Overview

Dataset statistics

Number of variables50
Number of observations1734
Missing cells14962
Missing cells (%)17.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory731.7 KiB
Average record size in memory432.1 B

Variable types

Numeric17
Categorical19
Text7
Unsupported4
DateTime1
Boolean2

Dataset

Description6270000_대구광역시_03_11_03_P_숙박업_7월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000048440&dataSetDetailId=DDI_0000048466&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (56.2%)Imbalance
위생업태명 is highly imbalanced (59.0%)Imbalance
조건부허가시작일자 is highly imbalanced (99.3%)Imbalance
조건부허가종료일자 is highly imbalanced (99.3%)Imbalance
남성종사자수 is highly imbalanced (90.4%)Imbalance
침대수 is highly imbalanced (57.5%)Imbalance
다중이용업소여부 is highly imbalanced (98.7%)Imbalance
인허가취소일자 has 1734 (100.0%) missing valuesMissing
폐업일자 has 877 (50.6%) missing valuesMissing
휴업시작일자 has 1734 (100.0%) missing valuesMissing
휴업종료일자 has 1734 (100.0%) missing valuesMissing
재개업일자 has 1734 (100.0%) missing valuesMissing
소재지전화 has 94 (5.4%) missing valuesMissing
도로명전체주소 has 610 (35.2%) missing valuesMissing
도로명우편번호 has 635 (36.6%) missing valuesMissing
좌표정보(X) has 109 (6.3%) missing valuesMissing
좌표정보(Y) has 109 (6.3%) missing valuesMissing
건물지상층수 has 188 (10.8%) missing valuesMissing
건물지하층수 has 378 (21.8%) missing valuesMissing
사용시작지상층 has 325 (18.7%) missing valuesMissing
사용끝지상층 has 381 (22.0%) missing valuesMissing
한실수 has 164 (9.5%) missing valuesMissing
양실수 has 193 (11.1%) missing valuesMissing
좌석수 has 536 (30.9%) missing valuesMissing
조건부허가신고사유 has 1733 (99.9%) missing valuesMissing
여성종사자수 has 1668 (96.2%) missing valuesMissing
좌석수 is highly skewed (γ1 = 30.4514456)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 302 (17.4%) zerosZeros
건물지하층수 has 607 (35.0%) zerosZeros
사용시작지상층 has 418 (24.1%) zerosZeros
사용끝지상층 has 263 (15.2%) zerosZeros
한실수 has 423 (24.4%) zerosZeros
양실수 has 175 (10.1%) zerosZeros
좌석수 has 1191 (68.7%) zerosZeros
여성종사자수 has 32 (1.8%) zerosZeros

Reproduction

Analysis started2024-04-19 06:10:28.054361
Analysis finished2024-04-19 06:10:29.153438
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1734
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean867.5
Minimum1
Maximum1734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:29.218296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile87.65
Q1434.25
median867.5
Q31300.75
95-th percentile1647.35
Maximum1734
Range1733
Interquartile range (IQR)866.5

Descriptive statistics

Standard deviation500.707
Coefficient of variation (CV)0.57718386
Kurtosis-1.2
Mean867.5
Median Absolute Deviation (MAD)433.5
Skewness0
Sum1504245
Variance250707.5
MonotonicityStrictly increasing
2024-04-19T15:10:29.378161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1154 1
 
0.1%
1165 1
 
0.1%
1164 1
 
0.1%
1163 1
 
0.1%
1162 1
 
0.1%
1161 1
 
0.1%
1160 1
 
0.1%
1159 1
 
0.1%
1158 1
 
0.1%
Other values (1724) 1724
99.4%
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 (%)
1734 1
0.1%
1733 1
0.1%
1732 1
0.1%
1731 1
0.1%
1730 1
0.1%
1729 1
0.1%
1728 1
0.1%
1727 1
0.1%
1726 1
0.1%
1725 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
숙박업
1734 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업 1734
100.0%

Length

2024-04-19T15:10:29.511630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:29.610934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업 1734
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
03_11_03_P
1734 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row03_11_03_P
2nd row03_11_03_P
3rd row03_11_03_P
4th row03_11_03_P
5th row03_11_03_P

Common Values

ValueCountFrequency (%)
03_11_03_P 1734
100.0%

Length

2024-04-19T15:10:29.752713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:29.875684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03_11_03_p 1734
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3438021.9
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:29.963719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3430000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21556.769
Coefficient of variation (CV)0.0062701079
Kurtosis-1.156569
Mean3438021.9
Median Absolute Deviation (MAD)20000
Skewness0.40157899
Sum5.96153 × 109
Variance4.6469427 × 108
MonotonicityIncreasing
2024-04-19T15:10:30.075453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3420000 426
24.6%
3430000 300
17.3%
3410000 232
13.4%
3450000 206
11.9%
3470000 203
11.7%
3460000 191
11.0%
3440000 99
 
5.7%
3480000 77
 
4.4%
ValueCountFrequency (%)
3410000 232
13.4%
3420000 426
24.6%
3430000 300
17.3%
3440000 99
 
5.7%
3450000 206
11.9%
3460000 191
11.0%
3470000 203
11.7%
3480000 77
 
4.4%
ValueCountFrequency (%)
3480000 77
 
4.4%
3470000 203
11.7%
3460000 191
11.0%
3450000 206
11.9%
3440000 99
 
5.7%
3430000 300
17.3%
3420000 426
24.6%
3410000 232
13.4%

관리번호
Text

UNIQUE 

Distinct1734
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-19T15:10:30.253698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters38148
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

Unique1734 ?
Unique (%)100.0%

Sample

1st row3410000-201-2010-00001
2nd row3410000-201-1981-00006
3rd row3410000-201-2004-00003
4th row3410000-201-1980-00004
5th row3410000-201-1969-00004
ValueCountFrequency (%)
3410000-201-2010-00001 1
 
0.1%
3450000-201-1997-00035 1
 
0.1%
3450000-201-2001-00003 1
 
0.1%
3450000-201-2000-00001 1
 
0.1%
3450000-201-1995-00001 1
 
0.1%
3450000-201-1998-00005 1
 
0.1%
3450000-201-1997-00024 1
 
0.1%
3450000-201-1997-00023 1
 
0.1%
3450000-201-1999-00015 1
 
0.1%
3450000-201-1997-00044 1
 
0.1%
Other values (1724) 1724
99.4%
2024-04-19T15:10:30.802301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16640
43.6%
- 5202
 
13.6%
1 3898
 
10.2%
2 3576
 
9.4%
3 2699
 
7.1%
4 2225
 
5.8%
9 1486
 
3.9%
7 773
 
2.0%
8 601
 
1.6%
6 553
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32946
86.4%
Dash Punctuation 5202
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16640
50.5%
1 3898
 
11.8%
2 3576
 
10.9%
3 2699
 
8.2%
4 2225
 
6.8%
9 1486
 
4.5%
7 773
 
2.3%
8 601
 
1.8%
6 553
 
1.7%
5 495
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 5202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16640
43.6%
- 5202
 
13.6%
1 3898
 
10.2%
2 3576
 
9.4%
3 2699
 
7.1%
4 2225
 
5.8%
9 1486
 
3.9%
7 773
 
2.0%
8 601
 
1.6%
6 553
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16640
43.6%
- 5202
 
13.6%
1 3898
 
10.2%
2 3576
 
9.4%
3 2699
 
7.1%
4 2225
 
5.8%
9 1486
 
3.9%
7 773
 
2.0%
8 601
 
1.6%
6 553
 
1.4%

인허가일자
Real number (ℝ)

Distinct1249
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19953756
Minimum19601112
Maximum20190528
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:30.943102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19601112
5-th percentile19730529
Q119870626
median20000128
Q320030718
95-th percentile20101150
Maximum20190528
Range589416
Interquartile range (IQR)160092.5

Descriptive statistics

Standard deviation114531.18
Coefficient of variation (CV)0.0057398307
Kurtosis-0.046919969
Mean19953756
Median Absolute Deviation (MAD)30898.5
Skewness-0.80505369
Sum3.4599814 × 1010
Variance1.3117392 × 1010
MonotonicityNot monotonic
2024-04-19T15:10:31.079087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030718 131
 
