Overview

Dataset statistics

Number of variables44
Number of observations821
Missing cells9418
Missing cells (%)26.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory303.2 KiB
Average record size in memory378.2 B

Variable types

Numeric16
Categorical12
Text7
Unsupported6
DateTime1
Boolean2

Dataset

Description22년11월_6270000_대구광역시_11_44_01_P_목욕장업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000097102&dataSetDetailId=DDI_0000097122&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (71.4%)Imbalance
위생업태명 is highly imbalanced (71.4%)Imbalance
다중이용업소여부 is highly imbalanced (82.2%)Imbalance
인허가취소일자 has 821 (100.0%) missing valuesMissing
폐업일자 has 256 (31.2%) missing valuesMissing
휴업시작일자 has 821 (100.0%) missing valuesMissing
휴업종료일자 has 821 (100.0%) missing valuesMissing
재개업일자 has 821 (100.0%) missing valuesMissing
소재지전화 has 34 (4.1%) missing valuesMissing
도로명전체주소 has 330 (40.2%) missing valuesMissing
도로명우편번호 has 340 (41.4%) missing valuesMissing
좌표정보(X) has 57 (6.9%) missing valuesMissing
좌표정보(Y) has 57 (6.9%) missing valuesMissing
건물지상층수 has 174 (21.2%) missing valuesMissing
건물지하층수 has 235 (28.6%) missing valuesMissing
사용시작지상층 has 221 (26.9%) missing valuesMissing
사용끝지상층 has 282 (34.3%) missing valuesMissing
욕실수 has 239 (29.1%) missing valuesMissing
조건부허가신고사유 has 820 (99.9%) missing valuesMissing
조건부허가시작일자 has 821 (100.0%) missing valuesMissing
조건부허가종료일자 has 821 (100.0%) missing valuesMissing
여성종사자수 has 721 (87.8%) missing valuesMissing
남성종사자수 has 718 (87.5%) missing valuesMissing
폐업일자 is highly skewed (γ1 = -23.57705038)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 131 (16.0%) zerosZeros
건물지하층수 has 176 (21.4%) zerosZeros
사용시작지상층 has 152 (18.5%) zerosZeros
사용끝지상층 has 92 (11.2%) zerosZeros
욕실수 has 188 (22.9%) zerosZeros
여성종사자수 has 80 (9.7%) zerosZeros
남성종사자수 has 82 (10.0%) zerosZeros

Reproduction

Analysis started2024-04-21 07:19:01.311523
Analysis finished2024-04-21 07:19:02.766324
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct821
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411
Minimum1
Maximum821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:02.895886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile42
Q1206
median411
Q3616
95-th percentile780
Maximum821
Range820
Interquartile range (IQR)410

Descriptive statistics

Standard deviation237.14658
Coefficient of variation (CV)0.57699898
Kurtosis-1.2
Mean411
Median Absolute Deviation (MAD)205
Skewness0
Sum337431
Variance56238.5
MonotonicityStrictly increasing
2024-04-21T16:19:03.176081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
553 1
 
0.1%
543 1
 
0.1%
544 1
 
0.1%
545 1
 
0.1%
546 1
 
0.1%
547 1
 
0.1%
548 1
 
0.1%
549 1
 
0.1%
550 1
 
0.1%
Other values (811) 811
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 (%)
821 1
0.1%
820 1
0.1%
819 1
0.1%
818 1
0.1%
817 1
0.1%
816 1
0.1%
815 1
0.1%
814 1
0.1%
813 1
0.1%
812 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
목욕장업
821 

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 821
100.0%

Length

2024-04-21T16:19:03.624119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:03.789457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목욕장업 821
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
11_44_01_P
821 

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 821
100.0%

Length

2024-04-21T16:19:03.975940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:04.173229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11_44_01_p 821
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3444859.9
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:04.345335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21060.566
Coefficient of variation (CV)0.0061136203
Kurtosis-1.2348846
Mean3444859.9
Median Absolute Deviation (MAD)20000
Skewness-0.12877927
Sum2.82823 × 109
Variance4.4354743 × 108
MonotonicityIncreasing
2024-04-21T16:19:04.583866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 142
17.3%
3420000 136
16.6%
3450000 131
16.0%
3460000 131
16.0%
3430000 91
11.1%
3440000 80
9.7%
3410000 71
8.6%
3480000 39
 
4.8%
ValueCountFrequency (%)
3410000 71
8.6%
3420000 136
16.6%
3430000 91
11.1%
3440000 80
9.7%
3450000 131
16.0%
3460000 131
16.0%
3470000 142
17.3%
3480000 39
 
4.8%
ValueCountFrequency (%)
3480000 39
 
4.8%
3470000 142
17.3%
3460000 131
16.0%
3450000 131
16.0%
3440000 80
9.7%
3430000 91
11.1%
3420000 136
16.6%
3410000 71
8.6%

관리번호
Text

UNIQUE 

Distinct821
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-21T16:19:05.273828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters18062
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

Unique821 ?
Unique (%)100.0%

Sample

1st row3410000-202-1983-00002
2nd row3410000-202-1970-00004
3rd row3410000-202-1970-00005
4th row3410000-202-1974-00003
5th row3410000-202-2003-00003
ValueCountFrequency (%)
3410000-202-1983-00002 1
 
0.1%
3460000-202-2001-00010 1
 
0.1%
3460000-202-1997-00001 1
 
0.1%
3460000-202-1999-00008 1
 
0.1%
3460000-202-1997-00014 1
 
0.1%
3460000-202-2008-00001 1
 
0.1%
3460000-202-2009-00002 1
 
0.1%
3460000-202-2012-00001 1
 
0.1%
3460000-202-1998-00011 1
 
0.1%
3460000-202-2008-00004 1
 
0.1%
Other values (811) 811
98.8%
2024-04-21T16:19:06.190568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8026
44.4%
2 2466
 
13.7%
- 2463
 
13.6%
3 1198
 
6.6%
4 1075
 
6.0%
1 934
 
5.2%
9 764
 
4.2%
7 404
 
2.2%
5 261
 
1.4%
6 257
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15599
86.4%
Dash Punctuation 2463
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8026
51.5%
2 2466
 
