 411
8.0%
4 409
8.0%
5 402
7.9%
2 389
7.6%
3 386
7.6%
6 361
7.1%
8 339
 
6.6%
7 312
 
6.1%
Other values (2) 421
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 865
16.9%
. 813
15.9%
1 411
8.0%
4 409
8.0%
5 402
7.9%
2 389
7.6%
3 386
7.6%
6 361
7.1%
8 339
 
6.6%
7 312
 
6.1%
Other values (2) 421
8.2%

소재지우편번호
Real number (ℝ)

Distinct380
Distinct (%)46.9%
Missing3
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean704193.05
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:56.682456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700806
Q1701866.5
median703844
Q3705823.5
95-th percentile706851
Maximum711892
Range11882
Interquartile range (IQR)3957

Descriptive statistics

Standard deviation2555.4358
Coefficient of variation (CV)0.0036288853
Kurtosis1.3176047
Mean704193.05
Median Absolute Deviation (MAD)1979
Skewness0.93994971
Sum5.7110056 × 108
Variance6530252.4
MonotonicityNot monotonic
2023-12-11T04:29:56.825714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704060 10
 
1.2%
704080 9
 
1.1%
702040 9
 
1.1%
703812 7
 
0.9%
704837 7
 
0.9%
701846 6
 
0.7%
711852 6
 
0.7%
705828 6
 
0.7%
706170 6
 
0.7%
706833 6
 
0.7%
Other values (370) 739
90.8%
ValueCountFrequency (%)
700010 1
 
0.1%
700020 3
0.4%
700082 1
 
0.1%
700111 1
 
0.1%
700160 4
0.5%
700180 1
 
0.1%
700192 2
0.2%
700210 1
 
0.1%
700230 1
 
0.1%
700261 1
 
0.1%
ValueCountFrequency (%)
711892 1
 
0.1%
711891 1
 
0.1%
711874 2
 
0.2%
711872 1
 
0.1%
711863 1
 
0.1%
711861 1
 
0.1%
711858 1
 
0.1%
711852 6
0.7%
711844 2
 
0.2%
711842 1
 
0.1%

소재지전체주소
Text

Distinct751
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T04:29:57.395036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length22.697789
Min length16

Characters and Unicode

Total characters18476
Distinct characters193
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

Unique692 ?
Unique (%)85.0%

Sample

1st row대구광역시 중구 동인동1가 262-3번지
2nd row대구광역시 중구 달성동 116-0014번지
3rd row대구광역시 중구 남성로 10-2번지
4th row대구광역시 중구 인교동 215-2번지
5th row대구광역시 중구 삼덕동2가 213-5번지
ValueCountFrequency (%)
대구광역시 814
23.6%
달서구 141
 
4.1%
동구 134
 
3.9%
수성구 130
 
3.8%
북구 130
 
3.8%
서구 90
 
2.6%
남구 80
 
2.3%
중구 70
 
2.0%
대명동 51
 
1.5%
달성군 39
 
1.1%
Other values (987) 1775
51.4%
2023-12-11T04:29:57.855955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3454
18.7%
구 1599
 
8.7%
동 932
 
5.0%
대 899
 
4.9%
1 887
 
4.8%
시 821
 
4.4%
광 815
 
4.4%
역 815
 
4.4%
지 748
 
4.0%
- 694
 
3.8%
Other values (183) 6812
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10290
55.7%
Decimal Number 3941
 
21.3%
Space Separator 3454
 
18.7%
Dash Punctuation 694
 
3.8%
Other Punctuation 54
 
0.3%
Open Punctuation 19
 
0.1%
Close Punctuation 19
 
0.1%
Uppercase Letter 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1599
15.5%
동 932
 
9.1%
대 899
 
8.7%
시 821
 
8.0%
광 815
 
7.9%
역 815
 
7.9%
지 748
 
7.3%
번 669
 
6.5%
서 242
 
2.4%
성 235
 
2.3%
Other values (163) 2515
24.4%
Decimal Number
ValueCountFrequency (%)
1 887
22.5%
2 540
13.7%
0 434
11.0%
3 381
9.7%
4 351
 
8.9%
5 329
 
8.3%
6 289
 
7.3%
7 270
 
6.9%
8 238
 
6.0%
9 222
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 52
96.3%
. 1
 
1.9%
@ 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
B 2
50.0%
Space Separator
ValueCountFrequency (%)
3454
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 694
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10290
55.7%
Common 8182
44.3%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1599
15.5%
동 932
 
9.1%
대 899
 
8.7%
시 821
 
8.0%
광 815
 
7.9%
역 815
 
7.9%
지 748
 
7.3%
번 669
 
6.5%
서 242
 
2.4%
성 235
 
2.3%
Other values (163) 2515
24.4%
Common
ValueCountFrequency (%)
3454
42.2%
1 887
 
10.8%
- 694
 
8.5%
2 540
 
6.6%
0 434
 
5.3%
3 381
 
4.7%
4 351
 
4.3%
5 329
 
4.0%
6 289
 
3.5%
7 270
 
3.3%
Other values (8) 553
 
6.8%
Latin
ValueCountFrequency (%)
A 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10290
55.7%
ASCII 8186
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3454
42.2%
1 887
 
