Overview

Dataset statistics

Number of variables51
Number of observations4896
Missing cells47668
Missing cells (%)19.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 MiB
Average record size in memory441.0 B

Variable types

Numeric14
Categorical22
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-01-04
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123089

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (94.3%)Imbalance
위생업태명 is highly imbalanced (94.3%)Imbalance
사용끝지하층 is highly imbalanced (57.3%)Imbalance
조건부허가시작일자 is highly imbalanced (99.6%)Imbalance
조건부허가종료일자 is highly imbalanced (99.6%)Imbalance
건물소유구분명 is highly imbalanced (52.6%)Imbalance
여성종사자수 is highly imbalanced (75.6%)Imbalance
남성종사자수 is highly imbalanced (79.6%)Imbalance
침대수 is highly imbalanced (66.7%)Imbalance
인허가취소일자 has 4896 (100.0%) missing valuesMissing
폐업일자 has 1321 (27.0%) missing valuesMissing
휴업시작일자 has 4896 (100.0%) missing valuesMissing
휴업종료일자 has 4896 (100.0%) missing valuesMissing
재개업일자 has 4896 (100.0%) missing valuesMissing
소재지전화 has 1388 (28.3%) missing valuesMissing
도로명전체주소 has 2597 (53.0%) missing valuesMissing
도로명우편번호 has 2651 (54.1%) missing valuesMissing
좌표정보(x) has 388 (7.9%) missing valuesMissing
좌표정보(y) has 388 (7.9%) missing valuesMissing
건물지상층수 has 1730 (35.3%) missing valuesMissing
건물지하층수 has 2234 (45.6%) missing valuesMissing
사용시작지상층 has 2099 (42.9%) missing valuesMissing
사용끝지상층 has 2728 (55.7%) missing valuesMissing
발한실여부 has 100 (2.0%) missing valuesMissing
의자수 has 607 (12.4%) missing valuesMissing
조건부허가신고사유 has 4895 (> 99.9%) missing valuesMissing
Unnamed: 50 has 4896 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -27.25398013)Skewed
폐업일자 is highly skewed (γ1 = -28.10947249)Skewed
건물지하층수 is highly skewed (γ1 = 48.78577757)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
Unnamed: 50 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물지상층수 has 1196 (24.4%) zerosZeros
건물지하층수 has 1699 (34.7%) zerosZeros
사용시작지상층 has 1000 (20.4%) zerosZeros
사용끝지상층 has 583 (11.9%) zerosZeros
의자수 has 338 (6.9%) zerosZeros

Reproduction

Analysis started2024-04-17 22:49:40.105579
Analysis finished2024-04-17 22:49:41.494814
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4896
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2448.5
Minimum1
Maximum4896
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:41.566019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile245.75
Q11224.75
median2448.5
Q33672.25
95-th percentile4651.25
Maximum4896
Range4895
Interquartile range (IQR)2447.5

Descriptive statistics

Standard deviation1413.4978
Coefficient of variation (CV)0.57729132
Kurtosis-1.2
Mean2448.5
Median Absolute Deviation (MAD)1224
Skewness0
Sum11987856
Variance1997976
MonotonicityStrictly increasing
2024-04-18T07:49:41.699913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3263 1
 
< 0.1%
3270 1
 
< 0.1%
3269 1
 
< 0.1%
3268 1
 
< 0.1%
3267 1
 
< 0.1%
3266 1
 
< 0.1%
3265 1
 
< 0.1%
3264 1
 
< 0.1%
3262 1
 
< 0.1%
Other values (4886) 4886
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
4896 1
< 0.1%
4895 1
< 0.1%
4894 1
< 0.1%
4893 1
< 0.1%
4892 1
< 0.1%
4891 1
< 0.1%
4890 1
< 0.1%
4889 1
< 0.1%
4888 1
< 0.1%
4887 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
이용업
4896 

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 4896
100.0%

Length

2024-04-18T07:49:41.831172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:41.911337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 4896
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
05_19_01_P
4896 

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 4896
100.0%

Length

2024-04-18T07:49:42.005545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:42.097631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4896
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324546.6
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:42.179547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13290000
median3320000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation40368.561
Coefficient of variation (CV)0.012142576
Kurtosis-0.9397324
Mean3324546.6
Median Absolute Deviation (MAD)30000
Skewness0.055273892
Sum1.627698 × 1010
Variance1.6296207 × 109
MonotonicityNot monotonic
2024-04-18T07:49:42.297602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 496
10.1%
3340000 495
10.1%
3300000 418
8.5%
3320000 409
 
8.4%
3330000 392
 
8.0%
3350000 380
 
7.8%
3390000 331
 
6.8%
3370000 330
 
6.7%
3310000 323
 
6.6%
3380000 283
 
5.8%
Other values (6) 1039
21.2%
ValueCountFrequency (%)
3250000 165
 
3.4%
3260000 213
4.4%
3270000 257
5.2%
3280000 206
4.2%
3290000 496
10.1%
3300000 418
8.5%
3310000 323
6.6%
3320000 409
8.4%
3330000 392
8.0%
3340000 495
10.1%
ValueCountFrequency (%)
3400000 109
 
2.2%
3390000 331
6.8%
3380000 283
5.8%
3370000 330
6.7%
3360000 89
 
1.8%
3350000 380
7.8%
3340000 495
10.1%
3330000 392
8.0%
3320000 409
8.4%
3310000 323
6.6%

관리번호
Text

UNIQUE 

Distinct4896
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
2024-04-18T07:49:42.491791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters107712
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

Unique4896 ?
Unique (%)100.0%

Sample

1st row3280000-203-2018-00003
2nd row3390000-203-2019-00001
3rd row3350000-203-2019-00001
4th row3390000-203-2019-00002
5th row3390000-203-2019-00003
ValueCountFrequency (%)
3280000-203-2018-00003 1
 
< 0.1%
3350000-203-2002-00003 1
 
< 0.1%
3380000-203-1994-00007 1
 
< 0.1%
3380000-203-2002-00004 1
 
< 0.1%
3380000-203-2001-00005 1
 
< 0.1%
3380000-203-1997-00001 1
 
< 0.1%
3380000-203-2002-00003 1
 
< 0.1%
3380000-203-2010-00005 1
 
< 0.1%
3380000-203-2003-00006 1
 
< 0.1%
3380000-203-2008-00001 1
 
< 0.1%
Other values (4886) 4886
99.8%
2024-04-18T07:49:42.793631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43011
39.9%
3 15390
 
