Overview

Dataset statistics

Number of variables51
Number of observations4925
Missing cells47854
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

Description2021-06-01
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 (56.9%)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 (74.5%)Imbalance
남성종사자수 is highly imbalanced (78.7%)Imbalance
침대수 is highly imbalanced (66.4%)Imbalance
인허가취소일자 has 4925 (100.0%) missing valuesMissing
폐업일자 has 1318 (26.8%) missing valuesMissing
휴업시작일자 has 4925 (100.0%) missing valuesMissing
휴업종료일자 has 4925 (100.0%) missing valuesMissing
재개업일자 has 4925 (100.0%) missing valuesMissing
소재지전화 has 1414 (28.7%) missing valuesMissing
도로명전체주소 has 2596 (52.7%) missing valuesMissing
도로명우편번호 has 2649 (53.8%) missing valuesMissing
좌표정보(x) has 387 (7.9%) missing valuesMissing
좌표정보(y) has 387 (7.9%) missing valuesMissing
건물지상층수 has 1728 (35.1%) missing valuesMissing
건물지하층수 has 2230 (45.3%) missing valuesMissing
사용시작지상층 has 2100 (42.6%) missing valuesMissing
사용끝지상층 has 2728 (55.4%) missing valuesMissing
발한실여부 has 100 (2.0%) missing valuesMissing
의자수 has 607 (12.3%) missing valuesMissing
조건부허가신고사유 has 4924 (> 99.9%) missing valuesMissing
Unnamed: 50 has 4925 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -26.97901869)Skewed
폐업일자 is highly skewed (γ1 = -28.20517648)Skewed
건물지하층수 is highly skewed (γ1 = 49.06493)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 1210 (24.6%) zerosZeros
건물지하층수 has 1724 (35.0%) zerosZeros
사용시작지상층 has 1004 (20.4%) zerosZeros
사용끝지상층 has 591 (12.0%) zerosZeros
의자수 has 338 (6.9%) zerosZeros

Reproduction

Analysis started2024-04-17 22:58:41.537846
Analysis finished2024-04-17 22:58:43.026332
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4925
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2463
Minimum1
Maximum4925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:43.090489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile247.2
Q11232
median2463
Q33694
95-th percentile4678.8
Maximum4925
Range4924
Interquartile range (IQR)2462

Descriptive statistics

Standard deviation1421.8694
Coefficient of variation (CV)0.57729166
Kurtosis-1.2
Mean2463
Median Absolute Deviation (MAD)1231
Skewness0
Sum12130275
Variance2021712.5
MonotonicityStrictly increasing
2024-04-18T07:58:43.239586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3282 1
 
< 0.1%
3289 1
 
< 0.1%
3288 1
 
< 0.1%
3287 1
 
< 0.1%
3286 1
 
< 0.1%
3285 1
 
< 0.1%
3284 1
 
< 0.1%
3283 1
 
< 0.1%
3281 1
 
< 0.1%
Other values (4915) 4915
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 (%)
4925 1
< 0.1%
4924 1
< 0.1%
4923 1
< 0.1%
4922 1
< 0.1%
4921 1
< 0.1%
4920 1
< 0.1%
4919 1
< 0.1%
4918 1
< 0.1%
4917 1
< 0.1%
4916 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
이용업
4925 

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 4925
100.0%

Length

2024-04-18T07:58:43.367150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:43.447491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이용업 4925
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
05_19_01_P
4925 

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 4925
100.0%

Length

2024-04-18T07:58:43.527951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:43.612482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_19_01_p 4925
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324497.5
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:43.687777image/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 deviation40379.197
Coefficient of variation (CV)0.012145955
Kurtosis-0.94068333
Mean3324497.5
Median Absolute Deviation (MAD)30000
Skewness0.058057361
Sum1.637315 × 1010
Variance1.6304795 × 109
MonotonicityNot monotonic
2024-04-18T07:58:43.796619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3290000 504
10.2%
3340000 496
10.1%
3300000 422
8.6%
3320000 409
 
8.3%
3330000 393
 
8.0%
3350000 384
 
7.8%
3390000 333
 
6.8%
3370000 331
 
6.7%
3310000 324
 
6.6%
3380000 284
 
5.8%
Other values (6) 1045
21.2%
ValueCountFrequency (%)
3250000 167
 
3.4%
3260000 213
4.3%
3270000 257
5.2%
3280000 209
4.2%
3290000 504
10.2%
3300000 422
8.6%
3310000 324
6.6%
3320000 409
8.3%
3330000 393
8.0%
3340000 496
10.1%
ValueCountFrequency (%)
3400000 110
 
2.2%
3390000 333
6.8%
3380000 284
5.8%
3370000 331
6.7%
3360000 89
 
1.8%
3350000 384
7.8%
3340000 496
10.1%
3330000 393
8.0%
3320000 409
8.3%
3310000 324
6.6%

관리번호
Text

UNIQUE 

Distinct4925
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-18T07:58:43.976529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters108350
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

Unique4925 ?
Unique (%)100.0%

Sample

1st row3280000-203-2018-00003
2nd row3350000-203-2019-00001
3rd row3390000-203-2019-00002
4th row3390000-203-2019-00003
5th row3330000-203-2019-00001
ValueCountFrequency (%)
3280000-203-2018-00003 1
 
< 0.1%
3380000-203-1998-00009 1
 
< 0.1%
3350000-203-1985-00726 1
 
< 0.1%
3350000-203-2013-00002 1
 
< 0.1%
3350000-203-2012-00001 1
 
< 0.1%
3350000-203-2004-00020 1
 
< 0.1%
3350000-203-2012-00004 1
 
< 0.1%
3350000-203-2010-00006 1
 
< 0.1%
3350000-203-2012-00003 1
 
< 0.1%
3380000-203-1996-00004 1
 
< 0.1%
Other values (4915) 4915
99.8%
2024-04-18T07:58:44.308124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43303
40.0%
3 15469
 
14.3%
- 14775
 
13.6%
2 10904
 
10.1%
1 6167
 
5.7%
9 6022
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2332
 
2.2%
5 2140
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 93575
86.4%
Dash Punctuation 14775
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43303
46.3%
3 15469
 
16.5%
2 10904
 
11.7%
1 6167
 
6.6%
9 6022
 
6.4%
8 2657
 
2.8%
7 2444
 
2.6%
4 2332
 
2.5%
5 2140
 
2.3%
6 2137
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 14775
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43303
40.0%
3 15469
 
14.3%
- 14775
 
13.6%
2 10904
 
10.1%
1 6167
 
5.7%
9 6022
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2332
 
2.2%
5 2140
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43303
40.0%
3 15469
 
