Overview

Dataset statistics

Number of variables51
Number of observations10000
Missing cells99487
Missing cells (%)19.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 MiB
Average record size in memory449.0 B

Variable types

Numeric16
Categorical20
Text7
Unsupported5
DateTime1
Boolean2

Dataset

Description2021-06-01
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
사용시작지하층 is highly imbalanced (52.6%)Imbalance
사용끝지하층 is highly imbalanced (56.8%)Imbalance
조건부허가시작일자 is highly imbalanced (99.8%)Imbalance
조건부허가종료일자 is highly imbalanced (99.7%)Imbalance
남성종사자수 is highly imbalanced (58.8%)Imbalance
다중이용업소여부 is highly imbalanced (99.3%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 4984 (49.8%) 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 3011 (30.1%) missing valuesMissing
소재지우편번호 has 111 (1.1%) missing valuesMissing
도로명전체주소 has 2996 (30.0%) missing valuesMissing
도로명우편번호 has 3055 (30.6%) missing valuesMissing
좌표정보(x) has 303 (3.0%) missing valuesMissing
좌표정보(y) has 303 (3.0%) missing valuesMissing
건물지상층수 has 2009 (20.1%) missing valuesMissing
건물지하층수 has 2930 (29.3%) missing valuesMissing
사용시작지상층 has 2621 (26.2%) missing valuesMissing
사용끝지상층 has 4082 (40.8%) missing valuesMissing
발한실여부 has 138 (1.4%) missing valuesMissing
의자수 has 758 (7.6%) missing valuesMissing
조건부허가신고사유 has 9998 (> 99.9%) missing valuesMissing
여성종사자수 has 7540 (75.4%) missing valuesMissing
침대수 has 4601 (46.0%) missing valuesMissing
Unnamed: 50 has 10000 (100.0%) missing valuesMissing
인허가일자 is highly skewed (γ1 = -33.18632991)Skewed
폐업일자 is highly skewed (γ1 = -48.89620225)Skewed
사용끝지상층 is highly skewed (γ1 = 55.38329537)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 2937 (29.4%) zerosZeros
건물지하층수 has 5194 (51.9%) zerosZeros
사용시작지상층 has 1510 (15.1%) zerosZeros
사용끝지상층 has 1042 (10.4%) zerosZeros
의자수 has 1415 (14.1%) zerosZeros
여성종사자수 has 2303 (23.0%) zerosZeros
침대수 has 3675 (36.8%) zerosZeros

Reproduction

Analysis started2024-04-17 03:26:15.228686
Analysis finished2024-04-17 03:26:17.474239
Duration2.25 seconds
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%
Mean11534.54
Minimum1
Maximum23120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:17.528278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1111.95
Q15804.25
median11523.5
Q317306.25
95-th percentile21965.05
Maximum23120
Range23119
Interquartile range (IQR)11502

Descriptive statistics

Standard deviation6669.1858
Coefficient of variation (CV)0.57819261
Kurtosis-1.1951696
Mean11534.54
Median Absolute Deviation (MAD)5749
Skewness0.0037805373
Sum1.153454 × 108
Variance44478040
MonotonicityNot monotonic
2024-04-17T12:26:17.627710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3871 1
 
< 0.1%
20820 1
 
< 0.1%
12328 1
 
< 0.1%
16891 1
 
< 0.1%
16086 1
 
< 0.1%
3303 1
 
< 0.1%
8733 1
 
< 0.1%
10455 1
 
< 0.1%
6401 1
 
< 0.1%
6175 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
23120 1
< 0.1%
23118 1
< 0.1%
23117 1
< 0.1%
23114 1
< 0.1%
23112 1
< 0.1%
23111 1
< 0.1%
23106 1
< 0.1%
23104 1
< 0.1%
23103 1
< 0.1%
23098 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

2024-04-17T12:26:17.718158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:17.784805image/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

2024-04-17T12:26:17.853949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:17.925304image/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%
Mean3325466
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:18.009470image/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 deviation37754.541
Coefficient of variation (CV)0.011353158
Kurtosis-0.74296141
Mean3325466
Median Absolute Deviation (MAD)30000
Skewness0.042183223
Sum3.325466 × 1010
Variance1.4254054 × 109
MonotonicityNot monotonic
2024-04-17T12:26:18.114438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 1260
12.6%
3290000 1241
12.4%
3340000 986
9.9%
3300000 865
8.6%
3310000 777
7.8%
3320000 750
7.5%
3380000 726
7.3%
3370000 718
7.2%
3350000 715
7.1%
3390000 426
 
4.3%
Other values (6) 1536
15.4%
ValueCountFrequency (%)
3250000 347
 
3.5%
3260000 269
 
2.7%
3270000 278
 
2.8%
3280000 318
 
3.2%
3290000 1241
12.4%
3300000 865
8.6%
3310000 777
7.8%
3320000 750
7.5%
3330000 1260
12.6%
3340000 986
9.9%
ValueCountFrequency (%)
3400000 200
 
2.0%
3390000 426
 
4.3%
3380000 726
7.3%
3370000 718
7.2%
3360000 124
 
1.2%
3350000 715
7.1%
3340000 986
9.9%
3330000 1260
12.6%
3320000 750
7.5%
3310000 777
7.8%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T12:26:18.274591image/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 row3260000-204-1991-00082
2nd row3330000-213-2012-00011
3rd row3340000-204-1998-00222
4th row3280000-212-2009-00003
5th row3320000-212-2009-00020
ValueCountFrequency (%)
3260000-204-1991-00082 1
 
< 0.1%
3380000-224-2009-00001 1
 
< 0.1%
3280000-212-2018-00002 1
 
< 0.1%
3330000-212-2011-00008 1
 
< 0.1%
3290000-204-2001-01020 1
 
< 0.1%
3340000-204-1989-01173 1
 
< 0.1%
3350000-204-2007-00012 1
 
< 0.1%
3300000-211-2019-00022 1
 
< 0.1%
3360000-211-2002-00002 1
 
< 0.1%
3250000-211-2015-00004 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-17T12:26:18.527740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 87619
39.8%
- 30000
 
13.6%
2 26317
 
12.0%
1 22269
 
10.1%
3 21977
 
10.0%
9 8881
 
4.0%
4 7983
 
3.6%
8 4292
 
2.0%
5 4131
 
1.9%
7 3628
 
1.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 87619
46.1%
2 26317
 
13.9%
1 22269
 
11.7%
3 21977
 
11.6%
9 8881
 
4.7%
4 7983
 
4.2%
8 4292
 
2.3%
5 4131
 
2.2%
7 3628
 
1.9%
6 2903
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 87619
39.8%
- 30000
 
13.6%
2 26317
 
12.0%
1 22269
 
10.1%
3 21977
 
10.0%
9 8881
 
4.0%
4 7983
 
3.6%
8 4292
 
2.0%
5 4131
 
1.9%
7 3628
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 87619
39.8%
- 30000
 
13.6%
2 26317
 
12.0%
1 22269
 
10.1%
3 21977
 
10.0%
9 8881
 
4.0%
4 7983
 
3.6%
8 4292
 
2.0%
5 4131
 
1.9%
7 3628
 
1.6%

인허가일자
Real number (ℝ)

SKEWED 

Distinct5759
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20053333
Minimum9980406
Maximum20210430
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:18.650025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9980406
5-th percentile19840707
Q119980916
median20080321
Q320151029
95-th percentile20200213
Maximum20210430
Range10230024
Interquartile range (IQR)170113.25

Descriptive statistics

Standard deviation183579.45
Coefficient of variation (CV)0.0091545607
Kurtosis1807.8417
Mean20053333
Median Absolute Deviation (MAD)80386
Skewness-33.18633
Sum2.0053333 × 1011
Variance3.3701414 × 1010
MonotonicityNot monotonic
2024-04-17T12:26:18.778191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000712 26
 
0.3%
20030225 14
 
0.1%
20030224 14
 
0.1%
20000415 14
 
0.1%
20001114 13
 
0.1%
19980930 11
 
0.1%
20020508 10
 
0.1%
20180305 9
 
0.1%
20191122 9
 
0.1%
20010927 8
 
0.1%
Other values (5749) 9872
98.7%
ValueCountFrequency (%)
9980406 1
 
< 0.1%
9990827 1
 
< 0.1%
19581017 2
< 0.1%
19630110 4
< 0.1%
19630318 1
 
< 0.1%
19630520 1
 
< 0.1%
19630617 1
 
< 0.1%
19630731 1
 
< 0.1%
19631111 1
 
< 0.1%
19650427 1
 
< 0.1%
ValueCountFrequency (%)
20210430 1
 
< 0.1%
20210429 2
 
< 0.1%
20210428 2
 
< 0.1%
20210427 7
0.1%
20210423 1
 
< 0.1%
20210422 1
 
< 0.1%
20210420 1
 
< 0.1%
20210419 4
< 0.1%
20210415 3
< 0.1%
20210414 3
< 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
5016 
1
4984 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 5016
50.2%
1 4984
49.8%