15.8%
3 1198
 
7.7%
4 1075
 
6.9%
1 934
 
6.0%
9 764
 
4.9%
7 404
 
2.6%
5 261
 
1.7%
6 257
 
1.6%
8 214
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2463
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18062
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8026
44.4%
2 2466
 
13.7%
- 2463
 
13.6%
3 1198
 
6.6%
4 1075
 
6.0%
1 934
 
5.2%
9 764
 
4.2%
7 404
 
2.2%
5 261
 
1.4%
6 257
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8026
44.4%
2 2466
 
13.7%
- 2463
 
13.6%
3 1198
 
6.6%
4 1075
 
6.0%
1 934
 
5.2%
9 764
 
4.2%
7 404
 
2.2%
5 261
 
1.4%
6 257
 
1.4%

인허가일자
Real number (ℝ)

Distinct663
Distinct (%)80.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19976487
Minimum19601125
Maximum20221114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:06.607481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19601125
5-th percentile19741230
Q119950322
median19990220
Q320030804
95-th percentile20160119
Maximum20221114
Range619989
Interquartile range (IQR)80482

Descriptive statistics

Standard deviation106249.63
Coefficient of variation (CV)0.0053187342
Kurtosis0.86198084
Mean19976487
Median Absolute Deviation (MAD)40502
Skewness-0.65718918
Sum1.6400696 × 1010
Variance1.1288983 × 1010
MonotonicityNot monotonic
2024-04-21T16:19:06.939974image/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%
19970718 3
 
0.4%
Other values (653) 694
84.5%
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 (%)
20221114 1
0.1%
20220919 1
0.1%
20220624 1
0.1%
20220623 1
0.1%
20220105 1
0.1%
20211101 1
0.1%
20210824 1
0.1%
20210618 1
0.1%
20210119 1
0.1%
20201211 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
3
565 
1
256 

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 (%)
3 565
68.8%
1 256
31.2%

Length

2024-04-21T16:19:07.210163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:07.404633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 565
68.8%
1 256
31.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
565 
영업/정상
256 

Length

Max length5
Median length2
Mean length2.9354446
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 565
68.8%
영업/정상 256
31.2%

Length

2024-04-21T16:19:07.629289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:07.845457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 565
68.8%
영업/정상 256
31.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2
565 
1
256 

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 (%)
2 565
68.8%
1 256
31.2%

Length

2024-04-21T16:19:08.051501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:08.246396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 565
68.8%
1 256
31.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
폐업
565 
영업
256 

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 565
68.8%
영업 256
31.2%

Length

2024-04-21T16:19:08.421278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:08.617391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 565
68.8%
영업 256
31.2%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct505
Distinct (%)89.4%
Missing256
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean20072671
Minimum200201
Maximum20221122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:08.858886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200201
5-th percentile20030502
Q120051005
median20091223
Q320160712
95-th percentile20210817
Maximum20221122
Range20020921
Interquartile range (IQR)109707

Descriptive statistics

Standard deviation839789.24
Coefficient of variation (CV)0.041837443
Kurtosis558.89475
Mean20072671
Median Absolute Deviation (MAD)49986
Skewness-23.57705
Sum1.1341059 × 1010
Variance7.0524597 × 1011
MonotonicityNot monotonic
2024-04-21T16:19:09.174145image/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%
20120111 3
 
0.4%
20041103 3
 
0.4%
20190701 3
 
0.4%
20031229 3
 
0.4%
20050117 3
 
0.4%
20090108 3
 
0.4%
20060419 3
 
0.4%
Other values (495) 525
63.9%
(Missing) 256
31.2%
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 (%)
20221122 1
0.1%
20221116 1
0.1%
20221107 2
0.2%
20221027 1
0.1%
20221013 1
0.1%
20221007 1
0.1%
20220915 1
0.1%
20220818 1
0.1%
20220816 1
0.1%
20220708 1
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

소재지전화
Text

MISSING 

Distinct759
Distinct (%)96.4%
Missing34
Missing (%)4.1%
Memory size6.5 KiB
2024-04-21T16:19:10.469341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.750953
Min length7

Characters and Unicode

Total characters8461
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

Unique731 ?
Unique (%)92.9%

Sample

1st row053 4225055
2nd row053 4254720
3rd row053 4247143
4th row053 4218241
5th row053 6641155
ValueCountFrequency (%)
053 647
40.3%
767 8
 
0.5%
753 6
 
0.4%
743 6
 
0.4%
781 6
 
0.4%
765 5
 
0.3%
752 5
 
0.3%
792 4
 
0.2%
323 4
 
0.2%
763 4
 
0.2%
Other values (836) 912
56.8%
2024-04-21T16:19:12.156060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1506
17.8%
0 1277
15.1%
3 1257
14.9%
827
9.8%
2 604
7.1%
6 599
 
7.1%
7 542
 
6.4%
1 493
 
5.8%
4 469
 
5.5%
8 452
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7634
90.2%
Space Separator 827
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1506
19.7%
0 1277
16.7%
3 1257
16.5%
2 604
7.9%
6 599
 
7.8%
7 542
 
7.1%
1 493
 
6.5%
4 469
 
6.1%
8 452
 
5.9%
9 435
 
5.7%
Space Separator
ValueCountFrequency (%)
827
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1506
17.8%
0 1277
15.1%
3 1257
14.9%
827
9.8%
2 604
7.1%
6 599
 
7.1%
7 542
 
6.4%
1 493
 
5.8%
4 469
 
5.5%
8 452
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1506
17.8%
0 1277
15.1%
3 1257
14.9%
827
9.8%
2 604
7.1%
6 599
 
7.1%
7 542
 
6.4%
1 493
 
5.8%
4 469
 
5.5%
8 452
 
5.3%

소재지면적
Text

Distinct762
Distinct (%)92.9%
Missing1
Missing (%)0.1%
Memory size6.5 KiB
2024-04-21T16:19:13.390117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.2865854
Min length3