14.3%
- 14775
 
13.6%
2 10904
 
10.1%
1 6167
 
5.7%
9 6022
 
5.6%
8 2657
 
2.5%
7 2444
 
2.3%
4 2332
 
2.2%
5 2140
 
2.0%

인허가일자
Real number (ℝ)

SKEWED 

Distinct3654
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19959026
Minimum9710223
Maximum20210421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:44.470647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9710223
5-th percentile19691141
Q119880105
median19980507
Q320060109
95-th percentile20170891
Maximum20210421
Range10500198
Interquartile range (IQR)180004

Descriptive statistics

Standard deviation201199.22
Coefficient of variation (CV)0.010080613
Kurtosis1366.5625
Mean19959026
Median Absolute Deviation (MAD)90004
Skewness-26.979019
Sum9.8298201 × 1010
Variance4.0481125 × 1010
MonotonicityNot monotonic
2024-04-18T07:58:44.596911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19660301 35
 
0.7%
19770830 35
 
0.7%
20000420 19
 
0.4%
20020506 17
 
0.3%
20000623 13
 
0.3%
20030224 9
 
0.2%
19630630 9
 
0.2%
20030410 7
 
0.1%
19721129 7
 
0.1%
20030213 6
 
0.1%
Other values (3644) 4768
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 (%)
20210421 1
< 0.1%
20210419 1
< 0.1%
20210402 1
< 0.1%
20210401 1
< 0.1%
20210330 1
< 0.1%
20210324 1
< 0.1%
20210323 1
< 0.1%
20210318 1
< 0.1%
20210310 2
< 0.1%
20210309 1
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4925
Missing (%)100.0%
Memory size43.4 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
3
3607 
1
1318 

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 3607
73.2%
1 1318
 
26.8%

Length

2024-04-18T07:58:44.711981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:44.801559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3607
73.2%
1 1318
 
26.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3607 
영업/정상
1318 

Length

Max length5
Median length2
Mean length2.8028426
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 3607
73.2%
영업/정상 1318
 
26.8%

Length

2024-04-18T07:58:44.897141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:44.995908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3607
73.2%
영업/정상 1318
 
26.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2
3607 
1
1318 

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 3607
73.2%
1 1318
 
26.8%

Length

2024-04-18T07:58:45.084234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:45.163764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3607
73.2%
1 1318
 
26.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
폐업
3607 
영업
1318 

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 3607
73.2%
영업 1318
 
26.8%

Length

2024-04-18T07:58:45.248524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:45.330752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3607
73.2%
영업 1318
 
26.8%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2283
Distinct (%)63.3%
Missing1318
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean20066932
Minimum2019071
Maximum20800812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:45.426211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2019071
5-th percentile20000120
Q120040512
median20070628
Q320130767
95-th percentile20190778
Maximum20800812
Range18781741
Interquartile range (IQR)90255

Descriptive statistics

Standard deviation453310.15
Coefficient of variation (CV)0.022589908
Kurtosis906.53588
Mean20066932
Median Absolute Deviation (MAD)39913
Skewness-28.205176
Sum7.2381422 × 1010
Variance2.0549009 × 1011
MonotonicityNot monotonic
2024-04-18T07:58:45.564276image/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%
20020222 33
 
0.7%
20030305 33
 
0.7%
20030221 32
 
0.6%
20030101 17
 
0.3%
20051011 16
 
0.3%
20030215 13
 
0.3%
20061226 13
 
0.3%
Other values (2273) 3315
67.3%
(Missing) 1318
 
26.8%
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%
20210430 3
0.1%
20210427 1
 
< 0.1%
20210422 1
 
< 0.1%
20210421 1
 
< 0.1%
20210413 1
 
< 0.1%
20210412 2
< 0.1%
20210409 2
< 0.1%
20210402 1
 
< 0.1%
20210329 1
 
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4925
Missing (%)100.0%
Memory size43.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4925
Missing (%)100.0%
Memory size43.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4925
Missing (%)100.0%
Memory size43.4 KiB

소재지전화
Text

MISSING 

Distinct2874
Distinct (%)81.9%
Missing1414
Missing (%)28.7%
Memory size38.6 KiB
2024-04-18T07:58:45.863904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.9404728
Min length3

Characters and Unicode

Total characters34901
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

Unique2725 ?
Unique (%)77.6%

Sample

1st row051 727 5320
2nd row051 728 3988
3rd row051 364 2651
4th row051 7549944
5th row051 7596288
ValueCountFrequency (%)
051 3301
48.3%
893 8
 
0.1%
554 8
 
0.1%
292 6
 
0.1%
868 6
 
0.1%
754 6
 
0.1%
727 6
 
0.1%
051643 6
 
0.1%
724 5
 
0.1%
305 5
 
0.1%
Other values (3076) 3482
50.9%
2024-04-18T07:58:46.282685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31555
90.4%
Space Separator 3344
 
9.6%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6048
19.2%
1 5286
16.8%
0 5188
16.4%
2 2844
9.0%
4 2312
 
7.3%
6 2243
 
7.1%
3 2210
 
7.0%
7 2077
 
6.6%
8 1971
 
6.2%
9 1376
 
4.4%
Space Separator
ValueCountFrequency (%)
3344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 34901
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34901
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6048
17.3%
1 5286
15.1%
0 5188
14.9%
3344
9.6%
2 2844
8.1%
4 2312
 
6.6%
6 2243
 
6.4%
3 2210
 
6.3%
7 2077
 
6.0%
8 1971
 
5.6%
Other values (2) 1378
 
3.9%

소재지면적
Text

Distinct2134
Distinct (%)43.6%
Missing34
Missing (%)0.7%
Memory size38.6 KiB
2024-04-18T07:58:46.616971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.632386
Min length3

Characters and Unicode

Total characters22657
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

Unique1379 ?
Unique (%)28.2%

Sample

1st row10.12
2nd row42.80
3rd row62.07
4th row16.91
5th row5.70
ValueCountFrequency (%)
00 494
 
10.1%
9.00 50
 
1.0%
10.00 50
 
1.0%
12.00 43
 
0.9%
15.00 37
 
0.8%
8.40 33
 
0.7%
8.00 32
 
0.7%
18.00 31
 
0.6%
6.00 29
 
0.6%
30.00 27
 
0.6%
Other values (2124) 4065
83.1%
2024-04-18T07:58:47.085924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4891
21.6%
0 4478
19.8%
1 2290
10.1%
2 2177
9.6%
5 1425
 