Length

2024-04-17T12:26:18.891239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:18.980294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5016
50.2%
1 4984
49.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5016 
영업/정상
4984 

Length

Max length5
Median length2
Mean length3.4952
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5016
50.2%
영업/정상 4984
49.8%

Length

2024-04-17T12:26:19.059096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:19.133601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5016
50.2%
영업/정상 4984
49.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
5016 
1
4984 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 5016
50.2%
1 4984
49.8%

Length

2024-04-17T12:26:19.224262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:19.313502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5016
50.2%
1 4984
49.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
5016 
영업
4984 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5016
50.2%
영업 4984
49.8%

Length

2024-04-17T12:26:19.392331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:19.460471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5016
50.2%
영업 4984
49.8%

폐업일자
Real number (ℝ)

MISSING  SKEWED 

Distinct2920
Distinct (%)58.2%
Missing4984
Missing (%)49.8%
Infinite0
Infinite (%)0.0%
Mean20094058
Minimum11111111
Maximum20210429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:19.543992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11111111
5-th percentile19991128
Q120040324
median20090922
Q320160215
95-th percentile20200418
Maximum20210429
Range9099318
Interquartile range (IQR)119891.5

Descriptive statistics

Standard deviation143525.95
Coefficient of variation (CV)0.0071427061
Kurtosis3060.4773
Mean20094058
Median Absolute Deviation (MAD)59894
Skewness-48.896202
Sum1.007918 × 1011
Variance2.05997 × 1010
MonotonicityNot monotonic
2024-04-17T12:26:19.646779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030227 156
 
1.6%
20050117 69
 
0.7%
20050510 40
 
0.4%
20030226 36
 
0.4%
20010321 32
 
0.3%
20030101 30
 
0.3%
20030606 26
 
0.3%
20000531 23
 
0.2%
20021217 21
 
0.2%
20210322 21
 
0.2%
Other values (2910) 4562
45.6%
(Missing) 4984
49.8%
ValueCountFrequency (%)
11111111 1
< 0.1%
19851118 1
< 0.1%
19891116 1
< 0.1%
19900615 1
< 0.1%
19910430 1
< 0.1%
19911029 1
< 0.1%
19930209 1
< 0.1%
19930806 1
< 0.1%
19931207 1
< 0.1%
19940725 1
< 0.1%
ValueCountFrequency (%)
20210429 1
< 0.1%
20210428 1
< 0.1%
20210423 1
< 0.1%
20210422 2
< 0.1%
20210420 2
< 0.1%
20210419 1
< 0.1%
20210416 1
< 0.1%
20210415 1
< 0.1%
20210413 1
< 0.1%
20210408 1
< 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 

Distinct6215
Distinct (%)88.9%
Missing3011
Missing (%)30.1%
Memory size156.2 KiB
2024-04-17T12:26:20.111849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.640864
Min length3

Characters and Unicode

Total characters74369
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6029 ?
Unique (%)86.3%

Sample

1st row051 2473870
2nd row051 744 3358
3rd row051
4th row070 86398554
5th row051 338 7865
ValueCountFrequency (%)
051 6536
41.9%
070 130
 
0.8%
868 32
 
0.2%
727 30
 
0.2%
746 29
 
0.2%
852 27
 
0.2%
747 24
 
0.2%
701 23
 
0.1%
853 23
 
0.1%
851 22
 
0.1%
Other values (6163) 8720
55.9%
2024-04-17T12:26:20.495579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12161
16.4%
0 11267
15.2%
1 10874
14.6%
8665
11.7%
2 5665
7.6%
7 4728
 
6.4%
3 4688
 
6.3%
6 4521
 
6.1%
8 4421
 
5.9%
4 4392
 
5.9%
Other values (3) 2987
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65700
88.3%
Space Separator 8665
 
11.7%
Dash Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 12161
18.5%
0 11267
17.1%
1 10874
16.6%
2 5665
8.6%
7 4728
 
7.2%
3 4688
 
7.1%
6 4521
 
6.9%
8 4421
 
6.7%
4 4392
 
6.7%
9 2983
 
4.5%
Space Separator
ValueCountFrequency (%)
8665
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 12161
16.4%
0 11267
15.2%
1 10874
14.6%
8665
11.7%
2 5665
7.6%
7 4728
 
6.4%
3 4688
 
6.3%
6 4521
 
6.1%
8 4421
 
5.9%
4 4392
 
5.9%
Other values (3) 2987
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 12161
16.4%
0 11267
15.2%
1 10874
14.6%
8665
11.7%
2 5665
7.6%
7 4728
 
6.4%
3 4688
 
6.3%
6 4521
 
6.1%
8 4421
 
5.9%
4 4392
 
5.9%
Other values (3) 2987
 
4.0%

소재지면적
Text

Distinct4060
Distinct (%)40.7%
Missing34
Missing (%)0.3%
Memory size156.2 KiB
2024-04-17T12:26:20.786530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9052779
Min length3

Characters and Unicode

Total characters48886
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

Unique2532 ?
Unique (%)25.4%

Sample

1st row31.90
2nd row28.20
3rd row.00
4th row24.70
5th row35.12
ValueCountFrequency (%)
00 788
 
7.9%
33.00 136
 
1.4%
30.00 66
 
0.7%
24.00 62
 
0.6%
20.00 60
 
0.6%
18.00 51
 
0.5%
27.00 47
 
0.5%
16.00 44
 
0.4%
26.40 43
 
0.4%
16.50 41
 
0.4%
Other values (4050) 8628
86.6%
2024-04-17T12:26:21.175568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9966
20.4%
0 8858
18.1%
2 4969
10.2%
1 4814
9.8%
3 3751
 
7.7%
4 3377
 
6.9%
5 3056
 
6.3%
6 2972
 
6.1%
8 2661
 
5.4%
7 2234
 
4.6%
Other values (2) 2228
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38917
79.6%
Other Punctuation 9969
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8858
22.8%
2 4969
12.8%
1 4814
12.4%
3 3751
9.6%
4 3377
 
8.7%
5 3056
 
7.9%
6 2972
 
7.6%
8 2661
 
6.8%
7 2234
 
5.7%
9 2225
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 9966
> 99.9%
, 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 48886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9966
20.4%
0 8858
18.1%
2 4969
10.2%
1 4814
9.8%
3 3751
 
7.7%
4 3377
 
6.9%
5 3056
 
6.3%
6 2972
 
6.1%
8 2661
 
5.4%
7 2234
 
4.6%
Other values (2) 2228
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9966
20.4%
0 8858
18.1%
2 4969
10.2%
1 4814
9.8%
3 3751
 
7.7%
4 3377
 
6.9%
5 3056
 
6.3%
6 2972
 
6.1%
8 2661
 
5.4%
7 2234
 
4.6%
Other values (2) 2228
 
4.6%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct857
Distinct (%)8.7%
Missing111
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean610694.43
Minimum361856
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:21.295013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum361856
5-th percentile601818
Q1607813
median611820
Q3614810
95-th percentile617813
Maximum619953
Range258097
Interquartile range (IQR)6997

Descriptive statistics

Standard deviation5409.7149
Coefficient of variation (CV)0.0088583007
Kurtosis451.45882
Mean610694.43
Median Absolute Deviation (MAD)3030
Skewness-10.098142
Sum6.0391573 × 109
Variance29265016
MonotonicityNot monotonic
2024-04-17T12:26:21.410248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
609839 118
 
1.2%
614847 94
 
0.9%
604851 92
 
0.9%
616852 75
 
0.8%
612824 72
 
0.7%
608805 68
 
0.7%
612842 66
 
0.7%
614845 63
 
0.6%
614846 62
 
0.6%
612847 58
 
0.6%
Other values (847) 9121
91.2%
(Missing) 111
 
1.1%
ValueCountFrequency (%)
361856 1
 
< 0.1%
600012 1
 
< 0.1%
600013 6
0.1%
600015 2
 
< 0.1%
600016 4
< 0.1%
600017 1
 
< 0.1%
600021 2
 
< 0.1%
600022 2
 
< 0.1%
600023 4
< 0.1%
600024 1
 
< 0.1%
ValueCountFrequency (%)
619953 3
 
< 0.1%
619952 4
 
< 0.1%
619951 1
 
< 0.1%
619913 4
 
< 0.1%
619912 6
 
0.1%
619911 1
 
< 0.1%
619906 4
 
< 0.1%
619905 22
0.2%
619904 1
 
< 0.1%
619903 27
0.3%

소재지전체주소
Text

Distinct9324
Distinct (%)93.4%
Missing13
Missing (%)0.1%
Memory size156.2 KiB
2024-04-17T12:26:21.681007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length53
Mean length24.887053
Min length16