7.6%
19961218 34
 
2.0%
19970108 19
 
1.1%
19970123 17
 
1.0%
20030801 15
 
0.9%
19970124 14
 
0.8%
20030805 12
 
0.7%
20030826 11
 
0.6%
19970306 8
 
0.5%
19970129 8
 
0.5%
Other values (1239) 1465
84.5%
ValueCountFrequency (%)
19601112 1
0.1%
19630401 1
0.1%
19630611 1
0.1%
19630826 1
0.1%
19631102 1
0.1%
19631112 2
0.1%
19640101 1
0.1%
19640115 1
0.1%
19641009 1
0.1%
19641027 1
0.1%
ValueCountFrequency (%)
20190528 1
0.1%
20190523 1
0.1%
20190425 1
0.1%
20190313 1
0.1%
20181105 1
0.1%
20180719 1
0.1%
20180423 1
0.1%
20180123 1
0.1%
20171222 1
0.1%
20171212 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1734
Missing (%)100.0%
Memory size15.4 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
1
875 
3
859 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 875
50.5%
3 859
49.5%

Length

2024-04-19T15:10:31.239898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:31.356349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 875
50.5%
3 859
49.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
영업/정상
875 
폐업
859 

Length

Max length5
Median length5
Mean length3.5138408
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 875
50.5%
폐업 859
49.5%

Length

2024-04-19T15:10:31.477821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:31.596602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 875
50.5%
폐업 859
49.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
1
875 
2
859 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 875
50.5%
2 859
49.5%

Length

2024-04-19T15:10:31.738132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:31.858109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 875
50.5%
2 859
49.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
영업
875 
폐업
859 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 875
50.5%
폐업 859
49.5%

Length

2024-04-19T15:10:31.999782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:32.126795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 875
50.5%
폐업 859
49.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct655
Distinct (%)76.4%
Missing877
Missing (%)50.6%
Infinite0
Infinite (%)0.0%
Mean20085808
Minimum20000430
Maximum20190626
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:32.258306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000430
5-th percentile20030189
Q120040331
median20070321
Q320131223
95-th percentile20180831
Maximum20190626
Range190196
Interquartile range (IQR)90892

Descriptive statistics

Standard deviation54094.018
Coefficient of variation (CV)0.0026931462
Kurtosis-1.0775059
Mean20085808
Median Absolute Deviation (MAD)39193
Skewness0.58040709
Sum1.7213538 × 1010
Variance2.9261628 × 109
MonotonicityNot monotonic
2024-04-19T15:10:32.464530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030718 20
 
1.2%
20050117 12
 
0.7%
20031128 11
 
0.6%
20031230 10
 
0.6%
20031231 9
 
0.5%
20031222 9
 
0.5%
20031112 8
 
0.5%
20031226 7
 
0.4%
20031229 7
 
0.4%
20040417 5
 
0.3%
Other values (645) 759
43.8%
(Missing) 877
50.6%
ValueCountFrequency (%)
20000430 1
0.1%
20010505 1
0.1%
20010517 1
0.1%
20010706 1
0.1%
20010725 1
0.1%
20010908 1
0.1%
20010920 2
0.1%
20011009 1
0.1%
20020326 2
0.1%
20020408 1
0.1%
ValueCountFrequency (%)
20190626 1
 
0.1%
20190513 2
0.1%
20190510 1
 
0.1%
20190507 1
 
0.1%
20190401 1
 
0.1%
20190326 1
 
0.1%
20190320 3
0.2%
20190314 2
0.1%
20190313 2
0.1%
20190304 2
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1734
Missing (%)100.0%
Memory size15.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1734
Missing (%)100.0%
Memory size15.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1734
Missing (%)100.0%
Memory size15.4 KiB

소재지전화
Text

MISSING 

Distinct1583
Distinct (%)96.5%
Missing94
Missing (%)5.4%
Memory size13.7 KiB
2024-04-19T15:10:32.728750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.795732
Min length1

Characters and Unicode

Total characters17705
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

Unique1529 ?
Unique (%)93.2%

Sample

1st row053 2522286
2nd row053 4230031
3rd row053 2523750
4th row053 4228902
5th row053 2550059
ValueCountFrequency (%)
053 1450
43.5%
768 16
 
0.5%
765 12
 
0.4%
764 11
 
0.3%
761 11
 
0.3%
763 10
 
0.3%
766 10
 
0.3%
762 7
 
0.2%
752 6
 
0.2%
753 5
 
0.1%
Other values (1669) 1798
53.9%
2024-04-19T15:10:33.231039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 3385
19.1%
3 2664
15.0%
0 2517
14.2%
1746
9.9%
2 1284
 
7.3%
6 1238
 
7.0%
7 1170
 
6.6%
4 1010
 
5.7%
1 960
 
5.4%
9 934
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15959
90.1%
Space Separator 1746
 
9.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3385
21.2%
3 2664
16.7%
0 2517
15.8%
2 1284
 
8.0%
6 1238
 
7.8%
7 1170
 
7.3%
4 1010
 
6.3%
1 960
 
6.0%
9 934
 
5.9%
8 797
 
5.0%
Space Separator
ValueCountFrequency (%)
1746
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 3385
19.1%
3 2664
15.0%
0 2517
14.2%
1746
9.9%
2 1284
 
7.3%
6 1238
 
7.0%
7 1170
 
6.6%
4 1010
 
5.7%
1 960
 
5.4%
9 934
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 3385
19.1%
3 2664
15.0%
0 2517
14.2%
1746
9.9%
2 1284
 
7.3%
6 1238
 
7.0%
7 1170
 
6.6%
4 1010
 
5.7%
1 960
 
5.4%
9 934
 
5.3%

소재지면적
Text

Distinct1472
Distinct (%)85.3%
Missing8
Missing (%)0.5%
Memory size13.7 KiB
2024-04-19T15:10:33.609048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.1993048
Min length3

Characters and Unicode

Total characters10700
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

Unique1337 ?
Unique (%)77.5%

Sample

1st row288.88
2nd row383.00
3rd row1,384.31
4th row528.18
5th row110.88
ValueCountFrequency (%)
00 72
 
4.2%
264.00 7
 
0.4%
48.00 6
 
0.3%
100.00 6
 
0.3%
35.00 6
 
0.3%
20.00 4
 
0.2%
132.00 4
 
0.2%
900.00 4
 
0.2%
1,835.44 4
 
0.2%
490.00 3
 
0.2%
Other values (1462) 1610
93.3%
2024-04-19T15:10:34.067722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1888
17.6%
. 1726
16.1%
1 987
9.2%
2 799
7.5%
4 788
7.4%
8 770
7.2%
5 749
 
7.0%
6 701
 
6.6%
3 697
 
6.5%
9 635
 
5.9%
Other values (2) 960
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8595
80.3%
Other Punctuation 2105
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1888
22.0%
1 987
11.5%
2 799
9.3%
4 788
9.2%
8 770
9.0%
5 749
 
8.7%
6 701
 
8.2%
3 697
 
8.1%
9 635
 
7.4%
7 581
 
6.8%
Other Punctuation
ValueCountFrequency (%)
. 1726
82.0%
, 379
 
18.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1888
17.6%
. 1726
16.1%
1 987
9.2%
2 799
7.5%
4 788
7.4%
8 770
7.2%
5 749
 
7.0%
6 701
 
6.6%
3 697
 
6.5%
9 635
 
5.9%
Other values (2) 960
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1888
17.6%
. 1726
16.1%
1 987
9.2%
2 799
7.5%
4 788
7.4%
8 770
7.2%
5 749
 
7.0%
6 701
 
6.6%
3 697
 
6.5%
9 635
 
5.9%
Other values (2) 960
9.0%

소재지우편번호
Real number (ℝ)

Distinct296
Distinct (%)17.1%
Missing7
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean703602.83
Minimum700020
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:34.267968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700020
5-th percentile700290
Q1701817.5
median703031
Q3704914
95-th percentile706853
Maximum711892
Range11872
Interquartile range (IQR)3096.5