6.3%
3 1422
 
6.3%
8 1410
 
6.2%
4 1294
 
5.7%
6 1271
 
5.6%
9 1006
 
4.4%
Other values (2) 993
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17762
78.4%
Other Punctuation 4895
 
21.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4478
25.2%
1 2290
12.9%
2 2177
12.3%
5 1425
 
8.0%
3 1422
 
8.0%
8 1410
 
7.9%
4 1294
 
7.3%
6 1271
 
7.2%
9 1006
 
5.7%
7 989
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 4891
99.9%
, 4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22657
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4891
21.6%
0 4478
19.8%
1 2290
10.1%
2 2177
9.6%
5 1425
 
6.3%
3 1422
 
6.3%
8 1410
 
6.2%
4 1294
 
5.7%
6 1271
 
5.6%
9 1006
 
4.4%
Other values (2) 993
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4891
21.6%
0 4478
19.8%
1 2290
10.1%
2 2177
9.6%
5 1425
 
6.3%
3 1422
 
6.3%
8 1410
 
6.2%
4 1294
 
5.7%
6 1271
 
5.6%
9 1006
 
4.4%
Other values (2) 993
 
4.4%

소재지우편번호
Real number (ℝ)

Distinct777
Distinct (%)15.9%
Missing24
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean610452.94
Minimum600011
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:47.236069image/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 deviation5292.4809
Coefficient of variation (CV)0.0086697607
Kurtosis-1.0156935
Mean610452.94
Median Absolute Deviation (MAD)4962
Skewness-0.18896533
Sum2.9918298 × 109
Variance28010354
MonotonicityNot monotonic
2024-04-18T07:58:47.392708image/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
 
0.5%
612847 26
 
0.5%
607826 24
 
0.5%
616807 24
 
0.5%
611803 23
 
0.5%
617818 22
 
0.4%
604813 22
 
0.4%
Other values (767) 4646
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%

소재지전체주소
Text

Distinct4356
Distinct (%)88.5%
Missing3
Missing (%)0.1%
Memory size38.6 KiB
2024-04-18T07:58:47.685352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length48
Mean length23.577204
Min length6

Characters and Unicode

Total characters116047
Distinct characters374
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

Unique3924 ?
Unique (%)79.7%

Sample

1st row부산광역시 영도구 동삼동 1123-7
2nd row부산광역시 금정구 서동 118-27번지
3rd row부산광역시 사상구 주례동 507-1번지
4th row부산광역시 사상구 엄궁동 266번지
5th row부산광역시 해운대구 우동 1417번지 부산유스호스텔아르피나
ValueCountFrequency (%)
부산광역시 4921
 
22.3%
t통b반 763
 
3.5%
부산진구 504
 
2.3%
사하구 498
 
2.3%
동래구 422
 
1.9%
북구 411
 
1.9%
해운대구 393
 
1.8%
금정구 384
 
1.7%
사상구 333
 
1.5%
연제구 329
 
1.5%
Other values (4751) 13111
59.4%
2024-04-18T07:58:48.138608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17151
 
14.8%
산 5837
 
5.0%
동 5787
 
5.0%
부 5784
 
5.0%
광 5092
 
4.4%
1 5061
 
4.4%
구 5055
 
4.4%
시 4949
 
4.3%
역 4927
 
4.2%
지 4676
 
4.0%
Other values (364) 51728
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68892
59.4%
Decimal Number 23431
 
20.2%
Space Separator 17151
 
14.8%
Dash Punctuation 4474
 
3.9%
Uppercase Letter 1573
 
1.4%
Open Punctuation 218
 
0.2%
Close Punctuation 217
 
0.2%
Other Punctuation 88
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 5837
 
8.5%
동 5787
 
8.4%
부 5784
 
8.4%
광 5092
 
7.4%
구 5055
 
7.3%
시 4949
 
7.2%
역 4927
 
7.2%
지 4676
 
6.8%
번 4477
 
6.5%
사 949
 
1.4%
Other values (331) 21359
31.0%
Uppercase Letter
ValueCountFrequency (%)
B 783
49.8%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
G 2
 
0.1%
F 2
 
0.1%
C 2
 
0.1%
S 1
 
0.1%
O 1
 
0.1%
P 1
 
0.1%
Other values (2) 2
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 5061
21.6%
2 3159
13.5%
3 2709
11.6%
4 2237
9.5%
5 2170
9.3%
6 1735
 
7.4%
0 1711
 
7.3%
8 1667
 
7.1%
7 1611
 
6.9%
9 1371
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 76
86.4%
@ 6
 
6.8%
/ 3
 
3.4%
. 2
 
2.3%
& 1
 
1.1%
Space Separator
ValueCountFrequency (%)
17151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4474
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 68890
59.4%
Common 45581
39.3%
Latin 1574
 
1.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5837
 
8.5%
동 5787
 
8.4%
부 5784
 
8.4%
광 5092
 
7.4%
구 5055
 
7.3%
시 4949
 
7.2%
역 4927
 
7.2%
지 4676
 
6.8%
번 4477
 
6.5%
사 949
 
1.4%
Other values (330) 21357
31.0%
Common
ValueCountFrequency (%)
17151
37.6%
1 5061
 
11.1%
- 4474
 
9.8%
2 3159
 
6.9%
3 2709
 
5.9%
4 2237
 
4.9%
5 2170
 
4.8%
6 1735
 
3.8%
0 1711
 
3.8%
8 1667
 
3.7%
Other values (10) 3507
 
7.7%
Latin
ValueCountFrequency (%)
B 783
49.7%
T 766
48.7%
A 10
 
0.6%
L 3
 
0.2%
G 2
 
0.1%
F 2
 
0.1%
C 2
 
0.1%
S 1
 
0.1%
O 1
 
0.1%
P 1
 
0.1%
Other values (3) 3
 
0.2%
Han
ValueCountFrequency (%)
內 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68890
59.4%
ASCII 47155
40.6%
CJK 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17151
36.4%
1 5061
 
10.7%
- 4474
 
9.5%
2 3159
 
6.7%
3 2709
 
5.7%
4 2237
 
4.7%
5 2170
 
4.6%
6 1735
 
3.7%
0 1711
 
3.6%
8 1667
 
3.5%
Other values (23) 5081
 
10.8%
Hangul
ValueCountFrequency (%)
산 5837
 
8.5%
동 5787
 
8.4%
부 5784
 
8.4%
광 5092
 
7.4%
구 5055
 
7.3%
시 4949
 
7.2%
역 4927
 
7.2%
지 4676
 
6.8%
번 4477
 
6.5%
사 949
 
1.4%
Other values (330) 21357
31.0%
CJK
ValueCountFrequency (%)
內 2
100.0%

도로명전체주소
Text

MISSING 

Distinct2241
Distinct (%)96.2%
Missing2596
Missing (%)52.7%
Memory size38.6 KiB
2024-04-18T07:58:48.484803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length54
Mean length28.709317
Min length17

