Overview

Dataset statistics

Number of variables44
Number of observations3201
Missing cells33006
Missing cells (%)23.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory380.0 B

Variable types

Numeric15
Categorical14
Text6
Unsupported7
DateTime1
Boolean1

Dataset

Description22년10월_6270000_대구광역시_05_19_01_P_이용업
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000096815&dataSetDetailId=DDI_0000096831&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
업태구분명 is highly imbalanced (90.9%)Imbalance
위생업태명 is highly imbalanced (90.9%)Imbalance
여성종사자수 is highly imbalanced (67.8%)Imbalance
남성종사자수 is highly imbalanced (55.7%)Imbalance
다중이용업소여부 is highly imbalanced (99.6%)Imbalance
인허가취소일자 has 3201 (100.0%) missing valuesMissing
폐업일자 has 908 (28.4%) missing valuesMissing
휴업시작일자 has 3201 (100.0%) missing valuesMissing
휴업종료일자 has 3201 (100.0%) missing valuesMissing
재개업일자 has 3201 (100.0%) missing valuesMissing
소재지전화 has 995 (31.1%) missing valuesMissing
도로명전체주소 has 1411 (44.1%) missing valuesMissing
도로명우편번호 has 1436 (44.9%) missing valuesMissing
좌표정보(X) has 147 (4.6%) missing valuesMissing
좌표정보(Y) has 147 (4.6%) missing valuesMissing
건물지상층수 has 582 (18.2%) missing valuesMissing
건물지하층수 has 945 (29.5%) missing valuesMissing
사용시작지상층 has 816 (25.5%) missing valuesMissing
사용끝지상층 has 1048 (32.7%) missing valuesMissing
의자수 has 349 (10.9%) missing valuesMissing
조건부허가신고사유 has 3201 (100.0%) missing valuesMissing
조건부허가시작일자 has 3201 (100.0%) missing valuesMissing
조건부허가종료일자 has 3201 (100.0%) missing valuesMissing
침대수 has 1782 (55.7%) missing valuesMissing
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
조건부허가신고사유 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 647 (20.2%) zerosZeros
건물지하층수 has 1221 (38.1%) zerosZeros
사용시작지상층 has 531 (16.6%) zerosZeros
사용끝지상층 has 311 (9.7%) zerosZeros
의자수 has 164 (5.1%) zerosZeros
침대수 has 1403 (43.8%) zerosZeros

Reproduction

Analysis started2023-12-10 20:05:35.558672
Analysis finished2023-12-10 20:05:37.926806
Duration2.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1601
Minimum1
Maximum3201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:38.061318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile161
Q1801
median1601
Q32401
95-th percentile3041
Maximum3201
Range3200
Interquartile range (IQR)1600

Descriptive statistics

Standard deviation924.19343
Coefficient of variation (CV)0.57726011
Kurtosis-1.2
Mean1601
Median Absolute Deviation (MAD)800
Skewness0
Sum5124801
Variance854133.5
MonotonicityStrictly increasing
2023-12-11T05:05:38.314596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2139 1
 
< 0.1%
2129 1
 
< 0.1%
2130 1
 
< 0.1%
2131 1
 
< 0.1%
2132 1
 
< 0.1%
2133 1
 
< 0.1%
2134 1
 
< 0.1%
2135 1
 
< 0.1%
2136 1
 
< 0.1%
Other values (3191) 3191
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3201 1
< 0.1%
3200 1
< 0.1%
3199 1
< 0.1%
3198 1
< 0.1%
3197 1
< 0.1%
3196 1
< 0.1%
3195 1
< 0.1%
3194 1
< 0.1%
3193 1
< 0.1%
3192 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
이용업
3201 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
이용업 3201
100.0%

Length

2023-12-11T05:05:38.547514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:38.712687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 3201
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
05_19_01_P
3201 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_19_01_P
2nd row05_19_01_P
3rd row05_19_01_P
4th row05_19_01_P
5th row05_19_01_P

Common Values

ValueCountFrequency (%)
05_19_01_P 3201
100.0%

Length

2023-12-11T05:05:38.887790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:39.056223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 3201
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3445342.1
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:39.217218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13430000
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation21027.143
Coefficient of variation (CV)0.006103064
Kurtosis-1.2541581
Mean3445342.1
Median Absolute Deviation (MAD)20000
Skewness-0.12581638
Sum1.102854 × 1010
Variance4.4214076 × 108
MonotonicityIncreasing
2023-12-11T05:05:39.419533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 624
19.5%
3450000 518
16.2%
3420000 514
16.1%
3460000 452
14.1%
3430000 416
13.0%
3440000 278
8.7%
3410000 248
 
7.7%
3480000 151
 
4.7%
ValueCountFrequency (%)
3410000 248
 
7.7%
3420000 514
16.1%
3430000 416
13.0%
3440000 278
8.7%
3450000 518
16.2%
3460000 452
14.1%
3470000 624
19.5%
3480000 151
 
4.7%
ValueCountFrequency (%)
3480000 151
 
4.7%
3470000 624
19.5%
3460000 452
14.1%
3450000 518
16.2%
3440000 278
8.7%
3430000 416
13.0%
3420000 514
16.1%
3410000 248
 
7.7%

관리번호
Text

UNIQUE 

Distinct3201
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-11T05:05:39.748721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters70422
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

Unique3201 ?
Unique (%)100.0%

Sample

1st row3410000-203-2008-00003
2nd row3410000-203-2010-00003
3rd row3410000-203-2010-00004
4th row3410000-203-2001-00001
5th row3410000-203-2010-00005
ValueCountFrequency (%)
3410000-203-2008-00003 1
 
< 0.1%
3460000-203-1999-00010 1
 
< 0.1%
3460000-203-2001-00012 1
 
< 0.1%
3460000-203-1998-00016 1
 
< 0.1%
3460000-203-1998-00018 1
 
< 0.1%
3460000-203-1998-00019 1
 
< 0.1%
3460000-203-1999-00028 1
 
< 0.1%
3460000-203-2002-00017 1
 
< 0.1%
3460000-203-2002-00019 1
 
< 0.1%
3460000-203-1997-00005 1
 
< 0.1%
Other values (3191) 3191
99.7%
2023-12-11T05:05:40.252640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31104
44.2%
- 9603
 
13.6%
3 7872
 
11.2%
2 6795
 
9.6%
4 4194
 
6.0%
1 3561
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1273
 
1.8%
5 1097
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60819
86.4%
Dash Punctuation 9603
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31104
51.1%
3 7872
 