Characters and Unicode

Total characters248547
Distinct characters520
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8753 ?
Unique (%)87.6%

Sample

1st row부산광역시 서구 동대신동2가 390-8번지
2nd row부산광역시 해운대구 우동 829-75번지
3rd row부산광역시 사하구 괴정동 494-32번지
4th row부산광역시 영도구 동삼동 356-19번지
5th row부산광역시 북구 만덕동 216-7번지 그린코아@ 상가동 3-3호
ValueCountFrequency (%)
부산광역시 9986
 
21.2%
해운대구 1260
 
2.7%
부산진구 1234
 
2.6%
사하구 985
 
2.1%
t통b반 922
 
2.0%
동래구 864
 
1.8%
남구 777
 
1.7%
북구 757
 
1.6%
수영구 726
 
1.5%
금정구 715
 
1.5%
Other values (10191) 28826
61.3%
2024-04-17T12:26:22.078591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37082
 
14.9%
산 12085
 
4.9%
부 12073
 
4.9%
동 12030
 
4.8%
1 11896
 
4.8%
광 10389
 
4.2%
구 10182
 
4.1%
시 10138
 
4.1%
역 10001
 
4.0%
- 9012
 
3.6%
Other values (510) 113659
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146554
59.0%
Decimal Number 52498
 
21.1%
Space Separator 37082
 
14.9%
Dash Punctuation 9012
 
3.6%
Uppercase Letter 2303
 
0.9%
Open Punctuation 385
 
0.2%
Close Punctuation 384
 
0.2%
Other Punctuation 250
 
0.1%
Lowercase Letter 65
 
< 0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 12085
 
8.2%
부 12073
 
8.2%
동 12030
 
8.2%
광 10389
 
7.1%
구 10182
 
6.9%
시 10138
 
6.9%
역 10001
 
6.8%
지 8694
 
5.9%
번 8290
 
5.7%
대 2329
 
1.6%
Other values (448) 50343
34.4%
Uppercase Letter
ValueCountFrequency (%)
B 990
43.0%
T 933
40.5%
A 76
 
3.3%
S 56
 
2.4%
K 47
 
2.0%
E 25
 
1.1%
I 24
 
1.0%
G 23
 
1.0%
H 21
 
0.9%
L 16
 
0.7%
Other values (15) 92
 
4.0%
Lowercase Letter
ValueCountFrequency (%)
e 12
18.5%
l 12
18.5%
s 10
15.4%
i 8
12.3%
k 4
 
6.2%
o 3
 
4.6%
t 3
 
4.6%
b 2
 
3.1%
d 2
 
3.1%
n 2
 
3.1%
Other values (6) 7
10.8%
Decimal Number
ValueCountFrequency (%)
1 11896
22.7%
2 7367
14.0%
3 5920
11.3%
4 4858
9.3%
0 4406
 
8.4%
5 4387
 
8.4%
6 3689
 
7.0%
7 3597
 
6.9%
8 3292
 
6.3%
9 3086
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 198
79.2%
@ 31
 
12.4%
. 13
 
5.2%
/ 6
 
2.4%
· 2
 
0.8%
Space Separator
ValueCountFrequency (%)
37082
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9012
100.0%
Open Punctuation
ValueCountFrequency (%)
( 385
100.0%
Close Punctuation
ValueCountFrequency (%)
) 384
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146554
59.0%
Common 99623
40.1%
Latin 2370
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 12085
 
8.2%
부 12073
 
8.2%
동 12030
 
8.2%
광 10389
 
7.1%
구 10182
 
6.9%
시 10138
 
6.9%
역 10001
 
6.8%
지 8694
 
5.9%
번 8290
 
5.7%
대 2329
 
1.6%
Other values (448) 50343
34.4%
Latin
ValueCountFrequency (%)
B 990
41.8%
T 933
39.4%
A 76
 
3.2%
S 56
 
2.4%
K 47
 
2.0%
E 25
 
1.1%
I 24
 
1.0%
G 23
 
1.0%
H 21
 
0.9%
L 16
 
0.7%
Other values (32) 159
 
6.7%
Common
ValueCountFrequency (%)
37082
37.2%
1 11896
 
11.9%
- 9012
 
9.0%
2 7367
 
7.4%
3 5920
 
5.9%
4 4858
 
4.9%
0 4406
 
4.4%
5 4387
 
4.4%
6 3689
 
3.7%
7 3597
 
3.6%
Other values (10) 7409
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146553
59.0%
ASCII 101989
41.0%
None 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37082
36.4%
1 11896
 
11.7%
- 9012
 
8.8%
2 7367
 
7.2%
3 5920
 
5.8%
4 4858
 
4.8%
0 4406
 
4.3%
5 4387
 
4.3%
6 3689
 
3.6%
7 3597
 
3.5%
Other values (50) 9775
 
9.6%
Hangul
ValueCountFrequency (%)
산 12085
 
8.2%
부 12073
 
8.2%
동 12030
 
8.2%
광 10389
 
7.1%
구 10182
 
6.9%
시 10138
 
6.9%
역 10001
 
6.8%
지 8694
 
5.9%
번 8290
 
5.7%
대 2329
 
1.6%
Other values (447) 50342
34.4%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Compat Jamo
ValueCountFrequency (%)
ㅀ 1
100.0%

도로명전체주소
Text

MISSING 

Distinct6805
Distinct (%)97.2%
Missing2996
Missing (%)30.0%
Memory size156.2 KiB
2024-04-17T12:26:22.396028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length55
Mean length31.976728
Min length18

Characters and Unicode

Total characters223965
Distinct characters535
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

Unique6610 ?
Unique (%)94.4%

Sample

1st row부산광역시 서구 구덕로296번길 23 (동대신동2가)
2nd row부산광역시 해운대구 해운대로 543-1, 1층 (우동)
3rd row부산광역시 북구 덕천로234번길 47, 상가동 3-3호 (만덕동, 그린코아@)
4th row부산광역시 사하구 낙동대로 482-1, 2층 (하단동)
5th row부산광역시 기장군 정관읍 산단1로 124, 1층
ValueCountFrequency (%)
부산광역시 7003
 
16.1%
1층 1763
 
4.0%
부산진구 998
 
2.3%
2층 968
 
2.2%
해운대구 818
 
1.9%
동래구 627
 
1.4%
사하구 627
 
1.4%
남구 534
 
1.2%
수영구 524
 
1.2%
금정구 512
 
1.2%
Other values (5612) 29192
67.0%
2024-04-17T12:26:22.821470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36567
 
16.3%
동 9624
 
4.3%
1 9433
 
4.2%
부 8890
 
4.0%
산 8719
 
3.9%
광 7540
 
3.4%
시 7471
 
3.3%
구 7201
 
3.2%
역 7015
 
3.1%
) 6967
 
3.1%
Other values (525) 114538
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129222
57.7%
Space Separator 36567
 
16.3%
Decimal Number 36399
 
16.3%
Close Punctuation 6967
 
3.1%
Open Punctuation 6966
 
3.1%
Other Punctuation 6112
 
2.7%
Dash Punctuation 1125
 
0.5%
Uppercase Letter 511
 
0.2%
Lowercase Letter 66
 
< 0.1%
Math Symbol 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9624
 
7.4%
부 8890
 
6.9%
산 8719
 
6.7%
광 7540
 
5.8%
시 7471
 
5.8%
구 7201
 
5.6%
역 7015
 
5.4%
로 6864
 
5.3%
층 3566
 
2.8%
길 3447
 
2.7%
Other values (464) 58885
45.6%
Uppercase Letter
ValueCountFrequency (%)
B 105
20.5%
A 91
17.8%
S 64
12.5%
K 50
9.8%
E 28
 
5.5%
H 21
 
4.1%
I 21
 
4.1%
C 16
 
3.1%
G 14
 
2.7%
Y 12
 
2.3%
Other values (14) 89
17.4%
Lowercase Letter
ValueCountFrequency (%)
e 14
21.2%
l 12
18.2%
s 10
15.2%
i 8
12.1%
k 6
9.1%
o 3
 
4.5%
t 3
 
4.5%
n 2
 
3.0%
w 2
 
3.0%
a 2
 
3.0%
Other values (4) 4
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 9433
25.9%
2 6141
16.9%
3 3986
11.0%
0 3578
 
9.8%
4 2901
 
8.0%
5 2531
 
7.0%
6 2242
 
6.2%
8 1949
 
5.4%
7 1910
 
5.2%
9 1728
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 6079
99.5%
@ 22
 
0.4%
. 5
 
0.1%
/ 3
 
< 0.1%
· 2
 
< 0.1%
& 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 27
96.4%
～ 1
 
3.6%
Space Separator
ValueCountFrequency (%)
36567
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6967
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6966
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1125
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129222
57.7%
Common 94164
42.0%
Latin 579
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9624
 