Descriptive statistics

Standard deviation2582.7458
Coefficient of variation (CV)0.0036707439
Kurtosis1.9781816
Mean703602.83
Median Absolute Deviation (MAD)1216
Skewness1.2598134
Sum1.2151221 × 109
Variance6670575.8
MonotonicityNot monotonic
2024-04-19T15:10:34.439785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
703848 53
 
3.1%
706800 53
 
3.1%
701816 50
 
2.9%
701827 46
 
2.7%
704914 45
 
2.6%
701812 41
 
2.4%
703819 37
 
2.1%
706853 36
 
2.1%
701815 31
 
1.8%
703824 29
 
1.7%
Other values (286) 1306
75.3%
ValueCountFrequency (%)
700020 6
0.3%
700030 4
0.2%
700040 1
 
0.1%
700050 4
0.2%
700060 1
 
0.1%
700070 1
 
0.1%
700081 3
0.2%
700093 1
 
0.1%
700100 1
 
0.1%
700111 4
0.2%
ValueCountFrequency (%)
711892 2
 
0.1%
711891 3
 
0.2%
711874 1
 
0.1%
711873 1
 
0.1%
711872 5
 
0.3%
711863 16
0.9%
711861 1
 
0.1%
711858 1
 
0.1%
711852 12
0.7%
711851 1
 
0.1%

소재지전체주소
Text

Distinct1577
Distinct (%)91.1%
Missing2
Missing (%)0.1%
Memory size13.7 KiB
2024-04-19T15:10:34.754744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length50
Mean length22.643187
Min length18

Characters and Unicode

Total characters39218
Distinct characters160
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

Unique1428 ?
Unique (%)82.4%

Sample

1st row대구광역시 중구 종로1가 0041-0082번지
2nd row대구광역시 중구 대봉동 0734-0005번지
3rd row대구광역시 중구 시장북로 0011-0010번지
4th row대구광역시 중구 교동 0070-0019번지
5th row대구광역시 중구 북성로1가 0069-0001번지
ValueCountFrequency (%)
대구광역시 1732
24.3%
동구 426
 
6.0%
서구 300
 
4.2%
중구 232
 
3.3%
북구 205
 
2.9%
달서구 203
 
2.8%
수성구 191
 
2.7%
신암동 147
 
2.1%
비산동 144
 
2.0%
신천동 128
 
1.8%
Other values (1732) 3426
48.0%
2024-04-19T15:10:35.214765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7133
18.2%
구 3397
 
8.7%
동 2098
 
5.3%
대 1884
 
4.8%
지 1815
 
4.6%
시 1746
 
4.5%
역 1735
 
4.4%
번 1733
 
4.4%
광 1732
 
4.4%
1 1646
 
4.2%
Other values (150) 14299
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21919
55.9%
Decimal Number 8489
 
21.6%
Space Separator 7133
 
18.2%
Dash Punctuation 1560
 
4.0%
Other Punctuation 65
 
0.2%
Open Punctuation 18
 
< 0.1%
Close Punctuation 18
 
< 0.1%
Math Symbol 9
 
< 0.1%
Uppercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3397
15.5%
동 2098
9.6%
대 1884
 
8.6%
지 1815
 
8.3%
시 1746
 
8.0%
역 1735
 
7.9%
번 1733
 
7.9%
광 1732
 
7.9%
서 514
 
2.3%
성 386
 
1.8%
Other values (124) 4879
22.3%
Decimal Number
ValueCountFrequency (%)
1 1646
19.4%
0 1280
15.1%
2 1143
13.5%
3 917
10.8%
4 683
8.0%
5 661
7.8%
8 561
 
6.6%
7 560
 
6.6%
6 557
 
6.6%
9 481
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
L 1
14.3%
T 1
14.3%
P 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 50
76.9%
. 14
 
21.5%
' 1
 
1.5%
Open Punctuation
ValueCountFrequency (%)
( 17
94.4%
{ 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 17
94.4%
} 1
 
5.6%
Math Symbol
ValueCountFrequency (%)
~ 8
88.9%
> 1
 
11.1%
Space Separator
ValueCountFrequency (%)
7133
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1560
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21919
55.9%
Common 17292
44.1%
Latin 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3397
15.5%
동 2098
9.6%
대 1884
 
8.6%
지 1815
 
8.3%
시 1746
 
8.0%
역 1735
 
7.9%
번 1733
 
7.9%
광 1732
 
7.9%
서 514
 
2.3%
성 386
 
1.8%
Other values (124) 4879
22.3%
Common
ValueCountFrequency (%)
7133
41.3%
1 1646
 
9.5%
- 1560
 
9.0%
0 1280
 
7.4%
2 1143
 
6.6%
3 917
 
5.3%
4 683
 
3.9%
5 661
 
3.8%
8 561
 
3.2%
7 560
 
3.2%
Other values (11) 1148
 
6.6%
Latin
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
L 1
14.3%
T 1
14.3%
P 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21919
55.9%
ASCII 17299
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7133
41.2%
1 1646
 
9.5%
- 1560
 
9.0%
0 1280
 
7.4%
2 1143
 
6.6%
3 917
 
5.3%
4 683
 
3.9%
5 661
 
3.8%
8 561
 
3.2%
7 560
 
3.2%
Other values (16) 1155
 
6.7%
Hangul
ValueCountFrequency (%)
구 3397
15.5%
동 2098
9.6%
대 1884
 
8.6%
지 1815
 
8.3%
시 1746
 
8.0%
역 1735
 
7.9%
번 1733
 
7.9%
광 1732
 
7.9%
서 514
 
2.3%
성 386
 
1.8%
Other values (124) 4879
22.3%

도로명전체주소
Text

MISSING 

Distinct1108
Distinct (%)98.6%
Missing610
Missing (%)35.2%
Memory size13.7 KiB
2024-04-19T15:10:35.556924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length39
Mean length25.086299
Min length19

Characters and Unicode

Total characters28197
Distinct characters197
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1093 ?
Unique (%)97.2%

Sample

1st row대구광역시 중구 종로 44-31 (종로1가)
2nd row대구광역시 중구 명륜로26길 61 (대봉동)
3rd row대구광역시 중구 국채보상로99길 38 (시장북로)
4th row대구광역시 중구 교동2길 29-11 (교동)
5th row대구광역시 중구 북성로 100-23 (북성로1가)
ValueCountFrequency (%)
대구광역시 1124
 
19.7%
동구 285
 
5.0%
달서구 163
 
2.9%
서구 163
 
2.9%
중구 153
 
2.7%
북구 126
 
2.2%
수성구 110
 
1.9%
신천동 88
 
1.5%
신암동 87
 
1.5%
비산동 75
 
1.3%
Other values (1086) 3330
58.4%
2024-04-19T15:10:36.053942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4580
 
16.2%
구 2361
 
8.4%
동 1584
 
5.6%
대 1479
 
5.2%
시 1141
 
4.0%
역 1127
 
4.0%
광 1124
 
4.0%
로 1122
 
4.0%
( 1074
 
3.8%
) 1074
 
3.8%
Other values (187) 11531
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16522
58.6%
Space Separator 4580
 
16.2%
Decimal Number 4411
 
15.6%
Open Punctuation 1074
 
3.8%
Close Punctuation 1074
 
3.8%
Dash Punctuation 367
 
1.3%
Other Punctuation 121
 
0.4%
Math Symbol 48
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2361
14.3%
동 1584
 
9.6%
대 1479
 
9.0%
시 1141
 
6.9%
역 1127
 
6.8%
광 1124
 
6.8%
로 1122
 
6.8%
길 619
 
3.7%
서 463
 
2.8%
성 345
 
2.1%
Other values (168) 5157
31.2%
Decimal Number
ValueCountFrequency (%)
1 1001
22.7%
2 785
17.8%
3 485
11.0%
4 392
 
8.9%
5 378
 
8.6%
6 340
 
7.7%
8 276
 
6.3%
0 275
 
6.2%
7 259
 
5.9%
9 220
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 116
95.9%
. 4
 
3.3%
' 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 47
97.9%
> 1
 
2.1%
Space Separator
ValueCountFrequency (%)
4580
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1074
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1074
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16522
58.6%
Common 11675
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2361
14.3%
동 1584
 