10.8%
- 694
 
8.5%
2 540
 
6.6%
0 434
 
5.3%
3 381
 
4.7%
4 351
 
4.3%
5 329
 
4.0%
6 289
 
3.5%
7 270
 
3.3%
Other values (10) 557
 
6.8%
Hangul
ValueCountFrequency (%)
구 1599
15.5%
동 932
 
9.1%
대 899
 
8.7%
시 821
 
8.0%
광 815
 
7.9%
역 815
 
7.9%
지 748
 
7.3%
번 669
 
6.5%
서 242
 
2.4%
성 235
 
2.3%
Other values (163) 2515
24.4%

도로명전체주소
Text

MISSING 

Distinct478
Distinct (%)98.8%
Missing330
Missing (%)40.5%
Memory size6.5 KiB
2023-12-11T04:29:58.192495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length25.797521
Min length20

Characters and Unicode

Total characters12486
Distinct characters235
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique472 ?
Unique (%)97.5%

Sample

1st row대구광역시 중구 국채보상로 611, 7층 (문화동)
2nd row대구광역시 중구 국채보상로 611, 23층 (문화동)
3rd row대구광역시 중구 달성공원로 2 (대신동)
4th row대구광역시 중구 남산로13길 17 (남산동, 보성황실사우나 116동 지하1호)
5th row대구광역시 중구 경상감영길 117-7, 3층 (향촌동)
ValueCountFrequency (%)
대구광역시 484
 
18.8%
달서구 83
 
3.2%
동구 81
 
3.2%
수성구 76
 
3.0%
북구 71
 
2.8%
서구 54
 
2.1%
남구 50
 
1.9%
중구 36
 
1.4%
대명동 34
 
1.3%
달성군 33
 
1.3%
Other values (840) 1569
61.0%
2023-12-11T04:29:58.891089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2087
 
16.7%
구 996
 
8.0%
대 628
 
5.0%
동 616
 
4.9%
시 492
 
3.9%
역 488
 
3.9%
광 485
 
3.9%
( 460
 
3.7%
) 460
 
3.7%
로 457
 
3.7%
Other values (225) 5317
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7343
58.8%
Space Separator 2087
 
16.7%
Decimal Number 1881
 
15.1%
Open Punctuation 460
 
3.7%
Close Punctuation 460
 
3.7%
Other Punctuation 152
 
1.2%
Dash Punctuation 77
 
0.6%
Math Symbol 15
 
0.1%
Uppercase Letter 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 996
 
13.6%
대 628
 
8.6%
동 616
 
8.4%
시 492
 
6.7%
역 488
 
6.6%
광 485
 
6.6%
로 457
 
6.2%
길 240
 
3.3%
서 175
 
2.4%
성 171
 
2.3%
Other values (204) 2595
35.3%
Decimal Number
ValueCountFrequency (%)
1 385
20.5%
2 306
16.3%
3 227
12.1%
0 167
8.9%
5 163
8.7%
4 155
8.2%
6 150
 
8.0%
7 127
 
6.8%
8 102
 
5.4%
9 99
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 150
98.7%
· 1
 
0.7%
. 1
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
A 6
54.5%
B 4
36.4%
C 1
 
9.1%
Space Separator
ValueCountFrequency (%)
2087
100.0%
Open Punctuation
ValueCountFrequency (%)
( 460
100.0%
Close Punctuation
ValueCountFrequency (%)
) 460
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7343
58.8%
Common 5132
41.1%
Latin 11
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 996
 
13.6%
대 628
 
8.6%
동 616
 
8.4%
시 492
 
6.7%
역 488
 
6.6%
광 485
 
6.6%
로 457
 
6.2%
길 240
 
3.3%
서 175
 
2.4%
성 171
 
2.3%
Other values (204) 2595
35.3%
Common
ValueCountFrequency (%)
2087
40.7%
( 460
 
9.0%
) 460
 
9.0%
1 385
 
7.5%
2 306
 
6.0%
3 227
 
4.4%
0 167
 
3.3%
5 163
 
3.2%
4 155
 
3.0%
6 150
 
2.9%
Other values (8) 572
 
11.1%
Latin
ValueCountFrequency (%)
A 6
54.5%
B 4
36.4%
C 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7343
58.8%
ASCII 5142
41.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2087
40.6%
( 460
 
8.9%
) 460
 
8.9%
1 385
 
7.5%
2 306
 
6.0%
3 227
 
4.4%
0 167
 
3.2%
5 163
 
3.2%
4 155
 
3.0%
6 150
 
2.9%
Other values (10) 582
 
11.3%
Hangul
ValueCountFrequency (%)
구 996
 
13.6%
대 628
 
8.6%
동 616
 
8.4%
시 492
 
6.7%
역 488
 
6.6%
광 485
 
6.6%
로 457
 
6.2%
길 240
 
3.3%
서 175
 
2.4%
성 171
 
2.3%
Other values (204) 2595
35.3%
None
ValueCountFrequency (%)
· 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct387
Distinct (%)81.6%
Missing340
Missing (%)41.8%
Infinite0
Infinite (%)0.0%
Mean42013.135
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:29:59.095780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41112
Q141535.25
median41977
Q342495.25
95-th percentile42938.7
Maximum43024
Range2024
Interquartile range (IQR)960