7.4%
부 8890
 
6.9%
산 8719
 
6.7%
광 7540
 
5.8%
시 7471
 
5.8%
구 7201
 
5.6%
역 7015
 
5.4%
로 6864
 
5.3%
층 3566
 
2.8%
길 3447
 
2.7%
Other values (464) 58885
45.6%
Latin
ValueCountFrequency (%)
B 105
18.1%
A 91
15.7%
S 64
11.1%
K 50
 
8.6%
E 28
 
4.8%
H 21
 
3.6%
I 21
 
3.6%
C 16
 
2.8%
e 14
 
2.4%
G 14
 
2.4%
Other values (29) 155
26.8%
Common
ValueCountFrequency (%)
36567
38.8%
1 9433
 
10.0%
) 6967
 
7.4%
( 6966
 
7.4%
2 6141
 
6.5%
, 6079
 
6.5%
3 3986
 
4.2%
0 3578
 
3.8%
4 2901
 
3.1%
5 2531
 
2.7%
Other values (12) 9015
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129222
57.7%
ASCII 94738
42.3%
None 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36567
38.6%
1 9433
 
10.0%
) 6967
 
7.4%
( 6966
 
7.4%
2 6141
 
6.5%
, 6079
 
6.4%
3 3986
 
4.2%
0 3578
 
3.8%
4 2901
 
3.1%
5 2531
 
2.7%
Other values (48) 9589
 
10.1%
Hangul
ValueCountFrequency (%)
동 9624
 
7.4%
부 8890
 
6.9%
산 8719
 
6.7%
광 7540
 
5.8%
시 7471
 
5.8%
구 7201
 
5.6%
역 7015
 
5.4%
로 6864
 
5.3%
층 3566
 
2.8%
길 3447
 
2.7%
Other values (464) 58885
45.6%
None
ValueCountFrequency (%)
· 2
66.7%
～ 1
33.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct1582
Distinct (%)22.8%
Missing3055
Missing (%)30.6%
Infinite0
Infinite (%)0.0%
Mean47805.435
Minimum28465
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:22.942921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28465
5-th percentile46245
Q147146
median47842
Q348493
95-th percentile49382
Maximum49525
Range21060
Interquartile range (IQR)1347

Descriptive statistics

Standard deviation987.8022
Coefficient of variation (CV)0.020662969
Kurtosis20.051192
Mean47805.435
Median Absolute Deviation (MAD)663
Skewness-1.0916922
Sum3.3200874 × 108
Variance975753.19
MonotonicityNot monotonic
2024-04-17T12:26:23.044918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46726 44
 
0.4%
48111 38
 
0.4%
48060 38
 
0.4%
48059 34
 
0.3%
46291 33
 
0.3%
48947 32
 
0.3%
48110 30
 
0.3%
47286 29
 
0.3%
46526 28
 
0.3%
47247 28
 
0.3%
Other values (1572) 6611
66.1%
(Missing) 3055
30.6%
ValueCountFrequency (%)
28465 1
 
< 0.1%
46002 1
 
< 0.1%
46007 7
 
0.1%
46008 19
0.2%
46009 1
 
< 0.1%
46010 2
 
< 0.1%
46011 1
 
< 0.1%
46012 5
 
0.1%
46013 3
 
< 0.1%
46015 13
0.1%
ValueCountFrequency (%)
49525 3
 
< 0.1%
49524 2
 
< 0.1%
49523 2
 
< 0.1%
49522 2
 
< 0.1%
49521 1
 
< 0.1%
49520 10
0.1%
49519 9
0.1%
49518 8
0.1%
49516 1
 
< 0.1%
49515 11
0.1%

사업장명
Text

Distinct8194
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-17T12:26:23.310331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length5.5707
Min length1

Characters and Unicode

Total characters55707
Distinct characters902
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7274 ?
Unique (%)72.7%

Sample

1st row수림헤어샵
2nd row서지수 미용실
3rd row챠리미용실
4th row나띠르피부관리실
5th row백지영에스테틱
ValueCountFrequency (%)
미용실 301
 
2.4%
헤어 269
 
2.1%
네일 101
 
0.8%
에스테틱 100
 
0.8%
헤어샵 88
 
0.7%
hair 62
 
0.5%
뷰티 53
 
0.4%
nail 47
 
0.4%
더 46
 
0.4%
by 30
 
0.2%
Other values (8194) 11512
91.3%
2024-04-17T12:26:23.701319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 3572
 
6.4%
헤 3510
 
6.3%
2611
 
4.7%
미 1862
 
3.3%
스 1331
 
2.4%
리 1160
 
2.1%
실 1119
 
2.0%
용 1097
 
2.0%
이 1042
 
1.9%
일 777
 
1.4%
Other values (892) 37626
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46876
84.1%
Space Separator 2611
 
4.7%
Lowercase Letter 2335
 
4.2%
Uppercase Letter 2094
 
3.8%
Close Punctuation 580
 
1.0%
Open Punctuation 579
 
1.0%
Other Punctuation 335
 
0.6%
Decimal Number 252
 
0.5%
Dash Punctuation 31
 
0.1%
Connector Punctuation 6
 
< 0.1%
Other values (4) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 3572
 
7.6%
헤 3510
 
7.5%
미 1862
 
4.0%
스 1331
 
2.8%
리 1160
 
2.5%
실 1119
 
2.4%
용 1097
 
2.3%
이 1042
 
2.2%
일 777
 
1.7%
네 750
 
1.6%
Other values (805) 30656
65.4%
Lowercase Letter
ValueCountFrequency (%)
a 313
13.4%
e 254
10.9%
i 252
10.8%
n 204
8.7%
o 189
 
8.1%
l 181
 
7.8%
r 127
 
5.4%
y 115
 
4.9%
h 107
 
4.6%
s 92
 
3.9%
Other values (16) 501
21.5%
Uppercase Letter
ValueCountFrequency (%)
A 222
 
10.6%
N 163
 
7.8%
I 151
 
7.2%
S 148
 
7.1%
H 132
 
6.3%
M 127
 
6.1%
L 124
 
5.9%
E 122
 
5.8%
B 110
 
5.3%
R 104
 
5.0%
Other values (16) 691
33.0%
Other Punctuation
ValueCountFrequency (%)
& 126
37.6%
. 76
22.7%
, 43
 
12.8%
# 40
 
11.9%
' 23
 
6.9%
: 10
 
3.0%
· 5
 
1.5%
? 3
 
0.9%
＃ 3
 
0.9%
/ 2
 
0.6%
Other values (3) 4
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 61
24.2%
2 49
19.4%
0 45
17.9%
9 24
 
9.5%
3 18
 
7.1%
7 17
 
6.7%
5 14
 
5.6%
4 11
 
4.4%
8 9
 
3.6%
6 4
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 578
99.7%
] 2
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 577
99.7%
[ 2
 
0.3%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2611
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Other Number
ValueCountFrequency (%)
₂ 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46841
84.1%
Latin 4429
 
8.0%
Common 4402
 
7.9%
Han 35
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 3572
 
7.6%
헤 3510
 
7.5%
미 1862
 
4.0%
스 1331
 
2.8%
리 1160
 
2.5%
실 1119
 
2.4%
용 1097
 
2.3%
이 1042
 
2.2%
일 777
 
1.7%
네 750
 
1.6%
Other values (791) 30621
65.4%
Latin
ValueCountFrequency (%)
a 313
 
7.1%
e 254
 
5.7%
i 252
 
5.7%
A 222
 
5.0%
n 204
 
4.6%
o 189
 
4.3%
l 181
 
4.1%
N 163
 
3.7%
I 151
 
3.4%
S 148
 
3.3%
Other values (42) 2352
53.1%
Common
ValueCountFrequency (%)
2611
59.3%
) 578
 
13.1%
( 577
 
13.1%
& 126
 
2.9%
. 76
 
1.7%
1 61
 
1.4%
2 49
 
1.1%
0 45
 
1.0%
, 43
 
1.0%
# 40
 
0.9%
Other values (25) 196
 
4.5%
Han
ValueCountFrequency (%)
美 20
57.1%
空 2
 
5.7%
間 2
 
5.7%
愛 1
 
2.9%
安 1
 
2.9%
白 1
 
2.9%
毛 1
 
2.9%
裕 1
 
2.9%
場 1
 
2.9%
水 1
 
2.9%
Other values (4) 4
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46841
84.1%
ASCII 8821
 
15.8%
CJK 35
 
0.1%
None 10
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 3572
 
7.6%
헤 3510
 
7.5%
미 1862
 
4.0%
스 1331
 
2.8%
리 1160
 
2.5%
실 1119
 
2.4%
용 1097
 
2.3%
이 1042
 
2.2%
일 777
 
1.7%
네 750
 
1.6%
Other values (791) 30621
65.4%
ASCII
ValueCountFrequency (%)
2611
29.6%
) 578
 