9.6%
대 1479
 
9.0%
시 1141
 
6.9%
역 1127
 
6.8%
광 1124
 
6.8%
로 1122
 
6.8%
길 619
 
3.7%
서 463
 
2.8%
성 345
 
2.1%
Other values (168) 5157
31.2%
Common
ValueCountFrequency (%)
4580
39.2%
( 1074
 
9.2%
) 1074
 
9.2%
1 1001
 
8.6%
2 785
 
6.7%
3 485
 
4.2%
4 392
 
3.4%
5 378
 
3.2%
- 367
 
3.1%
6 340
 
2.9%
Other values (9) 1199
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16522
58.6%
ASCII 11675
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4580
39.2%
( 1074
 
9.2%
) 1074
 
9.2%
1 1001
 
8.6%
2 785
 
6.7%
3 485
 
4.2%
4 392
 
3.4%
5 378
 
3.2%
- 367
 
3.1%
6 340
 
2.9%
Other values (9) 1199
 
10.3%
Hangul
ValueCountFrequency (%)
구 2361
14.3%
동 1584
 
9.6%
대 1479
 
9.0%
시 1141
 
6.9%
역 1127
 
6.8%
광 1124
 
6.8%
로 1122
 
6.8%
길 619
 
3.7%
서 463
 
2.8%
성 345
 
2.1%
Other values (168) 5157
31.2%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct336
Distinct (%)30.6%
Missing635
Missing (%)36.6%
Infinite0
Infinite (%)0.0%
Mean41892.21
Minimum41001
Maximum43017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:36.204579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41001
5-th percentile41144.8
Q141345
median41858
Q342409
95-th percentile42904
Maximum43017
Range2016
Interquartile range (IQR)1064

Descriptive statistics

Standard deviation567.57643
Coefficient of variation (CV)0.013548496
Kurtosis-1.0010417
Mean41892.21
Median Absolute Deviation (MAD)551
Skewness0.29121076
Sum46039539
Variance322143
MonotonicityNot monotonic
2024-04-19T15:10:36.355247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42149 23
 
1.3%
42713 21
 
1.2%
42684 21
 
1.2%
41223 19
 
1.1%
42171 17
 
1.0%
41918 17
 
1.0%
41216 16
 
0.9%
41911 16
 
0.9%
42714 16
 
0.9%
41007 16
 
0.9%
Other values (326) 917
52.9%
(Missing) 635
36.6%
ValueCountFrequency (%)
41001 6
 
0.3%
41002 3
 
0.2%
41005 3
 
0.2%
41007 16
0.9%
41008 4
 
0.2%
41009 1
 
0.1%
41026 1
 
0.1%
41043 3
 
0.2%
41047 1
 
0.1%
41052 1
 
0.1%
ValueCountFrequency (%)
43017 1
 
0.1%
43013 2
0.1%
43008 1
 
0.1%
43003 1
 
0.1%
43000 1
 
0.1%
42999 3
0.2%
42993 1
 
0.1%
42990 2
0.1%
42988 2
0.1%
42986 1
 
0.1%

사업장명
Text

Distinct1451
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2024-04-19T15:10:36.666495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length4.5374856
Min length1

Characters and Unicode

Total characters7868
Distinct characters489
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1247 ?
Unique (%)71.9%

Sample

1st row아리랑 민속모텔
2nd row삼익장
3rd row야자(YAJA)대구서문시장점
4th row호원장여관
5th row명신
ValueCountFrequency (%)
모텔 24
 
1.3%
여관 21
 
1.1%
호텔 12
 
0.7%
산장여관 8
 
0.4%
hotel 6
 
0.3%
젠모텔 5
 
0.3%
청수여관 5
 
0.3%
현대여인숙 5
 
0.3%
앤모텔 5
 
0.3%
유림장여관 4
 
0.2%
Other values (1464) 1744
94.8%
2024-04-19T15:10:37.077832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 652
 
8.3%
여 577
 
7.3%
모 516
 
6.6%
관 488
 
6.2%
장 359
 
4.6%
호 170
 
2.2%
스 160
 
2.0%
인 130
 
1.7%
동 119
 
1.5%
성 117
 
1.5%
Other values (479) 4580
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7117
90.5%
Uppercase Letter 284
 
3.6%
Space Separator 107
 
1.4%
Close Punctuation 104
 
1.3%
Open Punctuation 104
 
1.3%
Lowercase Letter 79
 
1.0%
Decimal Number 60
 
0.8%
Other Punctuation 9
 
0.1%
Dash Punctuation 3
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 652
 
9.2%
여 577
 
8.1%
모 516
 
7.3%
관 488
 
6.9%
장 359
 
5.0%
호 170
 
2.4%
스 160
 
2.2%
인 130
 
1.8%
동 119
 
1.7%
성 117
 
1.6%
Other values (412) 3829
53.8%
Uppercase Letter
ValueCountFrequency (%)
O 29
 
10.2%
E 26
 
9.2%
T 25
 
8.8%
L 24
 
8.5%
M 21
 
7.4%
S 20
 
7.0%
A 15
 
5.3%
H 14
 
4.9%
G 12
 
4.2%
K 11
 
3.9%
Other values (15) 87
30.6%
Lowercase Letter
ValueCountFrequency (%)
o 12
15.2%
e 12
15.2%
i 7
 
8.9%
n 7
 
8.9%
g 5
 
6.3%
h 4
 
5.1%
t 4
 
5.1%
l 4
 
5.1%
u 3
 
3.8%
d 3
 
3.8%
Other values (12) 18
22.8%
Decimal Number
ValueCountFrequency (%)
2 28
46.7%
1 7
 
11.7%
7 6
 
10.0%
0 5
 
8.3%
3 4
 
6.7%
5 3
 
5.0%
6 3
 
5.0%
9 2
 
3.3%
4 1
 
1.7%
8 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 3
33.3%
' 3
33.3%
# 1
 
11.1%
, 1
 
11.1%
! 1
 
11.1%
Space Separator
ValueCountFrequency (%)
107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7116
90.4%
Common 388
 
4.9%
Latin 363
 
4.6%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 652
 
9.2%
여 577
 
8.1%
모 516
 
7.3%
관 488
 
6.9%
장 359
 
5.0%
호 170
 
2.4%
스 160
 
2.2%
인 130
 
1.8%
동 119
 
1.7%
성 117
 
1.6%
Other values (411) 3828
53.8%
Latin
ValueCountFrequency (%)
O 29
 
8.0%
E 26
 
7.2%
T 25
 
6.9%
L 24
 
6.6%
M 21
 
5.8%
S 20
 
5.5%
A 15
 
4.1%
H 14
 
3.9%
o 12
 
3.3%
e 12
 
3.3%
Other values (37) 165
45.5%
Common
ValueCountFrequency (%)
107
27.6%
) 104
26.8%
( 104
26.8%
2 28
 
7.2%
1 7
 
1.8%
7 6
 
1.5%
0 5
 
1.3%
3 4
 
1.0%
5 3
 
0.8%
. 3
 
0.8%
Other values (10) 17
 
4.4%
Han
ValueCountFrequency (%)
月 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7116
90.4%
ASCII 751
 
9.5%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 652
 
9.2%
여 577
 
8.1%
모 516
 
7.3%
관 488
 
6.9%
장 359
 
5.0%
호 170
 
2.4%
스 160
 
2.2%
인 130
 
1.8%
동 119
 
1.7%
성 117
 
1.6%
Other values (411) 3828
53.8%
ASCII
ValueCountFrequency (%)
107
14.2%
) 104
 
13.8%
( 104
 
13.8%
O 29
 
3.9%
2 28
 
3.7%
E 26
 
3.5%
T 25
 
3.3%
L 24
 
3.2%
M 21
 
2.8%
S 20
 
2.7%
Other values (57) 263
35.0%
CJK
ValueCountFrequency (%)
月 1
100.0%

최종수정시점
Real number (ℝ)

