Overview

Dataset statistics

Number of variables51
Number of observations10000
Missing cells109914
Missing cells (%)21.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 MiB
Average record size in memory449.0 B

Variable types

Numeric17
Categorical19
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123088

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
발한실여부 has constant value ""Constant
업태구분명 is highly imbalanced (50.3%)Imbalance
사용시작지하층 is highly imbalanced (52.5%)Imbalance
사용끝지하층 is highly imbalanced (57.2%)Imbalance
조건부허가시작일자 is highly imbalanced (99.7%)Imbalance
남성종사자수 is highly imbalanced (59.8%)Imbalance
다중이용업소여부 is highly imbalanced (99.7%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 4947 (49.5%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
소재지전화 has 3000 (30.0%) missing valuesMissing
소재지우편번호 has 109 (1.1%) missing valuesMissing
도로명전체주소 has 2991 (29.9%) missing valuesMissing
도로명우편번호 has 3065 (30.6%) missing valuesMissing
좌표정보(x) has 278 (2.8%) missing valuesMissing
좌표정보(y) has 278 (2.8%) missing valuesMissing
건물지상층수 has 2085 (20.8%) missing valuesMissing
건물지하층수 has 2981 (29.8%) missing valuesMissing
사용시작지상층 has 2678 (26.8%) missing valuesMissing
사용끝지상층 has 4149 (41.5%) missing valuesMissing
발한실여부 has 152 (1.5%) missing valuesMissing
의자수 has 786 (7.9%) missing valuesMissing
조건부허가신고사유 has 9995 (> 99.9%) missing valuesMissing
조건부허가종료일자 has 9992 (99.9%) missing valuesMissing
여성종사자수 has 7631 (76.3%) missing valuesMissing
침대수 has 4732 (47.3%) missing valuesMissing
Unnamed: 50 has 10000 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -33.66524071)Skewed
사용시작지상층 is highly skewed (γ1 = 70.0164244)Skewed
사용끝지상층 is highly skewed (γ1 = 66.33236571)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 2898 (29.0%) zerosZeros
건물지하층수 has 5182 (51.8%) zerosZeros
사용시작지상층 has 1493 (14.9%) zerosZeros
사용끝지상층 has 1027 (10.3%) zerosZeros
의자수 has 1385 (13.9%) zerosZeros
여성종사자수 has 2237 (22.4%) zerosZeros
침대수 has 3527 (35.3%) zerosZeros

Reproduction

Analysis started2024-04-17 03:27:17.581478
Analysis finished2024-04-17 03:27:19.536039
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11510.302
Minimum4
Maximum23132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:19.589916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile1168.9
Q15719.5
median11486
Q317332.25
95-th percentile21931.1
Maximum23132
Range23128
Interquartile range (IQR)11612.75

Descriptive statistics

Standard deviation6692.5035
Coefficient of variation (CV)0.58143596
Kurtosis-1.2125914
Mean11510.302
Median Absolute Deviation (MAD)5802
Skewness0.017449781
Sum1.1510302 × 108
Variance44789603
MonotonicityNot monotonic
2024-04-17T12:27:19.690826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16776 1
 
< 0.1%
18224 1
 
< 0.1%
2607 1
 
< 0.1%
21089 1
 
< 0.1%
468 1
 
< 0.1%
13418 1
 
< 0.1%
846 1
 
< 0.1%
21554 1
 
< 0.1%
9426 1
 
< 0.1%
14802 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
4 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
19 1
< 0.1%
23 1
< 0.1%
24 1
< 0.1%
ValueCountFrequency (%)
23132 1
< 0.1%
23129 1
< 0.1%
23128 1
< 0.1%
23127 1
< 0.1%
23126 1
< 0.1%
23125 1
< 0.1%
23122 1
< 0.1%
23119 1
< 0.1%
23118 1
< 0.1%
23117 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
미용업
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 10000
100.0%

Length

2024-04-17T12:27:19.784499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:19.849677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미용업 10000
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
05_18_01_P
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05_18_01_P
2nd row05_18_01_P
3rd row05_18_01_P
4th row05_18_01_P
5th row05_18_01_P

Common Values

ValueCountFrequency (%)
05_18_01_P 10000
100.0%

Length

2024-04-17T12:27:19.920688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:19.987964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05_18_01_p 10000
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3324859
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:20.053126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation37747.882
Coefficient of variation (CV)0.011353228
Kurtosis-0.74902868
Mean3324859
Median Absolute Deviation (MAD)30000
Skewness0.052300598
Sum3.324859 × 1010
Variance1.4249026 × 109
MonotonicityNot monotonic
2024-04-17T12:27:20.159664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1259
12.6%
3290000 1243
12.4%
3340000 968
9.7%
3300000 928
9.3%
3310000 774
7.7%
3350000 753
7.5%
3370000 730
7.3%
3320000 692
6.9%
3380000 687
6.9%
3390000 411
 
4.1%
Other values (6) 1555
15.6%
ValueCountFrequency (%)
3250000 343
 
3.4%
3260000 292
 
2.9%
3270000 304
 
3.0%
3280000 307
 
3.1%
3290000 1243
12.4%
3300000 928
9.3%
3310000 774
7.7%
3320000 692
6.9%
3330000 1259
12.6%
3340000 968
9.7%
ValueCountFrequency (%)
3400000 195
 
1.9%
3390000 411
 
4.1%
3380000 687
6.9%
3370000 730
7.3%
3360000 114
 
1.1%
3350000 753
7.5%
3340000 968
9.7%
3330000 1259
12.6%
3320000 692
6.9%
3310000 774
7.7%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T12:27:20.339451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3320000-204-2002-00019
2nd row3310000-204-2005-00018
3rd row3370000-212-2018-00007
4th row3330000-211-1999-00001
5th row3340000-211-2014-00038
ValueCountFrequency (%)
3320000-204-2002-00019 1
 
< 0.1%
3390000-212-2009-00005 1
 
< 0.1%
3380000-218-2011-00001 1
 
< 0.1%
3310000-217-2018-00001 1
 
< 0.1%
3340000-211-2010-00004 1
 
< 0.1%
3330000-204-2001-00958 1
 
< 0.1%
3330000-213-2017-00019 1
 
< 0.1%
3370000-211-1989-00001 1
 
< 0.1%
3360000-221-2019-00001 1
 
< 0.1%
3370000-204-2005-00034 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T12:27:20.597957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87763
39.9%
- 30000
 
13.6%
2 26094
 
11.9%
1 22144
 
10.1%
3 22067
 
10.0%
9 8716
 
4.0%
4 7927
 
3.6%
8 4408
 
2.0%
5 4224
 
1.9%
7 3637
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87763
46.2%
2 26094
 
13.7%
1 22144
 
11.7%
3 22067
 
11.6%
9 8716
 
4.6%
4 7927
 
4.2%
8 4408
 
2.3%
5 4224
 
2.2%
7 3637
 
1.9%
6 3020
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87763
39.9%
- 30000
 
13.6%
2 26094
 
11.9%
1 22144
 
10.1%
3 22067
 
10.0%
9 8716
 
4.0%
4 7927
 
3.6%
8 4408
 
2.0%
5 4224
 
1.9%
7 3637
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87763
39.9%
- 30000
 
13.6%
2 26094
 
11.9%
1 22144
 
10.1%
3 22067
 
10.0%
9 8716
 
4.0%
4 7927
 
3.6%
8 4408
 
2.0%
5 4224
 
1.9%
7 3637
 
1.7%

인허가일자
Real number (ℝ)

SKEWED 

Distinct5729
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20052369
Minimum9890627
Maximum20210128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:20.716025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9890627
5-th percentile19840503
Q119980904
median20080418
Q320150820
95-th percentile20191018
Maximum20210128
Range10319501
Interquartile range (IQR)169915.75

Descriptive statistics

Standard deviation183598.95
Coefficient of variation (CV)0.0091559728
Kurtosis1842.8707
Mean20052369
Median Absolute Deviation (MAD)80106
Skewness-33.665241
Sum2.0052369 × 1011
Variance3.3708573 × 1010
MonotonicityNot monotonic
2024-04-17T12:27:20.823817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000712 26
 