14.3%
- 14688
 
13.6%
2 10799
 
10.0%
1 6125
 
5.7%
9 6010
 
5.6%
8 2651
 
2.5%
7 2442
 
2.3%
4 2327
 
2.2%
6 2136
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93024
86.4%
Dash Punctuation 14688
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43011
46.2%
3 15390
 
16.5%
2 10799
 
11.6%
1 6125
 
6.6%
9 6010
 
6.5%
8 2651
 
2.8%
7 2442
 
2.6%
4 2327
 
2.5%
6 2136
 
2.3%
5 2133
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14688
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107712
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43011
39.9%
3 15390
 
14.3%
- 14688
 
13.6%
2 10799
 
10.0%
1 6125
 
5.7%
9 6010
 
5.6%
8 2651
 
2.5%
7 2442
 
2.3%
4 2327
 
2.2%
6 2136
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43011
39.9%
3 15390
 
14.3%
- 14688
 
13.6%
2 10799
 
10.0%
1 6125
 
5.7%
9 6010
 
5.6%
8 2651
 
2.5%
7 2442
 
2.3%
4 2327
 
2.2%
6 2136
 
2.0%

인허가일자
Real number (ℝ)

SKEWED 

Distinct3631
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19957601
Minimum9710223
Maximum20201217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:42.954899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691119
Q119871227
median19980410
Q320051121
95-th percentile20170503
Maximum20201217
Range10490994
Interquartile range (IQR)179894

Descriptive statistics

Standard deviation200890.87
Coefficient of variation (CV)0.010065883
Kurtosis1382.3761
Mean19957601
Median Absolute Deviation (MAD)89948.5
Skewness-27.25398
Sum9.7712413 × 1010
Variance4.0357141 × 1010
MonotonicityNot monotonic
2024-04-18T07:49:43.103390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19770830 35
 
0.7%
19660301 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
19630630 9
 
0.2%
20030224 9
 
0.2%
20030410 7
 
0.1%
19721129 7
 
0.1%
20030213 6
 
0.1%
Other values (3621) 4739
96.8%
ValueCountFrequency (%)
9710223 1
 
< 0.1%
19300722 1
 
< 0.1%
19610922 1
 
< 0.1%
19621202 1
 
< 0.1%
19630110 6
0.1%
19630522 1
 
< 0.1%
19630525 1
 
< 0.1%
19630529 4
0.1%
19630601 1
 
< 0.1%
19630622 1
 
< 0.1%
ValueCountFrequency (%)
20201217 2
< 0.1%
20201215 2
< 0.1%
20201214 1
 
< 0.1%
20201208 1
 
< 0.1%
20201203 1
 
< 0.1%
20201201 1
 
< 0.1%
20201103 3
0.1%
20201029 1
 
< 0.1%
20201022 1
 
< 0.1%
20201012 1
 
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4896
Missing (%)100.0%
Memory size43.2 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
3
3575 
1
1321 

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 (%)
3 3575
73.0%
1 1321
 
27.0%

Length

2024-04-18T07:49:43.269559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:43.357882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3575
73.0%
1 1321
 
27.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
폐업
3575 
영업/정상
1321 

Length

Max length5
Median length2
Mean length2.8094363
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 (%)
폐업 3575
73.0%
영업/정상 1321
 
27.0%

Length

2024-04-18T07:49:43.451823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:43.541502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3575
73.0%
영업/정상 1321
 
27.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
2
3575 
1
1321 

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 (%)
2 3575
73.0%
1 1321
 
27.0%

Length

2024-04-18T07:49:43.633849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:43.717971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3575
73.0%
1 1321
 
27.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
폐업
3575 
영업
1321 

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 (%)
폐업 3575
73.0%
영업 1321
 
27.0%

Length

2024-04-18T07:49:43.809822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:43.920917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3575
73.0%
영업 1321
 
27.0%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2256
Distinct (%)63.1%
Missing1321
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean20065648
Minimum2019071
Maximum20800812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:44.028975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2019071
5-th percentile20000115
Q120040428
median20070605
Q320130514
95-th percentile20190403
Maximum20800812
Range18781741
Interquartile range (IQR)90086

Descriptive statistics

Standard deviation455131.04
Coefficient of variation (CV)0.0226821
Kurtosis899.77742
Mean20065648
Median Absolute Deviation (MAD)39889
Skewness-28.109472
Sum7.1734692 × 1010
Variance2.0714426 × 1011
MonotonicityNot monotonic
2024-04-18T07:49:44.170040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030715 58
 
1.2%
20050214 41
 
0.8%
20031213 36
 
0.7%
20030305 33
 
0.7%
20020222 33
 
0.7%
20030221 32
 
0.7%
20030101 17
 
0.3%
20051011 16
 
0.3%
20030215 13
 
0.3%
20061226 13
 
0.3%
Other values (2246) 3283
67.1%
(Missing) 1321
27.0%
ValueCountFrequency (%)
2019071 1
 
< 0.1%
11111111 5
0.1%
19931124 1
 
< 0.1%
19950206 1
 
< 0.1%
19950210 1
 
< 0.1%
19950331 1
 
< 0.1%
19950413 1
 
< 0.1%
19950515 1
 
< 0.1%
19950818 1
 
< 0.1%
19950828 1
 
< 0.1%
ValueCountFrequency (%)
20800812 1
< 0.1%
20201231 1
< 0.1%
20201229 1
< 0.1%
20201223 2
< 0.1%
20201214 1
< 0.1%
20201209 1
< 0.1%
20201207 2
< 0.1%
20201203 1
< 0.1%
20201201 1
< 0.1%
20201130 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4896
Missing (%)100.0%
Memory size43.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4896
Missing (%)100.0%
Memory size43.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4896
Missing (%)100.0%
Memory size43.2 KiB

소재지전화
Text

MISSING 

Distinct2871
Distinct (%)81.8%
Missing1388
Missing (%)28.3%
Memory size38.4 KiB
2024-04-18T07:49:44.406163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.9367161
Min length3

Characters and Unicode

Total characters34858
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2723 ?
Unique (%)77.6%

Sample

1st row051 727 5320
2nd row051 728 3988
3rd row051 364 2651
4th row051 7549944
5th row051 7596288
ValueCountFrequency (%)
051 3300
48.3%
893 8
 