Characters and Unicode

Total characters5155
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

Unique724 ?
Unique (%)88.3%

Sample

1st row637.60
2nd row750.85
3rd row309.60
4th row390.00
5th row1,030.10
ValueCountFrequency (%)
00 16
 
2.0%
660.00 5
 
0.6%
492.00 3
 
0.4%
165.00 3
 
0.4%
450.00 3
 
0.4%
762.74 2
 
0.2%
446.00 2
 
0.2%
1,171.00 2
 
0.2%
167.67 2
 
0.2%
650.00 2
 
0.2%
Other values (752) 780
95.1%
2024-04-21T16:19:14.839628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 870
16.9%
. 820
15.9%
1 418
8.1%
4 415
8.1%
5 404
7.8%
2 395
7.7%
3 387
7.5%
6 363
7.0%
8 347
 
6.7%
7 313
 
6.1%
Other values (2) 423
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4189
81.3%
Other Punctuation 966
 
18.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 870
20.8%
1 418
10.0%
4 415
9.9%
5 404
9.6%
2 395
9.4%
3 387
9.2%
6 363
8.7%
8 347
 
8.3%
7 313
 
7.5%
9 277
 
6.6%
Other Punctuation
ValueCountFrequency (%)
. 820
84.9%
, 146
 
15.1%

Most occurring scripts

ValueCountFrequency (%)
Common 5155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 870
16.9%
. 820
15.9%
1 418
8.1%
4 415
8.1%
5 404
7.8%
2 395
7.7%
3 387
7.5%
6 363
7.0%
8 347
 
6.7%
7 313
 
6.1%
Other values (2) 423
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 870
16.9%
. 820
15.9%
1 418
8.1%
4 415
8.1%
5 404
7.8%
2 395
7.7%
3 387
7.5%
6 363
7.0%
8 347
 
6.7%
7 313
 
6.1%
Other values (2) 423
8.2%

소재지우편번호
Real number (ℝ)

Distinct382
Distinct (%)46.8%
Missing4
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean704173.19
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:15.144290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700804.4
Q1701866
median703842
Q3705823
95-th percentile706850.2
Maximum711892
Range11882
Interquartile range (IQR)3957

Descriptive statistics

Standard deviation2540.5936
Coefficient of variation (CV)0.0036079102
Kurtosis1.3239066
Mean704173.19
Median Absolute Deviation (MAD)1980
Skewness0.93182947
Sum5.753095 × 108
Variance6454616.1
MonotonicityNot monotonic
2024-04-21T16:19:15.432064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704060 10
 
1.2%
702040 9
 
1.1%
704080 9
 
1.1%
703812 7
 
0.9%
706170 7
 
0.9%
704837 7
 
0.9%
703846 6
 
0.7%
711852 6
 
0.7%
706833 6
 
0.7%
701846 6
 
0.7%
Other values (372) 744
90.6%
ValueCountFrequency (%)
700010 1
 
0.1%
700020 3
0.4%
700082 1
 
0.1%
700092 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%
ValueCountFrequency (%)
711892 1
 
0.1%
711891 1
 
0.1%
711874 1
 
0.1%
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

Distinct761
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-21T16:19:16.368382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length22.601705
Min length16

Characters and Unicode

Total characters18556
Distinct characters197
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

Unique705 ?
Unique (%)85.9%

Sample

1st row대구광역시 중구 동인동2가 0227-0008번지
2nd row대구광역시 중구 동문동 18-4번지
3rd row대구광역시 중구 삼덕동3가 342-2번지
4th row대구광역시 중구 동인동3가 271번지
5th row대구광역시 중구 서성로1가 0109-0001
ValueCountFrequency (%)
대구광역시 821
23.5%
달서구 142
 
4.1%
동구 136
 
3.9%
북구 131
 
3.8%
수성구 131
 
3.8%
서구 91
 
2.6%
남구 80
 
2.3%
중구 71
 
2.0%
대명동 51
 
1.5%
달성군 39
 
1.1%
Other values (1004) 1795
51.5%
2024-04-21T16:19:17.587916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3487
18.8%
구 1613
 
8.7%
동 942
 
5.1%
대 906
 
4.9%
1 896
 
4.8%
시 829
 
4.5%
광 822
 
4.4%
역 822
 
4.4%
지 706
 
3.8%
- 700
 
3.8%
Other values (187) 6833
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10288
55.4%
Decimal Number 3981
 
21.5%
Space Separator 3487
 
18.8%
Dash Punctuation 700
 
3.8%
Other Punctuation 55
 
0.3%
Close Punctuation 19
 
0.1%
Open Punctuation 19
 
0.1%
Uppercase Letter 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1613
15.7%
동 942
 
9.2%
대 906
 
8.8%
시 829
 
8.1%
광 822
 
8.0%
역 822
 
8.0%
지 706
 
6.9%
번 625
 
6.1%
서 244
 
2.4%
성 237
 
2.3%
Other values (166) 2542
24.7%
Decimal Number
ValueCountFrequency (%)
1 896
22.5%
2 544
13.7%
0 443
11.1%
3 383
9.6%
4 353
 
8.9%
5 331
 
8.3%
6 294
 
7.4%
7 273
 
6.9%
8 239
 
6.0%
9 225
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 53
96.4%
. 1
 
1.8%
@ 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
L 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3487
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 700
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10288
55.4%
Common 8262
44.5%
Latin 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1613
15.7%
동 942
 
9.2%
대 906
 
8.8%
시 829
 
8.1%
광 822
 
8.0%
역 822
 
8.0%
지 706
 
6.9%
번 625
 
6.1%
서 244
 
2.4%
성 237
 
2.3%
Other values (166) 2542
24.7%
Common
ValueCountFrequency (%)
3487
42.2%
1 896
 
10.8%
- 700
 
8.5%
2 544
 
6.6%
0 443
 
5.4%
3 383
 
4.6%
4 353
 
4.3%
5 331
 
4.0%
6 294
 
3.6%
7 273
 
3.3%
Other values (8) 558
 
6.8%
Latin
ValueCountFrequency (%)
B 3
50.0%
A 2
33.3%
L 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10288
55.4%
ASCII 8268
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3487
42.2%
1 896
 