0.3%
20030225 14
 
0.1%
20000415 14
 
0.1%
20001114 11
 
0.1%
20030224 11
 
0.1%
20020122 9
 
0.1%
20160415 8
 
0.1%
20130103 8
 
0.1%
20180115 8
 
0.1%
19980709 8
 
0.1%
Other values (5719) 9883
98.8%
ValueCountFrequency (%)
9890627 1
< 0.1%
9980406 1
< 0.1%
19330331 1
< 0.1%
19630130 1
< 0.1%
19630420 1
< 0.1%
19630520 1
< 0.1%
19650113 1
< 0.1%
19650426 1
< 0.1%
19650609 1
< 0.1%
19660107 1
< 0.1%
ValueCountFrequency (%)
20210128 2
< 0.1%
20210125 2
< 0.1%
20210122 1
 
< 0.1%
20210121 1
 
< 0.1%
20210120 3
< 0.1%
20210119 1
 
< 0.1%
20210115 3
< 0.1%
20210114 3
< 0.1%
20210112 2
< 0.1%
20210111 2
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

영업상태구분코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
5053 
1
4947 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
3 5053
50.5%
1 4947
49.5%

Length

2024-04-17T12:27:20.915545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:20.982510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5053
50.5%
1 4947
49.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5053 
영업/정상
4947 

Length

Max length5
Median length2
Mean length3.4841
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5053
50.5%
영업/정상 4947
49.5%

Length

2024-04-17T12:27:21.058815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:21.134837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5053
50.5%
영업/정상 4947
49.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5053 
1
4947 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 5053
50.5%
1 4947
49.5%

Length

2024-04-17T12:27:21.214991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:21.283996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5053
50.5%
1 4947
49.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5053 
영업
4947 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5053
50.5%
영업 4947
49.5%

Length

2024-04-17T12:27:21.355198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:21.434470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5053
50.5%
영업 4947
49.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct2883
Distinct (%)57.1%
Missing4947
Missing (%)49.5%
Infinite0
Infinite (%)0.0%
Mean20096241
Minimum19851118
Maximum20210121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:21.514919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19851118
5-th percentile19990820
Q120040513
median20091109
Q320160315
95-th percentile20200123
Maximum20210121
Range359003
Interquartile range (IQR)119802

Descriptive statistics

Standard deviation66608.184
Coefficient of variation (CV)0.0033144598
Kurtosis-1.1625384
Mean20096241
Median Absolute Deviation (MAD)59898
Skewness-0.030132136
Sum1.0154631 × 1011
Variance4.4366501 × 109
MonotonicityNot monotonic
2024-04-17T12:27:21.626238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030227 160
 
1.6%
20050117 64
 
0.6%
20030226 49
 
0.5%
20050510 40
 
0.4%
20000712 31
 
0.3%
20010321 26
 
0.3%
20030101 21
 
0.2%
20021217 21
 
0.2%
20030606 20
 
0.2%
20000531 17
 
0.2%
Other values (2873) 4604
46.0%
(Missing) 4947
49.5%
ValueCountFrequency (%)
19851118 1
< 0.1%
19910430 1
< 0.1%
19911029 1
< 0.1%
19921012 1
< 0.1%
19921210 1
< 0.1%
19930806 1
< 0.1%
19930909 1
< 0.1%
19930924 1
< 0.1%
19940623 1
< 0.1%
19940711 1
< 0.1%
ValueCountFrequency (%)
20210121 1
 
< 0.1%
20210120 3
< 0.1%
20210118 1
 
< 0.1%
20210115 1
 
< 0.1%
20210112 1
 
< 0.1%
20210106 2
< 0.1%
20210104 1
 
< 0.1%
20201231 3
< 0.1%
20201228 2
< 0.1%
20201224 2
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지전화
Text

MISSING 

Distinct6237
Distinct (%)89.1%
Missing3000
Missing (%)30.0%
Memory size156.2 KiB
2024-04-17T12:27:21.916783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.665286
Min length3

Characters and Unicode

Total characters74657
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

Unique6042 ?
Unique (%)86.3%

Sample

1st row051 3384949
2nd row051 6221318
3rd row051 781 4321
4th row051 206 9007
5th row051 7810535
ValueCountFrequency (%)
051 6527
41.7%
070 137
 
0.9%
808 31
 
0.2%
852 30
 
0.2%
868 28
 
0.2%
746 27
 
0.2%
727 27
 
0.2%
747 26
 
0.2%
867 26
 
0.2%
611 24
 
0.2%
Other values (6205) 8780
56.1%
2024-04-17T12:27:22.299046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12352
16.5%
0 11257
15.1%
1 11009
14.7%
8714
11.7%
2 5800
7.8%
7 4755
 
6.4%
3 4679
 
6.3%
6 4475
 
6.0%
8 4385
 
5.9%
4 4290
 
5.7%
Other values (2) 2941
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65941
88.3%
Space Separator 8714
 
11.7%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 12352
18.7%
0 11257
17.1%
1 11009
16.7%
2 5800
8.8%
7 4755
 
7.2%
3 4679
 
7.1%
6 4475
 
6.8%
8 4385
 
6.6%
4 4290
 
6.5%
9 2939
 
4.5%
Space Separator
ValueCountFrequency (%)
8714
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74657
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 12352
16.5%
0 11257
15.1%
1 11009
14.7%
8714
11.7%
2 5800
7.8%
7 4755
 
6.4%
3 4679
 
6.3%
6 4475
 
6.0%
8 4385
 
5.9%
4 4290
 
5.7%
Other values (2) 2941
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 12352
16.5%
0 11257
15.1%
1 11009
14.7%
8714
11.7%
2 5800
7.8%
7 4755
 
6.4%
3 4679
 
6.3%
6 4475
 
6.0%
8 4385
 
5.9%
4 4290
 
5.7%
Other values (2) 2941
 
3.9%

소재지면적
Text

Distinct4052
Distinct (%)40.7%
Missing49
Missing (%)0.5%
Memory size156.2 KiB
2024-04-17T12:27:22.619081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9145814
Min length3

Characters and Unicode

Total characters48905
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

Unique2521 ?
Unique (%)25.3%

Sample

1st row13.20
2nd row54.33
3rd row38.40
4th row52.90
5th row42.84
ValueCountFrequency (%)
00 758
 
7.6%
33.00 115
 
1.2%
30.00 52
 
0.5%
20.00 52
 
0.5%
24.00 50
 
0.5%
26.40 47
 
0.5%
27.00 46
 
0.5%
18.00 44
 
0.4%
23.00 43
 
0.4%
16.50 42
 
0.4%
Other values (4042) 8702
87.4%
2024-04-17T12:27:23.032630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9951
20.3%
0 8770
17.9%
2 4995
10.2%
1 4880
10.0%
3 3834
 
7.8%
4 3313
 
6.8%
5 3105
 
6.3%
6 3005
 
6.1%
8 2605
 
5.3%
7 2238
 
4.6%
Other values (2) 2209
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38950
79.6%
Other Punctuation 9955
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8770
22.5%
2 4995
12.8%
1 4880
12.5%
3 3834
9.8%
4 3313
 
8.5%
5 3105
 
8.0%
6 3005
 
7.7%
8 2605
 
6.7%
7 2238
 
5.7%
9 2205
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 9951
> 99.9%
, 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 48905
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9951
20.3%
0 8770
17.9%
2 4995
10.2%
1 4880
10.0%
3 3834
 
7.8%
4 3313
 
6.8%
5 3105
 
6.3%
6 3005
 
6.1%
8 2605
 
5.3%
7 2238
 
4.6%
Other values (2) 2209
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9951
20.3%
0 8770
17.9%
2 4995
10.2%
1 4880
10.0%
3 3834
 
7.8%
4 3313
 
6.8%
5 3105
 
6.3%
6 3005
 
6.1%
8 2605
 
5.3%
7 2238
 
4.6%
Other values (2) 2209
 
4.5%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct860
Distinct (%)8.7%
Missing109
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean610618.33
Minimum600012
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:23.150834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile601817.5
Q1607811
median611814
Q3614803
95-th percentile617810
Maximum619953
Range19941
Interquartile range (IQR)6992

Descriptive statistics

Standard deviation4780.5965
Coefficient of variation (CV)0.0078291074
Kurtosis-0.68496733
Mean610618.33
Median Absolute Deviation (MAD)3034
Skewness-0.35623885
Sum6.0396259 × 109
Variance22854103
MonotonicityNot monotonic
2024-04-17T12:27:23.263832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609839 104
 