0.1%
554 8
 
0.1%
868 6
 
0.1%
727 6
 
0.1%
754 6
 
0.1%
051643 6
 
0.1%
292 6
 
0.1%
305 5
 
0.1%
051624 5
 
0.1%
Other values (3073) 3477
50.9%
2024-04-18T07:49:44.732290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6040
17.3%
1 5282
15.2%
0 5181
14.9%
3341
9.6%
2 2841
8.2%
4 2311
 
6.6%
6 2240
 
6.4%
3 2204
 
6.3%
7 2073
 
5.9%
8 1969
 
5.6%
Other values (2) 1376
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31515
90.4%
Space Separator 3341
 
9.6%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6040
19.2%
1 5282
16.8%
0 5181
16.4%
2 2841
9.0%
4 2311
 
7.3%
6 2240
 
7.1%
3 2204
 
7.0%
7 2073
 
6.6%
8 1969
 
6.2%
9 1374
 
4.4%
Space Separator
ValueCountFrequency (%)
3341
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34858
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6040
17.3%
1 5282
15.2%
0 5181
14.9%
3341
9.6%
2 2841
8.2%
4 2311
 
6.6%
6 2240
 
6.4%
3 2204
 
6.3%
7 2073
 
5.9%
8 1969
 
5.6%
Other values (2) 1376
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6040
17.3%
1 5282
15.2%
0 5181
14.9%
3341
9.6%
2 2841
8.2%
4 2311
 
6.6%
6 2240
 
6.4%
3 2204
 
6.3%
7 2073
 
5.9%
8 1969
 
5.6%
Other values (2) 1376
 
3.9%
Distinct2120
Distinct (%)43.6%
Missing35
Missing (%)0.7%
Memory size38.4 KiB
2024-04-18T07:49:45.031664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.6313516
Min length3

Characters and Unicode

Total characters22513
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

Unique1369 ?
Unique (%)28.2%

Sample

1st row10.12
2nd row34.99
3rd row42.80
4th row62.07
5th row16.91
ValueCountFrequency (%)
00 494
 
10.2%
10.00 49
 
1.0%
9.00 49
 
1.0%
12.00 43
 
0.9%
15.00 37
 
0.8%
8.40 33
 
0.7%
18.00 32
 
0.7%
8.00 32
 
0.7%
6.00 30
 
0.6%
30.00 27
 
0.6%
Other values (2110) 4035
83.0%
2024-04-18T07:49:45.512858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4861
21.6%
0 4455
19.8%
1 2285
10.1%
2 2167
9.6%
5 1416
 
6.3%
3 1402
 
6.2%
8 1400
 
6.2%
4 1286
 
5.7%
6 1264
 
5.6%
9 995
 
4.4%
Other values (2) 982
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17648
78.4%
Other Punctuation 4865
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4455
25.2%
1 2285
12.9%
2 2167
12.3%
5 1416
 
8.0%
3 1402
 
7.9%
8 1400
 
7.9%
4 1286
 
7.3%
6 1264
 
7.2%
9 995
 
5.6%
7 978
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 4861
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4861
21.6%
0 4455
19.8%
1 2285
10.1%
2 2167
9.6%
5 1416
 
6.3%
3 1402
 
6.2%
8 1400
 
6.2%
4 1286
 
5.7%
6 1264
 
5.6%
9 995
 
4.4%
Other values (2) 982
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4861
21.6%
0 4455
19.8%
1 2285
10.1%
2 2167
9.6%
5 1416
 
6.3%
3 1402
 
6.2%
8 1400
 
6.2%
4 1286
 
5.7%
6 1264
 
5.6%
9 995
 
4.4%
Other values (2) 982
 
4.4%

소재지우편번호
Real number (ℝ)

Distinct776
Distinct (%)15.9%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610450.58
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:45.682918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600011
5-th percentile601812
Q1606070
median609852
Q3614826
95-th percentile617833
Maximum619953
Range19942
Interquartile range (IQR)8756

Descriptive statistics

Standard deviation5294.7445
Coefficient of variation (CV)0.0086735022
Kurtosis-1.0185718
Mean610450.58
Median Absolute Deviation (MAD)4962
Skewness-0.18807238
Sum2.9741152 × 109
Variance28034319
MonotonicityNot monotonic
2024-04-18T07:49:45.815878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
607833 31
 
0.6%
616801 28
 
0.6%
601829 28
 
0.6%
604851 27
 
0.6%
612847 26
 
0.5%
607826 24
 
0.5%
616807 24
 
0.5%
611803 23
 
0.5%
617818 22
 
0.4%
619903 21
 
0.4%
Other values (766) 4618
94.3%
(Missing) 24
 
0.5%
ValueCountFrequency (%)
600011 2
 
< 0.1%
600012 8
0.2%
600013 2
 
< 0.1%
600014 2
 
< 0.1%
600015 1
 
< 0.1%
600021 4
0.1%
600022 3
 
0.1%
600023 3
 
0.1%
600024 1
 
< 0.1%
600025 4
0.1%
ValueCountFrequency (%)
619953 3
 
0.1%
619952 6
0.1%
619951 5
 
0.1%
619950 1
 
< 0.1%
619913 3
 
0.1%
619912 5
 
0.1%
619911 6
0.1%
619906 9
0.2%
619905 14
0.3%
619904 2
 
< 0.1%
Distinct4321
Distinct (%)88.3%
Missing3
Missing (%)0.1%
Memory size38.4 KiB
2024-04-18T07:49:46.111905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length23.632332
Min length6

Characters and Unicode

Total characters115633
Distinct characters367
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

Unique3884 ?
Unique (%)79.4%

Sample

1st row부산광역시 영도구 동삼동 1123-7
2nd row부산광역시 사상구 학장동 574-57번지 학장동2차삼성아파트상가 205호
3rd row부산광역시 금정구 서동 118-27번지
4th row부산광역시 사상구 주례동 507-1번지
5th row부산광역시 사상구 엄궁동 266번지
ValueCountFrequency (%)
부산광역시 4892
 
22.3%
t통b반 763
 
3.5%
사하구 497
 
2.3%
부산진구 496
 
2.3%
동래구 418
 
1.9%
북구 411
 
1.9%
해운대구 392
 
1.8%
금정구 380
 
1.7%
사상구 331
 
1.5%
연제구 328
 
1.5%
Other values (4683) 13028
59.4%
2024-04-18T07:49:46.578232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17047
 