Descriptive statistics

Standard deviation584.85873
Coefficient of variation (CV)0.013920854
Kurtosis-1.1524577
Mean42013.135
Median Absolute Deviation (MAD)483.5
Skewness-0.028093168
Sum19914226
Variance342059.73
MonotonicityNot monotonic
2023-12-11T04:29:59.328583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41112 3
 
0.4%
42678 3
 
0.4%
42661 3
 
0.4%
42728 3
 
0.4%
42770 3
 
0.4%
42620 3
 
0.4%
42612 3
 
0.4%
42117 3
 
0.4%
42288 3
 
0.4%
41436 3
 
0.4%
Other values (377) 444
54.5%
(Missing) 340
41.8%
ValueCountFrequency (%)
41000 2
0.2%
41001 1
 
0.1%
41002 1
 
0.1%
41005 1
 
0.1%
41007 1
 
0.1%
41008 3
0.4%
41027 1
 
0.1%
41034 1
 
0.1%
41036 1
 
0.1%
41042 1
 
0.1%
ValueCountFrequency (%)
43024 1
0.1%
43013 1
0.1%
43003 1
0.1%
43000 1
0.1%
42996 1
0.1%
42994 1
0.1%
42986 1
0.1%
42985 1
0.1%
42980 1
0.1%
42979 1
0.1%

사업장명
Text

Distinct710
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T04:29:59.777736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length5.1117936
Min length2

Characters and Unicode

Total characters4161
Distinct characters303
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique637 ?
Unique (%)78.3%

Sample

1st row세종여자전용사우나
2nd row청수
3rd row다보
4th row일광
5th row삼보탕
ValueCountFrequency (%)
사우나 7
 
0.8%
한일목욕탕 5
 
0.6%
그린목욕탕 5
 
0.6%
호수탕 4
 
0.5%
동영목욕탕 4
 
0.5%
대청사우나 4
 
0.5%
대동탕 4
 
0.5%
청수목욕탕 4
 
0.5%
대림목욕탕 4
 
0.5%
천일탕 3
 
0.4%
Other values (723) 805
94.8%
2023-12-11T04:30:00.511751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 495
 
11.9%
목 278
 
6.7%
욕 278
 
6.7%
우 157
 
3.8%
사 153
 
3.7%
나 153
 
3.7%
스 104
 
2.5%
대 87
 
2.1%
동 74
 
1.8%
천 73
 
1.8%
Other values (293) 2309
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4057
97.5%
Space Separator 37
 
0.9%
Open Punctuation 22
 
0.5%
Close Punctuation 22
 
0.5%
Decimal Number 10
 
0.2%
Uppercase Letter 8
 
0.2%
Other Punctuation 4
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 495
 
12.2%
목 278
 
6.9%
욕 278
 
6.9%
우 157
 
3.9%
사 153
 
3.8%
나 153
 
3.8%
스 104
 
2.6%
대 87
 
2.1%
동 74
 
1.8%
천 73
 
1.8%
Other values (276) 2205
54.4%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
G 2
25.0%
O 1
12.5%
P 1
12.5%
M 1
12.5%
S 1
12.5%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
2 3
30.0%
0 2
20.0%
5 2
20.0%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
＆ 1
25.0%
/ 1
25.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4057
97.5%
Common 95
 
2.3%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 495
 
12.2%
목 278
 
6.9%
욕 278
 
6.9%
우 157
 
3.9%
사 153
 
3.8%
나 153
 
3.8%
스 104
 
2.6%
대 87
 
2.1%
동 74
 
1.8%
천 73
 
1.8%
Other values (276) 2205
54.4%
Common
ValueCountFrequency (%)
37
38.9%
( 22
23.2%
) 22
23.2%
3 3
 
3.2%
2 3
 
3.2%
0 2
 
2.1%
, 2
 
2.1%
5 2
 
2.1%
＆ 1
 
1.1%
/ 1
 
1.1%
Latin
ValueCountFrequency (%)
T 2
22.2%
G 2
22.2%
O 1
11.1%
P 1
11.1%
M 1
11.1%
S 1
11.1%
e 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4057
97.5%
ASCII 103
 
2.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 495
 
12.2%
목 278
 
6.9%
욕 278
 
6.9%
우 157
 
3.9%
사 153
 
3.8%
나 153
 
3.8%
스 104
 
2.6%
대 87
 
2.1%
동 74
 
1.8%
천 73
 
1.8%
Other values (276) 2205
54.4%
ASCII
ValueCountFrequency (%)
37
35.9%
( 22
21.4%
) 22
21.4%
3 3
 
2.9%
2 3
 
2.9%
0 2
 
1.9%
T 2
 
1.9%
, 2
 
1.9%
5 2
 
1.9%
G 2
 
1.9%
Other values (6) 6
 
5.8%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct698
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0120419 × 1013
Minimum2.0020201 × 1013
Maximum2.0210728 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:00.774416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020201 × 1013
5-th percentile2.002083 × 1013
Q12.004091 × 1013
median2.0120216 × 1013
Q32.0191024 × 1013
95-th percentile2.0210356 × 1013
Maximum2.0210728 × 1013
Range1.905271 × 1011
Interquartile range (IQR)1.501136 × 1011