1.0%
614847 101
 
1.0%
604851 82
 
0.8%
608805 78
 
0.8%
614845 77
 
0.8%
612842 71
 
0.7%
612824 71
 
0.7%
616852 64
 
0.6%
608832 61
 
0.6%
614846 59
 
0.6%
Other values (850) 9123
91.2%
(Missing) 109
 
1.1%
ValueCountFrequency (%)
600012 3
 
< 0.1%
600013 2
 
< 0.1%
600015 2
 
< 0.1%
600016 3
 
< 0.1%
600017 2
 
< 0.1%
600022 2
 
< 0.1%
600023 2
 
< 0.1%
600024 2
 
< 0.1%
600025 6
 
0.1%
600031 18
0.2%
ValueCountFrequency (%)
619953 3
 
< 0.1%
619952 1
 
< 0.1%
619951 5
 
0.1%
619913 2
 
< 0.1%
619912 11
 
0.1%
619911 2
 
< 0.1%
619906 4
 
< 0.1%
619905 25
0.2%
619904 1
 
< 0.1%
619903 30
0.3%

소재지전체주소
Text

Distinct9249
Distinct (%)92.6%
Missing16
Missing (%)0.2%
Memory size156.2 KiB
2024-04-17T12:27:23.521322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length49
Mean length24.989583
Min length16

Characters and Unicode

Total characters249496
Distinct characters511
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8633 ?
Unique (%)86.5%

Sample

1st row부산광역시 북구 만덕동 823-8번지 베르빌아파트 101동 2309호
2nd row부산광역시 남구 대연동 60-47번지
3rd row부산광역시 연제구 연산동 2220-3번지 주공아파트
4th row부산광역시 해운대구 재송동 1077-8번지
5th row부산광역시 사하구 하단동 497-24번지 103호
ValueCountFrequency (%)
부산광역시 9984
 
21.3%
해운대구 1259
 
2.7%
부산진구 1236
 
2.6%
사하구 965
 
2.1%
동래구 928
 
2.0%
t통b반 864
 
1.8%
남구 774
 
1.6%
금정구 753
 
1.6%
연제구 720
 
1.5%
북구 703
 
1.5%
Other values (10096) 28795
61.3%
2024-04-17T12:27:23.897290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37016
 
14.8%
동 12147
 
4.9%
부 12140
 
4.9%
산 12098
 
4.8%
1 11869
 
4.8%
광 10376
 
4.2%
구 10198
 
4.1%
시 10134
 
4.1%
역 10001
 
4.0%
지 9189
 
3.7%
Other values (501) 114328
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147486
59.1%
Decimal Number 52624
 
21.1%
Space Separator 37016
 
14.8%
Dash Punctuation 8994
 
3.6%
Uppercase Letter 2187
 
0.9%
Open Punctuation 425
 
0.2%
Close Punctuation 423
 
0.2%
Other Punctuation 282
 
0.1%
Lowercase Letter 47
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12147
 
8.2%
부 12140
 
8.2%
산 12098
 
8.2%
광 10376
 
7.0%
구 10198
 
6.9%
시 10134
 
6.9%
역 10001
 
6.8%
지 9189
 
6.2%
번 8723
 
5.9%
대 2368
 
1.6%
Other values (441) 50112
34.0%
Uppercase Letter
ValueCountFrequency (%)
B 936
42.8%
T 875
40.0%
A 76
 
3.5%
S 58
 
2.7%
K 49
 
2.2%
E 24
 
1.1%
I 21
 
1.0%
G 20
 
0.9%
H 18
 
0.8%
C 14
 
0.6%
Other values (14) 96
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 11
23.4%
l 8
17.0%
s 6
12.8%
i 5
10.6%
k 4
 
8.5%
b 3
 
6.4%
c 2
 
4.3%
o 2
 
4.3%
n 1
 
2.1%
a 1
 
2.1%
Other values (4) 4
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 11869
22.6%
2 7464
14.2%
3 5853
11.1%
4 4801
9.1%
0 4488
 
8.5%
5 4374
 
8.3%
6 3725
 
7.1%
7 3599
 
6.8%
8 3352
 
6.4%
9 3099
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 213
75.5%
@ 38
 
13.5%
. 15
 
5.3%
/ 12
 
4.3%
· 3
 
1.1%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
37016
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8994
100.0%
Open Punctuation
ValueCountFrequency (%)
( 425
100.0%
Close Punctuation
ValueCountFrequency (%)
) 423
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147486
59.1%
Common 99774
40.0%
Latin 2236
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12147
 
8.2%
부 12140
 
8.2%
산 12098
 
8.2%
광 10376
 
7.0%
구 10198
 
6.9%
시 10134
 
6.9%
역 10001
 
6.8%
지 9189
 
6.2%
번 8723
 
5.9%
대 2368
 
1.6%
Other values (441) 50112
34.0%
Latin
ValueCountFrequency (%)
B 936
41.9%
T 875
39.1%
A 76
 
3.4%
S 58
 
2.6%
K 49
 
2.2%
E 24
 
1.1%
I 21
 
0.9%
G 20
 
0.9%
H 18
 
0.8%
C 14
 
0.6%
Other values (29) 145
 
6.5%
Common
ValueCountFrequency (%)
37016
37.1%
1 11869
 
11.9%
- 8994
 
9.0%
2 7464
 
7.5%
3 5853
 
5.9%
4 4801
 
4.8%
0 4488
 
4.5%
5 4374
 
4.4%
6 3725
 
3.7%
7 3599
 
3.6%
Other values (11) 7591
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147486
59.1%
ASCII 102005
40.9%
None 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37016
36.3%
1 11869
 
11.6%
- 8994
 
8.8%
2 7464
 
7.3%
3 5853
 
5.7%
4 4801
 
4.7%
0 4488
 
4.4%
5 4374
 
4.3%
6 3725
 
3.7%
7 3599
 
3.5%
Other values (48) 9822
 
9.6%
Hangul
ValueCountFrequency (%)
동 12147
 
8.2%
부 12140
 
8.2%
산 12098
 
8.2%
광 10376
 
7.0%
구 10198
 
6.9%
시 10134
 
6.9%
역 10001
 
6.8%
지 9189
 
6.2%
번 8723
 
5.9%
대 2368
 
1.6%
Other values (441) 50112
34.0%
None
ValueCountFrequency (%)
· 3
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명전체주소
Text

MISSING 

Distinct6801
Distinct (%)97.0%
Missing2991
Missing (%)29.9%
Memory size156.2 KiB
2024-04-17T12:27:24.193673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length56
Mean length32.008418
Min length18

Characters and Unicode

Total characters224347
Distinct characters533
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6605 ?
Unique (%)94.2%

Sample

1st row부산광역시 연제구 토현로 10, 상가나동 2층 206호 (연산동, 주공아파트)
2nd row부산광역시 해운대구 해운대로123번길 35, 1층 102호 (재송동, 센텀장광리버빌)
3rd row부산광역시 사하구 낙동대로516번길 5, 103호 (하단동)
4th row부산광역시 금정구 부곡온천천로 190, 1층 113호 (부곡동, 퀸즈더블유장전역)
5th row부산광역시 연제구 중앙대로 1130, 2층 206호 (연산동, SK뷰)
ValueCountFrequency (%)
부산광역시 7009
 
16.1%
1층 1726
 
4.0%
부산진구 980
 
2.3%
2층 882
 
2.0%
해운대구 848
 
2.0%
동래구 664
 
1.5%
사하구 617
 
1.4%
남구 529
 
1.2%
금정구 526
 
1.2%
수영구 513
 
1.2%
Other values (5691) 29160
67.1%
2024-04-17T12:27:24.608905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36453
 
16.2%
동 9704
 
4.3%
1 9597
 
4.3%
부 8896
 
4.0%
산 8734
 
3.9%
광 7551
 
3.4%
시 7461
 
3.3%
구 7216
 
3.2%
역 7029
 
3.1%
( 6996
 
3.1%
Other values (523) 114710
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129543
57.7%
Decimal Number 36590
 
16.3%
Space Separator 36453
 
16.2%
Open Punctuation 6996
 
3.1%
Close Punctuation 6995
 
3.1%
Other Punctuation 6088
 
2.7%
Dash Punctuation 1120
 
0.5%
Uppercase Letter 484
 
0.2%
Lowercase Letter 47
 
< 0.1%
Math Symbol 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9704
 
7.5%
부 8896
 
6.9%
산 8734
 
6.7%
광 7551
 
5.8%
시 7461
 
5.8%
구 7216
 
5.6%
역 7029
 
5.4%
로 6894
 
5.3%
층 3481
 
2.7%
대 3479
 
2.7%
Other values (465) 59098
45.6%
Uppercase Letter
ValueCountFrequency (%)
B 102
21.1%
A 72
14.9%
S 66
13.6%
K 49
10.1%
E 29
 