14.7%
5797
 
5.0%
5753
 
5.0%
5743
 
5.0%
5062
 
4.4%
1 5043
 
4.4%
5026
 
4.3%
4919
 
4.3%
4899
 
4.2%
4806
 
4.2%
Other values (357) 51538
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68735
59.4%
Decimal Number 23308
 
20.2%
Space Separator 17047
 
14.7%
Dash Punctuation 4448
 
3.8%
Uppercase Letter 1570
 
1.4%
Open Punctuation 218
 
0.2%
Close Punctuation 217
 
0.2%
Other Punctuation 87
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5797
 
8.4%
5753
 
8.4%
5743
 
8.4%
5062
 
7.4%
5026
 
7.3%
4919
 
7.2%
4899
 
7.1%
4806
 
7.0%
4609
 
6.7%
943
 
1.4%
Other values (326) 21178
30.8%
Uppercase Letter
ValueCountFrequency (%)
B 783
49.9%
T 765
48.7%
A 10
 
0.6%
F 2
 
0.1%
G 2
 
0.1%
L 2
 
0.1%
C 2
 
0.1%
O 1
 
0.1%
P 1
 
0.1%
W 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5043
21.6%
2 3138
13.5%
3 2694
11.6%
4 2222
9.5%
5 2157
9.3%
6 1725
 
7.4%
0 1702
 
7.3%
8 1655
 
7.1%
7 1603
 
6.9%
9 1369
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 76
87.4%
@ 6
 
6.9%
/ 3
 
3.4%
. 2
 
2.3%
Space Separator
ValueCountFrequency (%)
17047
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4448
100.0%
Open Punctuation
ValueCountFrequency (%)
( 218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 217
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68733
59.4%
Common 45327
39.2%
Latin 1571
 
1.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5797
 
8.4%
5753
 
8.4%
5743
 
8.4%
5062
 
7.4%
5026
 
7.3%
4919
 
7.2%
4899
 
7.1%
4806
 
7.0%
4609
 
6.7%
943
 
1.4%
Other values (325) 21176
30.8%
Common
ValueCountFrequency (%)
17047
37.6%
1 5043
 
11.1%
- 4448
 
9.8%
2 3138
 
6.9%
3 2694
 
5.9%
4 2222
 
4.9%
5 2157
 
4.8%
6 1725
 
3.8%
0 1702
 
3.8%
8 1655
 
3.7%
Other values (9) 3496
 
7.7%
Latin
ValueCountFrequency (%)
B 783
49.8%
T 765
48.7%
A 10
 
0.6%
F 2
 
0.1%
G 2
 
0.1%
L 2
 
0.1%
C 2
 
0.1%
O 1
 
0.1%
P 1
 
0.1%
e 1
 
0.1%
Other values (2) 2
 
0.1%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68733
59.4%
ASCII 46898
40.6%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17047
36.3%
1 5043
 
10.8%
- 4448
 
9.5%
2 3138
 
6.7%
3 2694
 
5.7%
4 2222
 
4.7%
5 2157
 
4.6%
6 1725
 
3.7%
0 1702
 
3.6%
8 1655
 
3.5%
Other values (21) 5067
 
10.8%
Hangul
ValueCountFrequency (%)
5797
 
8.4%
5753
 
8.4%
5743
 
8.4%
5062
 
7.4%
5026
 
7.3%
4919
 
7.2%
4899
 
7.1%
4806
 
7.0%
4609
 
6.7%
943
 
1.4%
Other values (325) 21176
30.8%
CJK
ValueCountFrequency (%)
2
100.0%

도로명전체주소
Text

MISSING 

Distinct2215
Distinct (%)96.3%
Missing2597
Missing (%)53.0%
Memory size38.4 KiB
2024-04-18T07:49:46.902071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.61679
Min length17

Characters and Unicode

Total characters65790
Distinct characters388
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2138 ?
Unique (%)93.0%

Sample

1st row부산광역시 영도구 상리로 35 (동삼동)
2nd row부산광역시 사상구 학감대로123번길 89, 학장동2차삼성아파트상가205호 (학장동)
3rd row부산광역시 금정구 금사로 58-12, 1층 (서동)
4th row부산광역시 사상구 가야대로 290-4, 2층 (주례동)
5th row부산광역시 사상구 엄궁북로4번가길 17 (엄궁동, 진주식육점)
ValueCountFrequency (%)
부산광역시 2299
 
18.0%
1층 273
 
2.1%
부산진구 260
 
2.0%
동래구 224
 
1.8%
사하구 212
 
1.7%
사상구 187
 
1.5%
금정구 183
 
1.4%
해운대구 180
 
1.4%
남구 163
 
1.3%
북구 153
 
1.2%
Other values (2621) 8644
67.6%
2024-04-18T07:49:47.367513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10482
 
15.9%
2976
 
4.5%
2799
 
4.3%
2762
 
4.2%
1 2493
 
3.8%
2408
 
3.7%
2406
 
3.7%
2383
 
3.6%
2304
 
3.5%
( 2266
 
3.4%
Other values (378) 32511
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39249
59.7%
Space Separator 10482
 
15.9%
Decimal Number 10041
 
15.3%
Open Punctuation 2266
 
3.4%
Close Punctuation 2266
 
3.4%
Other Punctuation 1022
 
1.6%
Dash Punctuation 428
 
0.7%
Uppercase Letter 33
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2976
 
7.6%
2799
 
7.1%
2762
 
7.0%
2408
 
6.1%
2406
 
6.1%
2383
 
6.1%
2304
 
5.9%
2218
 
5.7%
1261
 
3.2%
1196
 
3.0%
Other values (351) 16536
42.1%
Decimal Number
ValueCountFrequency (%)
1 2493
24.8%
2 1532
15.3%
3 1173
11.7%
4 861
 
8.6%
5 799
 
8.0%
0 710
 
7.1%
6 673
 
6.7%
7 647
 
6.4%
8 597
 
5.9%
9 556
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 18
54.5%
A 6
 
18.2%
T 5
 
15.2%
F 1
 
3.0%
E 1
 
3.0%
W 1
 
3.0%
C 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 1010
98.8%
/ 5
 
0.5%
@ 5
 
0.5%
. 2
 
0.2%
Space Separator
ValueCountFrequency (%)
10482
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2266
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2266
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39249
59.7%
Common 26507
40.3%
Latin 34
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2976
 