12.9%
2 6795
 
11.2%
4 4194
 
6.9%
1 3561
 
5.9%
9 2617
 
4.3%
7 1390
 
2.3%
6 1273
 
2.1%
5 1097
 
1.8%
8 916
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9603
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70422
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31104
44.2%
- 9603
 
13.6%
3 7872
 
11.2%
2 6795
 
9.6%
4 4194
 
6.0%
1 3561
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1273
 
1.8%
5 1097
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70422
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31104
44.2%
- 9603
 
13.6%
3 7872
 
11.2%
2 6795
 
9.6%
4 4194
 
6.0%
1 3561
 
5.1%
9 2617
 
3.7%
7 1390
 
2.0%
6 1273
 
1.8%
5 1097
 
1.6%

인허가일자
Real number (ℝ)

Distinct2123
Distinct (%)66.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20019546
Minimum19601125
Maximum20221004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:40.481861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19601125
5-th percentile19810720
Q119970128
median20020911
Q320080401
95-th percentile20190226
Maximum20221004
Range619879
Interquartile range (IQR)110273

Descriptive statistics

Standard deviation102406.47
Coefficient of variation (CV)0.0051153243
Kurtosis1.2685568
Mean20019546
Median Absolute Deviation (MAD)50791
Skewness-0.63537358
Sum6.4082568 × 1010
Variance1.0487085 × 1010
MonotonicityNot monotonic
2023-12-11T05:05:40.706251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19961221 113
 
3.5%
19961224 97
 
3.0%
20030728 85
 
2.7%
20030708 77
 
2.4%
19961212 28
 
0.9%
19970114 23
 
0.7%
20030120 22
 
0.7%
19970120 22
 
0.7%
19961213 19
 
0.6%
19771112 16
 
0.5%
Other values (2113) 2699
84.3%
ValueCountFrequency (%)
19601125 1
< 0.1%
19601220 1
< 0.1%
19620824 1
< 0.1%
19630420 1
< 0.1%
19631009 1
< 0.1%
19631109 1
< 0.1%
19640812 1
< 0.1%
19650525 1
< 0.1%
19650731 1
< 0.1%
19661112 1
< 0.1%
ValueCountFrequency (%)
20221004 1
< 0.1%
20220929 1
< 0.1%
20220927 1
< 0.1%
20220926 1
< 0.1%
20220915 1
< 0.1%
20220907 1
< 0.1%
20220825 1
< 0.1%
20220803 1
< 0.1%
20220712 1
< 0.1%
20220711 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
3
2293 
1
908 

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 2293
71.6%
1 908
 
28.4%

Length

2023-12-11T05:05:40.954779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:41.142146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2293
71.6%
1 908
 
28.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
폐업
2293 
영업/정상
908 

Length

Max length5
Median length2
Mean length2.8509841
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2293
71.6%
영업/정상 908
 
28.4%

Length

2023-12-11T05:05:41.339273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:41.513594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2293
71.6%
영업/정상 908
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2
2293 
1
908 

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 2293
71.6%
1 908
 
28.4%

Length

2023-12-11T05:05:41.682087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:41.856772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2293
71.6%
1 908
 
28.4%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
폐업
2293 
영업
908 

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 2293
71.6%
영업 908
 
28.4%

Length

2023-12-11T05:05:42.046383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:42.217961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2293
71.6%
영업 908
 
28.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct1650
Distinct (%)72.0%
Missing908
Missing (%)28.4%
Infinite0
Infinite (%)0.0%
Mean20101732
Minimum19980506
Maximum20221026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:42.402089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980506
5-th percentile20030308
Q120041025
median20090129
Q320160308
95-th percentile20210624
Maximum20221026
Range240520
Interquartile range (IQR)119283

Descriptive statistics

Standard deviation62793.301
Coefficient of variation (CV)0.0031237756
Kurtosis-1.2051431
Mean20101732
Median Absolute Deviation (MAD)50023
Skewness0.40145626
Sum4.6093272 × 1010
Variance3.9429986 × 109
MonotonicityNot monotonic
2023-12-11T05:05:42.655860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040312 41
 
1.3%
20031231 28
 
0.9%
20030708 26
 
0.8%
20031120 25
 
0.8%
20031229 14
 
0.4%
20031226 11
 
0.3%
20050117 11
 
0.3%
20031128 10
 
0.3%
20031230 10
 
0.3%
20031222 9
 
0.3%
Other values (1640) 2108
65.9%
(Missing) 908
28.4%
ValueCountFrequency (%)
19980506 1
< 0.1%
19990524 1
< 0.1%
20000603 1
< 0.1%
20000710 1
< 0.1%
20000712 1
< 0.1%
20000812 1
< 0.1%
20000831 1
< 0.1%
20000925 1
< 0.1%
20001009 1
< 0.1%
20001212 1
< 0.1%
ValueCountFrequency (%)
20221026 2
0.1%
20221025 2
0.1%
20221024 1
< 0.1%
20221019 1
< 0.1%
20221011 1
< 0.1%
20221006 1
< 0.1%
20220929 1
< 0.1%
20220928 1
< 0.1%
20220927 1
< 0.1%
20220926 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB

소재지전화
Text

MISSING 

Distinct2082
Distinct (%)94.4%
Missing995
Missing (%)31.1%
Memory size25.1 KiB
2023-12-11T05:05:43.183704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.771079
Min length6

Characters and Unicode

Total characters23761
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

Unique1974 ?
Unique (%)89.5%

Sample

1st row053 2572955
2nd row053 2536037
3rd row053 4233939
4th row053 4236188
5th row053 2562176
ValueCountFrequency (%)
053 1920
41.9%
764 16
 
0.3%
352 11
 
0.2%
763 11
 
0.2%
791 10
 
0.2%
762 9
 
0.2%
956 9
 
0.2%
754 8
 
0.2%
756 8
 
0.2%
755 8
 
0.2%
Other values (2213) 2570
56.1%
2023-12-11T05:05:44.030296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4376
18.4%
3 3557
15.0%
0 2936
12.4%
2393
10.1%
2 1937
8.2%
6 1809
7.6%
7 1459
 
6.1%
4 1440
 
6.1%
1 1316
 
5.5%
8 1271
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21368
89.9%
Space Separator 2393
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4376
20.5%
3 3557
16.6%
0 2936
13.7%
2 1937
9.1%
6 1809
8.5%
7 1459
 
6.8%
4 1440
 
6.7%
1 1316
 
6.2%
8 1271
 
5.9%
9 1267
 
5.9%
Space Separator
ValueCountFrequency (%)
2393
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23761
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4376
18.4%
3 3557
15.0%
0 2936
12.4%
2393
10.1%
2 1937
8.2%
6 1809
7.6%
7 1459
 