Characters and Unicode

Total characters66864
Distinct characters396
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

Unique2161 ?
Unique (%)92.8%

Sample

1st row부산광역시 영도구 상리로 35 (동삼동)
2nd row부산광역시 금정구 금사로 58-12, 1층 (서동)
3rd row부산광역시 사상구 가야대로 290-4, 2층 (주례동)
4th row부산광역시 사상구 엄궁북로4번가길 17 (엄궁동, 진주식육점)
5th row부산광역시 해운대구 해운대해변로 35, 부산유스호스텔아르피나 지하1층 (우동)
ValueCountFrequency (%)
부산광역시 2329
 
17.9%
1층 286
 
2.2%
부산진구 269
 
2.1%
동래구 228
 
1.8%
사하구 213
 
1.6%
사상구 189
 
1.5%
금정구 187
 
1.4%
해운대구 181
 
1.4%
남구 164
 
1.3%
북구 153
 
1.2%
Other values (2647) 8793
67.7%
2024-04-18T07:58:48.938969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10667
 
16.0%
동 3019
 
4.5%
부 2842
 
4.3%
산 2804
 
4.2%
1 2528
 
3.8%
광 2442
 
3.7%
시 2439
 
3.6%
구 2416
 
3.6%
역 2333
 
3.5%
( 2296
 
3.4%
Other values (386) 33078
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39880
59.6%
Space Separator 10667
 
16.0%
Decimal Number 10196
 
15.2%
Open Punctuation 2296
 
3.4%
Close Punctuation 2296
 
3.4%
Other Punctuation 1060
 
1.6%
Dash Punctuation 429
 
0.6%
Uppercase Letter 37
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3019
 
7.6%
부 2842
 
7.1%
산 2804
 
7.0%
광 2442
 
6.1%
시 2439
 
6.1%
구 2416
 
6.1%
역 2333
 
5.9%
로 2247
 
5.6%
길 1272
 
3.2%
번 1206
 
3.0%
Other values (356) 16860
42.3%
Decimal Number
ValueCountFrequency (%)
1 2528
24.8%
2 1568
15.4%
3 1191
11.7%
4 876
 
8.6%
5 807
 
7.9%
0 722
 
7.1%
6 687
 
6.7%
7 652
 
6.4%
8 608
 
6.0%
9 557
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
B 19
51.4%
A 6
 
16.2%
T 6
 
16.2%
S 1
 
2.7%
E 1
 
2.7%
H 1
 
2.7%
L 1
 
2.7%
C 1
 
2.7%
F 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 1047
98.8%
@ 5
 
0.5%
/ 5
 
0.5%
. 2
 
0.2%
& 1
 
0.1%
Space Separator
ValueCountFrequency (%)
10667
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 429
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39880
59.6%
Common 26946
40.3%
Latin 38
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3019
 
7.6%
부 2842
 
7.1%
산 2804
 
7.0%
광 2442
 
6.1%
시 2439
 
6.1%
구 2416
 
6.1%
역 2333
 
5.9%
로 2247
 
5.6%
길 1272
 
3.2%
번 1206
 
3.0%
Other values (356) 16860
42.3%
Common
ValueCountFrequency (%)
10667
39.6%
1 2528
 
9.4%
( 2296
 
8.5%
) 2296
 
8.5%
2 1568
 
5.8%
3 1191
 
4.4%
, 1047
 
3.9%
4 876
 
3.3%
5 807
 
3.0%
0 722
 
2.7%
Other values (10) 2948
 
10.9%
Latin
ValueCountFrequency (%)
B 19
50.0%
A 6
 
15.8%
T 6
 
15.8%
S 1
 
2.6%
e 1
 
2.6%
E 1
 
2.6%
H 1
 
2.6%
L 1
 
2.6%
C 1
 
2.6%
F 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39880
59.6%
ASCII 26984
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10667
39.5%
1 2528
 
9.4%
( 2296
 
8.5%
) 2296
 
8.5%
2 1568
 
5.8%
3 1191
 
4.4%
, 1047
 
3.9%
4 876
 
3.2%
5 807
 
3.0%
0 722
 
2.7%
Other values (20) 2986
 
11.1%
Hangul
ValueCountFrequency (%)
동 3019
 
7.6%
부 2842
 
7.1%
산 2804
 
7.0%
광 2442
 
6.1%
시 2439
 
6.1%
구 2416
 
6.1%
역 2333
 
5.9%
로 2247
 
5.6%
길 1272
 
3.2%
번 1206
 
3.0%
Other values (356) 16860
42.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1156
Distinct (%)50.8%
Missing2649
Missing (%)53.8%
Infinite0
Infinite (%)0.0%
Mean47827.428
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:49.112889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46242
Q147008.75
median47802
Q348725.25
95-th percentile49407
Maximum49525
Range3523
Interquartile range (IQR)1716.5

Descriptive statistics

Standard deviation1010.9231
Coefficient of variation (CV)0.021136891
Kurtosis-1.1137455
Mean47827.428
Median Absolute Deviation (MAD)805
Skewness0.017265805
Sum1.0885523 × 108
Variance1021965.6
MonotonicityNot monotonic
2024-04-18T07:58:49.245603image/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%
48445 7
 
0.1%
47603 7
 
0.1%
49217 7
 
0.1%
46321 7
 
0.1%
48501 7
 
0.1%
48095 7
 
0.1%
Other values (1146) 2193
44.5%
(Missing) 2649
53.8%
ValueCountFrequency (%)
46002 3
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%

사업장명
Text

Distinct3339
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
2024-04-18T07:58:49.501069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length26
Mean length4.7707614
Min length1

Characters and Unicode

Total characters23496
Distinct characters569
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

Unique2659 ?
Unique (%)54.0%

Sample

1st row대광 이발
2nd row태후사랑
3rd row퀸즈헤나
4th row엄궁퀀즈헤나교실
5th row아르피나캇트
ValueCountFrequency (%)
이용원 369
 
6.5%
구내 53
 
0.9%
컷트실 50
 
0.9%
구내이용원 41
 
0.7%
현대 36
 
0.6%
우리 28
 
0.5%
제일 28
 
0.5%
블루클럽 24
 
0.4%
태후사랑 23
 
0.4%
구내이용 23
 
0.4%
Other values (3200) 5027
88.2%
2024-04-18T07:58:49.884030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 2096
 