7.6%
2799
 
7.1%
2762
 
7.0%
2408
 
6.1%
2406
 
6.1%
2383
 
6.1%
2304
 
5.9%
2218
 
5.7%
1261
 
3.2%
1196
 
3.0%
Other values (351) 16536
42.1%
Common
ValueCountFrequency (%)
10482
39.5%
1 2493
 
9.4%
( 2266
 
8.5%
) 2266
 
8.5%
2 1532
 
5.8%
3 1173
 
4.4%
, 1010
 
3.8%
4 861
 
3.2%
5 799
 
3.0%
0 710
 
2.7%
Other values (9) 2915
 
11.0%
Latin
ValueCountFrequency (%)
B 18
52.9%
A 6
 
17.6%
T 5
 
14.7%
e 1
 
2.9%
F 1
 
2.9%
E 1
 
2.9%
W 1
 
2.9%
C 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39249
59.7%
ASCII 26541
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10482
39.5%
1 2493
 
9.4%
( 2266
 
8.5%
) 2266
 
8.5%
2 1532
 
5.8%
3 1173
 
4.4%
, 1010
 
3.8%
4 861
 
3.2%
5 799
 
3.0%
0 710
 
2.7%
Other values (17) 2949
 
11.1%
Hangul
ValueCountFrequency (%)
2976
 
7.6%
2799
 
7.1%
2762
 
7.0%
2408
 
6.1%
2406
 
6.1%
2383
 
6.1%
2304
 
5.9%
2218
 
5.7%
1261
 
3.2%
1196
 
3.0%
Other values (351) 16536
42.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1153
Distinct (%)51.4%
Missing2651
Missing (%)54.1%
Infinite0
Infinite (%)0.0%
Mean47830.696
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:47.505547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46242.2
Q147008
median47808
Q348726
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1718

Descriptive statistics

Standard deviation1011.6844
Coefficient of variation (CV)0.021151363
Kurtosis-1.1161965
Mean47830.696
Median Absolute Deviation (MAD)813
Skewness0.013056018
Sum1.0737991 × 108
Variance1023505.4
MonotonicityNot monotonic
2024-04-18T07:49:47.639730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49256 12
 
0.2%
47709 11
 
0.2%
46219 9
 
0.2%
49476 9
 
0.2%
47511 7
 
0.1%
48501 7
 
0.1%
47603 7
 
0.1%
49217 7
 
0.1%
48095 7
 
0.1%
47256 6
 
0.1%
Other values (1143) 2163
44.2%
(Missing) 2651
54.1%
ValueCountFrequency (%)
46002 2
< 0.1%
46007 2
< 0.1%
46008 1
 
< 0.1%
46013 1
 
< 0.1%
46015 3
0.1%
46017 2
< 0.1%
46019 1
 
< 0.1%
46020 1
 
< 0.1%
46021 1
 
< 0.1%
46022 2
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 2
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49518 5
0.1%
49516 1
 
< 0.1%
49515 4
0.1%
49514 1
 
< 0.1%
49511 5
0.1%
49509 1
 
< 0.1%
Distinct3319
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
2024-04-18T07:49:47.852400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7579657
Min length1

Characters and Unicode

Total characters23295
Distinct characters568
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2643 ?
Unique (%)54.0%

Sample

1st row대광 이발
2nd row퀀즈헤나
3rd row태후사랑
4th row퀸즈헤나
5th row엄궁퀀즈헤나교실
ValueCountFrequency (%)
이용원 365
 
6.4%
구내 52
 
0.9%
컷트실 50
 
0.9%
구내이용원 41
 
0.7%
현대 36
 
0.6%
제일 28
 
0.5%
우리 28
 
0.5%
블루클럽 24
 
0.4%
캇트실 23
 
0.4%
현대이용원 23
 
0.4%
Other values (3179) 4997
88.2%
2024-04-18T07:49:48.727729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2078
 
8.9%
2005
 
8.6%
1922
 
8.3%
974
 
4.2%
842
 
3.6%
772
 
3.3%
582
 
2.5%
469
 
2.0%
403
 
1.7%
386
 
1.7%
Other values (558) 12862
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22086
94.8%
Space Separator 772
 
3.3%
Uppercase Letter 145
 
0.6%
Lowercase Letter 103
 
0.4%
Open Punctuation 63
 
0.3%
Close Punctuation 63
 
0.3%
Decimal Number 35
 
0.2%
Other Punctuation 20
 
0.1%
Dash Punctuation 6
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2078
 
9.4%
2005
 
9.1%
1922
 
8.7%
974
 
4.4%
842
 
3.8%
582
 
2.6%
469
 
2.1%
403
 
1.8%
386
 
1.7%
343
 
1.6%
Other values (498) 12082
54.7%
Uppercase Letter
ValueCountFrequency (%)
B 19
13.1%
O 13
 
9.0%
H 11
 
7.6%
R 10
 
6.9%
E 10
 
6.9%
A 9
 
6.2%
S 9
 
6.2%
M 8
 
5.5%
L 7
 
4.8%
N 7
 
4.8%
Other values (12) 42
29.0%
Lowercase Letter
ValueCountFrequency (%)
r 15
14.6%
a 9
8.7%
b 9
8.7%
e 9
8.7%
o 8
 
7.8%
i 8
 
7.8%
h 7
 
6.8%
s 7
 
6.8%
u 6
 
5.8%
y 5
 
4.9%
Other values (8) 20
19.4%
Decimal Number
ValueCountFrequency (%)
2 11
31.4%
1 9
25.7%
8 8
22.9%
5 3
 
8.6%
9 2
 
5.7%
4 1
 
2.9%
3 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 10
50.0%
& 4
 
20.0%
, 2
 
10.0%
: 1
 
5.0%
' 1
 
5.0%
# 1
 
5.0%
· 1
 
5.0%
Space Separator
ValueCountFrequency (%)
772
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22083
94.8%
Common 961
 