10.8%
- 700
 
8.5%
2 544
 
6.6%
0 443
 
5.4%
3 383
 
4.6%
4 353
 
4.3%
5 331
 
4.0%
6 294
 
3.6%
7 273
 
3.3%
Other values (11) 564
 
6.8%
Hangul
ValueCountFrequency (%)
구 1613
15.7%
동 942
 
9.2%
대 906
 
8.8%
시 829
 
8.1%
광 822
 
8.0%
역 822
 
8.0%
지 706
 
6.9%
번 625
 
6.1%
서 244
 
2.4%
성 237
 
2.3%
Other values (166) 2542
24.7%

도로명전체주소
Text

MISSING 

Distinct485
Distinct (%)98.8%
Missing330
Missing (%)40.2%
Memory size6.5 KiB
2024-04-21T16:19:18.751689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length25.900204
Min length20

Characters and Unicode

Total characters12717
Distinct characters237
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

Unique479 ?
Unique (%)97.6%

Sample

1st row대구광역시 중구 국채보상로140길 16 (동인동2가)
2nd row대구광역시 중구 경상감영길 1 (서성로1가)
3rd row대구광역시 중구 국채보상로 611, 23층 (문화동)
4th row대구광역시 중구 국채보상로 611, 7층 (문화동)
5th row대구광역시 중구 동덕로 115, 진석타워 지하1층 (삼덕동2가)
ValueCountFrequency (%)
대구광역시 491
 
18.8%
달서구 84
 
3.2%
동구 83
 
3.2%
수성구 77
 
2.9%
북구 72
 
2.8%
서구 55
 
2.1%
남구 50
 
1.9%
중구 37
 
1.4%
대명동 34
 
1.3%
달성군 33
 
1.3%
Other values (855) 1601
61.2%
2024-04-21T16:19:20.266788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2126
 
16.7%
구 1011
 
7.9%
대 636
 
5.0%
동 629
 
4.9%
시 500
 
3.9%
역 495
 
3.9%
광 492
 
3.9%
( 467
 
3.7%
) 467
 
3.7%
로 465
 
3.7%
Other values (227) 5429
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7467
58.7%
Space Separator 2126
 
16.7%
Decimal Number 1921
 
15.1%
Open Punctuation 467
 
3.7%
Close Punctuation 467
 
3.7%
Other Punctuation 162
 
1.3%
Dash Punctuation 79
 
0.6%
Math Symbol 15
 
0.1%
Uppercase Letter 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1011
 
13.5%
대 636
 
8.5%
동 629
 
8.4%
시 500
 
6.7%
역 495
 
6.6%
광 492
 
6.6%
로 465
 
6.2%
길 243
 
3.3%
서 177
 
2.4%
성 174
 
2.3%
Other values (205) 2645
35.4%
Decimal Number
ValueCountFrequency (%)
1 393
20.5%
2 317
16.5%
3 232
12.1%
0 168
8.7%
5 168
8.7%
4 157
 
8.2%
6 151
 
7.9%
7 129
 
6.7%
8 103
 
5.4%
9 103
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 6
46.2%
B 5
38.5%
L 1
 
7.7%
C 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 160
98.8%
· 1
 
0.6%
. 1
 
0.6%
Space Separator
ValueCountFrequency (%)
2126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 467
100.0%
Close Punctuation
ValueCountFrequency (%)
) 467
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7467
58.7%
Common 5237
41.2%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1011
 
13.5%
대 636
 
8.5%
동 629
 
8.4%
시 500
 
6.7%
역 495
 
6.6%
광 492
 
6.6%
로 465
 
6.2%
길 243
 
3.3%
서 177
 
2.4%
성 174
 
2.3%
Other values (205) 2645
35.4%
Common
ValueCountFrequency (%)
2126
40.6%
( 467
 
8.9%
) 467
 
8.9%
1 393
 
7.5%
2 317
 
6.1%
3 232
 
4.4%
0 168
 
3.2%
5 168
 
3.2%
, 160
 
3.1%
4 157
 
3.0%
Other values (8) 582
 
11.1%
Latin
ValueCountFrequency (%)
A 6
46.2%
B 5
38.5%
L 1
 
7.7%
C 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7467
58.7%
ASCII 5249
41.3%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2126
40.5%
( 467
 
8.9%
) 467
 
8.9%
1 393
 
7.5%
2 317
 
6.0%
3 232
 
4.4%
0 168
 
3.2%
5 168
 
3.2%
, 160
 
3.0%
4 157
 
3.0%
Other values (11) 594
 
11.3%
Hangul
ValueCountFrequency (%)
구 1011
 
13.5%
대 636
 
8.5%
동 629
 
8.4%
시 500
 
6.7%
역 495
 
6.6%
광 492
 
6.6%
로 465
 
6.2%
길 243
 
3.3%
서 177
 
2.4%
성 174
 
2.3%
Other values (205) 2645
35.4%
None
ValueCountFrequency (%)
· 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct392
Distinct (%)81.5%
Missing340
Missing (%)41.4%
Infinite0
Infinite (%)0.0%
Mean42009.674
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:20.678157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41112
Q141535
median41976
Q342493
95-th percentile42938
Maximum43024
Range2024
Interquartile range (IQR)958

Descriptive statistics

Standard deviation584.72836
Coefficient of variation (CV)0.013918898
Kurtosis-1.1543374
Mean42009.674
Median Absolute Deviation (MAD)485
Skewness-0.022269893
Sum20206653
Variance341907.26
MonotonicityNot monotonic
2024-04-21T16:19:21.141193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42728 3
 
0.4%
42413 3
 
0.4%
42439 3
 
0.4%
41436 3
 
0.4%
41463 3
 
0.4%
41112 3
 
0.4%
41557 3
 
0.4%
41008 3
 
0.4%
42117 3
 
0.4%
42288 3
 
0.4%
Other values (382) 451
54.9%
(Missing) 340
41.4%
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