Distinct1452
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0127041 × 1013
Minimum2.0020122 × 1013
Maximum2.0190629 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:37.207372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0020122 × 1013
5-th percentile2.0021209 × 1013
Q12.0050202 × 1013
median2.017112 × 1013
Q32.0180719 × 1013
95-th percentile2.0190522 × 1013
Maximum2.0190629 × 1013
Range1.7050716 × 1011
Interquartile range (IQR)1.3051711 × 1011

Descriptive statistics

Standard deviation6.5460204 × 1010
Coefficient of variation (CV)0.003252351
Kurtosis-1.4836628
Mean2.0127041 × 1013
Median Absolute Deviation (MAD)1.9303042 × 1010
Skewness-0.55938819
Sum3.490029 × 1016
Variance4.2850383 × 1021
MonotonicityNot monotonic
2024-04-19T15:10:37.338058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050202000000 31
 
1.8%
20040213000000 17
 
1.0%
20020327000000 16
 
0.9%
20020627000000 13
 
0.7%
20031202000000 12
 
0.7%
20030731000000 10
 
0.6%
20030814000000 10
 
0.6%
20031006000000 9
 
0.5%
20020328000000 9
 
0.5%
20040511000000 9
 
0.5%
Other values (1442) 1598
92.2%
ValueCountFrequency (%)
20020122000000 1
 
0.1%
20020129000000 1
 
0.1%
20020322000000 1
 
0.1%
20020327000000 16
0.9%
20020328000000 9
0.5%
20020329000000 5
 
0.3%
20020415000000 1
 
0.1%
20020502000000 1
 
0.1%
20020503000000 3
 
0.2%
20020508000000 1
 
0.1%
ValueCountFrequency (%)
20190629161155 1
0.1%
20190628171152 1
0.1%
20190628171115 1
0.1%
20190628144421 1
0.1%
20190628115520 1
0.1%
20190628103320 1
0.1%
20190628102952 1
0.1%
20190628101915 1
0.1%
20190628101256 1
0.1%
20190627171739 1
0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
I
1378 
U
356 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1378
79.5%
U 356
 
20.5%

Length

2024-04-19T15:10:37.463428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:37.579635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1378
79.5%
u 356
 
20.5%

데이터갱신일자
Date

Distinct150
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
Minimum2018-08-31 23:59:59
Maximum2019-07-02 02:40:00
2024-04-19T15:10:37.691827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:10:37.848805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
여관업
1367 
여인숙업
179 
숙박업 기타
 
97
일반호텔
 
44
관광호텔
 
40

Length

Max length7
Median length3
Mean length3.3356401
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업 기타
2nd row여관업
3rd row여관업
4th row여관업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 1367
78.8%
여인숙업 179
 
10.3%
숙박업 기타 97
 
5.6%
일반호텔 44
 
2.5%
관광호텔 40
 
2.3%
숙박업(생활) 7
 
0.4%

Length

2024-04-19T15:10:37.981077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:38.104827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 1367
74.7%
여인숙업 179
 
9.8%
숙박업 97
 
5.3%
기타 97
 
5.3%
일반호텔 44
 
2.4%
관광호텔 40
 
2.2%
숙박업(생활 7
 
0.4%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1437
Distinct (%)88.4%
Missing109
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean343517.26
Minimum326165.89
Maximum356639.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:38.246704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326165.89
5-th percentile335151.46
Q1340686.04
median343786.34
Q3346657.85
95-th percentile349154.46
Maximum356639.97
Range30474.084
Interquartile range (IQR)5971.8105

Descriptive statistics

Standard deviation4321.3774
Coefficient of variation (CV)0.012579797
Kurtosis1.5131606
Mean343517.26
Median Absolute Deviation (MAD)2965.9268
Skewness-0.53694782
Sum5.5821555 × 108
Variance18674303
MonotonicityNot monotonic
2024-04-19T15:10:38.394587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
346478.460358 3
 
0.2%
352544.044045 3
 
0.2%
355795.444667 3
 
0.2%
340507.314024 3
 
0.2%
340396.774505 3
 
0.2%
340458.952586 3
 
0.2%
340426.468133 3
 
0.2%
347204.783471 3
 
0.2%
344704.21692 3
 
0.2%
344309.75555 3
 
0.2%
Other values (1427) 1595
92.0%
(Missing) 109
 
6.3%
ValueCountFrequency (%)
326165.886517 1
0.1%
326172.635898 1
0.1%
327255.08935 2
0.1%
327367.90409 1
0.1%
327926.829643 1
0.1%
328249.701083 1
0.1%
328273.30899 1
0.1%
328508.323419 1
0.1%
328548.352834 1
0.1%
328571.129371 1
0.1%
ValueCountFrequency (%)
356639.970173 1
 
0.1%
355795.444667 3
0.2%
355779.785519 1
 
0.1%
355760.92746 1
 
0.1%
355744.44748 2
0.1%
354686.747751 1
 
0.1%
354683.486531 1
 
0.1%
354671.061614 1
 
0.1%
354275.276491 1
 
0.1%
354128.757834 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1437
Distinct (%)88.4%
Missing109
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean264088.44
Minimum239016.21
Maximum278167.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:38.537982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum239016.21
5-th percentile259454.92
Q1262054.8
median264729.85
Q3265883.66
95-th percentile268711.71
Maximum278167.56
Range39151.353
Interquartile range (IQR)3828.8581

Descriptive statistics

Standard deviation4367.6236
Coefficient of variation (CV)0.016538488
Kurtosis7.5595314
Mean264088.44
Median Absolute Deviation (MAD)1414.1414
Skewness-1.1354705
Sum4.2914371 × 108
Variance19076136
MonotonicityNot monotonic
2024-04-19T15:10:38.702337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
260883.377943 3
 
0.2%
277984.019293 3
 
0.2%
275764.967013 3
 
0.2%
263962.430615 3
 
0.2%
265870.157649 3
 
0.2%
264541.886823 3
 
0.2%
266143.989836 3
 
0.2%
266347.746271 3
 
0.2%
264809.327072 3
 
0.2%
265136.229046 3
 
0.2%
Other values (1427) 1595
92.0%
(Missing) 109
 
6.3%
ValueCountFrequency (%)
239016.209158 1
0.1%
239017.56085 1
0.1%
239802.49247 1
0.1%
240678.394981 1
0.1%
242124.922955 1
0.1%
244521.950088 1
0.1%
244752.614707 1
0.1%
245059.293029 1
0.1%
245205.925241 1
0.1%
245371.919272 1
0.1%
ValueCountFrequency (%)
278167.562594 2
0.1%
278147.643455 1
0.1%
278141.388025 2
0.1%
278105.634265 1
0.1%
278091.653532 1
0.1%
278082.12111 2
0.1%
278080.761551 1
0.1%
278066.857497 2
0.1%
278043.62211 2
0.1%
278031.37713 2
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
여관업
1364 
여인숙업
179 
숙박업 기타
 
97
일반호텔
 
44
관광호텔
 
40
Other values (2)
 
10

Length

Max length7
Median length3
Mean length3.3373702
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업 기타
2nd row여관업
3rd row여관업
4th row여관업
5th row여관업

Common Values

ValueCountFrequency (%)
여관업 1364
78.7%
여인숙업 179
 
10.3%
숙박업 기타 97
 
5.6%
일반호텔 44
 
2.5%
관광호텔 40
 
2.3%
숙박업(생활) 7
 
0.4%
<NA> 3
 
0.2%

Length

2024-04-19T15:10:39.200906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:39.344136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여관업 1364
74.5%
여인숙업 179
 
9.8%
숙박업 97
 
5.3%
기타 97
 
5.3%
일반호텔 44
 
2.4%
관광호텔 40
 
2.2%
숙박업(생활 7
 
0.4%
na 3
 
0.2%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)1.0%
Missing188
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean3.0608021
Minimum0
Maximum23
Zeros302
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:39.457560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile6
Maximum23
Range23
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.216777
Coefficient of variation (CV)0.72424708
Kurtosis5.5967917
Mean3.0608021
Median Absolute Deviation (MAD)1
Skewness1.0518867
Sum4732
Variance4.9141001
MonotonicityNot monotonic
2024-04-19T15:10:39.559674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4 323
18.6%
3 311
17.9%
0 302
17.4%
2 231
13.3%
5 182
10.5%
6 76
 