6.6%
( 577
 
6.5%
a 313
 
3.5%
e 254
 
2.9%
i 252
 
2.9%
A 222
 
2.5%
n 204
 
2.3%
o 189
 
2.1%
l 181
 
2.1%
Other values (73) 3440
39.0%
CJK
ValueCountFrequency (%)
美 20
57.1%
空 2
 
5.7%
間 2
 
5.7%
愛 1
 
2.9%
安 1
 
2.9%
白 1
 
2.9%
毛 1
 
2.9%
裕 1
 
2.9%
場 1
 
2.9%
水 1
 
2.9%
Other values (4) 4
 
11.4%
None
ValueCountFrequency (%)
· 5
50.0%
＃ 3
30.0%
₂ 1
 
10.0%
＆ 1
 
10.0%

최종수정시점
Real number (ℝ)

Distinct8152
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0131788 × 1013
Minimum1.9990125 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:23.813462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990125 × 1013
5-th percentile2.0010807 × 1013
Q12.0060821 × 1013
median2.0151216 × 1013
Q32.0191121 × 1013
95-th percentile2.0210204 × 1013
Maximum2.021043 × 1013
Range2.2030511 × 1011
Interquartile range (IQR)1.303002 × 1011

Descriptive statistics

Standard deviation6.9621531 × 1010
Coefficient of variation (CV)0.0034582885
Kurtosis-1.104259
Mean2.0131788 × 1013
Median Absolute Deviation (MAD)4.9212961 × 1010
Skewness-0.59880697
Sum2.0131788 × 1017
Variance4.8471576 × 1021
MonotonicityNot monotonic
2024-04-17T12:26:23.915964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030402000000 107
 
1.1%
20020823000000 42
 
0.4%
19990429000000 32
 
0.3%
20001209000000 32
 
0.3%
20040719000000 31
 
0.3%
19990420000000 30
 
0.3%
20040827000000 29
 
0.3%
20030627000000 28
 
0.3%
20030403000000 27
 
0.3%
20040102000000 26
 
0.3%
Other values (8142) 9616
96.2%
ValueCountFrequency (%)
19990125000000 3
 
< 0.1%
19990126000000 5
 
0.1%
19990222000000 3
 
< 0.1%
19990223000000 1
 
< 0.1%
19990224000000 3
 
< 0.1%
19990225000000 4
 
< 0.1%
19990226000000 1
 
< 0.1%
19990303000000 6
 
0.1%
19990304000000 13
0.1%
19990305000000 15
0.1%
ValueCountFrequency (%)
20210430110005 1
< 0.1%
20210429174110 1
< 0.1%
20210429163254 1
< 0.1%
20210429162603 1
< 0.1%
20210429160856 1
< 0.1%
20210429160514 1
< 0.1%
20210429144634 1
< 0.1%
20210429142845 1
< 0.1%
20210429141537 1
< 0.1%
20210429140841 1
< 0.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7030 
U
2970 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7030
70.3%
U 2970
29.7%

Length

2024-04-17T12:26:24.009595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:24.088527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7030
70.3%
u 2970
29.7%

데이터갱신일자
Date

Distinct988
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 00:22:57
2024-04-17T12:26:24.167758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T12:26:24.268265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반미용업
6981 
피부미용업
1880 
네일아트업
860 
메이크업업
 
175
기타
 
99

Length

Max length6
Median length5
Mean length4.9708
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반미용업 6981
69.8%
피부미용업 1880
 
18.8%
네일아트업 860
 
8.6%
메이크업업 175
 
1.8%
기타 99
 
1.0%
미용업 기타 5
 
0.1%

Length

2024-04-17T12:26:24.376501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:24.471887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반미용업 6981
69.8%
피부미용업 1880
 
18.8%
네일아트업 860
 
8.6%
메이크업업 175
 
1.7%
기타 104
 
1.0%
미용업 5
 
< 0.1%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct7477
Distinct (%)77.1%
Missing303
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean388210.78
Minimum241128.92
Maximum407824.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:24.569231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum241128.92
5-th percentile379639.13
Q1384384.6
median388614.36
Q3391815.8
95-th percentile397736.82
Maximum407824.89
Range166695.96
Interquartile range (IQR)7431.2005

Descriptive statistics

Standard deviation5569.7867
Coefficient of variation (CV)0.014347326
Kurtosis49.86277
Mean388210.78
Median Absolute Deviation (MAD)3620.8345
Skewness-1.9767934
Sum3.76448 × 109
Variance31022524
MonotonicityNot monotonic
2024-04-17T12:26:24.668534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
398237.363461482 19
 
0.2%
398491.352089522 16
 
0.2%
393239.237933586 16
 
0.2%
383412.190468328 15
 
0.1%
395388.715069604 15
 
0.1%
392474.578116018 15
 
0.1%
398320.764293408 14
 
0.1%
398330.516530402 14
 
0.1%
383934.836497921 14
 
0.1%
380398.062015138 13
 
0.1%
Other values (7467) 9546
95.5%
(Missing) 303
 
3.0%
ValueCountFrequency (%)
241128.922467 1
< 0.1%
366931.435995074 1
< 0.1%
367047.233040251 1
< 0.1%
367051.926419356 1
< 0.1%
367108.112280274 1
< 0.1%
367177.362435871 1
< 0.1%
367179.004823381 1
< 0.1%
367193.583454597 1
< 0.1%
367195.063042763 1
< 0.1%
367205.763155348 1
< 0.1%
ValueCountFrequency (%)
407824.887002439 1
< 0.1%
407739.046710947 1
< 0.1%
407556.4753504 1
< 0.1%
407446.00678665 1
< 0.1%
407161.891842701 1
< 0.1%
405370.623777615 1
< 0.1%
404194.966298269 1
< 0.1%
403981.485891989 1
< 0.1%
403822.851926784 1
< 0.1%
403804.630703364 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct7479
Distinct (%)77.1%
Missing303
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean187003.61
Minimum173942.79
Maximum349970.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:24.773936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173942.79
5-th percentile178280
Q1183162.81
median187192.55
Q3190846.96
95-th percentile195584.23
Maximum349970.06
Range176027.27
Interquartile range (IQR)7684.1533

Descriptive statistics

Standard deviation5777.6848
Coefficient of variation (CV)0.030896113
Kurtosis64.983022
Mean187003.61
Median Absolute Deviation (MAD)3716.4492
Skewness2.4857313
Sum1.813374 × 109
Variance33381642
MonotonicityNot monotonic
2024-04-17T12:26:24.895085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187720.511056894 19
 
0.2%
187644.220019205 16
 
0.2%
188619.149645081 16
 
0.2%
194288.416387155 15
 
0.1%
186268.853282623 15
 
0.1%
183052.21115244 15
 
0.1%
187928.258297607 14
 
0.1%
187771.511373596 14
 
0.1%
192378.532914385 14
 
0.1%
175314.286676535 13
 
0.1%
Other values (7469) 9546
95.5%
(Missing) 303
 
3.0%
ValueCountFrequency (%)
173942.787360397 2
< 0.1%
173961.914773076 1
 
< 0.1%
173969.719902491 1
 
< 0.1%
173994.386578688 1
 
< 0.1%
174031.935803657 3
< 0.1%
174035.700224564 1
 
< 0.1%
174096.498143437 2
< 0.1%
174101.406639044 3
< 0.1%
174106.09009853 1
 
< 0.1%
174156.617297535 1
 
< 0.1%
ValueCountFrequency (%)
349970.057043 1
 
< 0.1%
206512.517255249 1
 
< 0.1%
206353.855586145 2
 
< 0.1%
206347.031297375 1
 
< 0.1%
206298.919203021 1
 
< 0.1%
206285.479401732 1
 
< 0.1%
206248.235800687 1
 
< 0.1%
206246.675982691 1
 
< 0.1%
206242.308287228 1
 
< 0.1%
206184.609573703 5
0.1%

위생업태명
Categorical

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
미용업
3887 
미용업(일반)
2790 
미용업(피부)
951 
일반미용업
632 
미용업(손톱ㆍ발톱)
 
347
Other values (25)
1393 

Length

Max length31
Median length28
Mean length6.0253
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미용업 3887
38.9%
미용업(일반) 2790
27.9%
미용업(피부) 951
 
9.5%
일반미용업 632
 
6.3%
미용업(손톱ㆍ발톱) 347
 
3.5%
미용업(종합) 308
 
3.1%
피부미용업 225
 
2.2%
네일미용업 148
 
1.5%
종합미용업 87
 
0.9%
미용업(피부), 미용업(손톱ㆍ발톱) 75
 
0.8%
Other values (20) 550
 
5.5%

Length

2024-04-17T12:26:25.006741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미용업 4048
37.6%
미용업(일반 2926
27.2%
미용업(피부 1119
 