Distinct717
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2024-04-21T16:19:22.193719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length5.1339829
Min length2

Characters and Unicode

Total characters4215
Distinct characters307
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

Unique644 ?
Unique (%)78.4%

Sample

1st row라이온수
2nd row대구
3rd row청하탕
4th row영흥탕
5th row삼정 헬스사우나
ValueCountFrequency (%)
사우나 8
 
0.9%
그린목욕탕 5
 
0.6%
한일목욕탕 5
 
0.6%
청수목욕탕 4
 
0.5%
동영목욕탕 4
 
0.5%
대림목욕탕 4
 
0.5%
대동탕 4
 
0.5%
대청사우나 4
 
0.5%
호수탕 4
 
0.5%
덕고탕 3
 
0.3%
Other values (730) 813
94.8%
2024-04-21T16:19:23.651748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 495
 
11.7%
목 278
 
6.6%
욕 278
 
6.6%
우 159
 
3.8%
나 155
 
3.7%
사 155
 
3.7%
스 106
 
2.5%
대 87
 
2.1%
동 75
 
1.8%
천 73
 
1.7%
Other values (297) 2354
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4107
97.4%
Space Separator 39
 
0.9%
Close Punctuation 23
 
0.5%
Open Punctuation 23
 
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
 
12.1%
목 278
 
6.8%
욕 278
 
6.8%
우 159
 
3.9%
나 155
 
3.8%
사 155
 
3.8%
스 106
 
2.6%
대 87
 
2.1%
동 75
 
1.8%
천 73
 
1.8%
Other values (280) 2246
54.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
G 2
25.0%
P 1
12.5%
O 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 (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4107
97.4%
Common 99
 
2.3%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 495
 
12.1%
목 278
 
6.8%
욕 278
 
6.8%
우 159
 
3.9%
나 155
 
3.8%
사 155
 
3.8%
스 106
 
2.6%
대 87
 
2.1%
동 75
 
1.8%
천 73
 
1.8%
Other values (280) 2246
54.7%
Common
ValueCountFrequency (%)
39
39.4%
) 23
23.2%
( 23
23.2%
3 3
 
3.0%
2 3
 
3.0%
0 2
 
2.0%
, 2
 
2.0%
5 2
 
2.0%
＆ 1
 
1.0%
/ 1
 
1.0%
Latin
ValueCountFrequency (%)
T 2
22.2%
G 2
22.2%
P 1
11.1%
O 1
11.1%
M 1
11.1%
S 1
11.1%
e 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4107
97.4%
ASCII 107
 
2.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 495
 
12.1%
목 278
 
6.8%
욕 278
 
6.8%
우 159
 
3.9%
나 155
 
3.8%
사 155
 
3.8%
스 106
 
2.6%
대 87
 
2.1%
동 75
 
1.8%
천 73
 
1.8%
Other values (280) 2246
54.7%
ASCII
ValueCountFrequency (%)
39
36.4%
) 23
21.5%
( 23
21.5%
3 3
 
2.8%
2 3
 
2.8%
0 2
 
1.9%
T 2
 
1.9%
, 2
 
1.9%
5 2
 
1.9%
G 2
 
1.9%
Other values (6) 6
 
5.6%
None
ValueCountFrequency (%)
＆ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct705
Distinct (%)85.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0123716 × 1013
Minimum2.0020201 × 1013
Maximum2.0221123 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:24.072764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020201 × 1013
5-th percentile2.002083 × 1013
Q12.004092 × 1013
median2.0120216 × 1013
Q32.0200423 × 1013
95-th percentile2.0220422 × 1013
Maximum2.0221123 × 1013
Range2.0092214 × 1011
Interquartile range (IQR)1.5950312 × 1011

Descriptive statistics

Standard deviation7.3728831 × 1010
Coefficient of variation (CV)0.0036637782
Kurtosis-1.6201148
Mean2.0123716 × 1013
Median Absolute Deviation (MAD)7.989011 × 1010
Skewness-0.0899373
Sum1.6521571 × 1016
Variance5.4359406 × 1021
MonotonicityNot monotonic
2024-04-21T16:19:24.541232image/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%
20040213000000 3
 
0.4%
20041029000000 3
 
0.4%
20031121000000 3
 
0.4%
Other values (695) 734
89.4%
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 (%)
20221123140601 1
0.1%
20221122141710 1
0.1%
20221118155653 1
0.1%
20221116102740 1
0.1%
20221115185427 1
0.1%
20221111101643 1
0.1%
20221111101320 1
0.1%
20221109160137 1
0.1%
20221109113412 1
0.1%
20221109105328 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
I
530 
U
291 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 530
64.6%
U 291
35.4%

Length

2024-04-21T16:19:24.969135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:25.291111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 530
64.6%
u 291
35.4%

데이터갱신일자
Date

Distinct212
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2018-08-31 23:59:59
Maximum2022-11-25 02:40:00
2024-04-21T16:19:25.522676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T16:19:25.931596image/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
735 
공동탕업+찜질시설서비스영업
 
45
찜질시설서비스영업
 
17
한증막업
 
16
목욕장업 기타
 
8

Length

Max length14
Median length4
Mean length4.680877
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 735
89.5%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
1.9%
목욕장업 기타 8
 
1.0%

Length

2024-04-21T16:19:26.362890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:26.716705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 735
88.7%
공동탕업+찜질시설서비스영업 45
 
5.4%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
1.9%
목욕장업 8
 
1.0%
기타 8
 
1.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct658
Distinct (%)86.1%
Missing57
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean343332
Minimum327293.91
Maximum356189.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:27.085907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327293.91
5-th percentile335584.54
Q1340182.55
median343184.15
Q3346551.59
95-th percentile352375.27
Maximum356189.2
Range28895.287
Interquartile range (IQR)6369.0349

Descriptive statistics

Standard deviation4781.5512
Coefficient of variation (CV)0.013926902
Kurtosis0.65849484
Mean343332
Median Absolute Deviation (MAD)3179.5578
Skewness-0.057645048
Sum2.6230565 × 108
Variance22863232
MonotonicityNot monotonic
2024-04-21T16:19:27.508181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
337346.64886395 4
 