Descriptive statistics

Standard deviation7.1030798 × 1010
Coefficient of variation (CV)0.0035302843
Kurtosis-1.6203405
Mean2.0120419 × 1013
Median Absolute Deviation (MAD)7.0997522 × 1010
Skewness-0.098186377
Sum1.6378021 × 1016
Variance5.0453743 × 1021
MonotonicityNot monotonic
2023-12-11T04:30:01.041905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030927000000 21
 
2.6%
20020709000000 17
 
2.1%
20031027000000 13
 
1.6%
20030805000000 10
 
1.2%
20030804000000 9
 
1.1%
20020913000000 4
 
0.5%
20020408000000 4
 
0.5%
20031209000000 3
 
0.4%
20041029000000 3
 
0.4%
20020830000000 3
 
0.4%
Other values (688) 727
89.3%
ValueCountFrequency (%)
20020201000000 2
 
0.2%
20020408000000 4
 
0.5%
20020409000000 3
 
0.4%
20020411000000 1
 
0.1%
20020625000000 3
 
0.4%
20020626000000 1
 
0.1%
20020709000000 17
2.1%
20020710000000 3
 
0.4%
20020711000000 1
 
0.1%
20020712000000 1
 
0.1%
ValueCountFrequency (%)
20210728095333 1
0.1%
20210722093812 1
0.1%
20210714103525 1
0.1%
20210713161359 1
0.1%
20210702142250 1
0.1%
20210630152156 1
0.1%
20210622095304 1
0.1%
20210621165514 1
0.1%
20210621102859 1
0.1%
20210621102114 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
I
542 
U
272 

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 542
66.6%
U 272
33.4%

Length

2023-12-11T04:30:01.276927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:01.453788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 542
66.6%
u 272
33.4%

데이터갱신일자
Date

Distinct177
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2018-08-31 23:59:59
Maximum2021-07-30 02:40:00
2023-12-11T04:30:01.688420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T04:30:01.911580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
공동탕업
731 
공동탕업+찜질시설서비스영업
 
45
찜질시설서비스영업
 
17
한증막업
 
16
목욕장업 기타
 
5

Length

Max length14
Median length4
Mean length4.6756757
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 731
89.8%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
2.0%
목욕장업 기타 5
 
0.6%

Length

2023-12-11T04:30:02.169733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:02.407670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 731
89.3%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
2.0%
목욕장업 5
 
0.6%
기타 5
 
0.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct662
Distinct (%)86.3%
Missing47
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean343344.4
Minimum327293.91
Maximum356189.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:02.647235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327293.91
5-th percentile335728.27
Q1340192.46
median343243.77
Q3346534.65
95-th percentile351594.77
Maximum356189.2
Range28895.287
Interquartile range (IQR)6342.1908

Descriptive statistics

Standard deviation4729.2681
Coefficient of variation (CV)0.013774123
Kurtosis0.685658
Mean343344.4
Median Absolute Deviation (MAD)3187.3044
Skewness-0.072825648
Sum2.6334516 × 108
Variance22365977
MonotonicityNot monotonic
2023-12-11T04:30:02.931901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
337346.648864 4
 
0.5%
340286.680164 3
 
0.4%
340616.952958 3
 
0.4%
355698.459984 3
 
0.4%
339273.069927 3
 
0.4%
345310.581197 3
 
0.4%
338849.57742 3
 
0.4%
338536.724925 3
 
0.4%
343184.151781 3
 
0.4%
342666.445914 3
 
0.4%
Other values (652) 736
90.4%
(Missing) 47
 
5.8%
ValueCountFrequency (%)
327293.913425 1
0.1%
327529.514434 1
0.1%
328293.62359 1
0.1%
328965.130661 1
0.1%
330272.445579 1
0.1%
330338.711441 1
0.1%
330342.686681 1
0.1%
330497.842814 1
0.1%
330573.646469 1
0.1%
330585.519076 1
0.1%
ValueCountFrequency (%)
356189.20016 1
 
0.1%
355698.459984 3
0.4%
355655.045544 1
 
0.1%
355590.766869 1
 
0.1%
354755.033317 1
 
0.1%
354722.988899 1
 
0.1%
354683.486531 1
 
0.1%
354615.507123 1
 
0.1%
354510.585982 1
 
0.1%
354463.424853 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct662
Distinct (%)86.3%
Missing47
Missing (%)5.8%
Infinite0
Infinite (%)0.0%
Mean263533.71
Minimum238769.81
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:03.199327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238769.81
5-th percentile257720.96
Q1261396.79
median263846.27
Q3265817.53
95-th percentile270113.29
Maximum278091.65
Range39321.841
Interquartile range (IQR)4420.7395

Descriptive statistics

Standard deviation4333.6018
Coefficient of variation (CV)0.016444203
Kurtosis5.4803776
Mean263533.71
Median Absolute Deviation (MAD)2188.1649
Skewness-0.92897979
Sum2.0213035 × 108
Variance18780104
MonotonicityNot monotonic
2023-12-11T04:30:03.470001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
258035.007517 4
 