10.4%
일반미용업 703
 
6.5%
미용업(손톱ㆍ발톱 605
 
5.6%
미용업(종합 308
 
2.9%
피부미용업 299
 
2.8%
미용업(화장ㆍ분장 268
 
2.5%
네일미용업 253
 
2.3%
화장ㆍ분장 161
 
1.5%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct44
Distinct (%)0.6%
Missing2009
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.6264548
Minimum0
Maximum61
Zeros2937
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:25.335643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile8
Maximum61
Range61
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.1115236
Coefficient of variation (CV)1.5654272
Kurtosis40.629943
Mean2.6264548
Median Absolute Deviation (MAD)2
Skewness5.1584138
Sum20988
Variance16.904627
MonotonicityNot monotonic
2024-04-17T12:26:25.440238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 2937
29.4%
2 1324
13.2%
3 1146
 
11.5%
4 958
 
9.6%
5 493
 
4.9%
1 439
 
4.4%
6 194
 
1.9%
7 95
 
0.9%
8 69
 
0.7%
9 65
 
0.7%
Other values (34) 271
 
2.7%
(Missing) 2009
20.1%
ValueCountFrequency (%)
0 2937
29.4%
1 439
 
4.4%
2 1324
13.2%
3 1146
 
11.5%
4 958
 
9.6%
5 493
 
4.9%
6 194
 
1.9%
7 95
 
0.9%
8 69
 
0.7%
9 65
 
0.7%
ValueCountFrequency (%)
61 1
 
< 0.1%
51 2
 
< 0.1%
49 2
 
< 0.1%
47 1
 
< 0.1%
43 3
< 0.1%
42 7
0.1%
39 3
< 0.1%
38 2
 
< 0.1%
37 4
< 0.1%
36 2
 
< 0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.2%
Missing2930
Missing (%)29.3%
Infinite0
Infinite (%)0.0%
Mean0.39335219
Minimum0
Maximum30
Zeros5194
Zeros (%)51.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:25.529881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum30
Range30
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.029422
Coefficient of variation (CV)2.6170491
Kurtosis198.98301
Mean0.39335219
Median Absolute Deviation (MAD)0
Skewness9.8456037
Sum2781
Variance1.0597097
MonotonicityNot monotonic
2024-04-17T12:26:25.612311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 5194
51.9%
1 1508
 
15.1%
2 169
 
1.7%
3 83
 
0.8%
5 59
 
0.6%
4 25
 
0.2%
6 16
 
0.2%
7 5
 
0.1%
8 3
 
< 0.1%
10 3
 
< 0.1%
Other values (5) 5
 
0.1%
(Missing) 2930
29.3%
ValueCountFrequency (%)
0 5194
51.9%
1 1508
 
15.1%
2 169
 
1.7%
3 83
 
0.8%
4 25
 
0.2%
5 59
 
0.6%
6 16
 
0.2%
7 5
 
0.1%
8 3
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
14 1
 
< 0.1%
13 1
 
< 0.1%
10 3
 
< 0.1%
8 3
 
< 0.1%
7 5
 
0.1%
6 16
 
0.2%
5 59
0.6%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)0.2%
Missing2621
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean1.3427294
Minimum0
Maximum37
Zeros1510
Zeros (%)15.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:25.695052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum37
Range37
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3835104
Coefficient of variation (CV)1.0303717
Kurtosis82.003637
Mean1.3427294
Median Absolute Deviation (MAD)1
Skewness5.2621611
Sum9908
Variance1.914101
MonotonicityNot monotonic
2024-04-17T12:26:25.783218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 3592
35.9%
0 1510
15.1%
2 1427
 
14.3%
3 487
 
4.9%
4 162
 
1.6%
5 80
 
0.8%
6 50
 
0.5%
7 31
 
0.3%
9 12
 
0.1%
8 10
 
0.1%
Other values (7) 18
 
0.2%
(Missing) 2621
26.2%
ValueCountFrequency (%)
0 1510
15.1%
1 3592
35.9%
2 1427
 
14.3%
3 487
 
4.9%
4 162
 
1.6%
5 80
 
0.8%
6 50
 
0.5%
7 31
 
0.3%
8 10
 
0.1%
9 12
 
0.1%
ValueCountFrequency (%)
37 1
 
< 0.1%
24 1
 
< 0.1%
20 1
 
< 0.1%
13 2
 
< 0.1%
12 3
 
< 0.1%
11 5
 
0.1%
10 5
 
0.1%
9 12
 
0.1%
8 10
 
0.1%
7 31
0.3%

사용끝지상층
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct19
Distinct (%)0.3%
Missing4082
Missing (%)40.8%
Infinite0
Infinite (%)0.0%
Mean1.394221
Minimum0
Maximum206
Zeros1042
Zeros (%)10.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:25.871902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum206
Range206
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.974947
Coefficient of variation (CV)2.13377
Kurtosis3784.0507
Mean1.394221
Median Absolute Deviation (MAD)0
Skewness55.383295
Sum8251
Variance8.8503097
MonotonicityNot monotonic
2024-04-17T12:26:25.966163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 3045
30.4%
2 1185
 
11.8%
0 1042
 
10.4%
3 375
 
3.8%
4 123
 
1.2%
5 56
 
0.6%
6 37
 
0.4%
7 22
 
0.2%
9 8
 
0.1%
8 7
 
0.1%
Other values (9) 18
 
0.2%
(Missing) 4082
40.8%
ValueCountFrequency (%)
0 1042
 
10.4%
1 3045
30.4%
2 1185
 
11.8%
3 375
 
3.8%
4 123
 
1.2%
5 56
 
0.6%
6 37
 
0.4%
7 22
 
0.2%
8 7
 
0.1%
9 8
 
0.1%
ValueCountFrequency (%)
206 1
 
< 0.1%
24 1
 
< 0.1%
21 1
 
< 0.1%
20 1
 
< 0.1%
18 1
 
< 0.1%
13 3
 
< 0.1%
12 3
 
< 0.1%
11 1
 
< 0.1%
10 6
0.1%
9 8
0.1%

사용시작지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5656 
0
4174 
1
 
152
2
 
15
3
 
3

Length

Max length4
Median length4
Mean length2.6968
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5656
56.6%
0 4174
41.7%
1 152
 
1.5%
2 15
 
0.1%
3 3
 
< 0.1%

Length

2024-04-17T12:26:26.084106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:26.189871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5656
56.6%
0 4174
41.7%
1 152
 
1.5%
2 15
 
0.1%
3 3
 
< 0.1%

사용끝지하층
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6727 
0
3135 
1
 
123
2
 
13
3
 
2

Length

Max length4
Median length4
Mean length3.0181
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6727
67.3%
0 3135
31.4%
1 123
 
1.2%
2 13
 
0.1%
3 2
 
< 0.1%

Length

2024-04-17T12:26:26.294421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:26.379925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6727
67.3%
0 3135
31.4%
1 123
 
1.2%
2 13
 
0.1%
3 2
 
< 0.1%

한실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6713 
<NA>
3287 

Length

Max length4
Median length1
Mean length1.9861
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6713
67.1%
<NA> 3287
32.9%

Length

2024-04-17T12:26:26.483047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:26.568084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6713
67.1%
na 3287
32.9%

양실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6713 
<NA>
3287 

Length

Max length4
Median length1
Mean length1.9861
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6713
67.1%
<NA> 3287
32.9%

Length

2024-04-17T12:26:26.647605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:26.722260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6713
67.1%
na 3287
32.9%

욕실수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
6713 
<NA>
3287 

Length

Max length4
Median length1
Mean length1.9861
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 6713
67.1%
<NA> 3287
32.9%

Length

2024-04-17T12:26:26.806555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:26.880975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 6713
67.1%
na 3287
32.9%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing138
Missing (%)1.4%
Memory size97.7 KiB
False
9862 
(Missing)
 
138
ValueCountFrequency (%)
False 9862
98.6%
(Missing) 138
 
1.4%
2024-04-17T12:26:26.936975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)0.4%
Missing758
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean3.2834884
Minimum0
Maximum38
Zeros1415
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:27.007262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile8
Maximum38
Range38
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.8049005
Coefficient of variation (CV)0.85424406
Kurtosis18.574283
Mean3.2834884
Median Absolute Deviation (MAD)1
Skewness3.0431918
Sum30346
Variance7.8674668
MonotonicityNot monotonic
2024-04-17T12:26:27.108536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
3 3112
31.1%
4 1469
14.7%
2 1450
14.5%
0 1415
14.1%
5 537
 