0.5%
340616.952958188 3
 
0.4%
338849.57742046 3
 
0.4%
345310.581197132 3
 
0.4%
340286.680163588 3
 
0.4%
353142.033073587 3
 
0.4%
343184.151780859 3
 
0.4%
342666.445914153 3
 
0.4%
339273.069927148 3
 
0.4%
355698.45998424 3
 
0.4%
Other values (648) 733
89.3%
(Missing) 57
 
6.9%
ValueCountFrequency (%)
327293.913425497 1
0.1%
327526.386975054 1
0.1%
328293.623590322 1
0.1%
328965.130661119 1
0.1%
330272.445578617 1
0.1%
330338.711440998 1
0.1%
330342.686681021 1
0.1%
330497.842813587 1
0.1%
330573.646469099 1
0.1%
330585.519075694 1
0.1%
ValueCountFrequency (%)
356189.200160677 1
 
0.1%
355698.45998424 3
0.4%
355655.045544481 1
 
0.1%
355590.766868742 1
 
0.1%
354976.751149176 1
 
0.1%
354755.033316725 1
 
0.1%
354722.988899409 1
 
0.1%
354683.486530543 1
 
0.1%
354615.507123654 1
 
0.1%
354510.580081721 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct658
Distinct (%)86.1%
Missing57
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean263517.18
Minimum238769.81
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:27.934346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238769.81
5-th percentile257651.16
Q1261404.76
median263887.76
Q3265794.87
95-th percentile270187.55
Maximum278091.65
Range39321.841
Interquartile range (IQR)4390.1039

Descriptive statistics

Standard deviation4406.5508
Coefficient of variation (CV)0.016722063
Kurtosis5.6392524
Mean263517.18
Median Absolute Deviation (MAD)2150.6979
Skewness-1.0065815
Sum2.0132713 × 108
Variance19417690
MonotonicityNot monotonic
2024-04-21T16:19:28.408242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
258035.007517312 4
 
0.5%
266219.271085846 3
 
0.4%
257972.210093308 3
 
0.4%
261330.273815223 3
 
0.4%
271242.25696814 3
 
0.4%
261737.213765226 3
 
0.4%
264080.683792872 3
 
0.4%
263256.489079327 3
 
0.4%
269989.715359842 3
 
0.4%
275787.590179158 3
 
0.4%
Other values (648) 733
89.3%
(Missing) 57
 
6.9%
ValueCountFrequency (%)
238769.812521748 1
0.1%
240747.132592645 1
0.1%
242604.778959053 1
0.1%
244686.529495474 1
0.1%
244811.524282373 1
0.1%
244853.241727933 1
0.1%
244859.34472329 1
0.1%
245205.925240694 1
0.1%
248338.042553282 1
0.1%
248523.534087819 1
0.1%
ValueCountFrequency (%)
278091.653532319 1
 
0.1%
278070.885647028 1
 
0.1%
278032.753892201 1
 
0.1%
277467.078075227 1
 
0.1%
277462.879247206 1
 
0.1%
276154.019724205 1
 
0.1%
275787.590179158 3
0.4%
273077.612690691 1
 
0.1%
272997.707548012 1
 
0.1%
272960.803625499 1
 
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
공동탕업
735 
공동탕업+찜질시설서비스영업
 
45
찜질시설서비스영업
 
17
한증막업
 
16
목욕장업 기타
 
8

Length

Max length14
Median length4
Mean length4.680877
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동탕업 735
89.5%
공동탕업+찜질시설서비스영업 45
 
5.5%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
1.9%
목욕장업 기타 8
 
1.0%

Length

2024-04-21T16:19:28.867192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:29.222435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동탕업 735
88.7%
공동탕업+찜질시설서비스영업 45
 
5.4%
찜질시설서비스영업 17
 
2.1%
한증막업 16
 
1.9%
목욕장업 8
 
1.0%
기타 8
 
1.0%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)3.2%
Missing174
Missing (%)21.2%
Infinite0
Infinite (%)0.0%
Mean3.6646059
Minimum0
Maximum42
Zeros131
Zeros (%)16.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:29.572265image/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 deviation3.5728204
Coefficient of variation (CV)0.97495352
Kurtosis31.776792
Mean3.6646059
Median Absolute Deviation (MAD)2
Skewness4.1054047
Sum2371
Variance12.765046
MonotonicityNot monotonic
2024-04-21T16:19:29.924680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 131
16.0%
3 121
14.7%
4 121
14.7%
5 97
11.8%
2 66
 
8.0%
6 38
 
4.6%
7 20
 
2.4%
9 12
 
1.5%
1 11
 
1.3%
8 10
 
1.2%
Other values (11) 20
 
2.4%
(Missing) 174
21.2%
ValueCountFrequency (%)
0 131
16.0%
1 11
 
1.3%
2 66
8.0%
3 121
14.7%
4 121
14.7%
5 97
11.8%
6 38
 
4.6%
7 20
 
2.4%
8 10
 
1.2%
9 12
 
1.5%
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%
15 1
 
0.1%
11 4
0.5%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)1.2%
Missing235
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean0.89590444
Minimum0
Maximum9
Zeros176
Zeros (%)21.4%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:30.259436image/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 deviation0.89885984
Coefficient of variation (CV)1.0032988
Kurtosis24.217849
Mean0.89590444
Median Absolute Deviation (MAD)0
Skewness3.3662634
Sum525
Variance0.80794901
MonotonicityNot monotonic
2024-04-21T16:19:30.601386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 334
40.7%
0 176
21.4%
2 59
 
7.2%
4 7
 
0.9%
3 7
 
0.9%
9 2
 
0.2%
6 1
 
0.1%
(Missing) 235
28.6%
ValueCountFrequency (%)
0 176
21.4%
1 334
40.7%
2 59
 
7.2%
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 59
 
7.2%
1 334
40.7%
0 176
21.4%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.5%
Missing221
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean1.3933333
Minimum0
Maximum23
Zeros152
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:30.931234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum23
Range23
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5457267
Coefficient of variation (CV)1.1093732
Kurtosis64.39264
Mean1.3933333
Median Absolute Deviation (MAD)1
Skewness5.401192
Sum836
Variance2.389271
MonotonicityNot monotonic
2024-04-21T16:19:31.269949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 220
26.8%
2 156
19.0%
0 152
18.5%
3 37
 