6.1%
4 1440
 
6.1%
1 1316
 
5.5%
8 1271
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4376
18.4%
3 3557
15.0%
0 2936
12.4%
2393
10.1%
2 1937
8.2%
6 1809
7.6%
7 1459
 
6.1%
4 1440
 
6.1%
1 1316
 
5.5%
8 1271
 
5.3%
Distinct1407
Distinct (%)44.3%
Missing24
Missing (%)0.7%
Memory size25.1 KiB
2023-12-11T05:05:44.796392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.7758892
Min length3

Characters and Unicode

Total characters15173
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

Unique992 ?
Unique (%)31.2%

Sample

1st row9.36
2nd row12.60
3rd row6.20
4th row39.60
5th row56.10
ValueCountFrequency (%)
00 239
 
7.5%
16.50 60
 
1.9%
33.00 59
 
1.9%
19.80 49
 
1.5%
20.00 43
 
1.4%
23.10 40
 
1.3%
15.00 37
 
1.2%
6.60 32
 
1.0%
26.40 32
 
1.0%
18.00 31
 
1.0%
Other values (1397) 2555
80.4%
2023-12-11T05:05:46.062814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3363
22.2%
. 3177
20.9%
1 1472
9.7%
2 1450
9.6%
3 1001
 
6.6%
5 958
 
6.3%
6 893
 
5.9%
4 814
 
5.4%
8 759
 
5.0%
9 692
 
4.6%
Other values (2) 594
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11992
79.0%
Other Punctuation 3181
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3363
28.0%
1 1472
12.3%
2 1450
12.1%
3 1001
 
8.3%
5 958
 
8.0%
6 893
 
7.4%
4 814
 
6.8%
8 759
 
6.3%
9 692
 
5.8%
7 590
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 3177
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 15173
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3363
22.2%
. 3177
20.9%
1 1472
9.7%
2 1450
9.6%
3 1001
 
6.6%
5 958
 
6.3%
6 893
 
5.9%
4 814
 
5.4%
8 759
 
5.0%
9 692
 
4.6%
Other values (2) 594
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15173
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3363
22.2%
. 3177
20.9%
1 1472
9.7%
2 1450
9.6%
3 1001
 
6.6%
5 958
 
6.3%
6 893
 
5.9%
4 814
 
5.4%
8 759
 
5.0%
9 692
 
4.6%
Other values (2) 594
 
3.9%

소재지우편번호
Real number (ℝ)

Distinct544
Distinct (%)17.0%
Missing9
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean704176.09
Minimum700010
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:46.482567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700815
Q1702050
median703840
Q3705809
95-th percentile706852
Maximum711892
Range11882
Interquartile range (IQR)3759

Descriptive statistics

Standard deviation2488.444
Coefficient of variation (CV)0.0035338377
Kurtosis1.729931
Mean704176.09
Median Absolute Deviation (MAD)1965
Skewness1.0586631
Sum2.2477301 × 109
Variance6192353.5
MonotonicityNot monotonic
2023-12-11T05:05:46.846466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704080 41
 
1.3%
704060 35
 
1.1%
702040 30
 
0.9%
704932 25
 
0.8%
711852 23
 
0.7%
704834 23
 
0.7%
703805 22
 
0.7%
705809 22
 
0.7%
704904 22
 
0.7%
706839 21
 
0.7%
Other values (534) 2928
91.5%
ValueCountFrequency (%)
700010 7
0.2%
700020 3
0.1%
700030 4
0.1%
700040 1
 
< 0.1%
700060 1
 
< 0.1%
700070 1
 
< 0.1%
700081 1
 
< 0.1%
700082 4
0.1%
700093 1
 
< 0.1%
700111 4
0.1%
ValueCountFrequency (%)
711892 4
0.1%
711891 6
0.2%
711874 5
0.2%
711873 3
 
0.1%
711872 9
0.3%
711871 1
 
< 0.1%
711864 4
0.1%
711863 1
 
< 0.1%
711861 2
 
0.1%
711858 2
 
0.1%
Distinct2832
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-11T05:05:47.474534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length46
Mean length23.696345
Min length17

Characters and Unicode

Total characters75852
Distinct characters288
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2546 ?
Unique (%)79.5%

Sample

1st row대구광역시 중구 서성로1가 0109-0001번지 (2층)
2nd row대구광역시 중구 동인동4가 0347-0001번지
3rd row대구광역시 중구 남산동 0693-0008번지 지상2층
4th row대구광역시 중구 수창동 0099-0002번지
5th row대구광역시 중구 대신동 0115-0005번지 지상2층
ValueCountFrequency (%)
대구광역시 3201
22.8%
달서구 624
 
4.4%
북구 518
 
3.7%
동구 515
 
3.7%
수성구 451
 
3.2%
서구 416
 
3.0%
남구 278
 
2.0%
중구 248
 
1.8%
대명동 205
 
1.5%
달성군 151
 
1.1%
Other values (3207) 7436
53.0%
2023-12-11T05:05:48.456457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13922
18.4%
6301
 
8.3%
3777
 
5.0%
1 3635
 
4.8%
3540
 
4.7%
3233
 
4.3%
3209
 
4.2%
3205
 
4.2%
3172
 
4.2%
- 2774
 
3.7%
Other values (278) 29084
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42162
55.6%
Decimal Number 16268
 
21.4%
Space Separator 13922
 
18.4%
Dash Punctuation 2774
 
3.7%
Open Punctuation 311
 
0.4%
Close Punctuation 311
 
0.4%
Other Punctuation 61
 
0.1%
Uppercase Letter 42
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6301
14.9%
3777
 
9.0%
3540
 
8.4%
3233
 
7.7%
3209
 
7.6%
3205
 
7.6%
3172
 
7.5%
2731
 
6.5%
1109
 
2.6%
890
 
2.1%
Other values (251) 10995
26.1%
Decimal Number
ValueCountFrequency (%)
1 3635
22.3%
2 2199
13.5%
0 1955
12.0%
3 1577
9.7%
4 1428
 
8.8%
5 1270
 
7.8%
6 1098
 
6.7%
7 1072
 
6.6%
9 1036
 
6.4%
8 998
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 17
40.5%
B 13
31.0%
T 4
 
9.5%
P 4
 
9.5%
S 1
 
2.4%
C 1
 
2.4%
L 1
 
2.4%
H 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 54
88.5%
/ 3
 
4.9%
. 3
 
4.9%
@ 1
 
1.6%
Space Separator
ValueCountFrequency (%)
13922
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2774
100.0%
Open Punctuation
ValueCountFrequency (%)
( 311
100.0%
Close Punctuation
ValueCountFrequency (%)
) 311
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42161
55.6%
Common 33648
44.4%
Latin 42
 