5.4%
6 350
 
3.5%
1 223
 
2.2%
8 162
 
1.6%
7 131
 
1.3%
10 94
 
0.9%
Other values (24) 299
 
3.0%
(Missing) 758
 
7.6%
ValueCountFrequency (%)
0 1415
14.1%
1 223
 
2.2%
2 1450
14.5%
3 3112
31.1%
4 1469
14.7%
5 537
 
5.4%
6 350
 
3.5%
7 131
 
1.3%
8 162
 
1.6%
9 76
 
0.8%
ValueCountFrequency (%)
38 1
 
< 0.1%
36 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
29 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
25 1
 
< 0.1%
24 4
< 0.1%

조건부허가신고사유
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing9998
Missing (%)> 99.9%
Memory size156.2 KiB
2024-04-17T12:26:27.257056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length46.5
Mean length46.5
Min length10

Characters and Unicode

Total characters93
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row기한부영업신고기간:2006.10.19~2008.10.18 3. 이후 영업신고기간이 만료되어 연장신청을 하지않을경우 영업신고가 자동으로 말소됨
2nd row가설건축물 존치기간
ValueCountFrequency (%)
기한부영업신고기간:2006.10.19~2008.10.18 1
8.3%
3 1
8.3%
이후 1
8.3%
영업신고기간이 1
8.3%
만료되어 1
8.3%
연장신청을 1
8.3%
하지않을경우 1
8.3%
영업신고가 1
8.3%
자동으로 1
8.3%
말소됨 1
8.3%
Other values (2) 2
16.7%
2024-04-17T12:26:27.515051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15
 
16.1%
0 6
 
6.5%
. 5
 
5.4%
신 4
 
4.3%
1 4
 
4.3%
기 4
 
4.3%
고 3
 
3.2%
간 3
 
3.2%
업 3
 
3.2%
영 3
 
3.2%
Other values (38) 43
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
58.1%
Decimal Number 17
 
18.3%
Space Separator 15
 
16.1%
Other Punctuation 6
 
6.5%
Math Symbol 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 4
 
7.4%
기 4
 
7.4%
고 3
 
5.6%
간 3
 
5.6%
업 3
 
5.6%
영 3
 
5.6%
가 2
 
3.7%
을 2
 
3.7%
이 2
 
3.7%
우 1
 
1.9%
Other values (27) 27
50.0%
Decimal Number
ValueCountFrequency (%)
0 6
35.3%
1 4
23.5%
2 2
 
11.8%
8 2
 
11.8%
6 1
 
5.9%
9 1
 
5.9%
3 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
: 1
 
16.7%
Space Separator
ValueCountFrequency (%)
15
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
58.1%
Common 39
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 4
 
7.4%
기 4
 
7.4%
고 3
 
5.6%
간 3
 
5.6%
업 3
 
5.6%
영 3
 
5.6%
가 2
 
3.7%
을 2
 
3.7%
이 2
 
3.7%
우 1
 
1.9%
Other values (27) 27
50.0%
Common
ValueCountFrequency (%)
15
38.5%
0 6
 
15.4%
. 5
 
12.8%
1 4
 
10.3%
2 2
 
5.1%
8 2
 
5.1%
: 1
 
2.6%
6 1
 
2.6%
9 1
 
2.6%
~ 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
58.1%
ASCII 39
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15
38.5%
0 6
 
15.4%
. 5
 
12.8%
1 4
 
10.3%
2 2
 
5.1%
8 2
 
5.1%
: 1
 
2.6%
6 1
 
2.6%
9 1
 
2.6%
~ 1
 
2.6%
Hangul
ValueCountFrequency (%)
신 4
 
7.4%
기 4
 
7.4%
고 3
 
5.6%
간 3
 
5.6%
업 3
 
5.6%
영 3
 
5.6%
가 2
 
3.7%
을 2
 
3.7%
이 2
 
3.7%
우 1
 
1.9%
Other values (27) 27
50.0%

조건부허가시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9998 
20051019
 
1
20141231
 
1

Length

Max length8
Median length4
Mean length4.0008
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> 9998
> 99.9%
20051019 1
 
< 0.1%
20141231 1
 
< 0.1%

Length

2024-04-17T12:26:27.617371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:27.697308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9998
> 99.9%
20051019 1
 
< 0.1%
20141231 1
 
< 0.1%

조건부허가종료일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9995 
2
 
2
20061018
 
1
20161230
 
1
20080929
 
1

Length

Max length8
Median length4
Mean length4.0006
Min length1

Unique

Unique3 ?
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%
2 2
 
< 0.1%
20061018 1
 
< 0.1%
20161230 1
 
< 0.1%
20080929 1
 
< 0.1%

Length

2024-04-17T12:26:27.801762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:27.904332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9995
> 99.9%
2 2
 
< 0.1%
20061018 1
 
< 0.1%
20161230 1
 
< 0.1%
20080929 1
 
< 0.1%

건물소유구분명
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7689 
임대
2224 
자가
 
87

Length

Max length4
Median length4
Mean length3.5378
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> 7689
76.9%
임대 2224
 
22.2%
자가 87
 
0.9%

Length

2024-04-17T12:26:28.006033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:28.097808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7689
76.9%
임대 2224
 
22.2%
자가 87
 
0.9%

세탁기수
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5648 
<NA>
4351 
5
 
1

Length

Max length4
Median length1
Mean length2.3053
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 5648
56.5%
<NA> 4351
43.5%
5 1
 
< 0.1%

Length

2024-04-17T12:26:28.191570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:28.265183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5648
56.5%
na 4351
43.5%
5 1
 
< 0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.2%
Missing7540
Missing (%)75.4%
Infinite0
Infinite (%)0.0%
Mean0.080894309
Minimum0
Maximum7
Zeros2303
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:28.331637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.36794166
Coefficient of variation (CV)4.5484245
Kurtosis84.403521
Mean0.080894309
Median Absolute Deviation (MAD)0
Skewness7.426391
Sum199
Variance0.13538106
MonotonicityNot monotonic
2024-04-17T12:26:28.408442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 2303
 
23.0%
1 134
 
1.3%
2 12
 
0.1%
3 6
 
0.1%
4 4
 
< 0.1%
7 1
 
< 0.1%
(Missing) 7540
75.4%
ValueCountFrequency (%)
0 2303
23.0%
1 134
 
1.3%
2 12
 
0.1%
3 6
 
0.1%
4 4
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
4 4
 
< 0.1%
3 6
 
0.1%
2 12
 
0.1%
1 134
 
1.3%
0 2303
23.0%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
7558 
0
2417 
1
 
23
2
 
2

Length

Max length4
Median length4
Mean length3.2674
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 7558
75.6%
0 2417
 
24.2%
1 23
 
0.2%
2 2
 
< 0.1%

Length

2024-04-17T12:26:28.505084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:28.584026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7558
75.6%
0 2417
 
24.2%
1 23
 
0.2%
2 2
 
< 0.1%

회수건조수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
5416 
<NA>
4584 

Length

Max length4
Median length1
Mean length2.3752
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 5416
54.2%
<NA> 4584
45.8%

Length

2024-04-17T12:26:28.664542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T12:26:28.737581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5416
54.2%
na 4584
45.8%

침대수
Real number (ℝ)

MISSING  ZEROS 

Distinct15
Distinct (%)0.3%
Missing4601
Missing (%)46.0%
Infinite0
Infinite (%)0.0%
Mean0.9277644
Minimum0
Maximum14
Zeros3675
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-17T12:26:28.800635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7787926
Coefficient of variation (CV)1.9172891
Kurtosis8.1359352
Mean0.9277644
Median Absolute Deviation (MAD)0
Skewness2.5813892
Sum5009
Variance3.164103
MonotonicityNot monotonic
2024-04-17T12:26:28.882991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 3675
36.8%
2 537
 
5.4%
1 426
 
4.3%
3 296
 
3.0%
4 168
 
1.7%
5 110
 
1.1%
6 68
 
0.7%
7 54
 
0.5%
8 26
 
0.3%
9 15
 
0.1%
Other values (5) 24
 
0.2%
(Missing) 4601
46.0%
ValueCountFrequency (%)
0 3675
36.8%
1 426
 
4.3%
2 537
 
5.4%
3 296
 
3.0%
4 168
 
1.7%
5 110
 
1.1%
6 68
 
0.7%
7 54
 
0.5%
8 26
 
0.3%
9 15
 
0.1%
ValueCountFrequency (%)
14 2
 
< 0.1%
13 2
 
< 0.1%
12 6
 
0.1%
11 4
 
< 0.1%
10 10
 
0.1%
9 15
 
0.1%
8 26
 
0.3%
7 54
0.5%
6 68
0.7%
5 110
1.1%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size87.9 KiB
False
9994 
True
 