4.5%
4 15
 
1.8%
5 9
 
1.1%
7 5
 
0.6%
6 5
 
0.6%
23 1
 
0.1%
(Missing) 221
26.9%
ValueCountFrequency (%)
0 152
18.5%
1 220
26.8%
2 156
19.0%
3 37
 
4.5%
4 15
 
1.8%
5 9
 
1.1%
6 5
 
0.6%
7 5
 
0.6%
23 1
 
0.1%
ValueCountFrequency (%)
23 1
 
0.1%
7 5
 
0.6%
6 5
 
0.6%
5 9
 
1.1%
4 15
 
1.8%
3 37
 
4.5%
2 156
19.0%
1 220
26.8%
0 152
18.5%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)1.9%
Missing282
Missing (%)34.3%
Infinite0
Infinite (%)0.0%
Mean2.3747681
Minimum0
Maximum23
Zeros92
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:31.598804image/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 deviation1.836382
Coefficient of variation (CV)0.773289
Kurtosis29.26603
Mean2.3747681
Median Absolute Deviation (MAD)1
Skewness3.0529222
Sum1280
Variance3.372299
MonotonicityNot monotonic
2024-04-21T16:19:31.941257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 192
23.4%
3 121
14.7%
0 92
 
11.2%
4 52
 
6.3%
1 35
 
4.3%
5 25
 
3.0%
6 11
 
1.3%
8 6
 
0.7%
7 4
 
0.5%
23 1
 
0.1%
(Missing) 282
34.3%
ValueCountFrequency (%)
0 92
11.2%
1 35
 
4.3%
2 192
23.4%
3 121
14.7%
4 52
 
6.3%
5 25
 
3.0%
6 11
 
1.3%
7 4
 
0.5%
8 6
 
0.7%
23 1
 
0.1%
ValueCountFrequency (%)
23 1
 
0.1%
8 6
 
0.7%
7 4
 
0.5%
6 11
 
1.3%
5 25
 
3.0%
4 52
 
6.3%
3 121
14.7%
2 192
23.4%
1 35
 
4.3%
0 92
11.2%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
0
363 
<NA>
352 
1
97 
2
 
9

Length

Max length4
Median length1
Mean length2.2862363
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 363
44.2%
<NA> 352
42.9%
1 97
 
11.8%
2 9
 
1.1%

Length

2024-04-21T16:19:32.338825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:32.680093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 363
44.2%
na 352
42.9%
1 97
 
11.8%
2 9
 
1.1%

사용끝지하층
Categorical

Distinct5
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
411 
0
293 
1
107 
2
 
7
3
 
3

Length

Max length4
Median length4
Mean length2.501827
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 411
50.1%
0 293
35.7%
1 107
 
13.0%
2 7
 
0.9%
3 3
 
0.4%

Length

2024-04-21T16:19:33.073749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:33.417186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 411
50.1%
0 293
35.7%
1 107
 
13.0%
2 7
 
0.9%
3 3
 
0.4%

욕실수
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)2.4%
Missing239
Missing (%)29.1%
Infinite0
Infinite (%)0.0%
Mean1.7628866
Minimum0
Maximum22
Zeros188
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:33.758527image/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 deviation1.9152789
Coefficient of variation (CV)1.0864447
Kurtosis24.662811
Mean1.7628866
Median Absolute Deviation (MAD)0
Skewness3.3598674
Sum1026
Variance3.6682932
MonotonicityNot monotonic
2024-04-21T16:19:34.108286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 306
37.3%
0 188
22.9%
4 41
 
5.0%
1 14
 
1.7%
6 14
 
1.7%
8 5
 
0.6%
5 5
 
0.6%
10 2
 
0.2%
3 2
 
0.2%
22 1
 
0.1%
Other values (4) 4
 
0.5%
(Missing) 239
29.1%
ValueCountFrequency (%)
0 188
22.9%
1 14
 
1.7%
2 306
37.3%
3 2
 
0.2%
4 41
 
5.0%
5 5
 
0.6%
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 5
 
0.6%
4 41
5.0%

발한실여부
Boolean

Distinct2
Distinct (%)0.2%
Missing3
Missing (%)0.4%
Memory size1.7 KiB
False
480 
True
338 
(Missing)
 
3
ValueCountFrequency (%)
False 480
58.5%
True 338
41.2%
(Missing) 3
 
0.4%
2024-04-21T16:19:34.439374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing820
Missing (%)99.9%
Memory size6.5 KiB
2024-04-21T16:19:35.081753image/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%
2024-04-21T16:19:36.117910image/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 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing821
Missing (%)100.0%
Memory size7.3 KiB

건물소유구분명
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
<NA>
465 
자가
238 
임대
118 

Length

Max length4
Median length4
Mean length3.1327649
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 465
56.6%
자가 238
29.0%
임대 118
 
14.4%

Length

2024-04-21T16:19:36.542642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:19:36.899701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 465
56.6%
자가 238
29.0%
임대 118
 
14.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)7.0%
Missing721
Missing (%)87.8%
Infinite0
Infinite (%)0.0%
Mean0.52
Minimum0
Maximum7
Zeros80
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:37.209388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.267145
Coefficient of variation (CV)2.4368174
Kurtosis10.512483
Mean0.52
Median Absolute Deviation (MAD)0
Skewness3.069763
Sum52
Variance1.6056566
MonotonicityNot monotonic
2024-04-21T16:19:37.556143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 80
 