6.0%
H 21
 
4.3%
I 19
 
3.9%
G 16
 
3.3%
C 15
 
3.1%
W 13
 
2.7%
Other values (13) 82
16.9%
Lowercase Letter
ValueCountFrequency (%)
e 15
31.9%
l 8
17.0%
s 7
14.9%
k 5
 
10.6%
i 5
 
10.6%
o 2
 
4.3%
n 1
 
2.1%
a 1
 
2.1%
h 1
 
2.1%
w 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 9597
26.2%
2 6180
16.9%
3 4006
10.9%
0 3531
 
9.7%
4 2938
 
8.0%
5 2557
 
7.0%
6 2259
 
6.2%
7 1993
 
5.4%
8 1860
 
5.1%
9 1669
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 6044
99.3%
@ 23
 
0.4%
. 10
 
0.2%
/ 5
 
0.1%
· 3
 
< 0.1%
& 2
 
< 0.1%
# 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 28
96.6%
～ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
36453
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6996
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6995
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1120
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129543
57.7%
Common 94271
42.0%
Latin 533
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9704
 
7.5%
부 8896
 
6.9%
산 8734
 
6.7%
광 7551
 
5.8%
시 7461
 
5.8%
구 7216
 
5.6%
역 7029
 
5.4%
로 6894
 
5.3%
층 3481
 
2.7%
대 3479
 
2.7%
Other values (465) 59098
45.6%
Latin
ValueCountFrequency (%)
B 102
19.1%
A 72
13.5%
S 66
12.4%
K 49
 
9.2%
E 29
 
5.4%
H 21
 
3.9%
I 19
 
3.6%
G 16
 
3.0%
C 15
 
2.8%
e 15
 
2.8%
Other values (25) 129
24.2%
Common
ValueCountFrequency (%)
36453
38.7%
1 9597
 
10.2%
( 6996
 
7.4%
) 6995
 
7.4%
2 6180
 
6.6%
, 6044
 
6.4%
3 4006
 
4.2%
0 3531
 
3.7%
4 2938
 
3.1%
5 2557
 
2.7%
Other values (13) 8974
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129543
57.7%
ASCII 94798
42.3%
None 4
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36453
38.5%
1 9597
 
10.1%
( 6996
 
7.4%
) 6995
 
7.4%
2 6180
 
6.5%
, 6044
 
6.4%
3 4006
 
4.2%
0 3531
 
3.7%
4 2938
 
3.1%
5 2557
 
2.7%
Other values (45) 9501
 
10.0%
Hangul
ValueCountFrequency (%)
동 9704
 
7.5%
부 8896
 
6.9%
산 8734
 
6.7%
광 7551
 
5.8%
시 7461
 
5.8%
구 7216
 
5.6%
역 7029
 
5.4%
로 6894
 
5.3%
층 3481
 
2.7%
대 3479
 
2.7%
Other values (465) 59098
45.6%
None
ValueCountFrequency (%)
· 3
75.0%
～ 1
 
25.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1558
Distinct (%)22.5%
Missing3065
Missing (%)30.6%
Infinite0
Infinite (%)0.0%
Mean47815.969
Minimum46007
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:24.722608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46007
5-th percentile46243
Q147171
median47850
Q348485.5
95-th percentile49384
Maximum49525
Range3518
Interquartile range (IQR)1314.5

Descriptive statistics

Standard deviation953.2761
Coefficient of variation (CV)0.019936354
Kurtosis-0.86367267
Mean47815.969
Median Absolute Deviation (MAD)650
Skewness-0.031655883
Sum3.3160375 × 108
Variance908735.33
MonotonicityNot monotonic
2024-04-17T12:27:24.827495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46726 44
 
0.4%
48111 40
 
0.4%
48059 36
 
0.4%
46291 34
 
0.3%
48110 33
 
0.3%
48498 30
 
0.3%
46526 29
 
0.3%
47296 28
 
0.3%
47292 28
 
0.3%
47286 27
 
0.3%
Other values (1548) 6606
66.1%
(Missing) 3065
30.6%
ValueCountFrequency (%)
46007 6
 
0.1%
46008 15
0.1%
46010 4
 
< 0.1%
46011 1
 
< 0.1%
46012 7
0.1%
46013 3
 
< 0.1%
46014 1
 
< 0.1%
46015 16
0.2%
46016 1
 
< 0.1%
46017 11
0.1%
ValueCountFrequency (%)
49525 4
 
< 0.1%
49524 4
 
< 0.1%
49523 2
 
< 0.1%
49522 3
 
< 0.1%
49521 2
 
< 0.1%
49520 16
0.2%
49519 10
0.1%
49518 12
0.1%
49516 1
 
< 0.1%
49515 4
 
< 0.1%

사업장명
Text

Distinct8155
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T12:27:25.059569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length5.6108
Min length1

Characters and Unicode

Total characters56108
Distinct characters898
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7204 ?
Unique (%)72.0%

Sample

1st row은백
2nd row지펌(G-PERM)미용실 부경대점
3rd row강이진
4th row장현주 헤어필
5th row매쉬헤어
ValueCountFrequency (%)
미용실 305
 
2.4%
헤어 250
 
2.0%
에스테틱 112
 
0.9%
네일 93
 
0.7%
헤어샵 82
 
0.7%
hair 63
 
0.5%
뷰티 55
 
0.4%
nail 54
 
0.4%
더 35
 
0.3%
진 30
 
0.2%
Other values (8168) 11516
91.4%
2024-04-17T12:27:25.634616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 3516
 
6.3%
헤 3453
 
6.2%
2599
 
4.6%
미 1852
 
3.3%
스 1371
 
2.4%
리 1187
 
2.1%
실 1113
 
2.0%
용 1098
 
2.0%
이 1046
 
1.9%
일 819
 
1.5%
Other values (888) 38054
67.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47113
84.0%
Space Separator 2599
 
4.6%
Lowercase Letter 2451
 
4.4%
Uppercase Letter 2076
 
3.7%
Open Punctuation 579
 
1.0%
Close Punctuation 579
 
1.0%
Other Punctuation 357
 
0.6%
Decimal Number 300
 
0.5%
Dash Punctuation 37
 
0.1%
Math Symbol 8
 
< 0.1%
Other values (4) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 3516
 
7.5%
헤 3453
 
7.3%
미 1852
 
3.9%
스 1371
 
2.9%
리 1187
 
2.5%
실 1113
 
2.4%
용 1098
 
2.3%
이 1046
 
2.2%
일 819
 
1.7%
네 782
 
1.7%
Other values (799) 30876
65.5%
Lowercase Letter
ValueCountFrequency (%)
a 344
14.0%
i 256
10.4%
e 251
10.2%
o 210
8.6%
n 199
 
8.1%
l 176
 
7.2%
r 148
 
6.0%
y 135
 
5.5%
h 118
 
4.8%
u 95
 
3.9%
Other values (16) 519
21.2%
Uppercase Letter
ValueCountFrequency (%)
A 203
 
9.8%
N 182
 
8.8%
S 155
 
7.5%
I 139
 
6.7%
B 126
 
6.1%
H 126
 
6.1%
E 115
 
5.5%
J 113
 
5.4%
L 108
 
5.2%
M 107
 
5.2%
Other values (16) 702
33.8%
Other Punctuation
ValueCountFrequency (%)
& 116
32.5%
. 94
26.3%
# 47
13.2%
, 40
 
11.2%
' 26
 
7.3%
: 9
 
2.5%
· 6
 
1.7%
＆ 5
 
1.4%
; 4
 
1.1%
/ 2
 
0.6%
Other values (5) 8
 
2.2%
Decimal Number
ValueCountFrequency (%)
1 70
23.3%
2 67
22.3%
0 47
15.7%
3 24
 
8.0%
9 22
 
7.3%
5 19
 
6.3%
7 15
 
5.0%
4 15
 
5.0%
8 12
 
4.0%
6 9
 
3.0%
Open Punctuation
ValueCountFrequency (%)
( 578
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 578
99.8%
] 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 7
87.5%
∥ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
2599
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47067
83.9%
Latin 4528
 