4.1%
Latin 248
 
1.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2078
 
9.4%
2005
 
9.1%
1922
 
8.7%
974
 
4.4%
842
 
3.8%
582
 
2.6%
469
 
2.1%
403
 
1.8%
386
 
1.7%
343
 
1.6%
Other values (495) 12079
54.7%
Latin
ValueCountFrequency (%)
B 19
 
7.7%
r 15
 
6.0%
O 13
 
5.2%
H 11
 
4.4%
R 10
 
4.0%
E 10
 
4.0%
a 9
 
3.6%
A 9
 
3.6%
b 9
 
3.6%
S 9
 
3.6%
Other values (30) 134
54.0%
Common
ValueCountFrequency (%)
772
80.3%
( 63
 
6.6%
) 63
 
6.6%
2 11
 
1.1%
. 10
 
1.0%
1 9
 
0.9%
8 8
 
0.8%
- 6
 
0.6%
& 4
 
0.4%
5 3
 
0.3%
Other values (10) 12
 
1.2%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22083
94.8%
ASCII 1208
 
5.2%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2078
 
9.4%
2005
 
9.1%
1922
 
8.7%
974
 
4.4%
842
 
3.8%
582
 
2.6%
469
 
2.1%
403
 
1.8%
386
 
1.7%
343
 
1.6%
Other values (495) 12079
54.7%
ASCII
ValueCountFrequency (%)
772
63.9%
( 63
 
5.2%
) 63
 
5.2%
B 19
 
1.6%
r 15
 
1.2%
O 13
 
1.1%
H 11
 
0.9%
2 11
 
0.9%
. 10
 
0.8%
R 10
 
0.8%
Other values (49) 221
 
18.3%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

최종수정시점
Real number (ℝ)

Distinct3255
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0093598 × 1013
Minimum1.9990218 × 1013
Maximum2.0201231 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:48.865657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990624 × 1013
Q12.0031015 × 1013
median2.008012 × 1013
Q32.0160217 × 1013
95-th percentile2.0200827 × 1013
Maximum2.0201231 × 1013
Range2.1101317 × 1011
Interquartile range (IQR)1.2920239 × 1011

Descriptive statistics

Standard deviation6.7130738 × 1010
Coefficient of variation (CV)0.0033409018
Kurtosis-1.3321399
Mean2.0093598 × 1013
Median Absolute Deviation (MAD)4.9894137 × 1010
Skewness0.28349289
Sum9.8378254 × 1016
Variance4.5065359 × 1021
MonotonicityNot monotonic
2024-04-18T07:49:49.010942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030211000000 57
 
1.2%
20070501000000 49
 
1.0%
20020424000000 38
 
0.8%
20031215000000 38
 
0.8%
20030311000000 37
 
0.8%
20030502000000 35
 
0.7%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20030318000000 33
 
0.7%
20030221000000 33
 
0.7%
Other values (3245) 4507
92.1%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 11
0.2%
19990303000000 11
0.2%
19990304000000 20
0.4%
19990308000000 15
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20201231174955 1
< 0.1%
20201229141308 1
< 0.1%
20201228131544 1
< 0.1%
20201223141745 1
< 0.1%
20201223141555 1
< 0.1%
20201221143803 1
< 0.1%
20201217222101 1
< 0.1%
20201217160612 1
< 0.1%
20201217151407 1
< 0.1%
20201217151333 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
I
4172 
U
724 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4172
85.2%
U 724
 
14.8%

Length

2024-04-18T07:49:49.124148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:49.206593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4172
85.2%
u 724
 
14.8%
Distinct368
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-02 02:40:00
2024-04-18T07:49:49.296655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:49:49.438177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
일반이용업
4832 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079657
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4832
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:49:49.580453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:49.694657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4832
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3528
Distinct (%)78.3%
Missing388
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean387471.66
Minimum365567.31
Maximum407739.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:49.792808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365567.31
5-th percentile379534.86
Q1383498.28
median387761.23
Q3390956.33
95-th percentile396574.8
Maximum407739.05
Range42171.732
Interquartile range (IQR)7458.0516

Descriptive statistics

Standard deviation5376.4653
Coefficient of variation (CV)0.013875764
Kurtosis0.58648234
Mean387471.66
Median Absolute Deviation (MAD)3676.716
Skewness0.1154971
Sum1.7467223 × 109
Variance28906379
MonotonicityNot monotonic
2024-04-18T07:49:49.908463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400730.067993635 8
 
0.2%
388911.5369095 7
 
0.1%
383226.095097284 6
 
0.1%
382867.341996368 6
 
0.1%
381376.053716185 6
 
0.1%
392333.26238725 6
 
0.1%
379137.720990997 5
 
0.1%
383249.780553382 5
 
0.1%
387395.906194984 5
 
0.1%
382223.343951843 5
 
0.1%
Other values (3518) 4449
90.9%
(Missing) 388
 
7.9%
ValueCountFrequency (%)
365567.314347802 1
< 0.1%
365644.37444583 1
< 0.1%
366820.787750249 2
< 0.1%
367094.33981503 2
< 0.1%
367741.522165263 1
< 0.1%
367817.892752005 2
< 0.1%
367848.653623532 1
< 0.1%
370678.90382152 2
< 0.1%
370718.68095386 1
< 0.1%
370949.59316783 1
< 0.1%
ValueCountFrequency (%)
407739.046710947 3
0.1%
407530.734153914 2
< 0.1%
407147.657910169 1
 
< 0.1%
407041.865710589 1
 
< 0.1%
405392.621531798 1
 
< 0.1%
405392.303791546 1
 
< 0.1%
405390.19530521 1
 
< 0.1%
405172.859381319 2
< 0.1%
403998.423742534 1
 
< 0.1%
403520.239041375 1
 
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct3529
Distinct (%)78.3%
Missing388
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean186847.37
Minimum171356.38
Maximum206164.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:50.031272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171356.38
5-th percentile178125.87
Q1181985.09
median187063.29
Q3191093.63
95-th percentile195791.94
Maximum206164.58
Range34808.197
Interquartile range (IQR)9108.5345

Descriptive statistics

Standard deviation5700.9755
Coefficient of variation (CV)0.030511403
Kurtosis-0.32064666
Mean186847.37
Median Absolute Deviation (MAD)4358.4735
Skewness0.13321545
Sum8.4230796 × 108
Variance32501122
MonotonicityNot monotonic
2024-04-18T07:49:50.170033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189145.674198705 8
 