4.4%
1 47
 
2.7%
7 30
 
1.7%
8 22
 
1.3%
10 8
 
0.5%
Other values (6) 14
 
0.8%
(Missing) 188
10.8%
ValueCountFrequency (%)
0 302
17.4%
1 47
 
2.7%
2 231
13.3%
3 311
17.9%
4 323
18.6%
5 182
10.5%
6 76
 
4.4%
7 30
 
1.7%
8 22
 
1.3%
9 6
 
0.3%
ValueCountFrequency (%)
23 1
 
0.1%
17 1
 
0.1%
14 1
 
0.1%
12 3
 
0.2%
11 2
 
0.1%
10 8
 
0.5%
9 6
 
0.3%
8 22
 
1.3%
7 30
 
1.7%
6 76
4.4%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.6%
Missing378
Missing (%)21.8%
Infinite0
Infinite (%)0.0%
Mean0.59587021
Minimum0
Maximum9
Zeros607
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:39.667455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.66905059
Coefficient of variation (CV)1.1228126
Kurtosis30.014571
Mean0.59587021
Median Absolute Deviation (MAD)0
Skewness3.3041489
Sum808
Variance0.44762869
MonotonicityNot monotonic
2024-04-19T15:10:39.772628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 724
41.8%
0 607
35.0%
2 13
 
0.7%
4 4
 
0.2%
5 4
 
0.2%
3 2
 
0.1%
9 1
 
0.1%
7 1
 
0.1%
(Missing) 378
21.8%
ValueCountFrequency (%)
0 607
35.0%
1 724
41.8%
2 13
 
0.7%
3 2
 
0.1%
4 4
 
0.2%
5 4
 
0.2%
7 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
9 1
 
0.1%
7 1
 
0.1%
5 4
 
0.2%
4 4
 
0.2%
3 2
 
0.1%
2 13
 
0.7%
1 724
41.8%
0 607
35.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.8%
Missing325
Missing (%)18.7%
Infinite0
Infinite (%)0.0%
Mean1.2767921
Minimum0
Maximum10
Zeros418
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:39.884307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3557671
Coefficient of variation (CV)1.0618543
Kurtosis6.0804072
Mean1.2767921
Median Absolute Deviation (MAD)1
Skewness1.9330548
Sum1799
Variance1.8381045
MonotonicityNot monotonic
2024-04-19T15:10:39.999891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 569
32.8%
0 418
24.1%
2 213
 
12.3%
3 113
 
6.5%
4 58
 
3.3%
5 21
 
1.2%
6 5
 
0.3%
7 4
 
0.2%
8 4
 
0.2%
9 2
 
0.1%
(Missing) 325
18.7%
ValueCountFrequency (%)
0 418
24.1%
1 569
32.8%
2 213
 
12.3%
3 113
 
6.5%
4 58
 
3.3%
5 21
 
1.2%
6 5
 
0.3%
7 4
 
0.2%
8 4
 
0.2%
9 2
 
0.1%
ValueCountFrequency (%)
10 2
 
0.1%
9 2
 
0.1%
8 4
 
0.2%
7 4
 
0.2%
6 5
 
0.3%
5 21
 
1.2%
4 58
 
3.3%
3 113
 
6.5%
2 213
 
12.3%
1 569
32.8%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)1.2%
Missing381
Missing (%)22.0%
Infinite0
Infinite (%)0.0%
Mean3.0066519
Minimum0
Maximum22
Zeros263
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:40.113947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile6
Maximum22
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1762129
Coefficient of variation (CV)0.72379941
Kurtosis5.8922439
Mean3.0066519
Median Absolute Deviation (MAD)1
Skewness1.0919722
Sum4068
Variance4.7359025
MonotonicityNot monotonic
2024-04-19T15:10:40.231942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 303
17.5%
4 271
15.6%
0 263
15.2%
2 195
11.2%
5 151
 
8.7%
6 64
 
3.7%
1 48
 
2.8%
7 24
 
1.4%
8 16
 
0.9%
9 6
 
0.3%
Other values (6) 12
 
0.7%
(Missing) 381
22.0%
ValueCountFrequency (%)
0 263
15.2%
1 48
 
2.8%
2 195
11.2%
3 303
17.5%
4 271
15.6%
5 151
8.7%
6 64
 
3.7%
7 24
 
1.4%
8 16
 
0.9%
9 6
 
0.3%
ValueCountFrequency (%)
22 1
 
0.1%
17 1
 
0.1%
14 1
 
0.1%
12 2
 
0.1%
11 1
 
0.1%
10 6
 
0.3%
9 6
 
0.3%
8 16
 
0.9%
7 24
 
1.4%
6 64
3.7%

사용시작지하층
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1040 
<NA>
525 
1
168 
4
 
1

Length

Max length4
Median length1
Mean length1.9083045
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1040
60.0%
<NA> 525
30.3%
1 168
 
9.7%
4 1
 
0.1%

Length

2024-04-19T15:10:40.357434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:40.497202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1040
60.0%
na 525
30.3%
1 168
 
9.7%
4 1
 
0.1%

사용끝지하층
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
900 
<NA>
639 
1
194 
10
 
1

Length

Max length4
Median length1
Mean length2.106113
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 900
51.9%
<NA> 639
36.9%
1 194
 
11.2%
10 1
 
0.1%

Length

2024-04-19T15:10:40.687229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:40.829007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 900
51.9%
na 639
36.9%
1 194
 
11.2%
10 1
 
0.1%

한실수
Real number (ℝ)

MISSING  ZEROS 

Distinct36
Distinct (%)2.3%
Missing164
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean5.5624204
Minimum0
Maximum39
Zeros423
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:40.994736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q39
95-th percentile17
Maximum39
Range39
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.2697175
Coefficient of variation (CV)1.1271564
Kurtosis3.1995078
Mean5.5624204
Median Absolute Deviation (MAD)4
Skewness1.6159971
Sum8733
Variance39.309358
MonotonicityNot monotonic
2024-04-19T15:10:41.146741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 423
24.4%
2 135
 
7.8%
3 119
 
6.9%
1 104
 
6.0%
4 96
 
5.5%
6 83
 
4.8%
10 82
 
4.7%
5 77
 
4.4%
8 63
 
3.6%
7 60
 
3.5%
Other values (26) 328
18.9%
(Missing) 164
 
9.5%
ValueCountFrequency (%)
0 423
24.4%
1 104
 
6.0%
2 135
 
7.8%
3 119
 
6.9%
4 96
 
5.5%
5 77
 
4.4%
6 83
 
4.8%
7 60
 
3.5%
8 63
 
3.6%
9 52
 
3.0%
ValueCountFrequency (%)
39 1
 
0.1%
35 2
 
0.1%
34 2
 
0.1%
32 2
 
0.1%
31 1
 
0.1%
30 3
0.2%
29 7
0.4%
28 2
 
0.1%
27 3
0.2%
26 5
0.3%

양실수
Real number (ℝ)

MISSING  ZEROS 

Distinct77
Distinct (%)5.0%
Missing193
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean19.292018
Minimum0
Maximum343
Zeros175
Zeros (%)10.1%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:41.326630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median17
Q327
95-th percentile42
Maximum343
Range343
Interquartile range (IQR)18

Descriptive statistics

Standard deviation18.882937
Coefficient of variation (CV)0.97879533
Kurtosis91.049021
Mean19.292018
Median Absolute Deviation (MAD)9
Skewness6.7648731
Sum29729
Variance356.56532
MonotonicityNot monotonic
2024-04-19T15:10:41.492699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 175
 