8.1%
Common 4467
 
8.0%
Han 46
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 3516
 
7.5%
헤 3453
 
7.3%
미 1852
 
3.9%
스 1371
 
2.9%
리 1187
 
2.5%
실 1113
 
2.4%
용 1098
 
2.3%
이 1046
 
2.2%
일 819
 
1.7%
네 782
 
1.7%
Other values (782) 30830
65.5%
Latin
ValueCountFrequency (%)
a 344
 
7.6%
i 256
 
5.7%
e 251
 
5.5%
o 210
 
4.6%
A 203
 
4.5%
n 199
 
4.4%
N 182
 
4.0%
l 176
 
3.9%
S 155
 
3.4%
r 148
 
3.3%
Other values (43) 2404
53.1%
Common
ValueCountFrequency (%)
2599
58.2%
( 578
 
12.9%
) 578
 
12.9%
& 116
 
2.6%
. 94
 
2.1%
1 70
 
1.6%
2 67
 
1.5%
# 47
 
1.1%
0 47
 
1.1%
, 40
 
0.9%
Other values (26) 231
 
5.2%
Han
ValueCountFrequency (%)
美 27
58.7%
人 3
 
6.5%
安 2
 
4.3%
林 1
 
2.2%
守 1
 
2.2%
愛 1
 
2.2%
朴 1
 
2.2%
月 1
 
2.2%
日 1
 
2.2%
午 1
 
2.2%
Other values (7) 7
 
15.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47067
83.9%
ASCII 8981
 
16.0%
CJK 46
 
0.1%
None 12
 
< 0.1%
Math Operators 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 3516
 
7.5%
헤 3453
 
7.3%
미 1852
 
3.9%
스 1371
 
2.9%
리 1187
 
2.5%
실 1113
 
2.4%
용 1098
 
2.3%
이 1046
 
2.2%
일 819
 
1.7%
네 782
 
1.7%
Other values (782) 30830
65.5%
ASCII
ValueCountFrequency (%)
2599
28.9%
( 578
 
6.4%
) 578
 
6.4%
a 344
 
3.8%
i 256
 
2.9%
e 251
 
2.8%
o 210
 
2.3%
A 203
 
2.3%
n 199
 
2.2%
N 182
 
2.0%
Other values (74) 3581
39.9%
CJK
ValueCountFrequency (%)
美 27
58.7%
人 3
 
6.5%
安 2
 
4.3%
林 1
 
2.2%
守 1
 
2.2%
愛 1
 
2.2%
朴 1
 
2.2%
月 1
 
2.2%
日 1
 
2.2%
午 1
 
2.2%
Other values (7) 7
 
15.2%
None
ValueCountFrequency (%)
· 6
50.0%
＆ 5
41.7%
＃ 1
 
8.3%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct8152
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0129781 × 1013
Minimum1.9990125 × 1013
Maximum2.0210129 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:25.747690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990125 × 1013
5-th percentile2.0011125 × 1013
Q12.0061029 × 1013
median2.0150609 × 1013
Q32.0190703 × 1013
95-th percentile2.0201201 × 1013
Maximum2.0210129 × 1013
Range2.2000417 × 1011
Interquartile range (IQR)1.2967389 × 1011

Descriptive statistics

Standard deviation6.7675673 × 1010
Coefficient of variation (CV)0.0033619677
Kurtosis-1.0771719
Mean2.0129781 × 1013
Median Absolute Deviation (MAD)4.9522014 × 1010
Skewness-0.59899675
Sum2.0129781 × 1017
Variance4.5799967 × 1021
MonotonicityNot monotonic
2024-04-17T12:27:25.854548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030402000000 100
 
1.0%
20040719000000 31
 
0.3%
20001209000000 31
 
0.3%
20030403000000 31
 
0.3%
20061113000000 31
 
0.3%
19990429000000 29
 
0.3%
20020823000000 28
 
0.3%
20040827000000 27
 
0.3%
20030503000000 27
 
0.3%
20021218000000 24
 
0.2%
Other values (8142) 9641
96.4%
ValueCountFrequency (%)
19990125000000 2
 
< 0.1%
19990126000000 7
0.1%
19990211000000 1
 
< 0.1%
19990222000000 1
 
< 0.1%
19990223000000 4
 
< 0.1%
19990224000000 8
0.1%
19990225000000 5
 
0.1%
19990303000000 4
 
< 0.1%
19990304000000 13
0.1%
19990305000000 14
0.1%
ValueCountFrequency (%)
20210129171656 1
< 0.1%
20210129165051 1
< 0.1%
20210129151531 1
< 0.1%
20210129151341 1
< 0.1%
20210129135632 1
< 0.1%
20210129134525 1
< 0.1%
20210129102911 1
< 0.1%
20210129092442 1
< 0.1%
20210128154033 1
< 0.1%
20210128140350 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7258 
U
2742 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7258
72.6%
U 2742
 
27.4%

Length

2024-04-17T12:27:25.948346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:26.016310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7258
72.6%
u 2742
 
27.4%

데이터갱신일자
Date

Distinct881
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-31 02:40:00
2024-04-17T12:27:26.093781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T12:27:26.199152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반미용업
7000 
피부미용업
1864 
네일아트업
874 
메이크업업
 
161
기타
 
99

Length

Max length6
Median length5
Mean length4.9705
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반미용업
2nd row일반미용업
3rd row피부미용업
4th row일반미용업
5th row일반미용업

Common Values

ValueCountFrequency (%)
일반미용업 7000
70.0%
피부미용업 1864
 
18.6%
네일아트업 874
 
8.7%
메이크업업 161
 
1.6%
기타 99
 
1.0%
미용업 기타 2
 
< 0.1%

Length

2024-04-17T12:27:26.307620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:26.417335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 7000
70.0%
피부미용업 1864
 
18.6%
네일아트업 874
 
8.7%
메이크업업 161
 
1.6%
기타 101
 
1.0%
미용업 2
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct7484
Distinct (%)77.0%
Missing278
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean388299.71
Minimum366931.44
Maximum407556.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:26.512161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366931.44
5-th percentile379746.98
Q1384560.63
median388684.31
Q3391765.24
95-th percentile397682.46
Maximum407556.48
Range40625.039
Interquartile range (IQR)7204.6057

Descriptive statistics

Standard deviation5273.8987
Coefficient of variation (CV)0.013582031
Kurtosis0.14141822
Mean388299.71
Median Absolute Deviation (MAD)3529.7228
Skewness-0.095348696
Sum3.7750498 × 109
Variance27814007
MonotonicityNot monotonic
2024-04-17T12:27:26.622945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380398.062015138 19
 
0.2%
398330.516530402 16
 
0.2%
395388.715069604 16
 
0.2%
393239.237933586 16
 
0.2%
392474.578116018 16
 
0.2%
398407.043332602 16
 
0.2%
397926.518365471 14
 
0.1%
398491.352089522 14
 
0.1%
398237.363461482 13
 
0.1%
391411.212179843 13
 
0.1%
Other values (7474) 9569
95.7%
(Missing) 278
 
2.8%
ValueCountFrequency (%)
366931.435995074 1
< 0.1%
367051.926419356 2
< 0.1%
367058.667450096 1
< 0.1%
367145.447260979 1
< 0.1%
367177.362435871 1
< 0.1%
367193.583454597 1
< 0.1%
367225.322681497 1
< 0.1%
367226.483222999 1
< 0.1%
367397.014357092 1
< 0.1%
367451.087635496 1
< 0.1%
ValueCountFrequency (%)
407556.4753504 1
< 0.1%
407161.891842701 1
< 0.1%
407121.882187494 1
< 0.1%
407037.787059465 1
< 0.1%
406982.053033795 1
< 0.1%
406901.988020022 1
< 0.1%
405396.620775536 1
< 0.1%
405172.859381319 1
< 0.1%
404194.966298269 1
< 0.1%
403981.485891989 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct7486
Distinct (%)77.0%
Missing278
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean187003.09
Minimum173895.66
Maximum206512.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:26.733719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173895.66
5-th percentile178059.62
Q1183219.54
median187273.32
Q3190872.56
95-th percentile195690.64
Maximum206512.52
Range32616.862
Interquartile range (IQR)7653.0134

Descriptive statistics

Standard deviation5552.9785
Coefficient of variation (CV)0.029694581
Kurtosis0.13645418
Mean187003.09
Median Absolute Deviation (MAD)3687.0798
Skewness0.16577495
Sum1.8180441 × 109
Variance30835570
MonotonicityNot monotonic
2024-04-17T12:27:26.834924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
175314.286676535 19
 