0.5%
271242.256968 3
 
0.4%
266219.271086 3
 
0.4%
275787.590179 3
 
0.4%
269989.71536 3
 
0.4%
261330.273815 3
 
0.4%
257972.210093 3
 
0.4%
260859.548667 3
 
0.4%
264080.683793 3
 
0.4%
263256.489079 3
 
0.4%
Other values (652) 736
90.4%
(Missing) 47
 
5.8%
ValueCountFrequency (%)
238769.812522 1
0.1%
240746.717574 1
0.1%
244719.0 1
0.1%
244828.005203 1
0.1%
244853.241728 1
0.1%
244859.344723 1
0.1%
245205.925241 1
0.1%
248338.042553 1
0.1%
248523.534088 1
0.1%
248583.689867 1
0.1%
ValueCountFrequency (%)
278091.653532 1
 
0.1%
278070.885647 1
 
0.1%
278029.090204 1
 
0.1%
277507.397404 1
 
0.1%
277462.879247 1
 
0.1%
276154.019724 1
 
0.1%
275787.590179 3
0.4%
273077.919394 1
 
0.1%
272997.707548 1
 
0.1%
272960.724753 1
 
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
공동탕업
731 
공동탕업+찜질시설서비스영업
 
45
찜질시설서비스영업
 
17
한증막업
 
16
목욕장업 기타
 
5

Length

Max length14
Median length4
Mean length4.6756757
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 731
89.8%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
2.0%
목욕장업 기타 5
 
0.6%

Length

2023-12-11T04:30:03.740280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:03.967363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 731
89.3%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
2.0%
목욕장업 5
 
0.6%
기타 5
 
0.6%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)3.1%
Missing176
Missing (%)21.6%
Infinite0
Infinite (%)0.0%
Mean3.6520376
Minimum0
Maximum42
Zeros128
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:04.170039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q35
95-th percentile8
Maximum42
Range42
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.54977
Coefficient of variation (CV)0.97199711
Kurtosis33.076218
Mean3.6520376
Median Absolute Deviation (MAD)2
Skewness4.2017576
Sum2330
Variance12.600867
MonotonicityNot monotonic
2023-12-11T04:30:04.359865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 128
15.7%
3 120
14.7%
4 120
14.7%
5 97
11.9%
2 65
 
8.0%
6 38
 
4.7%
7 20
 
2.5%
9 11
 
1.4%
1 11
 
1.4%
8 9
 
1.1%
Other values (10) 19
 
2.3%
(Missing) 176
21.6%
ValueCountFrequency (%)
0 128
15.7%
1 11
 
1.4%
2 65
8.0%
3 120
14.7%
4 120
14.7%
5 97
11.9%
6 38
 
4.7%
7 20
 
2.5%
8 9
 
1.1%
9 11
 
1.4%
ValueCountFrequency (%)
42 1
 
0.1%
31 1
 
0.1%
28 1
 
0.1%
23 2
 
0.2%
20 1
 
0.1%
19 1
 
0.1%
18 1
 
0.1%
17 1
 
0.1%
11 4
0.5%
10 6
0.7%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.2%
Missing237
Missing (%)29.1%
Infinite0
Infinite (%)0.0%
Mean0.89948007
Minimum0
Maximum9
Zeros170
Zeros (%)20.9%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:04.562283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.89769172
Coefficient of variation (CV)0.9980118
Kurtosis24.71436
Mean0.89948007
Median Absolute Deviation (MAD)0
Skewness3.4210838
Sum519
Variance0.80585042
MonotonicityNot monotonic
2023-12-11T04:30:04.733703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 334
41.0%
0 170
20.9%
2 56
 
6.9%
4 7
 
0.9%
3 7
 
0.9%
9 2
 
0.2%
6 1
 
0.1%
(Missing) 237
29.1%
ValueCountFrequency (%)
0 170
20.9%
1 334
41.0%
2 56
 
6.9%
3 7
 
0.9%
4 7
 
0.9%
6 1
 
0.1%
9 2
 
0.2%
ValueCountFrequency (%)
9 2
 
0.2%
6 1
 
0.1%
4 7
 
0.9%
3 7
 
0.9%
2 56
 
6.9%
1 334
41.0%
0 170
20.9%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.5%
Missing224
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean1.379661
Minimum0
Maximum23
Zeros148
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:04.911471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.25
median1
Q32
95-th percentile4
Maximum23
Range23
Interquartile range (IQR)1.75

Descriptive statistics

Standard deviation1.522305
Coefficient of variation (CV)1.1033906
Kurtosis69.641854
Mean1.379661
Median Absolute Deviation (MAD)1
Skewness5.6523322
Sum814
Variance2.3174124
MonotonicityNot monotonic
2023-12-11T04:30:05.087720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 219
26.9%
2 154
18.9%
0 148
18.2%
3 37
 
4.5%
4 15
 
1.8%
5 7
 
0.9%
6 5
 
0.6%
7 4
 
0.5%
23 1
 
0.1%
(Missing) 224
27.5%
ValueCountFrequency (%)
0 148
18.2%
1 219
26.9%
2 154
18.9%
3 37
 