0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6301
14.9%
3777
 
9.0%
3540
 
8.4%
3233
 
7.7%
3209
 
7.6%
3205
 
7.6%
3172
 
7.5%
2731
 
6.5%
1109
 
2.6%
890
 
2.1%
Other values (250) 10994
26.1%
Common
ValueCountFrequency (%)
13922
41.4%
1 3635
 
10.8%
- 2774
 
8.2%
2 2199
 
6.5%
0 1955
 
5.8%
3 1577
 
4.7%
4 1428
 
4.2%
5 1270
 
3.8%
6 1098
 
3.3%
7 1072
 
3.2%
Other values (9) 2718
 
8.1%
Latin
ValueCountFrequency (%)
A 17
40.5%
B 13
31.0%
T 4
 
9.5%
P 4
 
9.5%
S 1
 
2.4%
C 1
 
2.4%
L 1
 
2.4%
H 1
 
2.4%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42161
55.6%
ASCII 33690
44.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13922
41.3%
1 3635
 
10.8%
- 2774
 
8.2%
2 2199
 
6.5%
0 1955
 
5.8%
3 1577
 
4.7%
4 1428
 
4.2%
5 1270
 
3.8%
6 1098
 
3.3%
7 1072
 
3.2%
Other values (17) 2760
 
8.2%
Hangul
ValueCountFrequency (%)
6301
14.9%
3777
 
9.0%
3540
 
8.4%
3233
 
7.7%
3209
 
7.6%
3205
 
7.6%
3172
 
7.5%
2731
 
6.5%
1109
 
2.6%
890
 
2.1%
Other values (250) 10994
26.1%
CJK
ValueCountFrequency (%)
1
100.0%

도로명전체주소
Text

MISSING 

Distinct1705
Distinct (%)95.3%
Missing1411
Missing (%)44.1%
Memory size25.1 KiB
2023-12-11T05:05:49.112992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length27.715084
Min length18

Characters and Unicode

Total characters49610
Distinct characters307
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

Unique1635 ?
Unique (%)91.3%

Sample

1st row대구광역시 중구 국채보상로 723 (동인동4가)
2nd row대구광역시 중구 국채보상로 458, 2층 (대신동)
3rd row대구광역시 중구 국채보상로 570-8 (전동)
4th row대구광역시 중구 달구벌대로447길 72-1 (삼덕동3가)
5th row대구광역시 중구 중앙대로77길 36 (종로2가)
ValueCountFrequency (%)
대구광역시 1790
 
17.7%
달서구 338
 
3.4%
1층 305
 
3.0%
동구 293
 
2.9%
북구 289
 
2.9%
수성구 253
 
2.5%
서구 208
 
2.1%
남구 172
 
1.7%
중구 138
 
1.4%
대명동 123
 
1.2%
Other values (2051) 6179
61.3%
2023-12-11T05:05:49.900700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8298
 
16.7%
3684
 
7.4%
2389
 
4.8%
2282
 
4.6%
1 2025
 
4.1%
1825
 
3.7%
) 1810
 
3.6%
( 1810
 
3.6%
1797
 
3.6%
1793
 
3.6%
Other values (297) 21897
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28692
57.8%
Space Separator 8298
 
16.7%
Decimal Number 7669
 
15.5%
Close Punctuation 1810
 
3.6%
Open Punctuation 1810
 
3.6%
Other Punctuation 976
 
2.0%
Dash Punctuation 320
 
0.6%
Uppercase Letter 34
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3684
 
12.8%
2389
 
8.3%
2282
 
8.0%
1825
 
6.4%
1797
 
6.3%
1793
 
6.2%
1704
 
5.9%
989
 
3.4%
747
 
2.6%
710
 
2.5%
Other values (271) 10772
37.5%
Decimal Number
ValueCountFrequency (%)
1 2025
26.4%
2 1134
14.8%
3 899
11.7%
0 633
 
8.3%
4 627
 
8.2%
5 549
 
7.2%
6 527
 
6.9%
7 474
 
6.2%
8 419
 
5.5%
9 382
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
A 15
44.1%
B 11
32.4%
E 2
 
5.9%
P 2
 
5.9%
T 2
 
5.9%
H 1
 
2.9%
S 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 973
99.7%
@ 1
 
0.1%
/ 1
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
8298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1810
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1810
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 320
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28692
57.8%
Common 20884
42.1%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3684
 
12.8%
2389
 
8.3%
2282
 
8.0%
1825
 
6.4%
1797
 
6.3%
1793
 
6.2%
1704
 
5.9%
989
 
3.4%
747
 
2.6%
710
 
2.5%
Other values (271) 10772
37.5%
Common
ValueCountFrequency (%)
8298
39.7%
1 2025
 
9.7%
) 1810
 
8.7%
( 1810
 
8.7%
2 1134
 
5.4%
, 973
 
4.7%
3 899
 
4.3%
0 633
 
3.0%
4 627
 
3.0%
5 549
 
2.6%
Other values (9) 2126
 
10.2%
Latin
ValueCountFrequency (%)
A 15
44.1%
B 11
32.4%
E 2
 
5.9%
P 2
 
5.9%
T 2
 
5.9%
H 1
 
2.9%
S 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28692
57.8%
ASCII 20918
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8298
39.7%
1 2025
 
9.7%
) 1810
 
8.7%
( 1810
 
8.7%
2 1134
 
5.4%
, 973
 
4.7%
3 899
 
4.3%
0 633
 
3.0%
4 627
 
3.0%
5 549
 
2.6%
Other values (16) 2160
 
10.3%
Hangul
ValueCountFrequency (%)
3684
 
12.8%
2389
 
8.3%
2282
 
8.0%
1825
 
6.4%
1797
 
6.3%
1793
 
6.2%
1704
 
5.9%
989
 
3.4%
747
 
2.6%
710
 
2.5%
Other values (271) 10772
37.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct850
Distinct (%)48.2%
Missing1436
Missing (%)44.9%
Infinite0
Infinite (%)0.0%
Mean42009.75
Minimum41000
Maximum43024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:50.111233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41000
5-th percentile41120.2
Q141535
median41963
Q342509
95-th percentile42918
Maximum43024
Range2024
Interquartile range (IQR)974

Descriptive statistics

Standard deviation577.50515
Coefficient of variation (CV)0.013746932
Kurtosis-1.1902217
Mean42009.75
Median Absolute Deviation (MAD)498
Skewness0.001189047
Sum74147208
Variance333512.2
MonotonicityNot monotonic
2023-12-11T05:05:50.321072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41558 9
 