0.2%
187771.511373596 16
 
0.2%
186268.853282623 16
 
0.2%
188619.149645081 16
 
0.2%
183052.21115244 16
 
0.2%
187784.843934451 16
 
0.2%
188980.774505655 14
 
0.1%
187644.220019205 14
 
0.1%
187720.511056894 13
 
0.1%
184052.409245407 13
 
0.1%
Other values (7476) 9569
95.7%
(Missing) 278
 
2.8%
ValueCountFrequency (%)
173895.655729558 1
 
< 0.1%
173942.787360397 2
< 0.1%
173961.753544726 1
 
< 0.1%
173961.914773076 1
 
< 0.1%
173969.719902491 1
 
< 0.1%
173982.009447475 1
 
< 0.1%
174031.935803657 3
< 0.1%
174035.700224564 1
 
< 0.1%
174092.497564851 1
 
< 0.1%
174096.498143437 2
< 0.1%
ValueCountFrequency (%)
206512.517255249 1
 
< 0.1%
206353.855586145 4
< 0.1%
206285.479401732 1
 
< 0.1%
206184.609573703 6
0.1%
206138.724866676 1
 
< 0.1%
206120.302153948 1
 
< 0.1%
206102.964822493 1
 
< 0.1%
206089.035101112 2
 
< 0.1%
206086.593324435 1
 
< 0.1%
206070.223360046 1
 
< 0.1%

위생업태명
Categorical

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
미용업
3929 
미용업(일반)
2941 
미용업(피부)
1005 
일반미용업
430 
미용업(손톱ㆍ발톱)
 
374
Other values (24)
1321 

Length

Max length31
Median length28
Mean length6.1414
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미용업
2nd row미용업
3rd row미용업(피부)
4th row미용업(일반)
5th row미용업(일반)

Common Values

ValueCountFrequency (%)
미용업 3929
39.3%
미용업(일반) 2941
29.4%
미용업(피부) 1005
 
10.1%
일반미용업 430
 
4.3%
미용업(손톱ㆍ발톱) 374
 
3.7%
미용업(종합) 329
 
3.3%
피부미용업 188
 
1.9%
네일미용업 99
 
1.0%
미용업(피부), 미용업(손톱ㆍ발톱) 89
 
0.9%
미용업(손톱ㆍ발톱), 미용업(화장ㆍ분장) 78
 
0.8%
Other values (19) 538
 
5.4%

Length

2024-04-17T12:27:26.936536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 4031
37.5%
미용업(일반 3114
29.0%
미용업(피부 1233
 
11.5%
미용업(손톱ㆍ발톱 679
 
6.3%
일반미용업 471
 
4.4%
미용업(종합 329
 
3.1%
미용업(화장ㆍ분장 312
 
2.9%
피부미용업 241
 
2.2%
네일미용업 178
 
1.7%
화장ㆍ분장 102
 
0.9%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)0.5%
Missing2085
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean2.6370183
Minimum0
Maximum63
Zeros2898
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:27.026569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile7
Maximum63
Range63
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.1788448
Coefficient of variation (CV)1.5846855
Kurtosis44.109217
Mean2.6370183
Median Absolute Deviation (MAD)2
Skewness5.36676
Sum20872
Variance17.462744
MonotonicityNot monotonic
2024-04-17T12:27:27.125943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 2898
29.0%
2 1358
13.6%
3 1111
 
11.1%
4 949
 
9.5%
5 510
 
5.1%
1 415
 
4.2%
6 192
 
1.9%
7 88
 
0.9%
8 72
 
0.7%
9 58
 
0.6%
Other values (33) 264
 
2.6%
(Missing) 2085
20.8%
ValueCountFrequency (%)
0 2898
29.0%
1 415
 
4.2%
2 1358
13.6%
3 1111
 
11.1%
4 949
 
9.5%
5 510
 
5.1%
6 192
 
1.9%
7 88
 
0.9%
8 72
 
0.7%
9 58
 
0.6%
ValueCountFrequency (%)
63 1
 
< 0.1%
61 1
 
< 0.1%
49 3
 
< 0.1%
47 3
 
< 0.1%
43 3
 
< 0.1%
42 8
0.1%
39 2
 
< 0.1%
38 2
 
< 0.1%
37 4
< 0.1%
36 1
 
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)0.2%
Missing2981
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean0.38509759
Minimum0
Maximum24
Zeros5182
Zeros (%)51.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:27.215553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum24
Range24
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.94143718
Coefficient of variation (CV)2.4446717
Kurtosis96.46698
Mean0.38509759
Median Absolute Deviation (MAD)0
Skewness6.7183364
Sum2703
Variance0.88630396
MonotonicityNot monotonic
2024-04-17T12:27:27.297007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 5182
51.8%
1 1467
 
14.7%
2 178
 
1.8%
3 76
 
0.8%
5 48
 
0.5%
4 27
 
0.3%
6 26
 
0.3%
7 9
 
0.1%
10 2
 
< 0.1%
18 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 2981
29.8%
ValueCountFrequency (%)
0 5182
51.8%
1 1467
 
14.7%
2 178
 
1.8%
3 76
 
0.8%
4 27
 
0.3%
5 48
 
0.5%
6 26
 
0.3%
7 9
 
0.1%
8 1
 
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
18 1
 
< 0.1%
15 1
 
< 0.1%
10 2
 
< 0.1%
8 1
 
< 0.1%
7 9
 
0.1%
6 26
 
0.3%
5 48
0.5%
4 27
 
0.3%
3 76
0.8%

사용시작지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.3%
Missing2678
Missing (%)26.8%
Infinite0
Infinite (%)0.0%
Mean1.3860967
Minimum0
Maximum325
Zeros1493
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:27.378492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum325
Range325
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.0498449
Coefficient of variation (CV)2.9217622
Kurtosis5572.6443
Mean1.3860967
Median Absolute Deviation (MAD)1
Skewness70.016424
Sum10149
Variance16.401244
MonotonicityNot monotonic
2024-04-17T12:27:27.477283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 3597
36.0%
0 1493
14.9%
2 1398
 
14.0%
3 481
 
4.8%
4 163
 
1.6%
5 67
 
0.7%
6 48
 
0.5%
7 29
 
0.3%
9 13
 
0.1%
8 12
 
0.1%
Other values (9) 21
 
0.2%
(Missing) 2678
26.8%
ValueCountFrequency (%)
0 1493
14.9%
1 3597
36.0%
2 1398
 
14.0%
3 481
 
4.8%
4 163
 
1.6%
5 67
 
0.7%
6 48
 
0.5%
7 29
 
0.3%
8 12
 
0.1%
9 13
 
0.1%
ValueCountFrequency (%)
325 1
 
< 0.1%
37 2
 
< 0.1%
24 1
 
< 0.1%
19 1
 
< 0.1%
15 2
 
< 0.1%
13 1
 
< 0.1%
12 2
 
< 0.1%
11 3
 
< 0.1%
10 8
0.1%
9 13
0.1%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct18
Distinct (%)0.3%
Missing4149
Missing (%)41.5%
Infinite0
Infinite (%)0.0%
Mean1.4330884
Minimum0
Maximum326
Zeros1027
Zeros (%)10.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:27.588304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum326
Range326
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.4528019
Coefficient of variation (CV)3.1071371
Kurtosis4827.6212
Mean1.4330884
Median Absolute Deviation (MAD)0
Skewness66.332366
Sum8385
Variance19.827445
MonotonicityNot monotonic
2024-04-17T12:27:27.685662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 2987
29.9%
2 1157
 
11.6%
0 1027
 
10.3%
3 401
 
4.0%
4 126
 
1.3%
5 54
 
0.5%
6 38
 
0.4%
7 23
 
0.2%
8 10
 
0.1%
10 10
 
0.1%
Other values (8) 18
 
0.2%
(Missing) 4149
41.5%
ValueCountFrequency (%)
0 1027
 
10.3%
1 2987
29.9%
2 1157
 
11.6%
3 401
 
4.0%
4 126
 
1.3%
5 54
 
0.5%
6 38
 
0.4%
7 23
 
0.2%
8 10
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
326 1
 
< 0.1%
24 1
 
< 0.1%
21 1
 
< 0.1%
19 1
 
< 0.1%
15 2
 
< 0.1%
12 2
 
< 0.1%
11 2
 
< 0.1%
10 10
0.1%
9 8
0.1%
8 10
0.1%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5773 
0
4043 
1
 