8.9%
용 2021
 
8.6%
원 1935
 
8.2%
탕 977
 
4.2%
내 844
 
3.6%
778
 
3.3%
구 582
 
2.5%
성 473
 
2.0%
트 405
 
1.7%
대 387
 
1.6%
Other values (559) 12998
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22253
94.7%
Space Separator 778
 
3.3%
Uppercase Letter 146
 
0.6%
Lowercase Letter 125
 
0.5%
Open Punctuation 65
 
0.3%
Close Punctuation 65
 
0.3%
Decimal Number 36
 
0.2%
Other Punctuation 20
 
0.1%
Dash Punctuation 6
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 2096
 
9.4%
용 2021
 
9.1%
원 1935
 
8.7%
탕 977
 
4.4%
내 844
 
3.8%
구 582
 
2.6%
성 473
 
2.1%
트 405
 
1.8%
대 387
 
1.7%
수 344
 
1.5%
Other values (499) 12189
54.8%
Uppercase Letter
ValueCountFrequency (%)
B 19
13.0%
O 13
 
8.9%
H 11
 
7.5%
E 10
 
6.8%
R 10
 
6.8%
A 9
 
6.2%
S 9
 
6.2%
M 8
 
5.5%
L 7
 
4.8%
N 7
 
4.8%
Other values (12) 43
29.5%
Lowercase Letter
ValueCountFrequency (%)
r 17
13.6%
e 15
12.0%
b 11
8.8%
s 10
8.0%
a 10
8.0%
h 9
 
7.2%
o 9
 
7.2%
i 8
 
6.4%
u 6
 
4.8%
g 6
 
4.8%
Other values (8) 24
19.2%
Decimal Number
ValueCountFrequency (%)
2 12
33.3%
1 9
25.0%
8 8
22.2%
5 3
 
8.3%
9 2
 
5.6%
4 1
 
2.8%
3 1
 
2.8%
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 (%)
778
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22250
94.7%
Common 972
 
4.1%
Latin 271
 
1.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 2096
 
9.4%
용 2021
 
9.1%
원 1935
 
8.7%
탕 977
 
4.4%
내 844
 
3.8%
구 582
 
2.6%
성 473
 
2.1%
트 405
 
1.8%
대 387
 
1.7%
수 344
 
1.5%
Other values (496) 12186
54.8%
Latin
ValueCountFrequency (%)
B 19
 
7.0%
r 17
 
6.3%
e 15
 
5.5%
O 13
 
4.8%
b 11
 
4.1%
H 11
 
4.1%
E 10
 
3.7%
s 10
 
3.7%
a 10
 
3.7%
R 10
 
3.7%
Other values (30) 145
53.5%
Common
ValueCountFrequency (%)
778
80.0%
( 65
 
6.7%
) 65
 
6.7%
2 12
 
1.2%
. 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 (%)
男 1
33.3%
子 1
33.3%
秀 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22250
94.7%
ASCII 1242
 
5.3%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 2096
 
9.4%
용 2021
 
9.1%
원 1935
 
8.7%
탕 977
 
4.4%
내 844
 
3.8%
구 582
 
2.6%
성 473
 
2.1%
트 405
 
1.8%
대 387
 
1.7%
수 344
 
1.5%
Other values (496) 12186
54.8%
ASCII
ValueCountFrequency (%)
778
62.6%
( 65
 
5.2%
) 65
 
5.2%
B 19
 
1.5%
r 17
 
1.4%
e 15
 
1.2%
O 13
 
1.0%
2 12
 
1.0%
b 11
 
0.9%
H 11
 
0.9%
Other values (49) 236
 
19.0%
CJK
ValueCountFrequency (%)
男 1
33.3%
子 1
33.3%
秀 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

최종수정시점
Real number (ℝ)

Distinct3321
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0096776 × 1013
Minimum1.9990218 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:50.032644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990218 × 1013
5-th percentile1.9990644 × 1013
Q12.0031029 × 1013
median2.0080422 × 1013
Q32.0161216 × 1013
95-th percentile2.0201203 × 1013
Maximum2.021043 × 1013
Range2.2021217 × 1011
Interquartile range (IQR)1.3018716 × 1011

Descriptive statistics

Standard deviation6.9374195 × 1010
Coefficient of variation (CV)0.0034520062
Kurtosis-1.3684168
Mean2.0096776 × 1013
Median Absolute Deviation (MAD)5.0102104 × 1010
Skewness0.26008393
Sum9.8976621 × 1016
Variance4.812779 × 1021
MonotonicityNot monotonic
2024-04-18T07:58:50.178197image/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%
19990428000000 35
 
0.7%
20020423000000 34
 
0.7%
20030318000000 33
 
0.7%
20030221000000 33
 
0.7%
20030616000000 31
 
0.6%
Other values (3311) 4540
92.2%
ValueCountFrequency (%)
19990218000000 1
 
< 0.1%
19990223000000 4
 
0.1%
19990224000000 1
 
< 0.1%
19990225000000 3
 
0.1%
19990302000000 10
0.2%
19990303000000 11
0.2%
19990304000000 20
0.4%
19990308000000 15
0.3%
19990309000000 5
 
0.1%
19990310000000 18
0.4%
ValueCountFrequency (%)
20210430170045 1
< 0.1%
20210430164517 1
< 0.1%
20210430160002 1
< 0.1%
20210430145935 1
< 0.1%
20210430141746 1
< 0.1%
20210430100719 1
< 0.1%
20210427114235 1
< 0.1%
20210427112748 1
< 0.1%
20210427102711 1
< 0.1%
20210422155504 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
I
4072 
U
853 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 4072
82.7%
U 853
 
17.3%

Length

2024-04-18T07:58:50.314523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:50.421378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 4072
82.7%
u 853
 
17.3%

데이터갱신일자
Date

Distinct412
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 02:40:00
2024-04-18T07:58:50.521687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:58:50.662408image/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 size38.6 KiB
일반이용업
4861 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079188
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4861
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:58:50.783583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:50.895829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4861
97.9%
이용업 40
 
0.8%
기타 40
 
0.8%
일반미용업 23
 
0.5%
na 1
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct3545
Distinct (%)78.1%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean387476.01
Minimum365567.31
Maximum407739.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:51.001530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum365567.31
5-th percentile379536.02
Q1383509.99
median387767.42
Q3390952.27
95-th percentile396565.19
Maximum407739.05
Range42171.732
Interquartile range (IQR)7442.2885