0.3%
41913 9
 
0.3%
42612 8
 
0.2%
41465 8
 
0.2%
41122 8
 
0.2%
42632 8
 
0.2%
41947 7
 
0.2%
41535 7
 
0.2%
42653 7
 
0.2%
42400 7
 
0.2%
Other values (840) 1687
52.7%
(Missing) 1436
44.9%
ValueCountFrequency (%)
41000 3
0.1%
41002 4
0.1%
41005 2
0.1%
41007 3
0.1%
41009 3
0.1%
41011 1
 
< 0.1%
41017 1
 
< 0.1%
41020 1
 
< 0.1%
41026 1
 
< 0.1%
41027 1
 
< 0.1%
ValueCountFrequency (%)
43024 1
 
< 0.1%
43013 4
0.1%
43010 2
0.1%
43006 1
 
< 0.1%
43005 1
 
< 0.1%
43004 1
 
< 0.1%
43003 1
 
< 0.1%
43000 4
0.1%
42999 3
0.1%
42996 3
0.1%
Distinct2034
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
2023-12-11T05:05:50.746570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length5
Mean length5.107154
Min length1

Characters and Unicode

Total characters16348
Distinct characters519
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1541 ?
Unique (%)48.1%

Sample

1st row삼정이용소
2nd row육교이용소
3rd row아미가
4th row월드
5th row서남이용소
ValueCountFrequency (%)
이용소 37
 
1.1%
현대이용소 26
 
0.8%
대성이용소 25
 
0.8%
명성이용소 20
 
0.6%
그린이용소 17
 
0.5%
삼성이용소 17
 
0.5%
동원이용소 15
 
0.5%
블루클럽 15
 
0.5%
보성이용소 13
 
0.4%
한일이용소 12
 
0.4%
Other values (1998) 3106
94.0%
2023-12-11T05:05:51.379908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2286
 
14.0%
2213
 
13.5%
2123
 
13.0%
342
 
2.1%
298
 
1.8%
205
 
1.3%
184
 
1.1%
183
 
1.1%
175
 
1.1%
160
 
1.0%
Other values (509) 8179
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15815
96.7%
Space Separator 183
 
1.1%
Uppercase Letter 128
 
0.8%
Lowercase Letter 82
 
0.5%
Open Punctuation 41
 
0.3%
Close Punctuation 41
 
0.3%
Decimal Number 40
 
0.2%
Other Punctuation 15
 
0.1%
Letter Number 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2286
 
14.5%
2213
 
14.0%
2123
 
13.4%
342
 
2.2%
298
 
1.9%
205
 
1.3%
184
 
1.2%
175
 
1.1%
160
 
1.0%
149
 
0.9%
Other values (448) 7680
48.6%
Uppercase Letter
ValueCountFrequency (%)
B 13
 
10.2%
S 11
 
8.6%
A 11
 
8.6%
E 10
 
7.8%
R 9
 
7.0%
O 8
 
6.2%
T 8
 
6.2%
M 7
 
5.5%
K 6
 
4.7%
I 5
 
3.9%
Other values (14) 40
31.2%
Lowercase Letter
ValueCountFrequency (%)
o 11
13.4%
r 10
12.2%
a 9
11.0%
s 8
9.8%
e 7
8.5%
b 7
8.5%
n 6
7.3%
h 6
7.3%
p 5
6.1%
l 3
 
3.7%
Other values (7) 10
12.2%
Decimal Number
ValueCountFrequency (%)
1 10
25.0%
8 8
20.0%
2 6
15.0%
0 6
15.0%
3 6
15.0%
4 2
 
5.0%
5 1
 
2.5%
9 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 7
46.7%
' 4
26.7%
& 1
 
6.7%
· 1
 
6.7%
, 1
 
6.7%
# 1
 
6.7%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
183
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15815
96.7%
Common 321
 
2.0%
Latin 212
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2286
 
14.5%
2213
 
14.0%
2123
 
13.4%
342
 
2.2%
298
 
1.9%
205
 
1.3%
184
 
1.2%
175
 
1.1%
160
 
1.0%
149
 
0.9%
Other values (448) 7680
48.6%
Latin
ValueCountFrequency (%)
B 13
 
6.1%
S 11
 
5.2%
o 11
 
5.2%
A 11
 
5.2%
E 10
 
4.7%
r 10
 
4.7%
R 9
 
4.2%
a 9
 
4.2%
O 8
 
3.8%
T 8
 
3.8%
Other values (33) 112
52.8%
Common
ValueCountFrequency (%)
183
57.0%
( 41
 
12.8%
) 41
 
12.8%
1 10
 
3.1%
8 8
 
2.5%
. 7
 
2.2%
2 6
 
1.9%
0 6
 
1.9%
3 6
 
1.9%
' 4
 
1.2%
Other values (8) 9
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15815
96.7%
ASCII 530
 
3.2%
Number Forms 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2286
 
14.5%
2213
 
14.0%
2123
 
13.4%
342
 
2.2%
298
 
1.9%
205
 
1.3%
184
 
1.2%
175
 
1.1%
160
 
1.0%
149
 
0.9%
Other values (448) 7680
48.6%
ASCII
ValueCountFrequency (%)
183
34.5%
( 41
 
7.7%
) 41
 
7.7%
B 13
 
2.5%
S 11
 
2.1%
o 11
 
2.1%
A 11
 
2.1%
E 10
 
1.9%
1 10
 
1.9%
r 10
 
1.9%
Other values (48) 189
35.7%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct2487
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0111547 × 1013
Minimum2.0011006 × 1013
Maximum2.0221027 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:51.609042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0011006 × 1013
5-th percentile2.0021011 × 1013
Q12.0040402 × 1013
median2.0110322 × 1013
Q32.0180814 × 1013
95-th percentile2.0211208 × 1013
Maximum2.0221027 × 1013
Range2.1002111 × 1011
Interquartile range (IQR)1.4041211 × 1011

Descriptive statistics

Standard deviation6.8903111 × 1010
Coefficient of variation (CV)0.0034260472
Kurtosis-1.4790656
Mean2.0111547 × 1013
Median Absolute Deviation (MAD)7.0085037 × 1010
Skewness0.16531713
Sum6.4377063 × 1016
Variance4.7476387 × 1021
MonotonicityNot monotonic
2023-12-11T05:05:51.819996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031031000000 39
 