161
2
 
21
3
 
2

Length

Max length4
Median length4
Mean length2.7319
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5773
57.7%
0 4043
40.4%
1 161
 
1.6%
2 21
 
0.2%
3 2
 
< 0.1%

Length

2024-04-17T12:27:27.786600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:27.865108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5773
57.7%
0 4043
40.4%
1 161
 
1.6%
2 21
 
0.2%
3 2
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6859 
0
2993 
1
 
128
2
 
18
3
 
2

Length

Max length4
Median length4
Mean length3.0577
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6859
68.6%
0 2993
29.9%
1 128
 
1.3%
2 18
 
0.2%
3 2
 
< 0.1%

Length

2024-04-17T12:27:27.951076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:28.032454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6859
68.6%
0 2993
29.9%
1 128
 
1.3%
2 18
 
0.2%
3 2
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6630 
<NA>
3370 

Length

Max length4
Median length1
Mean length2.011
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6630
66.3%
<NA> 3370
33.7%

Length

2024-04-17T12:27:28.122521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:28.200700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6630
66.3%
na 3370
33.7%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6630 
<NA>
3370 

Length

Max length4
Median length1
Mean length2.011
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6630
66.3%
<NA> 3370
33.7%

Length

2024-04-17T12:27:28.281242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:28.356357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6630
66.3%
na 3370
33.7%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6630 
<NA>
3370 

Length

Max length4
Median length1
Mean length2.011
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6630
66.3%
<NA> 3370
33.7%

Length

2024-04-17T12:27:28.439475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:28.519740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6630
66.3%
na 3370
33.7%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing152
Missing (%)1.5%
Memory size97.7 KiB
False
9848 
(Missing)
 
152
ValueCountFrequency (%)
False 9848
98.5%
(Missing) 152
 
1.5%
2024-04-17T12:27:28.582372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)0.3%
Missing786
Missing (%)7.9%
Infinite0
Infinite (%)0.0%
Mean3.3417625
Minimum0
Maximum36
Zeros1385
Zeros (%)13.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:28.646376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum36
Range36
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8588638
Coefficient of variation (CV)0.85549579
Kurtosis15.25787
Mean3.3417625
Median Absolute Deviation (MAD)1
Skewness2.8606441
Sum30791
Variance8.1731021
MonotonicityNot monotonic
2024-04-17T12:27:28.768423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3 3083
30.8%
4 1454
14.5%
2 1427
14.3%
0 1385
13.9%
5 575
 
5.8%
6 362
 
3.6%
1 216
 
2.2%
8 172
 
1.7%
7 119
 
1.2%
10 87
 
0.9%
Other values (20) 334
 
3.3%
(Missing) 786
 
7.9%
ValueCountFrequency (%)
0 1385
13.9%
1 216
 
2.2%
2 1427
14.3%
3 3083
30.8%
4 1454
14.5%
5 575
 
5.8%
6 362
 
3.6%
7 119
 
1.2%
8 172
 
1.7%
9 81
 
0.8%
ValueCountFrequency (%)
36 1
 
< 0.1%
33 1
 
< 0.1%
31 1
 
< 0.1%
28 2
 
< 0.1%
27 1
 
< 0.1%
24 11
0.1%
23 1
 
< 0.1%
22 4
 
< 0.1%
21 5
 
0.1%
20 13
0.1%

조건부허가신고사유
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing9995
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T12:27:28.919141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length44
Mean length43.6
Min length10

Characters and Unicode

Total characters218
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row가설건축물존치기한까지연장(영업신고기간:2017.03.01까지)
2nd row기한부영업신고기간:2006.10.19~2008.10.18 3. 이후 영업신고기간이 만료되어 연장신청을 하지않을경우 영업신고가 자동으로 말소됨
3rd row가설건축물 존치기간(2004.01.08부터 2005.01.07)까지 영업신고수리
4th row가설건축물 존치기간
5th row특정건축물 사용승인하였으나, 2007.7.13자 조건부영업신고 해제함(담당자:고제현)
ValueCountFrequency (%)
가설건축물 2
 
9.1%
가설건축물존치기한까지연장(영업신고기간:2017.03.01까지 1
 
4.5%
조건부영업신고 1
 
4.5%
2007.7.13자 1
 
4.5%
사용승인하였으나 1
 
4.5%
특정건축물 1
 
4.5%
존치기간 1
 
4.5%
영업신고수리 1
 
4.5%
2005.01.07)까지 1
 
4.5%
존치기간(2004.01.08부터 1
 
4.5%
Other values (11) 11
50.0%
2024-04-17T12:27:29.168482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
10.1%
0 19
 
8.7%
. 13
 
6.0%
1 9
 
4.1%
고 7
 
3.2%
기 7
 
3.2%
신 7
 
3.2%
2 6
 
2.8%
업 6
 
2.8%
영 6
 
2.8%
Other values (63) 116
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
56.9%
Decimal Number 48
 
22.0%
Space Separator 22
 
10.1%
Other Punctuation 17
 
7.8%
Close Punctuation 3
 
1.4%
Open Punctuation 3
 
1.4%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 7
 
5.6%
기 7
 
5.6%
신 7
 
5.6%
업 6
 
4.8%
영 6
 
4.8%
건 5
 
4.0%
간 5
 
4.0%
가 4
 
3.2%
지 4
 
3.2%
물 4
 
3.2%
Other values (46) 69
55.6%
Decimal Number
ValueCountFrequency (%)
0 19
39.6%
1 9
18.8%
2 6
 
12.5%
7 4
 
8.3%
3 3
 
6.2%
8 3
 
6.2%
5 1
 
2.1%
6 1
 
2.1%
9 1
 
2.1%
4 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 13
76.5%
: 3
 
17.6%
, 1
 
5.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
56.9%
Common 94
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 7
 
5.6%
기 7
 
5.6%
신 7
 
5.6%
업 6
 
4.8%
영 6
 
4.8%
건 5
 
4.0%
간 5
 
4.0%
가 4
 
3.2%
지 4
 
3.2%
물 4
 
3.2%
Other values (46) 69
55.6%
Common
ValueCountFrequency (%)
22
23.4%
0 19
20.2%
. 13
13.8%
1 9
9.6%
2 6
 
6.4%
7 4
 
4.3%
3 3
 
3.2%
8 3
 
3.2%
) 3
 
3.2%
: 3
 
3.2%
Other values (7) 9
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
56.9%
ASCII 94
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
23.4%
0 19
20.2%
. 13
13.8%
1 9
9.6%
2 6
 
6.4%
7 4
 
4.3%
3 3
 
3.2%
8 3
 
3.2%
) 3
 
3.2%
: 3
 
3.2%
Other values (7) 9
9.6%
Hangul
ValueCountFrequency (%)
고 7
 
5.6%
기 7
 
5.6%
신 7
 
5.6%
업 6
 
4.8%
영 6
 
4.8%
건 5
 
4.0%
간 5
 
4.0%
가 4
 
3.2%
지 4
 
3.2%
물 4
 
3.2%
Other values (46) 69
55.6%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9995 
20150331
 
1
20051019
 
1
20040119
 
1
20141231
 
1

Length

Max length8
Median length4
Mean length4.002
Min length4

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9995
> 99.9%
20150331 1
 
< 0.1%
20051019 1
 
< 0.1%
20040119 1
 
< 0.1%
20141231 1
 
< 0.1%
20060728 1
 
< 0.1%

Length

2024-04-17T12:27:29.274276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:29.359609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9995
> 99.9%
20150331 1
 
< 0.1%
20051019 1
 
< 0.1%
20040119 1
 
< 0.1%
20141231 1
 
< 0.1%
20060728 1
 
< 0.1%

조건부허가종료일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)75.0%
Missing9992
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean12564171
Minimum2
Maximum20170301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:29.431135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median20055562
Q320093337
95-th percentile20167126
Maximum20170301
Range20170299
Interquartile range (IQR)20093335

Descriptive statistics

Standard deviation10404213
Coefficient of variation (CV)0.82808593
Kurtosis-2.2399598
Mean12564171
Median Absolute Deviation (MAD)110203
Skewness-0.64399218
Sum1.0051337 × 108
Variance1.0824765 × 1014
MonotonicityNot monotonic
2024-04-17T12:27:29.513863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 3
 