Descriptive statistics

Standard deviation5365.5344
Coefficient of variation (CV)0.013847398
Kurtosis0.59379419
Mean387476.01
Median Absolute Deviation (MAD)3664.9009
Skewness0.11356856
Sum1.7583662 × 109
Variance28788960
MonotonicityNot monotonic
2024-04-18T07:58:51.123207image/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%
382223.343951843 5
 
0.1%
392251.396025486 5
 
0.1%
390057.531834683 5
 
0.1%
390388.167285664 5
 
0.1%
Other values (3535) 4479
90.9%
(Missing) 387
 
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 

Distinct3546
Distinct (%)78.1%
Missing387
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean186851.77
Minimum171356.38
Maximum206164.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:51.860662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum171356.38
5-th percentile178124.77
Q1181996.4
median187062.88
Q3191094.56
95-th percentile195809.02
Maximum206164.58
Range34808.197
Interquartile range (IQR)9098.1566

Descriptive statistics

Standard deviation5704.1947
Coefficient of variation (CV)0.030527914
Kurtosis-0.31704012
Mean186851.77
Median Absolute Deviation (MAD)4356.077
Skewness0.13463203
Sum8.4793331 × 108
Variance32537838
MonotonicityNot monotonic
2024-04-18T07:58:51.983649image/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%
191452.16648903 6
 
0.1%
190804.667916156 6
 
0.1%
189006.221241803 6
 
0.1%
187062.880208457 5
 
0.1%
196950.450593302 5
 
0.1%
190370.669695795 5
 
0.1%
180078.851352476 5
 
0.1%
Other values (3536) 4479
90.9%
(Missing) 387
 
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 size38.6 KiB
일반이용업
4861 
이용업 기타
 
40
일반미용업
 
23
<NA>
 
1

Length

Max length6
Median length5
Mean length5.0079188
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반이용업 4861
98.7%
이용업 기타 40
 
0.8%
일반미용업 23
 
0.5%
<NA> 1
 
< 0.1%

Length

2024-04-18T07:58:52.122084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:52.223749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반이용업 4861
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%
Missing1728
Missing (%)35.1%
Infinite0
Infinite (%)0.0%
Mean2.5060995
Minimum0
Maximum42
Zeros1210
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:52.321102image/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 deviation3.3290136
Coefficient of variation (CV)1.3283645
Kurtosis29.245259
Mean2.5060995
Median Absolute Deviation (MAD)2
Skewness3.9684712
Sum8012
Variance11.082331
MonotonicityNot monotonic
2024-04-18T07:58:52.441430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 1210
24.6%
3 480
 
9.7%
4 420
 
8.5%
2 408
 
8.3%
5 234
 
4.8%
1 167
 
3.4%
6 88
 
1.8%
7 53
 
1.1%
8 28
 
0.6%
9 25
 
0.5%
Other values (22) 84
 
1.7%
(Missing) 1728
35.1%
ValueCountFrequency (%)
0 1210
24.6%
1 167
 
3.4%
2 408
 
8.3%
3 480
 
9.7%
4 420
 
8.5%
5 234
 
4.8%
6 88
 
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%
Missing2230
Missing (%)45.3%
Infinite0
Infinite (%)0.0%
Mean0.52541744
Minimum0
Maximum208
Zeros1724
Zeros (%)35.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:52.550035image/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 deviation4.0748385
Coefficient of variation (CV)7.7554307
Kurtosis2497.3474
Mean0.52541744
Median Absolute Deviation (MAD)0
Skewness49.06493
Sum1416
Variance16.604309
MonotonicityNot monotonic
2024-04-18T07:58:52.666498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 1724
35.0%
1 839
 
17.0%
2 84
 
1.7%
3 22
 
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) 2230
45.3%
ValueCountFrequency (%)
0 1724
35.0%
1 839
17.0%
2 84
 
1.7%
3 22
 
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 22
 
0.4%
2 84
 
1.7%
1 839
17.0%
0 1724
35.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.5%
Missing2100
Missing (%)42.6%
Infinite0
Infinite (%)0.0%
Mean1.2584071
Minimum0
Maximum12
Zeros1004
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:52.782705image/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 deviation1.4050903
Coefficient of variation (CV)1.1165626
Kurtosis5.985506
Mean1.2584071
Median Absolute Deviation (MAD)1
Skewness1.8426782
Sum3555
Variance1.9742786
MonotonicityNot monotonic
2024-04-18T07:58:52.894920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1004
20.4%
1 877
17.8%
2 511
 
10.4%
3 251
 
5.1%
4 90
 
1.8%
5 56
 
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) 2100
42.6%
ValueCountFrequency (%)
0 1004
20.4%
1 877
17.8%
2 511
10.4%
3 251
 
5.1%
4 90
 
1.8%
5 56
 
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 56
 
1.1%
4 90
 
1.8%
3 251
5.1%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.5%
Missing2728
Missing (%)55.4%
Infinite0
Infinite (%)0.0%
Mean1.4132909
Minimum0
Maximum10
Zeros591
Zeros (%)12.0%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:53.003803image/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 deviation1.3574882
Coefficient of variation (CV)0.96051577
Kurtosis3.9714977
Mean1.4132909
Median Absolute Deviation (MAD)1
Skewness1.5176534
Sum3105
Variance1.8427741
MonotonicityNot monotonic
2024-04-18T07:58:53.116213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 759
 
15.4%
0 591
 
12.0%
2 478
 
9.7%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
0.9%
6 15
 
0.3%
7 7
 
0.1%
10 3
 
0.1%
8 2
 
< 0.1%
(Missing) 2728
55.4%
ValueCountFrequency (%)
0 591
12.0%
1 759
15.4%
2 478
9.7%
3 214
 
4.3%
4 81
 
1.6%
5 46
 
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 46
 
0.9%
4 81
 
1.6%
3 214
 
4.3%
2 478
9.7%
1 759
15.4%

사용시작지하층
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3069 
0
1529 
1
313 
2
 
13
22
 
1

Length

Max length4
Median length4
Mean length2.8696447
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row<NA>
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
<NA> 3069
62.3%
0 1529
31.0%
1 313
 
6.4%
2 13
 
0.3%
22 1
 
< 0.1%

Length

2024-04-18T07:58:53.234079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:53.327811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3069
62.3%
0 1529
31.0%
1 313
 
6.4%
2 13
 
0.3%
22 1
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3720 
0
934 
1
 
264
2
 
6
4
 
1

Length

Max length4
Median length4
Mean length3.2659898
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3720
75.5%
0 934
 
19.0%
1 264
 
5.4%
2 6
 
0.1%
4 1
 
< 0.1%

Length

2024-04-18T07:58:53.435373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:53.531620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3720
75.5%
0 934
 