1.2%
20040313000000 37
 
1.2%
20041129000000 34
 
1.1%
20020416000000 27
 
0.8%
20040312000000 25
 
0.8%
20031010000000 24
 
0.7%
20040213000000 23
 
0.7%
20021011000000 21
 
0.7%
20030731000000 17
 
0.5%
20020729000000 16
 
0.5%
Other values (2477) 2938
91.8%
ValueCountFrequency (%)
20011006000000 4
 
0.1%
20011218000000 1
 
< 0.1%
20020320000000 1
 
< 0.1%
20020330000000 1
 
< 0.1%
20020412000000 1
 
< 0.1%
20020416000000 27
0.8%
20020417000000 8
 
0.2%
20020418000000 3
 
0.1%
20020508000000 1
 
< 0.1%
20020510000000 1
 
< 0.1%
ValueCountFrequency (%)
20221027112147 1
< 0.1%
20221026150248 1
< 0.1%
20221026144643 1
< 0.1%
20221025150537 1
< 0.1%
20221025133916 1
< 0.1%
20221024114205 1
< 0.1%
20221019165330 1
< 0.1%
20221018093158 1
< 0.1%
20221017170405 1
< 0.1%
20221011140615 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
I
2449 
U
752 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2449
76.5%
U 752
 
23.5%

Length

2023-12-11T05:05:52.011556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:52.168136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2449
76.5%
u 752
 
23.5%
Distinct509
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
Minimum2018-08-31 23:59:59
Maximum2022-10-29 02:40:00
2023-12-11T05:05:52.653458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:05:52.904256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
일반이용업
3164 
이용업 기타
 
37

Length

Max length6
Median length5
Mean length5.0115589
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 3164
98.8%
이용업 기타 37
 
1.2%

Length

2023-12-11T05:05:53.107491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:53.281705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 3164
97.7%
이용업 37
 
1.1%
기타 37
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2359
Distinct (%)77.2%
Missing147
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean343046.62
Minimum327551.87
Maximum356728.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:53.458001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327551.87
5-th percentile335203.24
Q1339876.01
median342647.2
Q3346244.62
95-th percentile352829.43
Maximum356728.78
Range29176.904
Interquartile range (IQR)6368.6144

Descriptive statistics

Standard deviation4897.2
Coefficient of variation (CV)0.014275611
Kurtosis0.47276462
Mean343046.62
Median Absolute Deviation (MAD)3101.8293
Skewness0.059206656
Sum1.0476644 × 109
Variance23982568
MonotonicityNot monotonic
2023-12-11T05:05:53.673914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
342056.356661 10
 
0.3%
338881.747008 8
 
0.2%
342355.950931 8
 
0.2%
342647.200755 7
 
0.2%
344046.261885 7
 
0.2%
346440.105797 6
 
0.2%
342979.50183 6
 
0.2%
339440.669923 6
 
0.2%
335728.273517 6
 
0.2%
337346.648864 6
 
0.2%
Other values (2349) 2984
93.2%
(Missing) 147
 
4.6%
ValueCountFrequency (%)
327551.872352 1
 
< 0.1%
327693.456541 1
 
< 0.1%
327698.913649 1
 
< 0.1%
328243.083724 1
 
< 0.1%
328293.62359 3
0.1%
328337.353662 1
 
< 0.1%
328389.300033 1
 
< 0.1%
328436.659113 1
 
< 0.1%
328575.030436 1
 
< 0.1%
328656.357314 1
 
< 0.1%
ValueCountFrequency (%)
356728.776845 1
< 0.1%
356534.131252 2
0.1%
356515.752178 1
< 0.1%
356485.853105 1
< 0.1%
356437.578421 1
< 0.1%
356428.0866 1
< 0.1%
356290.801264 1
< 0.1%
356197.467672 1
< 0.1%
356142.765212 1
< 0.1%
356129.784535 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2359
Distinct (%)77.2%
Missing147
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean263523.33
Minimum238769.81
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:53.885896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum238769.81
5-th percentile257667.08
Q1261588.31
median263734.73
Q3265705.51
95-th percentile270321.91
Maximum278091.65
Range39321.841
Interquartile range (IQR)4117.1954

Descriptive statistics

Standard deviation4183.8432
Coefficient of variation (CV)0.015876557
Kurtosis6.2178572
Mean263523.33
Median Absolute Deviation (MAD)2063.2175
Skewness-1.241317
Sum8.0480024 × 108
Variance17504544
MonotonicityNot monotonic
2023-12-11T05:05:54.151596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261454.668093 10
 
0.3%
261852.136016 8
 
0.2%
261485.129229 8
 
0.2%
261846.398048 7
 
0.2%
261742.707245 7
 
0.2%
267083.375924 6
 
0.2%
262488.906251 6
 
0.2%
261637.957404 6
 
0.2%
262684.165543 6
 
0.2%
258035.007517 6
 
0.2%
Other values (2349) 2984
93.2%
(Missing) 147
 
4.6%
ValueCountFrequency (%)
238769.812522 3
0.1%
238810.537774 1
 
< 0.1%
240700.866897 1
 
< 0.1%
240715.325375 1
 
< 0.1%
240837.868215 1
 
< 0.1%
240992.822164 1
 
< 0.1%
241926.136957 1
 
< 0.1%
242247.9639 1
 
< 0.1%
242378.729863 1
 
< 0.1%
244504.04518 1
 
< 0.1%
ValueCountFrequency (%)
278091.653532 3
0.1%
277462.879247 4
0.1%
274407.551765 1
 
< 0.1%
274171.709713 2
0.1%
274148.35881 1
 
< 0.1%
273755.811454 1
 
< 0.1%
273712.082489 1
 
< 0.1%
273313.159204 1
 
< 0.1%
273237.600006 1
 
< 0.1%
273183.361741 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
일반이용업
3164 
이용업 기타
 
37

Length

Max length6
Median length5
Mean length5.0115589
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 3164
98.8%
이용업 기타 37
 
1.2%

Length

2023-12-11T05:05:54.363744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:54.506847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 3164
97.7%
이용업 37
 
1.1%
기타 37
 
1.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)0.8%
Missing582
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean2.5505918
Minimum0
Maximum35
Zeros647
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:54.656053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile6
Maximum35
Range35
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4966017
Coefficient of variation (CV)0.97883232
Kurtosis37.263256
Mean2.5505918
Median Absolute Deviation (MAD)2
Skewness3.8869746
Sum6680
Variance6.2330201
MonotonicityNot monotonic
2023-12-11T05:05:54.853444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 647
20.2%
3 557
17.4%
2 523
16.3%
4 341
10.7%
5 219
 