< 0.1%
20170301 1
 
< 0.1%
20061018 1
 
< 0.1%
20050107 1
 
< 0.1%
20161230 1
 
< 0.1%
20070706 1
 
< 0.1%
(Missing) 9992
99.9%
ValueCountFrequency (%)
2 3
< 0.1%
20050107 1
 
< 0.1%
20061018 1
 
< 0.1%
20070706 1
 
< 0.1%
20161230 1
 
< 0.1%
20170301 1
 
< 0.1%
ValueCountFrequency (%)
20170301 1
 
< 0.1%
20161230 1
 
< 0.1%
20070706 1
 
< 0.1%
20061018 1
 
< 0.1%
20050107 1
 
< 0.1%
2 3
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7623 
임대
2280 
자가
 
97

Length

Max length4
Median length4
Mean length3.5246
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7623
76.2%
임대 2280
 
22.8%
자가 97
 
1.0%

Length

2024-04-17T12:27:29.611649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:29.696427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7623
76.2%
임대 2280
 
22.8%
자가 97
 
1.0%

세탁기수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5559 
<NA>
4441 

Length

Max length4
Median length1
Mean length2.3323
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5559
55.6%
<NA> 4441
44.4%

Length

2024-04-17T12:27:29.784817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:29.872877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5559
55.6%
na 4441
44.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing7631
Missing (%)76.3%
Infinite0
Infinite (%)0.0%
Mean0.07471507
Minimum0
Maximum8
Zeros2237
Zeros (%)22.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:29.936641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3776793
Coefficient of variation (CV)5.054928
Kurtosis121.86818
Mean0.07471507
Median Absolute Deviation (MAD)0
Skewness8.8833653
Sum177
Variance0.14264165
MonotonicityNot monotonic
2024-04-17T12:27:30.019091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 2237
 
22.4%
1 107
 
1.1%
2 16
 
0.2%
4 4
 
< 0.1%
3 3
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
(Missing) 7631
76.3%
ValueCountFrequency (%)
0 2237
22.4%
1 107
 
1.1%
2 16
 
0.2%
3 3
 
< 0.1%
4 4
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
5 1
 
< 0.1%
4 4
 
< 0.1%
3 3
 
< 0.1%
2 16
 
0.2%
1 107
 
1.1%
0 2237
22.4%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7646 
0
2334 
1
 
18
2
 
2

Length

Max length4
Median length4
Mean length3.2938
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7646
76.5%
0 2334
 
23.3%
1 18
 
0.2%
2 2
 
< 0.1%

Length

2024-04-17T12:27:30.112203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:30.190589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7646
76.5%
0 2334
 
23.3%
1 18
 
0.2%
2 2
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5307 
<NA>
4693 

Length

Max length4
Median length1
Mean length2.4079
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5307
53.1%
<NA> 4693
46.9%

Length

2024-04-17T12:27:30.271105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:27:30.581649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5307
53.1%
na 4693
46.9%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)0.3%
Missing4732
Missing (%)47.3%
Infinite0
Infinite (%)0.0%
Mean0.99905087
Minimum0
Maximum20
Zeros3527
Zeros (%)35.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:27:30.648753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum20
Range20
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8995565
Coefficient of variation (CV)1.9013612
Kurtosis10.718498
Mean0.99905087
Median Absolute Deviation (MAD)0
Skewness2.7516871
Sum5263
Variance3.608315
MonotonicityNot monotonic
2024-04-17T12:27:30.738892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 3527
35.3%
2 529
 
5.3%
1 408
 
4.1%
3 299
 
3.0%
4 182
 
1.8%
5 107
 
1.1%
6 86
 
0.9%
7 57
 
0.6%
8 25
 
0.2%
9 17
 
0.2%
Other values (7) 31
 
0.3%
(Missing) 4732
47.3%
ValueCountFrequency (%)
0 3527
35.3%
1 408
 
4.1%
2 529
 
5.3%
3 299
 
3.0%
4 182
 
1.8%
5 107
 
1.1%
6 86
 
0.9%
7 57
 
0.6%
8 25
 
0.2%
9 17
 
0.2%
ValueCountFrequency (%)
20 1
 
< 0.1%
19 1
 
< 0.1%
16 2
 
< 0.1%
13 3
 
< 0.1%
12 8
 
0.1%
11 3
 
< 0.1%
10 13
 
0.1%
9 17
 
0.2%
8 25
0.2%
7 57
0.6%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2024-04-17T12:27:30.820097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Unnamed: 50
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
1677516776미용업05_18_01_P33200003320000-204-2002-0001920020508<NA>3폐업2폐업20040619<NA><NA><NA>051 338494913.20616830부산광역시 북구 만덕동 823-8번지 베르빌아파트 101동 2309호<NA><NA>은백20041119000000I2018-08-31 23:59:59.0일반미용업385448.635322192363.588239미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1716517166미용업05_18_01_P33100003310000-204-2005-0001820050512<NA>3폐업2폐업20100503<NA><NA><NA>051 622131854.33608805부산광역시 남구 대연동 60-47번지<NA><NA>지펌(G-PERM)미용실 부경대점20100329102657I2018-08-31 23:59:59.0일반미용업391417.159549183838.441676미용업4<NA>22<NA><NA><NA><NA><NA>N8<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1017110172미용업05_18_01_P33700003370000-212-2018-0000720180917<NA>1영업/정상1영업<NA><NA><NA><NA><NA>38.40611751부산광역시 연제구 연산동 2220-3번지 주공아파트부산광역시 연제구 토현로 10, 상가나동 2층 206호 (연산동, 주공아파트)47573강이진20181002144927U2018-10-04 02:36:17.0피부미용업392211.2253188714.202101미용업(피부)3122<NA><NA>000N0<NA><NA><NA>임대00002N<NA>
516517미용업05_18_01_P33300003330000-211-1999-0000119991112<NA>1영업/정상1영업<NA><NA><NA><NA>051 781 432152.90612831부산광역시 해운대구 재송동 1077-8번지부산광역시 해운대구 해운대로123번길 35, 1층 102호 (재송동, 센텀장광리버빌)48055장현주 헤어필20170630111441I2018-08-31 23:59:59.0일반미용업393294.356045189521.721103미용업(일반)000000000N3<NA><NA><NA><NA>0<NA><NA>00N<NA>
1483514836미용업05_18_01_P33400003340000-211-2014-0003820141117<NA>3폐업2폐업20161228<NA><NA><NA>051 206 900742.84604851부산광역시 사하구 하단동 497-24번지 103호부산광역시 사하구 낙동대로516번길 5, 103호 (하단동)49324매쉬헤어20141117152013I2018-08-31 23:59:59.0일반미용업379147.272723180885.627963미용업(일반)801<NA><NA><NA>000N4<NA><NA><NA><NA>00000N<NA>
1053910540미용업05_18_01_P33500003350000-211-2018-0002820181010<NA>1영업/정상1영업<NA><NA><NA><NA><NA>40.68609817부산광역시 금정구 부곡동 64-23번지 퀸즈더블유장전역부산광역시 금정구 부곡온천천로 190, 1층 113호 (부곡동, 퀸즈더블유장전역)46274안헤어20181018155214U2018-10-20 02:36:40.0일반미용업390222.855896195655.332589미용업(일반)2501100000N2<NA><NA><NA><NA>00000N<NA>
1419814199미용업05_18_01_P33700003370000-216-2014-0000120141212<NA>3폐업2폐업20200115<NA><NA><NA><NA>26.22611820부산광역시 연제구 연산동 587-8번지부산광역시 연제구 중앙대로 1130, 2층 206호 (연산동, SK뷰)47520MW 메이크업 앤왁싱20200115155750U2020-01-17 02:40:00.0메이크업업389510.788094189669.571671미용업(일반), 미용업(피부)2032200000N3<NA><NA><NA><NA>0<NA><NA>01N<NA>
15501551미용업05_18_01_P33300003330000-204-2004-0001720040305<NA>1영업/정상1영업<NA><NA><NA><NA>051 781053512.49612812부산광역시 해운대구 반여동 1291-171부산광역시 해운대구 재반로226번길 13-14 (반여동)48027민헤어나라20201125153239U2020-11-27 02:40:00.0일반미용업394104.457727190775.043204미용업4111<NA><NA><NA><NA><NA>N3<NA><NA><NA>임대<NA><NA><NA><NA><NA>N<NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
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