19.0%
1 264
 
5.4%
2 6
 
0.1%
4 1
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2702 
0
2223 

Length

Max length4
Median length4
Mean length2.6458883
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2702
54.9%
0 2223
45.1%

Length

2024-04-18T07:58:53.636621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:53.724428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2702
54.9%
0 2223
45.1%

양실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2701 
0
2223 
38
 
1

Length

Max length4
Median length4
Mean length2.6454822
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2701
54.8%
0 2223
45.1%
38 1
 
< 0.1%

Length

2024-04-18T07:58:53.824355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:53.922798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2701
54.8%
0 2223
45.1%
38 1
 
< 0.1%

욕실수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
2701 
0
2223 
2
 
1

Length

Max length4
Median length4
Mean length2.6452792
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2701
54.8%
0 2223
45.1%
2 1
 
< 0.1%

Length

2024-04-18T07:58:54.021121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:54.111553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2701
54.8%
0 2223
45.1%
2 1
 
< 0.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing100
Missing (%)2.0%
Memory size9.7 KiB
False
4825 
(Missing)
 
100
ValueCountFrequency (%)
False 4825
98.0%
(Missing) 100
 
2.0%
2024-04-18T07:58:54.180283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.4%
Missing607
Missing (%)12.3%
Infinite0
Infinite (%)0.0%
Mean3.1296897
Minimum0
Maximum24
Zeros338
Zeros (%)6.9%
Negative0
Negative (%)0.0%
Memory size43.4 KiB
2024-04-18T07:58:54.258688image/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 deviation2.1266029
Coefficient of variation (CV)0.67949323
Kurtosis3.3856783
Mean3.1296897
Median Absolute Deviation (MAD)1
Skewness1.280521
Sum13514
Variance4.5224401
MonotonicityNot monotonic
2024-04-18T07:58:54.363555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
2 1347
27.4%
3 884
17.9%
4 584
11.9%
0 338
 
6.9%
1 337
 
6.8%
5 263
 
5.3%
6 178
 
3.6%
7 168
 
3.4%
8 111
 
2.3%
9 66
 
1.3%
Other values (6) 42
 
0.9%
(Missing) 607
12.3%
ValueCountFrequency (%)
0 338
 
6.9%
1 337
 
6.8%
2 1347
27.4%
3 884
17.9%
4 584
11.9%
5 263
 
5.3%
6 178
 
3.6%
7 168
 
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%
7 168
3.4%
6 178
3.6%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing4924
Missing (%)> 99.9%
Memory size38.6 KiB
2024-04-18T07:58:54.476653image/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%
2024-04-18T07:58:54.717676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 1
20.0%
설 1
20.0%
건 1
20.0%
축 1
20.0%
물 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 1
20.0%
설 1
20.0%
건 1
20.0%
축 1
20.0%
물 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 1
20.0%
설 1
20.0%
건 1
20.0%
축 1
20.0%
물 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 1
20.0%
설 1
20.0%
건 1
20.0%
축 1
20.0%
물 1
20.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4923 
20050414
 
1
20050520
 
1

Length

Max length8
Median length4
Mean length4.0016244
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> 4923
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

Length

2024-04-18T07:58:54.839666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:54.942477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4923
> 99.9%
20050414 1
 
< 0.1%
20050520 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4923 
20050414
 
1
20060425
 
1

Length

Max length8
Median length4
Mean length4.0016244
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> 4923
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

Length

2024-04-18T07:58:55.050290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:55.146385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4923
> 99.9%
20050414 1
 
< 0.1%
20060425 1
 
< 0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3960 
임대
937 
자가
 
28

Length

Max length4
Median length4
Mean length3.6081218
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> 3960
80.4%
임대 937
 
19.0%
자가 28
 
0.6%

Length

2024-04-18T07:58:55.269312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:55.371067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3960
80.4%
임대 937
 
19.0%
자가 28
 
0.6%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3360 
0
1565 

Length

Max length4
Median length4
Mean length3.0467005
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3360
68.2%
0 1565
31.8%

Length

2024-04-18T07:58:55.468115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:55.556939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3360
68.2%
0 1565
31.8%

여성종사자수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4557 
0
 
351
1
 
17

Length

Max length4
Median length4
Mean length3.7758376
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4557
92.5%
0 351
 
7.1%
1 17
 
0.3%

Length

2024-04-18T07:58:55.648278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:55.736428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4557
92.5%
0 351
 
7.1%
1 17
 
0.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
4546 
0
 
345
1
 
33
2
 
1

Length

Max length4
Median length4
Mean length3.7691371
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4546
92.3%
0 345
 
7.0%
1 33
 
0.7%
2 1
 
< 0.1%

Length

2024-04-18T07:58:55.831199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:55.928283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4546
92.3%
0 345
 
7.0%
1 33
 
0.7%
2 1
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3542 
0
1383 

Length

Max length4
Median length4
Mean length3.1575635
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3542
71.9%
0 1383
 
28.1%

Length

2024-04-18T07:58:56.024673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:56.120675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3542
71.9%
0 1383
 
28.1%

침대수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
<NA>
3560 
0
1357 
2
 
4
3
 
2
1
 
1

Length

Max length4
Median length4
Mean length3.1685279
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3560
72.3%
0 1357
 
27.6%
2 4
 
0.1%
3 2
 
< 0.1%
1 1
 
< 0.1%
5 1
 
< 0.1%

Length

2024-04-18T07:58:56.217454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:58:56.312814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3560
72.3%
0 1357
 