6.8%
1 179
 
5.6%
6 58
 
1.8%
7 31
 
1.0%
9 23
 
0.7%
10 15
 
0.5%
Other values (11) 26
 
0.8%
(Missing) 582
18.2%
ValueCountFrequency (%)
0 647
20.2%
1 179
 
5.6%
2 523
16.3%
3 557
17.4%
4 341
10.7%
5 219
 
6.8%
6 58
 
1.8%
7 31
 
1.0%
8 10
 
0.3%
9 23
 
0.7%
ValueCountFrequency (%)
35 2
0.1%
31 1
 
< 0.1%
28 1
 
< 0.1%
23 1
 
< 0.1%
20 3
0.1%
19 1
 
< 0.1%
17 1
 
< 0.1%
15 2
0.1%
12 1
 
< 0.1%
11 3
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.4%
Missing945
Missing (%)29.5%
Infinite0
Infinite (%)0.0%
Mean0.55053191
Minimum0
Maximum9
Zeros1221
Zeros (%)38.1%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:55.020525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.76400142
Coefficient of variation (CV)1.3877514
Kurtosis19.155286
Mean0.55053191
Median Absolute Deviation (MAD)0
Skewness3.015448
Sum1242
Variance0.58369816
MonotonicityNot monotonic
2023-12-11T05:05:55.271203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 1221
38.1%
1 908
28.4%
2 94
 
2.9%
4 14
 
0.4%
3 9
 
0.3%
5 3
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
(Missing) 945
29.5%
ValueCountFrequency (%)
0 1221
38.1%
1 908
28.4%
2 94
 
2.9%
3 9
 
0.3%
4 14
 
0.4%
5 3
 
0.1%
6 3
 
0.1%
7 3
 
0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
7 3
 
0.1%
6 3
 
0.1%
5 3
 
0.1%
4 14
 
0.4%
3 9
 
0.3%
2 94
 
2.9%
1 908
28.4%
0 1221
38.1%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)0.4%
Missing816
Missing (%)25.5%
Infinite0
Infinite (%)0.0%
Mean1.3144654
Minimum0
Maximum9
Zeros531
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:55.479078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2346628
Coefficient of variation (CV)0.93928891
Kurtosis5.5986165
Mean1.3144654
Median Absolute Deviation (MAD)1
Skewness1.8672848
Sum3135
Variance1.5243922
MonotonicityNot monotonic
2023-12-11T05:05:55.645088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1147
35.8%
0 531
16.6%
2 374
 
11.7%
3 206
 
6.4%
4 71
 
2.2%
5 27
 
0.8%
6 12
 
0.4%
8 10
 
0.3%
7 6
 
0.2%
9 1
 
< 0.1%
(Missing) 816
25.5%
ValueCountFrequency (%)
0 531
16.6%
1 1147
35.8%
2 374
 
11.7%
3 206
 
6.4%
4 71
 
2.2%
5 27
 
0.8%
6 12
 
0.4%
7 6
 
0.2%
8 10
 
0.3%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 10
 
0.3%
7 6
 
0.2%
6 12
 
0.4%
5 27
 
0.8%
4 71
 
2.2%
3 206
 
6.4%
2 374
 
11.7%
1 1147
35.8%
0 531
16.6%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.4%
Missing1048
Missing (%)32.7%
Infinite0
Infinite (%)0.0%
Mean1.4393869
Minimum0
Maximum8
Zeros311
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:55.830763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2083854
Coefficient of variation (CV)0.83951393
Kurtosis5.3971973
Mean1.4393869
Median Absolute Deviation (MAD)0
Skewness1.8771611
Sum3099
Variance1.4601952
MonotonicityNot monotonic
2023-12-11T05:05:56.021679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 1147
35.8%
2 371
 
11.6%
0 311
 
9.7%
3 196
 
6.1%
4 70
 
2.2%
5 30
 
0.9%
6 13
 
0.4%
8 9
 
0.3%
7 6
 
0.2%
(Missing) 1048
32.7%
ValueCountFrequency (%)
0 311
 
9.7%
1 1147
35.8%
2 371
 
11.6%
3 196
 
6.1%
4 70
 
2.2%
5 30
 
0.9%
6 13
 
0.4%
7 6
 
0.2%
8 9
 
0.3%
ValueCountFrequency (%)
8 9
 
0.3%
7 6
 
0.2%
6 13
 
0.4%
5 30
 
0.9%
4 70
 
2.2%
3 196
 
6.1%
2 371
 
11.6%
1 1147
35.8%
0 311
 
9.7%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
0
1606 
<NA>
1398 
1
191 
2
 
5
6
 
1

Length

Max length4
Median length1
Mean length2.3102156
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 1606
50.2%
<NA> 1398
43.7%
1 191
 
6.0%
2 5
 
0.2%
6 1
 
< 0.1%

Length

2023-12-11T05:05:56.257684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:56.437638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1606
50.2%
na 1398
43.7%
1 191
 
6.0%
2 5
 
0.2%
6 1
 
< 0.1%
Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
1705 
0
1259 
1
231 
2
 
5
6
 
1

Length

Max length4
Median length4
Mean length2.5979381
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1705
53.3%
0 1259
39.3%
1 231
 
7.2%
2 5
 
0.2%
6 1
 
< 0.1%

Length

2023-12-11T05:05:56.653166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:56.852065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1705
53.3%
0 1259
39.3%
1 231
 
7.2%
2 5
 
0.2%
6 1
 
< 0.1%

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.6%
Missing349
Missing (%)10.9%
Infinite0
Infinite (%)0.0%
Mean3.4929874
Minimum0
Maximum18
Zeros164
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:57.030661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile9
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.5084116
Coefficient of variation (CV)0.71812789
Kurtosis1.9468508
Mean3.4929874
Median Absolute Deviation (MAD)1
Skewness1.3644249
Sum9962
Variance6.292129
MonotonicityNot monotonic
2023-12-11T05:05:57.239814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 744
23.2%
2 683
21.3%
4 370
11.6%
1 275
 
8.6%
0 164
 
5.1%
5 129
 
4.0%
6 106
 
3.3%
8 99
 
3.1%
7 96
 
3.0%
9 92
 
2.9%
Other values (6) 94
 
2.9%
(Missing) 349
10.9%
ValueCountFrequency (%)
0 164
 
5.1%
1 275
 
8.6%
2 683
21.3%
3 744
23.2%
4 370
11.6%
5 129
 
4.0%
6 106
 
3.3%
7 96
 
3.0%
8 99
 
3.1%
9 92
 
2.9%
ValueCountFrequency (%)
18 1
 
< 0.1%
15 2
 
0.1%
13 4
 
0.1%
12 22
 
0.7%
11 22
 
0.7%
10 43
1.3%
9 92
2.9%
8 99
3.1%
7 96
3.0%
6 106
3.3%

조건부허가신고사유
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3201
Missing (%)100.0%
Memory size28.3 KiB
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
1637 
임대
1423 
자가
 
141

Length

Max length4
Median length4
Mean length3.0228054
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1637
51.1%
임대 1423
44.5%
자가 141
 