4.5%
4 15
 
1.8%
5 7
 
0.9%
6 5
 
0.6%
7 4
 
0.5%
23 1
 
0.1%
ValueCountFrequency (%)
23 1
 
0.1%
7 4
 
0.5%
6 5
 
0.6%
5 7
 
0.9%
4 15
 
1.8%
3 37
 
4.5%
2 154
18.9%
1 219
26.9%
0 148
18.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.9%
Missing285
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean2.3724008
Minimum0
Maximum23
Zeros88
Zeros (%)10.8%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:05.269897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33
95-th percentile5
Maximum23
Range23
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8141056
Coefficient of variation (CV)0.76467082
Kurtosis31.307593
Mean2.3724008
Median Absolute Deviation (MAD)1
Skewness3.1711183
Sum1255
Variance3.2909793
MonotonicityNot monotonic
2023-12-11T04:30:05.450822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 191
23.5%
3 120
14.7%
0 88
 
10.8%
4 52
 
6.4%
1 34
 
4.2%
5 24
 
2.9%
6 10
 
1.2%
8 5
 
0.6%
7 4
 
0.5%
23 1
 
0.1%
(Missing) 285
35.0%
ValueCountFrequency (%)
0 88
10.8%
1 34
 
4.2%
2 191
23.5%
3 120
14.7%
4 52
 
6.4%
5 24
 
2.9%
6 10
 
1.2%
7 4
 
0.5%
8 5
 
0.6%
23 1
 
0.1%
ValueCountFrequency (%)
23 1
 
0.1%
8 5
 
0.6%
7 4
 
0.5%
6 10
 
1.2%
5 24
 
2.9%
4 52
 
6.4%
3 120
14.7%
2 191
23.5%
1 34
 
4.2%
0 88
10.8%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
357 
0
352 
1
97 
2
 
8

Length

Max length4
Median length1
Mean length2.3157248
Min length1

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> 357
43.9%
0 352
43.2%
1 97
 
11.9%
2 8
 
1.0%

Length

2023-12-11T04:30:05.661846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:05.853485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 357
43.9%
0 352
43.2%
1 97
 
11.9%
2 8
 
1.0%

사용끝지하층
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
416 
0
282 
1
107 
2
 
6
3
 
3

Length

Max length4
Median length4
Mean length2.5331695
Min length1

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> 416
51.1%
0 282
34.6%
1 107
 
13.1%
2 6
 
0.7%
3 3
 
0.4%

Length

2023-12-11T04:30:06.057325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:06.250896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 416
51.1%
0 282
34.6%
1 107
 
13.1%
2 6
 
0.7%
3 3
 
0.4%

한실수
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
0
428 
<NA>
385 
2
 
1

Length

Max length4
Median length1
Mean length2.4189189
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 (%)
0 428
52.6%
<NA> 385
47.3%
2 1
 
0.1%

Length

2023-12-11T04:30:06.454201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:06.632575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 428
52.6%
na 385
47.3%
2 1
 
0.1%

양실수
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
0
428 
<NA>
385 
34
 
1

Length

Max length4
Median length1
Mean length2.4201474
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 (%)
0 428
52.6%
<NA> 385
47.3%
34 1
 
0.1%

Length

2023-12-11T04:30:06.841975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:07.041874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 428
52.6%
na 385
47.3%
34 1
 
0.1%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)2.4%
Missing241
Missing (%)29.6%
Infinite0
Infinite (%)0.0%
Mean1.7539267
Minimum0
Maximum22
Zeros186
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:07.231744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile5
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.9180335
Coefficient of variation (CV)1.0935654
Kurtosis24.981915
Mean1.7539267
Median Absolute Deviation (MAD)0
Skewness3.401007
Sum1005
Variance3.6788526
MonotonicityNot monotonic
2023-12-11T04:30:07.413629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 302
37.1%
0 186
22.9%
4 39
 
4.8%
1 14
 
1.7%
6 14
 
1.7%
8 5
 
0.6%
5 4
 
0.5%
10 2
 
0.2%
3 2
 
0.2%
7 1
 
0.1%
Other values (4) 4
 
0.5%
(Missing) 241
29.6%
ValueCountFrequency (%)
0 186
22.9%
1 14
 
1.7%
2 302
37.1%
3 2
 
0.2%
4 39
 
4.8%
5 4
 
0.5%
6 14
 
1.7%
7 1
 
0.1%
8 5
 
0.6%
9 1
 
0.1%
ValueCountFrequency (%)
22 1
 
0.1%
12 1
 
0.1%
11 1
 
0.1%
10 2
 
0.2%
9 1
 
0.1%
8 5
 
0.6%
7 1
 
0.1%
6 14
 
1.7%
5 4
 
0.5%
4 39
4.8%

발한실여부
Boolean

Distinct2
Distinct (%)0.2%
Missing3
Missing (%)0.4%
Memory size1.7 KiB
False
476 
True
335 
(Missing)
 
3
ValueCountFrequency (%)
False 476
58.5%
True 335
41.2%
(Missing) 3
 
0.4%
2023-12-11T04:30:07.611787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
0
427 
<NA>
383 
3
 