27.6%
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
4925 
ValueCountFrequency (%)
False 4925
100.0%
2024-04-18T07:58:56.388666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4925
Missing (%)100.0%
Memory size43.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
01이용업05_19_01_P32800003280000-203-2018-0000320181102<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.12606080부산광역시 영도구 동삼동 1123-7부산광역시 영도구 상리로 35 (동삼동)49089대광 이발20201217113628U2020-12-19 02:40:00.0일반이용업388546.159102178137.194669일반이용업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
12이용업05_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>
23이용업05_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>
34이용업05_19_01_P33900003390000-203-2019-0000320190123<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.91617829부산광역시 사상구 엄궁동 266번지부산광역시 사상구 엄궁북로4번가길 17 (엄궁동, 진주식육점)47041엄궁퀀즈헤나교실20190130162256U2019-02-01 02:40:00.0이용업 기타379535.304649182741.485999이용업 기타001100000N1<NA><NA><NA><NA>00000N<NA>
45이용업05_19_01_P33300003330000-203-2019-0000120190121<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.70612894부산광역시 해운대구 우동 1417번지 부산유스호스텔아르피나부산광역시 해운대구 해운대해변로 35, 부산유스호스텔아르피나 지하1층 (우동)48089아르피나캇트20190121155039I2019-01-23 02:20:58.0일반이용업394725.789471187180.759947일반이용업00<NA><NA>1<NA>000N2<NA><NA><NA><NA>00000N<NA>
56이용업05_19_01_P34000003400000-203-2019-0000220190123<NA>1영업/정상1영업<NA><NA><NA><NA>051 727 532013.20<NA>부산광역시 기장군 정관읍 매학리 719-1번지 미래안 전통상가 A동 114호부산광역시 기장군 정관읍 정관6로 5-20, 미래안 전통상가 A동 114호46017엘샤론코리아20190131112246U2019-02-02 02:40:00.0일반이용업397757.734001204518.87912일반이용업001100000N2<NA><NA><NA><NA>00000N<NA>
67이용업05_19_01_P32800003280000-203-2019-0000220190115<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00606808부산광역시 영도구 동삼동 363-38 삼창파크맨션부산광역시 영도구 절영로 555, 201호 (동삼동, 삼창파크맨션)49108퀸즈헤나 영도점20201127125900U2020-11-29 02:40:00.0일반이용업388935.667814177113.452142일반이용업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
78이용업05_19_01_P33600003360000-203-2019-0000220190124<NA>1영업/정상1영업<NA><NA><NA><NA><NA>16.42618814부산광역시 강서구 명지동 3241번지 엘크루 블루오션 근린생활시설(C3)동 B101호부산광역시 강서구 명지오션시티12로 92, 근린생활시설(C3)동 B101호 (명지동, 엘크루 블루오션)46764퀸즈헤나20190219103615U2019-02-21 02:40:00.0이용업 기타373744.11244177424.186311이용업 기타00<NA><NA><NA><NA>000N2<NA><NA><NA><NA>00000N<NA>
89이용업05_19_01_P34000003400000-203-2019-0000120190114<NA>1영업/정상1영업<NA><NA><NA><NA>051 728 398843.00<NA>부산광역시 기장군 정관읍 방곡리 388-3번지부산광역시 기장군 정관읍 방곡2로 5, 103호46019엘샤론20190114142249I2019-01-16 02:20:50.0일반이용업398995.470988205097.400941일반이용업0011<NA><NA>000N3<NA><NA><NA><NA>00000N<NA>
910이용업05_19_01_P32800003280000-203-2019-0000120190110<NA>1영업/정상1영업<NA><NA><NA><NA><NA>37.23606820부산광역시 영도구 청학동 442-22번지부산광역시 영도구 청학남로 1, 2층 (청학동)49018해사이용원20190319111024U2019-03-21 02:40:00.0일반이용업387596.675809178741.589481일반이용업000000000N0<NA><NA><NA><NA>0<NA><NA>00N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
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49164917이용업05_19_01_P34000003400000-203-2005-0000420050729<NA>3폐업2폐업20060731<NA><NA><NA><NA>.00619906부산광역시 기장군 기장읍 청강리 18-2번지<NA><NA>현대이용원20050729000000I2018-08-31 23:59:59.0일반이용업401993.248159196177.299277일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
49174918이용업05_19_01_P34000003400000-203-2004-0000420040906<NA>3폐업2폐업20050905<NA><NA><NA><NA>9.45619903부산광역시 기장군 기장읍 대라리 59-11번지<NA><NA>석천캇트실20040906000000I2018-08-31 23:59:59.0일반이용업401657.28385196059.658422일반이용업413<NA><NA><NA><NA><NA><NA>N2<NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
49184919이용업05_19_01_P34000003400000-203-1996-0034619960320<NA>3폐업2폐업20090618<NA><NA><NA>051 7204230.00619913부산광역시 기장군 일광면 이천리 345번지 T통B반<NA><NA>한국유리 구내 이용원20030410000000I2018-08-31 23:59:59.0일반이용업<NA><NA>일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
49194920이용업05_19_01_P34000003400000-203-2003-0001420030331<NA>3폐업2폐업20030822<NA><NA><NA>051 722969636.31619906부산광역시 기장군 기장읍 청강리 290-2번지<NA><NA>혜성이용원20031229000000I2018-08-31 23:59:59.0일반이용업401937.500075195496.790451일반이용업1<NA>11<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
49204921이용업05_19_01_P34000003400000-203-1999-0012019990727<NA>3폐업2폐업20110920<NA><NA><NA>051 722391543.60619901부산광역시 기장군 기장읍 교리 348-12번지<NA><NA>교리이용원20100315131009I2018-08-31 23:59:59.0일반이용업401641.046222196906.772649일반이용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N6<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
49214922이용업05_19_01_P34000003400000-203-2010-0000320101005<NA>3폐업2폐업20111018<NA><NA><NA>070 5146656615.00619952부산광역시 기장군 장안읍 길천리 265번지 길천해수탕<NA><NA>길천해수탕이용원20101005114647I2018-08-31 23:59:59.0이용업 기타407739.046711205671.367299이용업 기타4133<NA><NA>000N2<NA><NA><NA>임대0<NA><NA>00N<NA>
49224923이용업05_19_01_P33000003300000-203-2018-0000720181218<NA>3폐업2폐업20201214<NA><NA><NA><NA>23.13607833부산광역시 동래구 온천동 210-47부산광역시 동래구 금강공원로 25-1, 2층 (온천동)47712아:스타헤어샵20201214102819U2020-12-16 02:40:00.0일반이용업389468.057399193064.168736일반이용업302200000N4<NA><NA><NA><NA>0<NA><NA>00N<NA>
49234924이용업05_19_01_P32900003290000-203-2020-0001420201215<NA>3폐업2폐업20201229<NA><NA><NA><NA>5.00614814부산광역시 부산진구 개금동 540-253부산광역시 부산진구 엄광로 60, 2층 (개금동)47388용정탕 구내 이용원20201229141308U2020-12-31 02:40:00.0일반이용업384250.731933185068.767351일반이용업00<NA><NA><NA><NA>000N1<NA><NA><NA><NA>00000N<NA>
49244925이용업05_19_01_P32800003280000-203-2021-0000120210129<NA>3폐업2폐업20210225<NA><NA><NA><NA>66.00606042부산광역시 영도구 영선동2가 44-2부산광역시 영도구 영선대로 67 (영선동2가)49056긱스(geeks)20210225131906U2021-02-27 02:40:00.0일반이용업386100.884001178372.437035일반이용업0011<NA><NA>000N4<NA><NA><NA><NA>00000N<NA>