0.2%
189958.23076541 7
 
0.1%
192077.564796439 6
 
0.1%
189006.221241803 6
 
0.1%
191452.16648903 6
 
0.1%
190804.667916156 6
 
0.1%
184141.142825361 5
 
0.1%
184985.713735355 5
 
0.1%
194837.216911232 5
 
0.1%
196950.450593302 5
 
0.1%
Other values (3519) 4449
90.9%
(Missing) 388
 
7.9%
ValueCountFrequency (%)
171356.377819897 1
 
< 0.1%
171745.287844766 1
 
< 0.1%
173914.718015169 2
< 0.1%
173969.719902491 1
 
< 0.1%
174068.494334685 1
 
< 0.1%
174097.616386311 2
< 0.1%
174101.406639044 1
 
< 0.1%
174279.164266 2
< 0.1%
174307.148168245 3
0.1%
174330.963124212 1
 
< 0.1%
ValueCountFrequency (%)
206164.575140106 1
 
< 0.1%
205995.903772118 2
< 0.1%
205709.503717342 2
< 0.1%
205678.034061751 2
< 0.1%
205671.36729929 3
0.1%
205473.9857853 1
 
< 0.1%
205441.669345456 1
 
< 0.1%
205178.593355644 1
 
< 0.1%
205097.400941024 1
 
< 0.1%
205095.722992576 1
 
< 0.1%

위생업태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
일반이용업
4832 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079657
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4832
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:49:50.304354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:50.399313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4832
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)1.0%
Missing1730
Missing (%)35.3%
Infinite0
Infinite (%)0.0%
Mean2.5101074
Minimum0
Maximum42
Zeros1196
Zeros (%)24.4%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:50.490142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile7
Maximum42
Range42
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3329783
Coefficient of variation (CV)1.327823
Kurtosis29.340759
Mean2.5101074
Median Absolute Deviation (MAD)2
Skewness3.9774991
Sum7947
Variance11.108745
MonotonicityNot monotonic
2024-04-18T07:49:50.603000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 1196
24.4%
3 475
 
9.7%
4 418
 
8.5%
2 403
 
8.2%
5 233
 
4.8%
1 166
 
3.4%
6 86
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
Other values (22) 83
 
1.7%
(Missing) 1730
35.3%
ValueCountFrequency (%)
0 1196
24.4%
1 166
 
3.4%
2 403
 
8.2%
3 475
 
9.7%
4 418
 
8.5%
5 233
 
4.8%
6 86
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
ValueCountFrequency (%)
42 2
< 0.1%
37 1
< 0.1%
34 1
< 0.1%
32 1
< 0.1%
30 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%
25 2
< 0.1%
23 1
< 0.1%
22 1
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.4%
Missing2234
Missing (%)45.6%
Infinite0
Infinite (%)0.0%
Mean0.52817431
Minimum0
Maximum208
Zeros1699
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:50.742112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum208
Range208
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.0993573
Coefficient of variation (CV)7.761372
Kurtosis2468.2716
Mean0.52817431
Median Absolute Deviation (MAD)0
Skewness48.785778
Sum1406
Variance16.80473
MonotonicityNot monotonic
2024-04-18T07:49:50.852792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1699
34.7%
1 832
 
17.0%
2 84
 
1.7%
3 21
 
0.4%
5 13
 
0.3%
4 6
 
0.1%
6 4
 
0.1%
208 1
 
< 0.1%
15 1
 
< 0.1%
7 1
 
< 0.1%
(Missing) 2234
45.6%
ValueCountFrequency (%)
0 1699
34.7%
1 832
17.0%
2 84
 
1.7%
3 21
 
0.4%
4 6
 
0.1%
5 13
 
0.3%
6 4
 
0.1%
7 1
 
< 0.1%
15 1
 
< 0.1%
208 1
 
< 0.1%
ValueCountFrequency (%)
208 1
 
< 0.1%
15 1
 
< 0.1%
7 1
 
< 0.1%
6 4
 
0.1%
5 13
 
0.3%
4 6
 
0.1%
3 21
 
0.4%
2 84
 
1.7%
1 832
17.0%
0 1699
34.7%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.5%
Missing2099
Missing (%)42.9%
Infinite0
Infinite (%)0.0%
Mean1.254916
Minimum0
Maximum12
Zeros1000
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:50.950797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4060015
Coefficient of variation (CV)1.1203949
Kurtosis6.0358756
Mean1.254916
Median Absolute Deviation (MAD)1
Skewness1.85091
Sum3510
Variance1.9768401
MonotonicityNot monotonic
2024-04-18T07:49:51.053654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1000
20.4%
1 865
17.7%
2 503
 
10.3%
3 251
 
5.1%
4 87
 
1.8%
5 55
 
1.1%
6 19
 
0.4%
7 5
 
0.1%
10 4
 
0.1%
9 3
 
0.1%
Other values (3) 5
 
0.1%
(Missing) 2099
42.9%
ValueCountFrequency (%)
0 1000
20.4%
1 865
17.7%
2 503
10.3%
3 251
 
5.1%
4 87
 
1.8%
5 55
 
1.1%
6 19
 
0.4%
7 5
 
0.1%
8 3
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 1
 
< 0.1%
10 4
 
0.1%
9 3
 
0.1%
8 3
 
0.1%
7 5
 
0.1%
6 19
 
0.4%
5 55
 
1.1%
4 87
 
1.8%
3 251
5.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing2728
Missing (%)55.7%
Infinite0
Infinite (%)0.0%
Mean1.4155904
Minimum0
Maximum10
Zeros583
Zeros (%)11.9%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:51.154932image/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 deviation1.3587219
Coefficient of variation (CV)0.95982697
Kurtosis3.990007
Mean1.4155904
Median Absolute Deviation (MAD)1
Skewness1.5179855
Sum3069
Variance1.8461251
MonotonicityNot monotonic
2024-04-18T07:49:51.260572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 746
 
15.2%
0 583
 
11.9%
2 473
 
9.7%
3 214
 
4.4%
4 79
 
1.6%
5 45
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
10 3
 
0.1%
8 2
 
< 0.1%
(Missing) 2728
55.7%
ValueCountFrequency (%)
0 583
11.9%
1 746
15.2%
2 473
9.7%
3 214
 
4.4%
4 79
 
1.6%
5 45
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
10 3
 
0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
7 7
 
0.1%
6 15
 
0.3%
5 45
 
0.9%
4 79
 
1.6%
3 214
 
4.4%
2 473
9.7%
1 746
15.2%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3064 
0
1510 
1
310 
2
 
11
22
 
1

Length

Max length4
Median length4
Mean length2.8776552
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3064
62.6%
0 1510
30.8%
1 310
 