2
4
 
1
6
 
1

Length

Max length4
Median length1
Mean length2.4115479
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 427
52.5%
<NA> 383
47.1%
3 2
 
0.2%
4 1
 
0.1%
6 1
 
0.1%

Length

2023-12-11T04:30:07.801002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:08.419822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 427
52.5%
na 383
47.1%
3 2
 
0.2%
4 1
 
0.1%
6 1
 
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing813
Missing (%)99.9%
Memory size6.5 KiB
2023-12-11T04:30:08.750347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters44
Distinct characters35
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

Unique1 ?
Unique (%)100.0%

Sample

1st row폐업,지위승계등금지(시간외청소년출입):2007.05.07(월)현재 행정처분진행중
ValueCountFrequency (%)
폐업,지위승계등금지(시간외청소년출입):2007.05.07(월)현재 1
50.0%
행정처분진행중 1
50.0%
2023-12-11T04:30:09.302293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
 
9.1%
( 2
 
4.5%
행 2
 
4.5%
7 2
 
4.5%
. 2
 
4.5%
) 2
 
4.5%
지 2
 
4.5%
정 1
 
2.3%
처 1
 
2.3%
1
 
2.3%
Other values (25) 25
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27
61.4%
Decimal Number 8
 
18.2%
Other Punctuation 4
 
9.1%
Open Punctuation 2
 
4.5%
Close Punctuation 2
 
4.5%
Space Separator 1
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
행 2
 
7.4%
지 2
 
7.4%
정 1
 
3.7%
처 1
 
3.7%
재 1
 
3.7%
현 1
 
3.7%
월 1
 
3.7%
분 1
 
3.7%
진 1
 
3.7%
폐 1
 
3.7%
Other values (15) 15
55.6%
Decimal Number
ValueCountFrequency (%)
0 4
50.0%
7 2
25.0%
5 1
 
12.5%
2 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
: 1
25.0%
, 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27
61.4%
Common 17
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
행 2
 
7.4%
지 2
 
7.4%
정 1
 
3.7%
처 1
 
3.7%
재 1
 
3.7%
현 1
 
3.7%
월 1
 
3.7%
분 1
 
3.7%
진 1
 
3.7%
폐 1
 
3.7%
Other values (15) 15
55.6%
Common
ValueCountFrequency (%)
0 4
23.5%
( 2
11.8%
7 2
11.8%
. 2
11.8%
) 2
11.8%
1
 
5.9%
: 1
 
5.9%
5 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
61.4%
ASCII 17
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
23.5%
( 2
11.8%
7 2
11.8%
. 2
11.8%
) 2
11.8%
1
 
5.9%
: 1
 
5.9%
5 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%
Hangul
ValueCountFrequency (%)
행 2
 
7.4%
지 2
 
7.4%
정 1
 
3.7%
처 1
 
3.7%
재 1
 
3.7%
현 1
 
3.7%
월 1
 
3.7%
분 1
 
3.7%
진 1
 
3.7%
폐 1
 
3.7%
Other values (15) 15
55.6%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing814
Missing (%)100.0%
Memory size7.3 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
464 
자가
237 
임대
113 

Length

Max length4
Median length4
Mean length3.1400491
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> 464
57.0%
자가 237
29.1%
임대 113
 
13.9%

Length

2023-12-11T04:30:09.533916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:09.747780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 464
57.0%
자가 237
29.1%
임대 113
 
13.9%

세탁기수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
456 
0
358 

Length

Max length4
Median length4
Mean length2.6805897
Min length1

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> 456
56.0%
0 358
44.0%

Length

2023-12-11T04:30:09.941288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:10.143462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 456
56.0%
0 358
44.0%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)11.3%
Missing761
Missing (%)93.5%
Infinite0
Infinite (%)0.0%
Mean0.83018868
Minimum0
Maximum7
Zeros35
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:10.297539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4509393
Coefficient of variation (CV)1.7477224
Kurtosis5.9337976
Mean0.83018868
Median Absolute Deviation (MAD)0
Skewness2.2312323
Sum44
Variance2.105225
MonotonicityNot monotonic
2023-12-11T04:30:10.487666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 35
 
4.3%
2 8
 
1.0%
3 4
 
0.5%
1 4
 
0.5%
7 1
 
0.1%
5 1
 
0.1%
(Missing) 761
93.5%
ValueCountFrequency (%)
0 35
4.3%
1 4
 
0.5%
2 8
 
1.0%
3 4
 
0.5%
5 1
 
0.1%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
5 1
 
0.1%
3 4
 
0.5%
2 8
 
1.0%
1 4
 
0.5%
0 35
4.3%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)10.9%
Missing759
Missing (%)93.2%
Infinite0
Infinite (%)0.0%
Mean0.89090909
Minimum0
Maximum7
Zeros35
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T04:30:10.669674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.5
95-th percentile3.6
Maximum7
Range7
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.5235525
Coefficient of variation (CV)1.7101099
Kurtosis4.795319
Mean0.89090909
Median Absolute Deviation (MAD)0
Skewness2.1143401
Sum49
Variance2.3212121
MonotonicityNot monotonic
2023-12-11T04:30:10.843712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 35
 