9.7%
2 9
 
1.1%
3 4
 
0.5%
1 4
 
0.5%
5 1
 
0.1%
7 1
 
0.1%
6 1
 
0.1%
(Missing) 721
87.8%
ValueCountFrequency (%)
0 80
9.7%
1 4
 
0.5%
2 9
 
1.1%
3 4
 
0.5%
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%
3 4
 
0.5%
2 9
 
1.1%
1 4
 
0.5%
0 80
9.7%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)5.8%
Missing718
Missing (%)87.5%
Infinite0
Infinite (%)0.0%
Mean0.48543689
Minimum0
Maximum7
Zeros82
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2024-04-21T16:19:37.887800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1952855
Coefficient of variation (CV)2.4622881
Kurtosis11.344727
Mean0.48543689
Median Absolute Deviation (MAD)0
Skewness3.1614632
Sum50
Variance1.4287074
MonotonicityNot monotonic
2024-04-21T16:19:38.444642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 82
 
10.0%
2 7
 
0.9%
1 7
 
0.9%
3 4
 
0.5%
5 2
 
0.2%
7 1
 
0.1%
(Missing) 718
87.5%
ValueCountFrequency (%)
0 82
10.0%
1 7
 
0.9%
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 7
 
0.9%
0 82
10.0%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size949.0 B
False
799 
True
 
22
ValueCountFrequency (%)
False 799
97.3%
True 22
 
2.7%
2024-04-21T16:19:38.777277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층욕실수발한실여부조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수다중이용업소여부
01목욕장업11_44_01_P34100003410000-202-1983-0000219830920<NA>3폐업2폐업20150703<NA><NA><NA>053 4225055637.60700843대구광역시 중구 동인동2가 0227-0008번지대구광역시 중구 국채보상로140길 16 (동인동2가)41944라이온수20120125113540I2018-08-31 23:59:59.0공동탕업344981.918922264289.975858공동탕업0000000N<NA><NA><NA><NA><NA><NA>N
12목욕장업11_44_01_P34100003410000-202-1970-0000419700914<NA>3폐업2폐업20090119<NA><NA><NA>053 4254720750.85700180대구광역시 중구 동문동 18-4번지<NA><NA>대구20070829132058I2018-08-31 23:59:59.0공동탕업344180.237905264782.329768공동탕업41<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N
23목욕장업11_44_01_P34100003410000-202-1970-0000519701008<NA>3폐업2폐업20060608<NA><NA><NA><NA>309.60700413대구광역시 중구 삼덕동3가 342-2번지<NA><NA>청하탕20040214000000I2018-08-31 23:59:59.0공동탕업344958.139165263805.13112공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N
34목욕장업11_44_01_P34100003410000-202-1974-0000319741230<NA>3폐업2폐업20090119<NA><NA><NA>053 4247143390.00700845대구광역시 중구 동인동3가 271번지<NA><NA>영흥탕20030723000000I2018-08-31 23:59:59.0공동탕업<NA><NA>공동탕업<NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA>N
45목욕장업11_44_01_P34100003410000-202-2003-0000320030313<NA>3폐업2폐업20201006<NA><NA><NA>053 42182411,030.10700261대구광역시 중구 서성로1가 0109-0001대구광역시 중구 경상감영길 1 (서성로1가)41919삼정 헬스사우나20201006112208U2020-10-08 02:40:00.0공동탕업343315.940921264622.218272공동탕업3112002Y<NA><NA><NA>자가<NA><NA>N
56목욕장업11_44_01_P34100003410000-202-2008-0000220080626<NA>3폐업2폐업20221107<NA><NA><NA>053 6641155244.40700160대구광역시 중구 문화동 0011-0001 (23층)대구광역시 중구 국채보상로 611, 23층 (문화동)41913노보텔 앰배서더 대구20221111101320U2022-11-13 02:40:00.0공동탕업344223.636477264597.611089공동탕업2392323004Y<NA><NA><NA>임대00N
67목욕장업11_44_01_P34100003410000-202-2010-0000120100909<NA>3폐업2폐업20221107<NA><NA><NA>053 664 11391,400.89700160대구광역시 중구 문화동 0011-0001 지상7층대구광역시 중구 국채보상로 611, 7층 (문화동)41913인발란스웰니스20221111101643U2022-11-13 02:40:00.0공동탕업344223.636477264597.611089공동탕업23977002Y<NA><NA><NA>임대22N
78목욕장업11_44_01_P34100003410000-202-2019-0000120190215<NA>1영업/정상1영업<NA><NA><NA><NA>053 4297771690.64700412대구광역시 중구 삼덕동2가 0210-0001번지 진석타워 지하1층대구광역시 중구 동덕로 115, 진석타워 지하1층 (삼덕동2가)41940센텀스파휘트니스20190820204753U2019-08-22 02:40:00.0공동탕업344686.259338263958.880864공동탕업0000110N<NA><NA><NA><NA>00N
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811812목욕장업11_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>12Y<NA><NA><NA>자가<NA><NA>N
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816817목욕장업11_44_01_P34800003480000-202-1980-0000219800418<NA>3폐업2폐업20140221<NA><NA><NA>05306145004192.24711891대구광역시 달성군 구지면 창리 472-2번지<NA><NA>구지목욕탕20140217150142I2018-08-31 23:59:59.0공동탕업327526.386975240747.132593공동탕업2<NA>11<NA><NA>2Y<NA><NA><NA>자가<NA><NA>N
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818819목욕장업11_44_01_P34800003480000-202-2012-0000320120720<NA>3폐업2폐업20191022<NA><NA><NA>053 583 2344176.70711821대구광역시 달성군 하빈면 하산리 37번지대구광역시 달성군 하빈면 하산4길 12642900하빈숯굴20191022094503U2019-10-24 02:40:00.0찜질시설서비스영업327293.913425267442.739468찜질시설서비스영업1011002Y<NA><NA><NA>자가<NA><NA>Y
819820목욕장업11_44_01_P34800003480000-202-1980-0000119801231<NA>3폐업2폐업20080918<NA><NA><NA>05306117827210.00711874대구광역시 달성군 현풍면 하리 115-5번지<NA><NA>명신목욕탕20030816000000I2018-08-31 23:59:59.0공동탕업330585.519076244859.344723공동탕업2<NA>11<NA><NA>2Y<NA><NA><NA>자가<NA><NA>N
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