10.1%
10 77
 
4.4%
17 57
 
3.3%
12 49
 
2.8%
20 49
 
2.8%
14 49
 
2.8%
18 48
 
2.8%
16 46
 
2.7%
22 45
 
2.6%
13 44
 
2.5%
Other values (67) 902
52.0%
(Missing) 193
 
11.1%
ValueCountFrequency (%)
0 175
10.1%
1 9
 
0.5%
2 20
 
1.2%
3 23
 
1.3%
4 19
 
1.1%
5 30
 
1.7%
6 24
 
1.4%
7 29
 
1.7%
8 36
 
2.1%
9 31
 
1.8%
ValueCountFrequency (%)
343 1
0.1%
273 1
0.1%
215 1
0.1%
204 1
0.1%
136 1
0.1%
129 1
0.1%
103 1
0.1%
82 1
0.1%
80 2
0.1%
79 1
0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1196 
<NA>
537 
2
 
1

Length

Max length4
Median length1
Mean length1.9290657
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1196
69.0%
<NA> 537
31.0%
2 1
 
0.1%

Length

2024-04-19T15:10:41.647282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:41.789988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1196
69.0%
na 537
31.0%
2 1
 
0.1%

발한실여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing6
Missing (%)0.3%
Memory size3.5 KiB
False
1728 
(Missing)
 
6
ValueCountFrequency (%)
False 1728
99.7%
(Missing) 6
 
0.3%
2024-04-19T15:10:41.886269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

좌석수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.5%
Missing536
Missing (%)30.9%
Infinite0
Infinite (%)0.0%
Mean0.043405676
Minimum0
Maximum30
Zeros1191
Zeros (%)68.7%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:41.984018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.90839531
Coefficient of variation (CV)20.92803
Kurtosis992.36419
Mean0.043405676
Median Absolute Deviation (MAD)0
Skewness30.451446
Sum52
Variance0.82518204
MonotonicityNot monotonic
2024-04-19T15:10:42.101774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1191
68.7%
4 2
 
0.1%
3 2
 
0.1%
30 1
 
0.1%
2 1
 
0.1%
6 1
 
0.1%
(Missing) 536
30.9%
ValueCountFrequency (%)
0 1191
68.7%
2 1
 
0.1%
3 2
 
0.1%
4 2
 
0.1%
6 1
 
0.1%
30 1
 
0.1%
ValueCountFrequency (%)
30 1
 
0.1%
6 1
 
0.1%
4 2
 
0.1%
3 2
 
0.1%
2 1
 
0.1%
0 1191
68.7%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1733
Missing (%)99.9%
Memory size13.7 KiB
2024-04-19T15:10:42.227569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories2 ?
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 row체류기간만 영업가능
ValueCountFrequency (%)
체류기간만 1
50.0%
영업가능 1
50.0%
2024-04-19T15:10:42.500647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
체 1
10.0%
류 1
10.0%
기 1
10.0%
간 1
10.0%
만 1
10.0%
1
10.0%
영 1
10.0%
업 1
10.0%
가 1
10.0%
능 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
90.0%
Space Separator 1
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
체 1
11.1%
류 1
11.1%
기 1
11.1%
간 1
11.1%
만 1
11.1%
영 1
11.1%
업 1
11.1%
가 1
11.1%
능 1
11.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
90.0%
Common 1
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
체 1
11.1%
류 1
11.1%
기 1
11.1%
간 1
11.1%
만 1
11.1%
영 1
11.1%
업 1
11.1%
가 1
11.1%
능 1
11.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
90.0%
ASCII 1
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
체 1
11.1%
류 1
11.1%
기 1
11.1%
간 1
11.1%
만 1
11.1%
영 1
11.1%
업 1
11.1%
가 1
11.1%
능 1
11.1%
ASCII
ValueCountFrequency (%)
1
100.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
1733 
20181101
 
1

Length

Max length8
Median length4
Mean length4.0023068
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1733
99.9%
20181101 1
 
0.1%

Length

2024-04-19T15:10:42.673350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:42.813477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1733
99.9%
20181101 1
 
0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
1733 
20190722
 
1

Length

Max length8
Median length4
Mean length4.0023068
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1733
99.9%
20190722 1
 
0.1%

Length

2024-04-19T15:10:42.962080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:43.088885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1733
99.9%
20190722 1
 
0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
808 
자가
595 
임대
331 

Length

Max length4
Median length2
Mean length2.9319493
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 808
46.6%
자가 595
34.3%
임대 331
19.1%

Length

2024-04-19T15:10:43.231248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:43.356139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 808
46.6%
자가 595
34.3%
임대 331
19.1%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1068 
<NA>
666 

Length

Max length4
Median length1
Mean length2.1522491
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1068
61.6%
<NA> 666
38.4%

Length

2024-04-19T15:10:43.466676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:43.573295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1068
61.6%
na 666
38.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)9.1%
Missing1668
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean1.7121212
Minimum0
Maximum40
Zeros32
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2024-04-19T15:10:43.668056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum40
Range40
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.0555509
Coefficient of variation (CV)3.5368705
Kurtosis31.862064
Mean1.7121212
Median Absolute Deviation (MAD)1
Skewness5.6180274
Sum113
Variance36.669697
MonotonicityNot monotonic
2024-04-19T15:10:43.787719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 32
 
1.8%
1 24
 
1.4%
2 7
 
0.4%
40 1
 
0.1%
30 1
 
0.1%
5 1
 
0.1%
(Missing) 1668
96.2%
ValueCountFrequency (%)
0 32
1.8%
1 24
1.4%
2 7
 
0.4%
5 1
 
0.1%
30 1
 
0.1%
40 1
 
0.1%
ValueCountFrequency (%)
40 1
 
0.1%
30 1
 
0.1%
5 1
 
0.1%
2 7
 
0.4%
1 24
1.4%
0 32
1.8%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
1679 
0
 
32
1
 
18
2
 
2
30
 
2

Length

Max length4
Median length4
Mean length3.9059977
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1679
96.8%
0 32
 
1.8%
1 18
 
1.0%
2 2
 
0.1%
30 2
 
0.1%
5 1
 
0.1%

Length

2024-04-19T15:10:43.954758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:44.068022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1679
96.8%
0 32
 
1.8%
1 18
 
1.0%
2 2
 
0.1%
30 2
 
0.1%
5 1
 
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1056 
<NA>
678 

Length

Max length4
Median length1
Mean length2.1730104
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1056
60.9%
<NA> 678
39.1%

Length

2024-04-19T15:10:44.185617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:44.301665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1056
60.9%
na 678
39.1%

침대수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
0
1052 
<NA>
679 
21
 
1
19
 
1
15
 
1

Length

Max length4
Median length1
Mean length2.1764706
Min length1

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1052
60.7%
<NA> 679
39.2%
21 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%

Length

2024-04-19T15:10:44.426409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:10:44.556518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1052
60.7%
na 679
39.2%
21 1
 
0.1%
19 1
 
0.1%
15 1
 
0.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing3
Missing (%)0.2%
Memory size3.5 KiB
False
1729 
True
 
2
(Missing)
 