4.3%
2 7
 
0.9%
1 6
 
0.7%
3 4
 
0.5%
5 2
 
0.2%
7 1
 
0.1%
(Missing) 759
93.2%
ValueCountFrequency (%)
0 35
4.3%
1 6
 
0.7%
2 7
 
0.9%
3 4
 
0.5%
5 2
 
0.2%
7 1
 
0.1%
ValueCountFrequency (%)
7 1
 
0.1%
5 2
 
0.2%
3 4
 
0.5%
2 7
 
0.9%
1 6
 
0.7%
0 35
4.3%

회수건조수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
477 
0
337 

Length

Max length4
Median length4
Mean length2.7579853
Min length1

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> 477
58.6%
0 337
41.4%

Length

2023-12-11T04:30:11.034540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:11.188833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 477
58.6%
0 337
41.4%

침대수
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
481 
0
333 

Length

Max length4
Median length4
Mean length2.7727273
Min length1

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> 481
59.1%
0 333
40.9%

Length

2023-12-11T04:30:11.367007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T04:30:11.550742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 481
59.1%
0 333
40.9%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size946.0 B
False
795 
True
 
19
ValueCountFrequency (%)
False 795
97.7%
True 19
 
2.3%
2023-12-11T04:30:11.733495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
01목욕장업11_44_01_P34100003410000-202-1976-0000119761020<NA>3폐업2폐업20090119<NA><NA><NA>053 4240045198.00700421대구광역시 중구 동인동1가 262-3번지<NA><NA>세종여자전용사우나20070829132156I2018-08-31 23:59:59.0공동탕업344737.766279264710.732438공동탕업1<NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
12목욕장업11_44_01_P34100003410000-202-1968-0000119680803<NA>3폐업2폐업20080603<NA><NA><NA>053 5548141.00700840대구광역시 중구 달성동 116-0014번지<NA><NA>청수20030730000000I2018-08-31 23:59:59.0공동탕업342667.799519265349.526877공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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45목욕장업11_44_01_P34100003410000-202-1993-0000119931126<NA>3폐업2폐업20091014<NA><NA><NA>053 4296062574.70700412대구광역시 중구 삼덕동2가 213-5번지<NA><NA>삼보탕20070202000000I2018-08-31 23:59:59.0공동탕업344680.158795264023.397519공동탕업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
804805목욕장업11_44_01_P34800003480000-202-1980-0000219800418<NA>3폐업2폐업20140221<NA><NA><NA>05306145004192.24711891대구광역시 달성군 구지면 창리 472-2번지<NA><NA>구지목욕탕20140217150142I2018-08-31 23:59:59.0공동탕업327529.514434240746.717574공동탕업2<NA>11<NA><NA><NA><NA>2Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
805806목욕장업11_44_01_P34800003480000-202-2008-0000120080229<NA>3폐업2폐업20141021<NA><NA><NA>053 586 8945191.40711811대구광역시 달성군 다사읍 달천리 81번지대구광역시 달성군 다사읍 다사로 48342907달래 황토찜질방20080325155915I2018-08-31 23:59:59.0찜질시설서비스영업333736.775561266365.714022찜질시설서비스영업0011<NA><NA>000Y0<NA><NA><NA>임대0<NA><NA><NA><NA>N
806807목욕장업11_44_01_P34800003480000-202-2000-0000820000925<NA>3폐업2폐업20100309<NA><NA><NA>053 6160336700.00711844대구광역시 달성군 옥포면 김흥리 1021번지<NA><NA>비슬산한증막20050706000000I2018-08-31 23:59:59.0공동탕업335007.529259250482.263766공동탕업1<NA>11<NA><NA><NA><NA>2Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
807808목욕장업11_44_01_P34800003480000-202-1967-0000119671116<NA>3폐업2폐업20200831<NA><NA><NA>053 6325464758.80711835대구광역시 달성군 화원읍 천내리 402-1대구광역시 달성군 화원읍 비슬로 2568-342962스파피아20200831140941U2020-09-02 02:40:00.0공동탕업335320.097323256917.0486공동탕업511300002Y0<NA><NA><NA>자가0<NA><NA>00N
808809목욕장업11_44_01_P34800003480000-202-1986-0000119861222<NA>3폐업2폐업20121029<NA><NA><NA>053 6140119378.40711841대구광역시 달성군 옥포면 간경리 850번지대구광역시 달성군 옥포면 비슬로457길 342972반도목욕탕20030816000000I2018-08-31 23:59:59.0공동탕업332870.658242255521.770518공동탕업4114<NA>1<NA><NA>2Y<NA><NA><NA><NA>자가<NA><NA><NA><NA><NA>N
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811812목욕장업11_44_01_P34800003480000-202-1990-0000319900929<NA>3폐업2폐업20080909<NA><NA><NA>053 6154828489.16711852대구광역시 달성군 논공읍 남리 1142-7번지<NA><NA>동성목욕탕20030318000000I2018-08-31 23:59:59.0공동탕업330272.445579248583.689867공동탕업5125<NA>1<NA><NA>2Y<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
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