6.3%
2 11
 
0.2%
22 1
 
< 0.1%

Length

2024-04-18T07:49:51.376304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:51.476753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3064
62.6%
0 1510
30.8%
1 310
 
6.3%
2 11
 
0.2%
22 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3716 
0
913 
1
 
262
2
 
4
4
 
1

Length

Max length4
Median length4
Mean length3.2769608
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3716
75.9%
0 913
 
18.6%
1 262
 
5.4%
2 4
 
0.1%
4 1
 
< 0.1%

Length

2024-04-18T07:49:51.596885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:51.694546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3716
75.9%
0 913
 
18.6%
1 262
 
5.4%
2 4
 
0.1%
4 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
2706 
0
2190 

Length

Max length4
Median length4
Mean length2.6580882
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2706
55.3%
0 2190
44.7%

Length

2024-04-18T07:49:51.801603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:51.886949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2706
55.3%
0 2190
44.7%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
2705 
0
2190 
38
 
1

Length

Max length4
Median length4
Mean length2.6576797
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2705
55.2%
0 2190
44.7%
38 1
 
< 0.1%

Length

2024-04-18T07:49:51.980279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:52.069507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2705
55.2%
0 2190
44.7%
38 1
 
< 0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
2705 
0
2190 
2
 
1

Length

Max length4
Median length4
Mean length2.6574755
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2705
55.2%
0 2190
44.7%
2 1
 
< 0.1%

Length

2024-04-18T07:49:52.169724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:52.275831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2705
55.2%
0 2190
44.7%
2 1
 
< 0.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing100
Missing (%)2.0%
Memory size9.7 KiB
False
4796 
(Missing)
 
100
ValueCountFrequency (%)
False 4796
98.0%
(Missing) 100
 
2.0%
2024-04-18T07:49:52.476370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.4%
Missing607
Missing (%)12.4%
Infinite0
Infinite (%)0.0%
Mean3.132665
Minimum0
Maximum24
Zeros338
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size43.2 KiB
2024-04-18T07:49:52.718669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum24
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1303989
Coefficient of variation (CV)0.68005959
Kurtosis3.3718394
Mean3.132665
Median Absolute Deviation (MAD)1
Skewness1.2778848
Sum13436
Variance4.5385993
MonotonicityNot monotonic
2024-04-18T07:49:52.939307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 1336
27.3%
3 878
17.9%
4 580
11.8%
0 338
 
6.9%
1 332
 
6.8%
5 261
 
5.3%
6 178
 
3.6%
7 167
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
Other values (6) 42
 
0.9%
(Missing) 607
12.4%
ValueCountFrequency (%)
0 338
 
6.9%
1 332
 
6.8%
2 1336
27.3%
3 878
17.9%
4 580
11.8%
5 261
 
5.3%
6 178
 
3.6%
7 167
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
ValueCountFrequency (%)
24 1
 
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%
12 3
 
0.1%
11 6
 
0.1%
10 30
 
0.6%
9 66
 
1.3%
8 111
2.3%
7 167
3.4%
6 178
3.6%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4895
Missing (%)> 99.9%
Memory size38.4 KiB
2024-04-18T07:49:53.096794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row가설건축물
ValueCountFrequency (%)
가설건축물 1
100.0%
2024-04-18T07:49:53.365287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4894 
20050414
 
1
20050520
 
1

Length

Max length8
Median length4
Mean length4.001634
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4894
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

Length

2024-04-18T07:49:53.518144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:53.658566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4894
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4894 
20050414
 
1
20060425
 
1

Length

Max length8
Median length4
Mean length4.001634
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4894
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

Length

2024-04-18T07:49:53.798676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:53.913085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4894
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3936 
임대
932 
자가
 
28

Length

Max length4
Median length4
Mean length3.6078431
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3936
80.4%
임대 932
 
19.0%
자가 28
 
0.6%

Length

2024-04-18T07:49:54.016957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:54.154044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3936
80.4%
임대 932
 
19.0%
자가 28
 
0.6%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3365 
0
1531 

Length

Max length4
Median length4
Mean length3.0618873
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3365
68.7%
0 1531
31.3%

Length

2024-04-18T07:49:54.279721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:54.397452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3365
68.7%
0 1531
31.3%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4552 
0
 
328
1
 
16

Length

Max length4
Median length4
Mean length3.7892157
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4552
93.0%
0 328
 
6.7%
1 16
 
0.3%

Length

2024-04-18T07:49:54.492317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:54.587007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4552
93.0%
0 328
 
6.7%
1 16
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
4541 
0
 
323
1
 
31
2
 
1

Length

Max length4
Median length4
Mean length3.7824755
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4541
92.7%
0 323
 
6.6%
1 31
 
0.6%
2 1
 
< 0.1%

Length

2024-04-18T07:49:54.689568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:54.797163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4541
92.7%
0 323
 
6.6%
1 31
 
0.6%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3548 
0
1348 

Length

Max length4
Median length4
Mean length3.1740196
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3548
72.5%
0 1348
 
27.5%

Length

2024-04-18T07:49:54.931715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:55.040756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3548
72.5%
0 1348
 
27.5%

침대수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.4 KiB
<NA>
3566 
0
1322 
2
 
4
3
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.185049
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3566
72.8%
0 1322
 
27.0%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-18T07:49:55.153403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:49:55.259038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3566
72.8%
0 1322
 
27.0%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
False
4896 
ValueCountFrequency (%)
False 4896
100.0%
2024-04-18T07:49:55.337080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4896
Missing (%)100.0%
Memory size43.2 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
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23이용업05_19_01_P33500003350000-203-2019-0000120190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.80609858부산광역시 금정구 서동 118-27번지부산광역시 금정구 금사로 58-12, 1층 (서동)46321태후사랑20190121104943I2019-01-23 02:20:58.0이용업 기타392010.437951192967.812353이용업 기타3111<NA><NA>000N3<NA><NA><NA><NA>00000N<NA>
34이용업05_19_01_P33900003390000-203-2019-0000220190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.07617838부산광역시 사상구 주례동 507-1번지부산광역시 사상구 가야대로 290-4, 2층 (주례동)47013퀸즈헤나20190129144431U2019-01-31 02:40:00.0일반이용업382596.186669185283.584397일반이용업002200000N2<NA><NA><NA><NA>00000N<NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
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