3
ValueCountFrequency (%)
False 1729
99.7%
True 2
 
0.1%
(Missing) 3
 
0.2%
2024-04-19T15:10:44.649448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
01숙박업03_11_03_P34100003410000-201-2010-0000120101111<NA>1영업/정상1영업<NA><NA><NA><NA>053 2522286288.88700191대구광역시 중구 종로1가 0041-0082번지대구광역시 중구 종로 44-31 (종로1가)41935아리랑 민속모텔20180221171836I2018-08-31 23:59:59.0숙박업 기타343746.379146264515.775816숙박업 기타0000001100N0<NA><NA><NA>자가0<NA><NA>00N
12숙박업03_11_03_P34100003410000-201-1981-0000619811231<NA>1영업/정상1영업<NA><NA><NA><NA>053 4230031383.00700813대구광역시 중구 대봉동 0734-0005번지대구광역시 중구 명륜로26길 61 (대봉동)41960삼익장20180709095631I2018-08-31 23:59:59.0여관업344220.564457263070.8599여관업3033001600N0<NA><NA><NA><NA>0<NA><NA>00N
23숙박업03_11_03_P34100003410000-201-2004-0000320040303<NA>1영업/정상1영업<NA><NA><NA><NA>053 25237501,384.31700290대구광역시 중구 시장북로 0011-0010번지대구광역시 중구 국채보상로99길 38 (시장북로)41921야자(YAJA)대구서문시장점20190517162225U2019-05-19 02:40:00.0여관업342900.048628264716.228398여관업7117113330N0<NA><NA><NA><NA>0<NA><NA>00N
34숙박업03_11_03_P34100003410000-201-1980-0000419801126<NA>1영업/정상1영업<NA><NA><NA><NA>053 4228902528.18700801대구광역시 중구 교동 0070-0019번지대구광역시 중구 교동2길 29-11 (교동)41912호원장여관20180219153941I2018-08-31 23:59:59.0여관업344281.329551264832.499636여관업4044002500N0<NA><NA><NA><NA>0<NA><NA>00N
45숙박업03_11_03_P34100003410000-201-1969-0000419690430<NA>1영업/정상1영업<NA><NA><NA><NA>053 2550059110.88700824대구광역시 중구 북성로1가 0069-0001번지대구광역시 중구 북성로 100-23 (북성로1가)41918명신20180807165723I2018-08-31 23:59:59.0여관업343805.814577264903.025595여관업2022002300N0<NA><NA><NA><NA>0<NA><NA>00N
56숙박업03_11_03_P34100003410000-201-2001-0000120010914<NA>1영업/정상1영업<NA><NA><NA><NA>053 252 3536932.00700850대구광역시 중구 수창동 0020-0003번지대구광역시 중구 서성로 100 (수창동)41916큐20180224113345I2018-08-31 23:59:59.0여관업343340.741039265089.189014여관업5144002900N0<NA><NA><NA><NA>0<NA><NA>00N
67숙박업03_11_03_P34100003410000-201-1988-0000219880628<NA>1영업/정상1영업<NA><NA><NA><NA>053 2571116612.48700280대구광역시 중구 대안동 0021-0001번지대구광역시 중구 서성로16길 84 (대안동)41918지프모텔20180221174330I2018-08-31 23:59:59.0여관업343712.374964264845.28268여관업4044000230N0<NA><NA><NA><NA>0<NA><NA>00N
78숙박업03_11_03_P34100003410000-201-1980-0000519800611<NA>1영업/정상1영업<NA><NA><NA><NA>053 4225454297.23700842대구광역시 중구 동인동2가 0062-0008번지대구광역시 중구 경상감영길 298-7 (동인동2가)41914아트모텔20180307112809I2018-08-31 23:59:59.0여관업344763.90984264541.777408여관업4044000230N0<NA><NA><NA>임대0<NA><NA>00N
89숙박업03_11_03_P34100003410000-201-1974-0000419740305<NA>1영업/정상1영업<NA><NA><NA><NA>053 554801825.00700814대구광역시 중구 대신동 0001-0026번지대구광역시 중구 달성공원로6길 9-1 (대신동)41925미모여인숙20190403184317U2019-04-05 02:40:00.0여인숙업342617.85997264790.554098여인숙업202200700N0<NA><NA><NA><NA>0<NA><NA>00N
910숙박업03_11_03_P34100003410000-201-1988-0000119880316<NA>1영업/정상1영업<NA><NA><NA><NA>053 4273178850.00700421대구광역시 중구 동인동1가 0257-0002번지대구광역시 중구 공평로20길 47 (동인동1가)41911궁모텔20190215135717U2019-02-17 02:40:00.0여관업344740.431055264688.048813여관업4044000290N0<NA><NA><NA><NA>0<NA><NA>00N
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부좌석수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
17241725숙박업03_11_03_P34800003480000-201-1995-0001219951229<NA>1영업/정상1영업<NA><NA><NA><NA>053 6165009794.00711844대구광역시 달성군 옥포면 반송리 350-2번지대구광역시 달성군 옥포면 용연사길 84-942977앤모텔20171123103410I2018-08-31 23:59:59.0여관업335776.367701251454.323528여관업4113000240N0<NA><NA><NA>임대0<NA><NA>00N
17251726숙박업03_11_03_P34800003480000-201-1997-0001319970430<NA>1영업/정상1영업<NA><NA><NA><NA>053 6160177658.89711874대구광역시 달성군 현풍면 하리 204번지대구광역시 달성군 현풍면 현풍중앙로 51-443003동원장여관20180726094909I2018-08-31 23:59:59.0여관업330623.604677244752.614707여관업40240013100N0<NA><NA><NA>자가0<NA><NA>00N
17261727숙박업03_11_03_P34800003480000-201-1994-0001019941220<NA>1영업/정상1영업<NA><NA><NA><NA>053 58188431,125.48711821대구광역시 달성군 하빈면 하산리 1054-3번지대구광역시 달성군 하빈면 하목정길 4942900비즈니스호텔 유럽20171123103004I2018-08-31 23:59:59.0여관업326172.635898265379.321278여관업41441120130N0<NA><NA><NA>자가0<NA><NA>00N
17271728숙박업03_11_03_P34800003480000-201-1995-0001119951130<NA>1영업/정상1영업<NA><NA><NA><NA>053 261 55771,050.56711844대구광역시 달성군 옥포면 김흥리 629-1번지대구광역시 달성군 옥포면 옥포로113길 342977비너스모텔20180730160747I2018-08-31 23:59:59.0여관업334845.417663250608.694875여관업51250011210N0<NA><NA><NA>자가0<NA><NA>00N
17281729숙박업03_11_03_P34800003480000-201-1986-0000119861222<NA>1영업/정상1영업<NA><NA><NA><NA>053 2635688608.00711841대구광역시 달성군 옥포면 간경리 850번지대구광역시 달성군 옥포면 비슬로457길 342972모텔 이너스20180518165734I2018-08-31 23:59:59.0여관업332870.658242255521.770518여관업4024001650N0<NA><NA><NA>자가0<NA><NA>00N
17291730숙박업03_11_03_P34800003480000-201-1988-0000319881220<NA>1영업/정상1영업<NA><NA><NA><NA>053 614 0477351.60711852대구광역시 달성군 논공읍 남리 224-96번지대구광역시 달성군 논공읍 논공로 83442978원앙파크장20180713173625I2018-08-31 23:59:59.0여관업329851.611095248437.262624여관업3123002130N0<NA><NA><NA>임대0<NA><NA>00N
17301731숙박업03_11_03_P34800003480000-201-1994-0000719940730<NA>1영업/정상1영업<NA><NA><NA><NA>053 7675002641.00711863대구광역시 달성군 가창면 삼산리 965번지대구광역시 달성군 가창면 우록길 6042940힐링20180730114543I2018-08-31 23:59:59.0여관업349820.526547249108.900599여관업3113002220N0<NA><NA><NA>자가0<NA><NA>00N
17311732숙박업03_11_03_P34800003480000-201-1995-0000619950315<NA>1영업/정상1영업<NA><NA><NA><NA>053 7682355940.00711863대구광역시 달성군 가창면 삼산리 276-2번지대구광역시 달성군 가창면 가창로 17842940레드모텔20171123103211I2018-08-31 23:59:59.0여관업350553.884052249356.52424여관업4014000200N0<NA><NA><NA>임대0<NA><NA>00N
17321733숙박업03_11_03_P34800003480000-201-1997-0001519970104<NA>1영업/정상1영업<NA><NA><NA><NA>053 627 6666801.66<NA>대구광역시 달성군 유가읍 유곡리 837-1번지대구광역시 달성군 유가읍 비슬로64길 2242993호텔히든20171123104025I2018-08-31 23:59:59.0여관업331020.000269242124.922955여관업4024006210N0<NA><NA><NA>자가0<NA><NA>00N
17331734숙박업03_11_03_P34800003480000-201-1996-0001219961227<NA>1영업/정상1영업<NA><NA><NA><NA>053 6162937861.00711844대구광역시 달성군 옥포면 김흥리 427번지대구광역시 달성군 옥포면 옥포로 61742977발렌타인 모텔20171123103820I2018-08-31 23:59:59.0여관업334369.738024250577.153468여관업3013004230N0<NA><NA><NA>임대0<NA><NA>00N