6
ValueCountFrequency (%)
False 9994
99.9%
True 6
 
0.1%
2024-04-17T12:26:28.959726image/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
38703871미용업05_18_01_P32600003260000-204-1991-0008219911228<NA>1영업/정상1영업<NA><NA><NA><NA>051 247387031.90602811부산광역시 서구 동대신동2가 390-8번지부산광역시 서구 구덕로296번길 23 (동대신동2가)49217수림헤어샵20140219114930I2018-08-31 23:59:59.0일반미용업383977.356634180974.183691미용업2<NA>11<NA><NA><NA><NA><NA>N4<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
63646365미용업05_18_01_P33300003330000-213-2012-0001120120424<NA>1영업/정상1영업<NA><NA><NA><NA>051 744 335828.20612822부산광역시 해운대구 우동 829-75번지부산광역시 해운대구 해운대로 543-1, 1층 (우동)48088서지수 미용실20200601112008U2020-06-04 02:40:00.0일반미용업395663.206758187124.139219미용업(종합)001<NA><NA><NA>000N3<NA><NA><NA><NA>0<NA><NA>00N<NA>
1953719538미용업05_18_01_P33400003340000-204-1998-0022219980805<NA>3폐업2폐업20030227<NA><NA><NA>051.00604812부산광역시 사하구 괴정동 494-32번지<NA><NA>챠리미용실20040719000000I2018-08-31 23:59:59.0일반미용업381584.975982179080.243261미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1987419875미용업05_18_01_P32800003280000-212-2009-0000320091211<NA>3폐업2폐업20110610<NA><NA><NA>070 8639855424.70606808부산광역시 영도구 동삼동 356-19번지<NA><NA>나띠르피부관리실20100324135327I2018-08-31 23:59:59.0피부미용업388872.891999177254.227993미용업(피부)202200000N0<NA><NA><NA><NA>0<NA><NA>02N<NA>
39333934미용업05_18_01_P33200003320000-212-2009-0002020091223<NA>1영업/정상1영업<NA><NA><NA><NA>051 338 786535.12616825부산광역시 북구 만덕동 216-7번지 그린코아@ 상가동 3-3호부산광역시 북구 덕천로234번길 47, 상가동 3-3호 (만덕동, 그린코아@)46605백지영에스테틱20160530150227I2018-08-31 23:59:59.0피부미용업384776.041134191712.881178미용업(피부)003300000N0<NA><NA><NA><NA>0<NA><NA>03N<NA>
1972319724미용업05_18_01_P32800003280000-204-2003-0001020030715<NA>3폐업2폐업20031004<NA><NA><NA><NA>31.85606819부산광역시 영도구 청학동 85번지 일신마리나상가501호<NA><NA>일신미용실20030715000000I2018-08-31 23:59:59.0일반미용업388149.688338178358.857294미용업3233<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1300413005미용업05_18_01_P33700003370000-204-2001-0084020011101<NA>3폐업2폐업20021202<NA><NA><NA>051 867717215.36611833부산광역시 연제구 연산동 1811-321번지 T통B반<NA><NA>선일20021202000000I2018-08-31 23:59:59.0일반미용업390851.552213187912.742184미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
19911992미용업05_18_01_P33400003340000-219-2018-0000120180419<NA>1영업/정상1영업<NA><NA><NA><NA>051 204 041497.60604849부산광역시 사하구 하단동 529-5번지 2층부산광역시 사하구 낙동대로 482-1, 2층 (하단동)49325매료뷰티20180419114258I2018-08-31 23:59:59.0메이크업업379338.930643180503.739388미용업(화장ㆍ분장)2022<NA><NA>000N5<NA><NA><NA>임대00005N<NA>
1087910880미용업05_18_01_P34000003400000-211-2017-0001220170703<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.40<NA>부산광역시 기장군 정관읍 달산리 1011-4번지부산광역시 기장군 정관읍 산단1로 124, 1층46024티(T)-안나속눈썹20170703161737I2018-08-31 23:59:59.0일반미용업398220.333718204273.136574미용업(일반)301100000N1<NA><NA><NA><NA>00002N<NA>
19191920미용업05_18_01_P33800003380000-211-2018-0001120180320<NA>1영업/정상1영업<NA><NA><NA><NA>051 542 055533.00613822부산광역시 수영구 망미동 431-10번지부산광역시 수영구 망미배산로10번길 28, 1층 (망미동)48210준헤어20181112132829U2018-11-14 02:36:17.0일반미용업391875.812186188252.795292미용업(일반)00<NA><NA><NA><NA>000N0<NA><NA><NA><NA>00000N<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부Unnamed: 50
1872318724미용업05_18_01_P33400003340000-204-2008-0000320080118<NA>3폐업2폐업20100610<NA><NA><NA>051 206 225321.15604815부산광역시 사하구 괴정동 1065번지 괴정자유3차아파트 상가109호<NA><NA>자유인헤어아트20080514180353I2018-08-31 23:59:59.0일반미용업381315.399349180084.414438미용업311100000<NA>3<NA><NA><NA>임대0<NA><NA><NA><NA>N<NA>
1374313744미용업05_18_01_P33300003330000-204-1974-0072019740916<NA>3폐업2폐업19990326<NA><NA><NA>051.00612040부산광역시 해운대구 송정동 364-1번지 T통B반<NA><NA>송정19990326000000I2018-08-31 23:59:59.0피부미용업400658.693024189195.244901미용업000<NA>0<NA>000N0<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1869818699미용업05_18_01_P33400003340000-204-2002-0005520020605<NA>3폐업2폐업20041213<NA><NA><NA>051 2661389.00604823부산광역시 사하구 다대동 943-14번지<NA><NA>다대미용실20030407000000I2018-08-31 23:59:59.0일반미용업379594.01394174641.982653미용업<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
2247022471미용업05_18_01_P33000003300000-211-2015-0000120150108<NA>3폐업2폐업20160704<NA><NA><NA><NA>27.00607828부산광역시 동래구 안락동 427-6번지부산광역시 동래구 명안로45번길 67-2, 1층 (안락동)47783요즘같은날20150114113845I2018-08-31 23:59:59.0일반미용업391261.519394191136.553543미용업(일반)3011<NA><NA><NA><NA><NA>N2<NA><NA><NA><NA><NA><NA><NA><NA>0N<NA>
54245425미용업05_18_01_P33200003320000-212-2009-0002620090422<NA>1영업/정상1영업<NA><NA><NA><NA>051 338 812842.18616829부산광역시 북구 만덕동 912-7번지 3층부산광역시 북구 덕천로 219, 3층 (만덕동)46571김남양코스메틱20160728164104I2018-08-31 23:59:59.0피부미용업384617.363809192058.180575미용업(피부)003300000N0<NA><NA><NA><NA>0<NA><NA>03N<NA>
21112112미용업05_18_01_P33400003340000-211-2012-0002120120327<NA>1영업/정상1영업<NA><NA><NA><NA>051 264 339424.00604822부산광역시 사하구 다대동 120-10번지 삼환@상가1동 115호부산광역시 사하구 다대로429번길 12 (다대동, 삼환@상가1동 115호)49519공주짱헤어20190314113849U2019-03-16 02:40:00.0일반미용업380635.076469175506.82671미용업(일반)4111<NA><NA>000N3<NA><NA><NA><NA>0<NA><NA>00N<NA>
1774417745미용업05_18_01_P33100003310000-204-1999-0070819990303<NA>3폐업2폐업19990525<NA><NA><NA>05112.82608838부산광역시 남구 용호동 482-44번지 T통B반<NA><NA>승현 미용실19990525000000I2018-08-31 23:59:59.0일반미용업392241.099153181562.42503미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1720417205미용업05_18_01_P32600003260000-204-1963-0052219631111<NA>3폐업2폐업20020222<NA><NA><NA>051 242882312.60602011부산광역시 서구 충무동1가 1-0번지 T통B반<NA><NA>영신20030130000000I2018-08-31 23:59:59.0일반미용업<NA><NA>미용업000<NA>0<NA>000N2<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1392913930미용업05_18_01_P33300003330000-204-1999-0157719990724<NA>3폐업2폐업20050422<NA><NA><NA>051 782595331.74612832부산광역시 해운대구 재송동 1154-17번지<NA><NA>헤어팜20030429000000I2018-08-31 23:59:59.0일반미용업394064.873388190132.173863미용업3<NA><NA>1<NA><NA><NA><NA><NA>N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>
1493914940미용업05_18_01_P33200003320000-204-1988-0040619881025<NA>3폐업2폐업20050117<NA><NA><NA>05115.75616807부산광역시 북구 구포동 1075-28번지 T통B반<NA><NA>천사미용19990420000000I2018-08-31 23:59:59.0피부미용업381592.04761190977.95949미용업000<NA>0<NA>000N3<NA><NA><NA><NA><NA><NA><NA><NA><NA>N<NA>