4.4%

Length

2023-12-11T05:05:57.487647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:57.681620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1637
51.1%
임대 1423
44.5%
자가 141
 
4.4%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
2714 
0
370 
1
 
112
2
 
4
3
 
1

Length

Max length4
Median length4
Mean length3.5435801
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> 2714
84.8%
0 370
 
11.6%
1 112
 
3.5%
2 4
 
0.1%
3 1
 
< 0.1%

Length

2023-12-11T05:05:57.843808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:58.019639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2714
84.8%
0 370
 
11.6%
1 112
 
3.5%
2 4
 
0.1%
3 1
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.1 KiB
<NA>
2610 
0
317 
1
269 
2
 
5

Length

Max length4
Median length4
Mean length3.4461106
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2610
81.5%
0 317
 
9.9%
1 269
 
8.4%
2 5
 
0.2%

Length

2023-12-11T05:05:58.227819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:05:58.428046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2610
81.5%
0 317
 
9.9%
1 269
 
8.4%
2 5
 
0.2%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.6%
Missing1782
Missing (%)55.7%
Infinite0
Infinite (%)0.0%
Mean0.055673009
Minimum0
Maximum8
Zeros1403
Zeros (%)43.8%
Negative0
Negative (%)0.0%
Memory size28.3 KiB
2023-12-11T05:05:58.594606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5870018
Coefficient of variation (CV)10.543741
Kurtosis133.04322
Mean0.055673009
Median Absolute Deviation (MAD)0
Skewness11.407409
Sum79
Variance0.34457111
MonotonicityNot monotonic
2023-12-11T05:05:58.780085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 1403
43.8%
7 5
 
0.2%
2 3
 
0.1%
8 2
 
0.1%
1 2
 
0.1%
6 2
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 1782
55.7%
ValueCountFrequency (%)
0 1403
43.8%
1 2
 
0.1%
2 3
 
0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 2
 
0.1%
7 5
 
0.2%
8 2
 
0.1%
ValueCountFrequency (%)
8 2
 
0.1%
7 5
 
0.2%
6 2
 
0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
2 3
 
0.1%
1 2
 
0.1%
0 1403
43.8%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
False
3200 
True
 
1
ValueCountFrequency (%)
False 3200
> 99.9%
True 1
 
< 0.1%
2023-12-11T05:05:58.934777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수침대수다중이용업소여부
01이용업05_19_01_P34100003410000-203-2008-0000320080604<NA>3폐업2폐업20100809<NA><NA><NA><NA>9.36700261대구광역시 중구 서성로1가 0109-0001번지 (2층)<NA><NA>삼정이용소20100614144140I2018-08-31 23:59:59.0일반이용업343315.940921264622.218272일반이용업5122001<NA><NA><NA><NA><NA><NA><NA>N
12이용업05_19_01_P34100003410000-203-2010-0000320101020<NA>3폐업2폐업20130122<NA><NA><NA><NA>12.60700848대구광역시 중구 동인동4가 0347-0001번지대구광역시 중구 국채보상로 723 (동인동4가)41907육교이용소20120208113538I2018-08-31 23:59:59.0일반이용업345308.284791264380.077089일반이용업0011001<NA><NA><NA>임대<NA><NA>0N
23이용업05_19_01_P34100003410000-203-2010-0000420101025<NA>3폐업2폐업20101215<NA><NA><NA><NA>6.20700802대구광역시 중구 남산동 0693-0008번지 지상2층<NA><NA>아미가20101028091811I2018-08-31 23:59:59.0일반이용업343879.713037263432.678243일반이용업0022002<NA><NA><NA>임대<NA><NA>0N
34이용업05_19_01_P34100003410000-203-2001-0000120010326<NA>3폐업2폐업20110120<NA><NA><NA>053 257295539.60700850대구광역시 중구 수창동 0099-0002번지<NA><NA>월드20101026121254I2018-08-31 23:59:59.0일반이용업343287.506361264938.059384일반이용업31<NA><NA>118<NA><NA><NA><NA><NA><NA><NA>N
45이용업05_19_01_P34100003410000-203-2010-0000520101124<NA>3폐업2폐업20120726<NA><NA><NA><NA>56.10700320대구광역시 중구 대신동 0115-0005번지 지상2층대구광역시 중구 국채보상로 458, 2층 (대신동)41926서남이용소20120208113611I2018-08-31 23:59:59.0일반이용업342714.834681264487.841783일반이용업9022007<NA><NA><NA><NA><NA><NA>0N
56이용업05_19_01_P34100003410000-203-1982-0000419820818<NA>3폐업2폐업20090817<NA><NA><NA>053 253603731.32700832대구광역시 중구 남산동 698-22번지<NA><NA>20081021113237I2018-08-31 23:59:59.0일반이용업343722.34105263487.941195일반이용업<NA><NA><NA><NA><NA><NA>7<NA><NA><NA><NA><NA><NA><NA>N
67이용업05_19_01_P34100003410000-203-2008-0000520080918<NA>3폐업2폐업20101015<NA><NA><NA><NA>4.32700821대구광역시 중구 동산동 0360번지 지하1층<NA><NA>엘디스리젠트20090310140131I2018-08-31 23:59:59.0일반이용업343184.151781264080.683793일반이용업8100111<NA><NA><NA>임대<NA><NA><NA>N
78이용업05_19_01_P34100003410000-203-2004-0000420040630<NA>3폐업2폐업20140410<NA><NA><NA>053 4233939102.00700030대구광역시 중구 전동 0035번지대구광역시 중구 국채보상로 570-8 (전동)41935새중앙20120208112755I2018-08-31 23:59:59.0일반이용업343774.488375264525.318535일반이용업0000115<NA><NA><NA><NA><NA><NA>0N
89이용업05_19_01_P34100003410000-203-2009-0000320090811<NA>3폐업2폐업20090928<NA><NA><NA><NA>6.00700810대구광역시 중구 대봉동 0044-0010번지 청운상가 305호<NA><NA>코스팜코리아20090812171018I2018-08-31 23:59:59.0일반이용업344728.621174263286.553667일반이용업3133001<NA><NA><NA><NA><NA>10N
910이용업05_19_01_P34100003410000-203-1972-0000619720915<NA>3폐업2폐업20170721<NA><NA><NA>053 423618819.50700413대구광역시 중구 삼덕동3가 0176-0005번지대구광역시 중구 달구벌대로447길 72-1 (삼덕동3가)41946동덕이용소20170721102403I2018-08-31 23:59:59.0일반이용업345197.205333264027.782156일반이용업2011002<NA><NA><NA><NA><NA><NA>0N
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명여성종사자수남성종사자수침대수다중이용업소여부
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